Type 2 diabetes in children and adolescents: literature review

OBJECTIVE: the objective of this manuscript was to perform a critical review of epidemiology, pathophysiology, diagnosis e treatment of T2DM in youth. SOURCES OF DATA: this review is based on the relevant literature published. The sources available for the authors were integrated with sources identified through Medline database. The key words used for searching were Type 2 Diabetes in the Youth in the last ten years. SUMMARY OF THE FINDINGS: the pathophysiology (altered beta-cell function and insulin resistance) of T2DM in youth is similar to adult's pathophysiology. Familiar Type 2 diabetes history, presence of obesity, acanthosis nigricans, high fasting plasma C-peptide levels and absence of islet-cell auto-antibodies are important clues to diagnostic the T2DM in youth. Five to 25% of these patients can present ketosis at diagnosis. Insulin therapy can be discontinued during the evolution. Compliance to diet and an exercise program essential aspects of the treatment of adolescents. CONCLUSION: as obesity in the young is currently increasing in several developed or developing countries, T2DM in the youth can be consider an emergent problem also in our population.OBJETIVO: análise crítica dos estudos sobre a epidemiologia, fisiopatologia, diagnóstico e tratamento do DM2 no jovem. MÉTODOS: revisão da literatura nos últimos 10 anos, através de pesquisa no banco de dados Medline, utilizando os termos diabetes do tipo 2 no jovem. RESULTADOS: a fisiopatologia do DM2 no jovem é semelhante à do adulto, e compreende tanto a resistência à ação da insulina como uma alteração na função da célula beta-pancreática. O antecedente familiar para DM2, a presença de obesidade, a acanthosis nigricans, o peptídeo C de jejum superior a 0,6 ng/ml, a ausência de auto-anticorpos antiilhotas pancreáticas, em combinações variáveis, são pontos importantes para o diagnóstico desse tipo de DM. Cinco a 25% dos jovens com esse tipo de DM podem apresentar cetoacidose no diagnóstico. Nesses pacientes, o tratamento inicial com insulina é possível de ser descontinuado durante a evolução. A aderência à dieta e ao exercício físico são os elementos mais importantes do tratamento destes adolescentes. CONCLUSÃO: como a obesidade nos jovens tem aumentado, tanto em países industrializados como nos países em industrialização, o DM2 no jovem pode ser considerado um problema emergente também na nossa população.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de MedicinaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Centro de DiabetesUNIFESP, EPM, Centro de DiabetesSciEL

Predicting the individual risk of acute severe colitis at diagnosis.

Background/Aim Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. Methods The development cohort included patients aged 16–89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. Results The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1–29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10 mg/l, or haemoglobin < 12 g/dl F or < 14 g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. Conclusions An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy

Embracing Monogenic Parkinson's Disease : The MJFF Global Genetic PD Cohort

As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. Methods: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype-phenotype relationships were analyzed. We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals, 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35, 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34%) were indicated as not previously published. Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward clinical and genetic stratification of patients for gene-targeted clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Supplement: "Localization and broadband follow-up of the gravitational-wave transient GW150914" (2016, ApJL, 826, L13)

This Supplement provides supporting material for Abbott et al. (2016a). We briefly summarize past electromagnetic (EM) follow-up efforts as well as the organization and policy of the current EM follow-up program. We compare the four probability sky maps produced for the gravitational-wave transient GW150914, and provide additional details of the EM follow-up observations that were performed in the different bands

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Constraints on the Cosmic Expansion History from GWTC-3

This material is based upon work supported by NSFʼs LIGO Laboratory, which is a major facility fully funded by the National Science Foundation. The authors also gratefully acknowledge the support of the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. The authors gratefully acknowledge the Italian Istituto Nazionale di Fisica Nucleare (INFN), the French Centre National de la Recherche Scientifique (CNRS), and the Netherlands Organization for Scientific Research (NWO), for the construction and operation of the Virgo detector and the creation and support of the EGO consortium. The authors also gratefully acknowledge research support from these agencies as well as by the Council of Scientific and Industrial Research of India, the Department of Science and Technology, India, the Science & Engineering Research Board (SERB), India, the Ministry of Human Resource Development, India, the Spanish Agencia Estatal de Investigación (AEI), the Spanish Ministerio de Ciencia e Innovación and Ministerio de Universidades, the Conselleria de Fons Europeus, Universitat i Cultura and the Direcció General de Política Universitaria i Recerca del Govern de les Illes Balears, the Conselleria d’Innovació Universitats, Ciència i Societat Digital de la Generalitat Valenciana and the CERCA Programme Generalitat de Catalunya, Spain, the National Science Centre of Poland and the European Union–European Regional Development Fund, Foundation for Polish Science (FNP), the Swiss National Science Foundation (SNSF), the Russian Foundation for Basic Research, the Russian Science Foundation, the European Commission, the European Social Funds (ESF), the European Regional Develop- ment Funds (ERDF), the Royal Society, the Scottish Funding Council, the Scottish Universities Physics Alliance, the Hungarian Scientific Research Fund (OTKA), the French Lyon Institute of Origins (LIO), the Belgian Fonds de la Recherche Scientifique (FRS-FNRS), Actions de Recherche Concertées (ARC) and Fonds Wetenschappelijk Onderzoek–Vlaanderen (FWO), Bel- gium, the Paris Île-de-France Region, the National Research, Development and Innovation Office Hungary (NKFIH), the National Research Foundation of Korea, the Natural Science and Engineering Research Council Canada, Canadian Foundation for Innovation (CFI), the Brazilian Ministry of Science, Technology, and Innovations, the International Center for Theoretical Physics South American Institute for Fundamental Research (ICTP- SAIFR), the Research Grants Council of Hong Kong, the National Natural Science Foundation of China (NSFC), the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology (MOST), Taiwan, the United States Department of Energy, and the Kavli Foundation. The authors gratefully acknowledge the support of the NSF, STFC, INFN, and CNRS for provision of computational resources. This work was supported by MEXT, JSPS Leading-edge Research Infrastructure Program, JSPS Grant-in-Aid for Specially Promoted Research 26000005, JSPS Grant-in-Aid for Scientific Research on Innovative Areas 2905: JP17H06358, JP17H06361, and JP17H06364, JSPS Core-to- Core Program A. Advanced Research Networks, JSPS Grant- in-Aid for Scientific Research (S) 17H06133 and 20H05639, JSPS Grant-in-Aid for Transformative Research Areas (A) 20A203: JP20H05854, the joint research program of the Institute for Cosmic Ray Research, University of Tokyo, National Research Foundation (NRF) and Computing Infra- structure Project of KISTI-GSDC in Korea, Academia Sinica (AS), AS Grid Center (ASGC), and the Ministry of Science and Technology (MoST) in Taiwan under grants including AS- CDA-105-M06, Advanced Technology Center (ATC) of NAOJ, Mechanical Engineering Center of KEK. We would like to thank all of the essential workers who put their health at risk during the COVID-19 pandemic, without whom we would not have been able to complete this work.Peer reviewe

