Social Network Analysis of Online Support Communities for Adolescent and Young Adult Cancer Survivors

There are an estimated 633,000 adolescent and young adult (AYA) cancer survivors in the U.S. and nearly 89,500 AYAs are diagnosed with cancer every year. Cancer creates developmental and life stage disruptions, which result in multiple survivorship challenges, particularly among AYAs. Despite the advances made in cancer oncology and survivorship care, AYA cancer survivors continue to face diverse and unique psychosocial needs. Research suggests that online support communities have the potential to positively impact psychosocial care by providing AYA cancer survivors with access to social support which can help them successfully transition from treatment back to normal life as well as improve their well-being. In addition, online support communities have become important sources of social support, particularly peer support, offering an opportunity for AYA cancer survivors to exchange support and overcome psychosocial challenges. However, despite an increasing use of online support communities by cancer survivors in general, there is limited evidence providing insights into how online social support can be leveraged by AYA cancer survivors to bridge existing gaps in their psychosocial care. This study provides a deeper understanding of online support exchange by examining the structures of support networks of online interactions among AYA cancer survivors. It applies an informatics approach that combines content analysis, computerized text analysis, and social network analysis. The results show that AYA cancer survivors are mostly exchanging emotional support but also exchange informational and esteem support in similar proportions. In addition, this study expands current understanding of how AYA cancer survivors are using language to exchange support online. Furthermore, the structural characteristics of support networks reveal they are characterized by low densities and average degrees. Moreover, subcommunities of network support developed among AYA cancer survivors, in spite oflow levels of cohesion and clustering between them. Additionally, support networks show that AYA cancer survivors who exchange informational or esteem support are also likely to exchange emotional support. Lastly, the novel data-driven insights gathered by applying an informatics approach may inform the future design and implementation of online support interventions that aim to address the unmet psychosocial needs of AYA cancer survivors

Precise Dynamic Consensus under Event-Triggered Communication

This work addresses the problem of dynamic consensus, which consists of estimating the dynamic average of a set of time-varying signals distributed across a communication network of multiple agents. This problem has many applications in robotics, with formation control and target tracking being some of the most prominent ones. In this work, we propose a consensus algorithm to estimate the dynamic average in a distributed fashion, where discrete sampling and event-triggered communication are adopted to reduce the communication burden. Compared to other linear methods in the state of the art, our proposal can obtain exact convergence under continuous communication even when the dynamic average signal is persistently varying. Contrary to other sliding-mode approaches, our method reduces chattering in the discrete-time setting. The proposal is based on the discretization of established exact dynamic consensus results that use high-order sliding modes. The convergence of the protocol is verified through formal analysis, based on homogeneity properties, as well as through several numerical experiments. Concretely, we numerically show that an advantageous trade-off exists between the maximum steady-state consensus error and the communication rate. As a result, our proposal can outperform other state-of-the-art approaches, even when event-triggered communication is used in our protocol

IRS-2 Deficiency Impairs NMDA Receptor-Dependent Long-term Potentiation

The beneficial effects of insulin and insulin-like growth factor I on cognition have been documented in humans and animal models. Conversely, obesity, hyperinsulinemia, and diabetes increase the risk for neurodegenerative disorders including Alzheimer's disease (AD). However, the mechanisms by which insulin regulates synaptic plasticity are not well understood. Here, we report that complete disruption of insulin receptor substrate 2 (Irs2) in mice impairs long-term potentiation (LTP) of synaptic transmission in the hippocampus. Basal synaptic transmission and paired-pulse facilitation were similar between the 2 groups of mice. Induction of LTP by high-frequency conditioning tetanus did not activate postsynaptic N-methyl-D-aspartate (NMDA) receptors in hippocampus slices from Irs2−/− mice, although the expression of NR2A, NR2B, and PSD95 was equivalent to wild-type controls. Activation of Fyn, AKT, and MAPK in response to tetanus stimulation was defective in Irs2−/− mice. Interestingly, IRS2 was phosphorylated during induction of LTP in control mice, revealing a potential new component of the signaling machinery which modulates synaptic plasticity. Given that IRS2 expression is diminished in Type 2 diabetics as well as in AD patients, these data may reveal an explanation for the prevalence of cognitive decline in humans with metabolic disorders by providing a mechanistic link between insulin resistance and impaired synaptic transmission

The perception of Engineering students toward teaching performance on online learning during COVID-19 pandemic

