Effect of exercise on bone health in children and adolescents with cancer during and after oncological treatment: A systematic review and meta-analysis

Background: Although regular physical activity and exercise programs might improve bone health caused by oncological treatment and the disease itself, it remains unknown the pooled effect of exercise interventions following frequency, intensity, time and type prescriptions. Objective: This systematic review and meta-analysis aimed to synthesise evidence regarding the effectiveness of exercise interventions on bone health in children and adolescents with cancer during and after oncological treatment. Methods: A systematic search was conducted in the MEDLINE (via PubMed), Web of Science and Scopus databases from November 2021 to January 2022. Randomised controlled trials (RCTs) and non-RCTs reporting pre-post changes of the effectiveness of exercise interventions on DXA-measured bone parameters in young population (1–19 years) during or after oncological treatment were included. Pooled (ESs) and 95% confidence intervals (95%CIs) were calculated. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Results: A total of eight trials with 341 participants were included. The metaanalyses did not reveal a statistically significant increase in whole body areal bone mineral density (ES = 0.10; 95%CI: −0.14, 0.34), lumbar spine (ES = 0.03; 95%CI: −0.21, 0.26) or femoral neck (ES = 0.10; 95%CI: −0.37, 0.56). Similarly, during the oncological treatment phase the ES was 0.04 (95%CI: −0.17, 0.25) and after the ES was 0.07 (95%CI: −0.20, 0.33). Conclusion: To date, exercise interventions have been inappropriate and therefore, ineffective to illustrate any beneficial effect on bone health in children and adolescents with cancer during and after oncological treatment.Spanish Ministry of Science and Innovation (ref: PID2020-117302RA-I00La Caixa Foundation (ref: LCF/BQ/PR19/11700007)the University of Granada Plan Propio de Investigación 2021-Excellence actions: Unit of Excellence on Exercise, Nutrition and Health (UCEENS)CIBEROBN, Centro de Investigación Biomédica en Red (CB22/03/ 00058Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – European Regional Development Fund. AM-P is recipient of a predoctoral fellowship (FPU20/05530) by the Spanish Ministry of Education, Culture and Sport. EU-G is supported by the Maria Zambrano fellowship by the Ministerio de Universidades y la Unión Europea—NextGenerationEU

Pre-treatment and extraction techniques for recovery of added value compounds from wastes throughout the agri-food chain

The enormous quantity of food wastes discarded annually force to look for alternatives for this interesting feedstock. Thus, food bio-waste valorisation is one of the imperatives of the nowadays society. This review is the most comprehensive overview of currently existing technologies and processes in this field. It tackles classical and innovative physical, physico-chemical and chemical methods of food waste pre-treatment and extraction for recovery of added value compounds and detection by modern technologies and are an outcome of the COST Action EUBIS, TD1203 Food Waste Valorisation for Sustainable Chemicals, Materials and Fuels

Conta to be geek

El documento describe el proceso de desarrollo de un reto de innovación, en la modalidad de innovación abierta y cocreación, donde el equipo de alumnos desarrolla una plataforma digital de educación, certificación y formación de una comunidad de contadores para el crecimiento y apoyo a profesionistas de la Licenciatura de Contaduría Pública

Expulsion and consumption of male ejaculates by promiscous female euxesta eluta and euxesta mazorca (Diptera: Ulidiidae)

While expulsion of male ejaculates by the females after copulation has been reported for various animal groups, expulsion followed by consumption of the expelled ejaculate is a rare behaviour outside spermatophylax-producing orthopterans. Among Diptera, this behaviour has been reported for a few species of Piophilidae, Empididae and Ulidiidae. Here we report on its occurrence among Euxesta eluta and Euxesta mazorca (Diptera: Ulidiidae). We also attempt to characterize the mating system of E. eluta in order to facilitate future hypothesis testing to understand the behavioural factors leading to the evolution of this peculiar behaviour. For this, courtship sequences, copulation duration, frequency of ejaculate expulsion and subsequent consumption, and latency to ejaculate expulsion for both E. eluta and E. mazorca were recorded. The time of sexual maturation, the time window of sexual receptivity during the day, and the mating frequency and variance in mating success for males and females (degree of polygamy) were determined for E. eluta. Both E. eluta and E. mazorca males engaged in elaborate courtship sequences involving visual and tactile displays before copulation. Females of both species almost invariably expelled and consumed ejaculates after copulation. Female E. eluta, required a 6-to 9-day period feeding on protein and sugar before becoming sexually receptive. Reproductive activity occurred continuously over the day with an early morning and late afternoon peak. Both males and females could mate multiply, with multiple partners over a 2-h observational period. Sexual network analysis revealed that some males and females had greater mating success than others. Ejaculate consumption appears to be widespread in the genus Euxesta. It is possible that females obtain nutrients from this behaviour while exerting some control over egg fertilization.Fil: Abraham, Solana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; ArgentinaFil: Rodríguez, Christian. Instituto de Ecologia, A.c.; MéxicoFil: Oviedo, Andrea Verónica de Fátima. Universidad Nacional de Tucumán; ArgentinaFil: Murúa, María Gabriela. Gobierno de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial Obispo Colombres; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Tecnología Agroindustrial del Noroeste Argentino. Provincia de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial "Obispo Colombres" (p). Instituto de Tecnología Agroindustrial del Noroeste Argentino; ArgentinaFil: Rull Gabayet, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; Argentin