Open Data from the Third Observing Run of LIGO, Virgo, KAGRA, and GEO

Calibration of the LIGO strain data was performed with a GstLAL-based calibration software pipeline (Viets et al. 2018). Calibration of the Virgo strain data was performed with C-based software (Acernese et al. 2022b). Data quality products and event-validation results were computed using the DMT (https://labcit.ligo.caltech.edu/~jzweizig/DMT-Project. html), DQR (https://docs.ligo.org/detchar/data-quality-report/), DQSEGDB (Fisher et al. 2021), gwdetchar (Macloed et al. 2021a), hveto (Smith et al. 2011), iDQ (Essick et al. 2020), and Omicron (Robinet et al. 2020) software packages and contribut- ing software tools. Analyses relied upon the LALSuite software library (LIGO Scientific Collaboration 2018). PESummary was used to postprocess and collate parameter estimation results (Hoy & Raymond 2021). For an exhaustive list of the software used for searching the GW signals and characterizing their source, see Abbott et al. (2021c). Plots were prepared with Matplotlib (Hunter 2007), seaborn (Waskom 2021), GWSumm (Macleod et al. 2021b), and GWpy (Macleod et al. 2021c). NumPy (Harris et al. 2020) and SciPy (Virtanen et al. 2020) were used in the preparation of the manuscript. This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation. The authors also gratefully acknowledge the support of the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max- Planck-Society (MPS), and the State of Niedersachsen/ Germany for support of the construction of Advanced LIGO and construction and operation of the GEO 600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. The authors gratefully acknowl- edge the Italian Istituto Nazionale di Fisica Nucleare (INFN), the French Centre National de la Recherche Scientifique (CNRS), and the Netherlands Organization for Scientific Research (NWO) for the construction and operation of the Virgo detector and the creation and support of the EGO consortium. The authors also gratefully acknowledge research support from these agencies as well as by the Council of Scientific and Industrial Research of India, the Department of Science and Technology, India, the Science & Engineering Research Board (SERB), India, the Ministry of Human Resource Development, India, the Spanish Agencia Estatal de Investigación (AEI), the Spanish Ministerio de Ciencia e Innovación and Ministerio de Universidades, the Conselleria de Fons Europeus, Universitat i Cultura and the Direcció General de Política Universitaria i Recerca del Govern de les Illes Balears, the Conselleria d'Innovació, Universitats, Ciència i Societat Digital de la Generalitat Valenciana and the CERCA Programme Generalitat de Catalunya, Spain, the National Science Centre of Poland and the European Union – European Regional Development Fund; Foundation for Polish Science (FNP), the Swiss National Science Foundation (SNSF), the Russian Foundation for Basic Research, the Russian Science Foundation, the European Commission, the European Social Funds (ESF), the European Regional Development Funds (ERDF), the Royal Society, the Scottish Funding Council, the Scottish Universities Physics Alliance, the Hungarian Scientific Research Fund (OTKA), the French Lyon Institute of Origins (LIO), the Belgian Fonds de la Recherche Scientifique (FRS- FNRS), Actions de Recherche Concertées (ARC) and Fonds Wetenschappelijk Onderzoek – Vlaanderen (FWO), Belgium, the Paris Île-de-France Region, the National Research, Development and Innovation Office Hungary (NKFIH), the National Research Foundation of Korea, the Natural Science and Engineering Research Council Canada, Canadian Founda- tion for Innovation (CFI), the Brazilian Ministry of Science, Technology, and Innovations, the International Center for Theoretical Physics South American Institute for Fundamental Research (ICTP-SAIFR), the Research Grants Council of Hong Kong, the National Natural Science Foundation of China (NSFC), the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology (MOST), Taiwan, the United States Department of Energy, and the Kavli Foundation. The authors gratefully acknowledge the support of the NSF, STFC, INFN, and CNRS for provision of computational resources. This work was supported by MEXT, JSPS Leading-edge Research Infrastructure Program, JSPS Grant-in-Aid for Specially Promoted Research 26000005, JSPS Grant-in-Aid for Scientific Research on Innovative Areas 2905: JP17H06358, JP17H06361 and JP17H06364, JSPS Core-to- Core Program A, Advanced Research Networks, JSPS Grant- in-Aid for Scientific Research (S) 17H06133 and 20H05639, JSPS Grant-in-Aid for Transformative Research Areas (A) 20A203: JP20H05854, the joint research program of the Institute for Cosmic Ray Research, University of Tokyo, National Research Foundation (NRF), Computing Infrastruc- ture Project of Global Science experimental Data hub Center (GSDC) at KISTI, Korea Astronomy and Space Science Institute (KASI), and Ministry of Science and ICT (MSIT) in Korea, Academia Sinica (AS), AS Grid Center (ASGC) and the National Science and Technology Council (NSTC) in Taiwan under grants including the Rising Star Program and Science Vanguard Research Program, Advanced Technology Center (ATC) of NAOJ, and Mechanical Engineering Center of KEK.Peer reviewe