This study analyzed the perception of Mechanical Engineering and Systems Engineering students in the process of evaluating teacher performance in online teaching due to the COVID-19 pandemic. This was descriptive-correlational research. The results showed that the Systems Engineering students performed a better perception with the class session management factor and low qualification to the didactic strategies factor. Likewise, the Pearson correlation test indicated a significant relationship (0.000) between the specific factors on the overall performance factor. The topic factor has the greatest strength on the qualification of the overall performance factor, with a constant Pearson's correlation of 0.964. The Mechanical Engineering students showed a better perception with the class session planning factor and low qualification to the didactic strategies factor. Likewise, the Pearson correlation test indicated a significant relationship (0.000) between the specific factors on the overall performance factor. The didactic strategies factor being the one that has the greatest strength on the qualification of the overall performance factor, with a correlation constant Pearson's of 0.983

Theobroma cacao L. compounds: Theoretical study and molecular modeling as inhibitors of main SARS-CoV-2 protease

Indexación: ScopusCocoa beans contain antioxidant molecules with the potential to inhibit type 2 coronavirus (SARS-CoV-2), which causes a severe acute respiratory syndrome (COVID-19). In particular, protease. Therefore, using in silico tests, 30 molecules obtained from cocoa were evaluated. Using molecular docking and quantum mechanics calculations, the chemical properties and binding efficiency of each ligand was evaluated, which allowed the selection of 5 compounds of this series. The ability of amentoflavone, isorhoifolin, nicotiflorin, naringin and rutin to bind to the main viral protease was studied by means of free energy calculations and structural analysis performed from molecular dynamics simulations of the enzyme/inhibitor complex. Isorhoifolin and rutin stand out, presenting a more negative binding ΔG than the reference inhibitor N-[(5-methylisoxazol-3-yl)carbonyl]alanyl-L-valyl-N~1~-((1R,2Z)−4-(benzyloxy)−4-oxo-1-{[(3R)−2-oxopyrrolidin-3-yl]methyl}but-2-enyl)-L-leucinamide (N3). These results are consistent with high affinities of these molecules for the major SARS-CoV-2. The results presented in this paper are a solid starting point for future in vitro and in vivo experiments aiming to validate these molecules and /or test similar substances as inhibitors of SARS-CoV-2 protease. © 2021 The Author

La enseñanza del metabolismo: retos y oportunidades

En el marco del Proyecto de Innovación Educativa de la Universidad de Málaga PIE15-163, cuya descripción y resultados incluimos, decidimos que esta era una excelente oportunidad para reflexionar acerca de la enseñanza del metabolismo y de poner por escrito dichas reflexiones en un libro. Quisimos y pudimos contar con la colaboración de buena parte de los compañeros del Departamento de Biología Molecular y Bioquímica que apoyaron con su firma el proyecto PIE15-163 y extendimos nuestra invitaciones a otros compañeros de dentro y fuera de la Universidad de Málaga. Del Departamento de Biología Molecular y Bioquímica de la Universidad de Málaga hemos recibido aportaciones de los catedráticos Victoriano Valpuesta Fernández, Ana Rodríguez Quesada y Antonio Heredia Bayona, los profesores titulares María Josefa Pérez Rodríguez, José Luis Urdiales Ruiz e Ignacio Fajardo Paredes y la investigadora postdoctoral y profesora sustituta interina Beatriz Martínez Poveda. De otros departamentos de la Universidad de Málaga hemos contado con las aportaciones de la catedrática del Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología Pilar Morata Losa, del catedrático del Departamento de Lenguajes y Ciencias de la Computación José Francisco Aldana Montes y los componentes de su grupo de investigación Khaos Ismael Navas Delgado, María Jesús García Godoy, Esteban López Camacho y Maciej Rybinski, del catedrático Ángel Blanco López, del Área de Conocimiento de Didáctica de las Ciencias Experimentales y del Doctor en Ciencias Químicas y actual doctorando del Programa de Doctorado "Educación y Comunicación Social" Ángel Luis García Ponce. De fuera de la Universidad de Málaga, hemos contado con las aportaciones del catedrático de la Universidad de La Laguna Néstor V. Torres Darias, de la catedrática de la Universitat de les Illes Balears Pilar Roca Salom y de sus compañeros los profesores Jorge Sastre Serra y Jordi Oliver, de los catedráticos de la Universidad de Granada Rafael Salto González y María Dolores Girón González y su colaborador el Dr. José Dámaso Vílchez Rienda, del profesor titular de la Universidad de Alcalá Ángel Herráez, del investigador postdoctoral de la Universidad de Erlangen (Alemania) Guido Santos y del investigador postdoctoral de la empresa Brain Dynamics Carlos Rodríguez Caso.Hemos estructurado los contenidos del libro en diversas secciones. La primera presenta el Proyecto en cuyo marco se ha gestado la iniciativa que ha conducido a la edición del presente libro. La segunda sección la hemos titulado "¿Qué metabolismo?" e incluye diversas aportaciones personales que reflexionan acerca de qué metabolismo debe conocer un graduado en Bioquímica, en Biología, en Química, en Farmacia o en Medicina, así como una aportación acerca de qué bioquímica estructural y enzimología son útiles y necesarias para un estudiante que vaya a afrontar el estudio del metabolismo. La tercera sección, "Bases conceptuales", analiza las aportaciones del aprendizaje colaborativo, el contrato de aprendizaje y el aprendizaje basado en la resolución de casos prácticos a la mejora del proceso enseñanza-aprendizaje dentro del campo de la Bioquímica y Biología Molecular, más concretamente en el estudio del metabolismo. La cuarta sección se titula "Herramientas", es la más extensa e incluye las diversas aportaciones centradas en propuestas concretas de aplicación relevantes y útiles para la mejora de la docencia-aprendizaje del metabolismo. Sigue una sección dedicada a presentar de forma resumida los "Resultados" del proyecto PIE15-163. El libro concluye con una "coda final" en la que se reflexiona acerca del aprendizaje de la Química a la luz de la investigación didáctica.Patrocinado por el Proyecto de Innovación Educativa de la Universidad de Málaga PIE15-16

The global retinoblastoma outcome study : a prospective, cluster-based analysis of 4064 patients from 149 countries

DATA SHARING : The study data will become available online once all analyses are complete.BACKGROUND : Retinoblastoma is the most common intraocular cancer worldwide. There is some evidence to suggest that major differences exist in treatment outcomes for children with retinoblastoma from different regions, but these differences have not been assessed on a global scale. We aimed to report 3-year outcomes for children with retinoblastoma globally and to investigate factors associated with survival. METHODS : We did a prospective cluster-based analysis of treatment-naive patients with retinoblastoma who were diagnosed between Jan 1, 2017, and Dec 31, 2017, then treated and followed up for 3 years. Patients were recruited from 260 specialised treatment centres worldwide. Data were obtained from participating centres on primary and additional treatments, duration of follow-up, metastasis, eye globe salvage, and survival outcome. We analysed time to death and time to enucleation with Cox regression models. FINDINGS : The cohort included 4064 children from 149 countries. The median age at diagnosis was 23·2 months (IQR 11·0–36·5). Extraocular tumour spread (cT4 of the cTNMH classification) at diagnosis was reported in five (0·8%) of 636 children from high-income countries, 55 (5·4%) of 1027 children from upper-middle-income countries, 342 (19·7%) of 1738 children from lower-middle-income countries, and 196 (42·9%) of 457 children from low-income countries. Enucleation surgery was available for all children and intravenous chemotherapy was available for 4014 (98·8%) of 4064 children. The 3-year survival rate was 99·5% (95% CI 98·8–100·0) for children from high-income countries, 91·2% (89·5–93·0) for children from upper-middle-income countries, 80·3% (78·3–82·3) for children from lower-middle-income countries, and 57·3% (52·1-63·0) for children from low-income countries. On analysis, independent factors for worse survival were residence in low-income countries compared to high-income countries (hazard ratio 16·67; 95% CI 4·76–50·00), cT4 advanced tumour compared to cT1 (8·98; 4·44–18·18), and older age at diagnosis in children up to 3 years (1·38 per year; 1·23–1·56). For children aged 3–7 years, the mortality risk decreased slightly (p=0·0104 for the change in slope). INTERPRETATION : This study, estimated to include approximately half of all new retinoblastoma cases worldwide in 2017, shows profound inequity in survival of children depending on the national income level of their country of residence. In high-income countries, death from retinoblastoma is rare, whereas in low-income countries estimated 3-year survival is just over 50%. Although essential treatments are available in nearly all countries, early diagnosis and treatment in low-income countries are key to improving survival outcomes.The Queen Elizabeth Diamond Jubilee Trust and the Wellcome Trust.https://www.thelancet.com/journals/langlo/homeam2023Paediatrics and Child Healt

Precise Dynamic Consensus under Event-Triggered Communication

This work addresses the problem of dynamic consensus, which consists of estimating the dynamic average of a set of time-varying signals distributed across a communication network of multiple agents. This problem has many applications in robotics, with formation control and target tracking being some of the most prominent ones. In this work, we propose a consensus algorithm to estimate the dynamic average in a distributed fashion, where discrete sampling and event-triggered communication are adopted to reduce the communication burden. Compared to other linear methods in the state of the art, our proposal can obtain exact convergence under continuous communication even when the dynamic average signal is persistently varying. Contrary to other sliding-mode approaches, our method reduces chattering in the discrete-time setting. The proposal is based on the discretization of established exact dynamic consensus results that use high-order sliding modes. The convergence of the protocol is verified through formal analysis, based on homogeneity properties, as well as through several numerical experiments. Concretely, we numerically show that an advantageous trade-off exists between the maximum steady-state consensus error and the communication rate. As a result, our proposal can outperform other state-of-the-art approaches, even when event-triggered communication is used in our protocol

Precise Dynamic Consensus under Event-Triggered Communication

This work addresses the problem of dynamic consensus, which consists of estimating the dynamic average of a set of time-varying signals distributed across a communication network of multiple agents. This problem has many applications in robotics, with formation control and target tracking being some of the most prominent ones. In this work, we propose a consensus algorithm to estimate the dynamic average in a distributed fashion, where discrete sampling and event-triggered communication are adopted to reduce the communication burden. Compared to other linear methods in the state of the art, our proposal can obtain exact convergence under continuous communication even when the dynamic average signal is persistently varying. Contrary to other sliding-mode approaches, our method reduces chattering in the discrete-time setting. The proposal is based on the discretization of established exact dynamic consensus results that use high-order sliding modes. The convergence of the protocol is verified through formal analysis, based on homogeneity properties, as well as through several numerical experiments. Concretely, we numerically show that an advantageous trade-off exists between the maximum steady-state consensus error and the communication rate. As a result, our proposal can outperform other state-of-the-art approaches, even when event-triggered communication is used in our protocol

Low dose thymoglobulin versus basiliximab in cytomegalovirus positive kidney transplant recipients: Effectiveness of preemptive cytomegalovirus modified strategy

Background: We performed a retrospective trial to determine asymptomatic CMV reactivation and CMV disease in kidney allograft recipients with positive CMV serostatus. Methods: Preemptive modified strategy under low dose thymoglobulin versus basiliximab induction was evaluated. Patients were monitored by CMV-polymerase chain reaction (PCR); if the viral load was >4000 copies/μl, they received valganciclovir adjusted for their renal function. Results: 132 recipients were included in the study, 84 and 48 receiving basiliximab and thymoglobulin induction respectively, and followed up for 12 months. Asymptomatic CMV reactivation was significantly higher for thymoglobulin (77.1% vs. 16.7%, p < 0.001). Treatment groups had similar rates of CMV disease (3.6% vs. 2.1%, p 0.538). The significant difference in asymptomatic CMV reactivation between two treatment groups did not have any impact on 1 year graft function (71 ± 26 ml/min vs. 74 ± 19 ml/min; p = 0.475) and no histological differences in protocol biopsies were observed among patients with asymptomatic CMV reactivation vs those without CMV reactivation. Conclusions: Due to the high asymptomatic CMV reactivation incidence in patients who received thymoglobulin induction, our results suggest that valganciclovir prophylaxis may be advantageous in CMV seropositive renal transplant recipients after low dose thymoglobulin induction. A preemptive strategy appeared to significantly reduce the likelihood of CMV disease in both groups. Rejection risk and negative impact in renal function associated with asymptomatic CMV reactivation was not found in our series. Resumen: Antecedentes: Llevamos a cabo un estudio retrospectivo para determinar la reactivación y enfermedad por CMV en receptores de trasplante renal CMV seropositivos bajo diferentes esquemas de inducción. Métodos: Una estrategia preventiva modificada bajo inducción con basiliximab y timoglobulina en dosis bajas fue evaluada. Se llevó a cabo un seguimiento de la carga viral-reacción de cadena de la polimerasa-CMV; los valores mayores de 4000 copias/μl recibieron valganciclovir ajustado a la función renal. Resultados: Un total de 132 receptores de trasplante renal fueron incluidos; 84 y 48 recibieron inducción con basiliximab y timoglobulina respectivamente. Seguimiento hasta el mes 12 postrasplante. La reactivación asintomática de CMV fue significativamente mayor para timoglobulina (77,1% vs. 16,7%, p < 0,001). La tasa de enfermedad por CMV fue similar en ambos grupos de tratamiento (3,6% vs. 2,1%, p = 0,538). Ningún impacto en la función renal un año postrasplante fue encontrado entre los grupos a pesar de la diferencia significativa en reactivación asintomática de CMV (71 ± 26 ml/min vs. 74 ± 19 ml/min; p = 0,475); igualmente, no encontramos diferencias en los hallazgos histológicos en biopsias por protocolo entre receptores con reactivación asintomática por CMV y aquellos sin reactivación. Conclusiones: La alta incidencia de reactivación asintomática por CMV en receptores seropositivos a pesar del uso de bajas dosis de timoglobulina sugiere que la profilaxis con valganciclovir es una estrategia apropiada en este grupo; sin embargo, una estrategia preventiva reduce significativamente la probabilidad de enfermedad por CMV en ambos grupos de tratamiento. El riesgo de rechazo y el impacto negativo en la función renal asociado a la reactivación asintomática por CMV no fue encontrado en nuestra experiencia