Is higher physical fitness associated with better psychological health in young pediatric cancer survivors? A cross-sectional study from the iBoneFIT project

Objective: To examine the associations of self-perceived and objectively-measured physical fitness with psychological well-being and distress indicators in young pediatric cancer survivors. Materials and Methods: A total of 116 participants (12.1 ± 3.3 years, 56.9% boys) from the iBoneFIT project participated in this cross-sectional study. Objectively-measured physical fitness (muscular fitness) was obtained by handgrip strength and standing long jump tests for the upper and lower body, respectively. Self-perceived physical fitness was obtained by the International Fitness Scale (IFIS). Positive and negative affect were assessed by the positive affect schedule for children (PANAS-C), happiness by Subjective Happiness Scale (SHS), optimism by Life Orientation Test-Revised (LOT-R), self-esteem by the Rosenberg Self-Esteem Scale (RSE), anxiety by State–Trait Anxiety Inventory for Children (STAIC-R), and depression by Children Depression Inventory (CDI). Multiple linear regressions adjusted by key covariates were performed to analyze associations. Results: No associations were found between objectively-measured muscular fitness and any of the psychological well-being and distress indicators (p > 0.05). Self-perceived overall fitness and flexibility were positively associated with positive affect (β ≥ 0.258, p < 0.05). Self-perceived cardiorespiratory fitness, speed/ agility, and flexibility were negatively associated with depression (β ≥ −0.222, p < 0.05). Finally, self-perceived cardiorespiratory fitness was also negatively associated with anxiety and negative affect (β ≥ −0.264, p < 0.05). Conclusions: Perceived physical fitness, but not objectively physical fitness, seems to be inversely related to psychological distress variables and to less extent positively related to psychological well-being. The findings from this study highlight the importance of promoting self-perceived fitness in the pediatric oncology population.Ministry of Science and Innovation, Spain (MICINN) Spanish Government PID2020-117302RA-I00La Caixa Foundation LCF/BQ/PR19/11700007European Union's Horizon 2020 research and inno-vation programme under the Marie Sklodowska Curie 10102892

Increased power by harmonizing structural MRI site differences with the ComBat batch method in ENIGMA

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega -analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related het-erogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega -analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random - effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning)

Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA

Altres ajuts: SRB: The Australian Schizophrenia Research Bank (ASRB) was supported by the National Health and Medical Research Council of Australia (NHMRC) (Enabling Grant, ID 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation and the Schizophrenia Research Institute. Chief Investigators for ASRB were Carr, V., Schall, U., Scott, R., Jablensky, A., Mowry, B., Michie, P., Catts, S., Henskens, F., Pantelis, C. We thank Loughland, C., the ASRB Manager, and acknowledge the help of Jason Bridge for ASRB database queries. CP was supported by NHMRC Senior Principal Research Fellowships (IDs: 628386 & 1105825); GC was supported by the Schizophrenia Research Institute utilizing infrastructure funding from the New South Wales Ministry of Health and New South Wales Ministry of Trade and Investment (Australia); JMF was supported by NHMRC project grant (1063960) and the Janette Mary O'Neil Research Fellowship; MJG was supported by NHMRC as an R.D. Wright Biomedical Career Development Fellow (1061875). MJC was supported by NHMRC Senior Research Fellowship (1121474). CASSI: CSW is funded by the NSW Ministry of Health, Office of Health and Medical Research. CSW is a recipient of a National Health and Medical Research Council (Australia) Principal Research Fellowship (PRF) (#1117079). CIAM: The CIAM study (FMH - PI) was supported by the University Research Committee, University of Cape Town and South African funding bodies National Research Foundation and Medical Research Council. COBRE: The COBRE dataset and investigators were supported by NIH grants R01EB006841 & P20GM103472, as well as NSF grant 1539067. JT (senior author) and VDC are supported by 5R01MH094524. JMS is supported by R01 AA021771 and P50 AA022534. EONCKS: This work was supported by a New Partnership for Africa's Development (NEPAD) grant through the Department of Science and Technology of South Africa, the Medical Research Council of South Africa (grant number 65174). ESO: The ESO study was funded by NPU I - LO1611 and Ministry of Health, Czech Republic - Conceptual Development of Research Organization 00023001 (IKEM). FIDMAG/Project: This work was supported by the Catalan Government and several grants from the Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, 'Investing in your future'): Miguel Servet Research Contracts and Research Project Grants. FOR2107 Marburg: The FOR2107 Marburg study was funded by the German Research Foundation (DFG), Tilo Kircher (speaker FOR2107; DFG grant numbers KI588/14-1, KI588/14-2), Axel Krug (KR 3822/5-1, KR 3822/7-2), Igor Nenadic (NE 2254/1-2), Carsten Konrad (KO 4291/3-1). FOR2107 Muenster: The FOR2107 Muenster study was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). TH was supported by grants from the German Research Foundation (DFG grants HA7070/2-2, HA7070/3, HA7070/4). Frankfurt: MRI was performed at the Frankfurt Brain Imaging Center, supported by the German Research Council (DFG) and the German Ministry for Education and Research (BMBF; Brain Imaging Center Frankfurt/Main, DLR 01GO0203). GIPSI: This study was supported by Colciencias PRISMA-U.T. Huilong1 & Huilong2: This study was funded by the National Natural Science Foundation of China (81761128021; 31671145; 81401115; 81401133), Beijing Municipal Science and Technology Commission grant (Z141107002514016) and Beijing Natural Science Foundation(7162087, Beijing Municipal Administration of Hospitals Clinical medicine Development of special funding (XMLX201609; zylx201409). IGP: This study was funded by Project Grants from the Australian National Health and Medical Research Council of Australia (NHMRC; APP630471 and APP1081603), the Macquarie University's Australian Research Council Centre of Excellence in Cognition and its Disorders (CE110001021). Johns Hopkins: Supported by National Institutes of Health Grant Nos. MH-092443, MH-094268 (Silvio O. Conte Center), MH-105660, and MH-107730; foundation grants from Stanley, RUSK/S-R, and NARSAD/Brain and Behavior Research Foundation. Madrid: Supported by the Spanish Ministry of Science, Innovation and Universities, Instituto de Salud Carlos III, co-financed by ERDF Funds from the European Commission, "A way of making Europe", CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds and European Union Seventh Framework Program and H2020 Program; Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. MPRC1 & MPRC2: Support was received from NIH grants U01MH108148, 2R01EB015611, R01MH112180, R01DA027680, R01MH085646, P50MH103222 and T32MH067533, a State of Maryland contract (M00B6400091) and NSF grant (1620457). OLIN: The Olin study was supported by NIH grants R37MH43375 and R01MH074797. Oxford: The Oxford study MRC G0500092. SLF Rome: Support from the Italian Ministry of Health grants RC-12-13-14-15-16-17-18-19/A. RSCZ: RSCZ data collection was supported by RFBR 15-06-05758 grant. SCORE: This study was supported in part by grant 3232BO_119382 from the Swiss National Science Foundation. We thank the FePsy (Frueherkennung von Psychosen; early detection of psychosis) Study Group from the University of Basel, Department of Psychiatry, Switzerland, for the recruitment of the study participants. The FePsy Study was supported in part by grant No. SNF 3200-057216/1, ext./2, ext./3. Singapore: This study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004; SIG/11003), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to KS. SNUH: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant no. 2013R1A2A1A03071089 and 2017M3C7A1029610). UCISZ: The UCISZ study was supported by the National Institutes of Mental Health grant number R21MH097196 to TGMvE. UCISZ data were processed by the UCI High Performance Computing cluster supported by Joseph Farran, Harry Mangalam, and Adam Brenner and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 TR000153. UNIBA: The UNIBA study was supported by grant funding from the Italian Ministry of Health (PE-2011-02347951). UNIMAAS: The study was supported by Dutch Organization for Health Research and Development (ZonMw 91112002) and a personal grant to Thérèse van Amelsvoort (ZonMw-VIDI: 91712394). The data was collected in a clinical trial registered in the Dutch clinical trial registry under ID: NTR5094 (http://www.trialregister.nl). UPenn: This study was supported by the National Institute of Mental Health grants MH064045, MH 60722, MH019112, MH085096 (DHW), and R01MH112847 (RTS and TDS). Zurich: This study was supported by the Swiss National Science Foundation (105314_140351 to S.K.). Matthias Kirschner acknowledges support from the National Bank Fellowship (McGill University) and the Swiss National Foundation (P2SKP3_178175). Research reported in this publication was also supported by the following National Institutes of Health grants: U54 EB020403 to PMT, R01 MH116147, U24 RR21992, R21MH097196, and TR000153 to TGMvE, S10 OD023696 and R01EB015611 to PK, T32 AG058507and 5T32 MH073526 to CRKC, R01 MH117601 to NJ, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA-COINSTAC: Advanced World-wide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246.A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning)