Computational relativistic quantum dynamics and its application to relativistic tunneling and Kapitza-Dirac scattering

Computational methods are indispensable to study the quantum dynamics of relativistic light-matter interactions in parameter regimes where analytical methods become inapplicable. We present numerical methods for solving the time-dependent Dirac equation and the time-dependent Klein-Gordon equation and their implementation on high performance graphics cards. These methods allow us to study tunneling from hydrogen-like highly charged ions in strong laser fields and Kapitza-Dirac scattering in the relativistic regime

Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers

Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi‐tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment

Perceived Stress, Reproductive Hormones, and Ovulatory Function: A Prospective Cohort Study

Stress has been shown to suppress ovulation in experimental models, but its effect on human reproduction at the population level is unclear

Missed treatment opportunities and barriers to comprehensive treatment for sexual violence survivors in Kenya: a mixed methods study

Background In Kenya, most sexual violence survivors either do not access healthcare, access healthcare late or do not complete treatment. To design interventions that ensure optimal healthcare for survivors, it is important to understand the characteristics of those who do and do not access healthcare. In this paper, we aim to: compare the characteristics of survivors who present for healthcare to those of survivors reporting violence on national surveys; understand the healthcare services provided to survivors; and, identify barriers to treatment. Methods A mixed methods approach was used. Hospital records for survivors from two referral hospitals were compared with national-level data from the Kenya Demographic and Health Survey 2014, and the Violence Against Children Survey 2010. Descriptive summaries were calculated and differences in characteristics of the survivors assessed using chi-square tests. Qualitative data from six in-depth interviews with healthcare providers were analysed thematically. Results Among the 543 hospital respondents, 93.2% were female; 69.5% single; 71.9% knew the perpetrator; and 69.2% were children below 18 years. Compared to respondents disclosing sexual violence in nationally representative datasets, those who presented at hospital were less likely to be partnered, male, or assaulted by an intimate partner. Data suggest missed opportunities for treatment among those who did present to hospital: HIV PEP and other STI prophylaxis was not given to 30 and 16% of survivors respectively; 43% of eligible women did not receive emergency contraceptive; and, laboratory results were missing in more than 40% of the records. Those aged 18 years or below and those assaulted by known perpetrators were more likely to miss being put on HIV PEP. Qualitative data highlighted challenges in accessing and providing healthcare that included stigma, lack of staff training, missing equipment and poor coordination of services. Conclusions Nationally, survivors at higher risk of not accessing healthcare include older survivors; partnered or ever partnered survivors; survivors experiencing sexual violence from intimate partners; children experiencing violence in schools; and men. Interventions at the community level should target survivors who are unlikely to access healthcare and address barriers to early access to care. Staff training and specific clinical guidelines/protocols for treating children are urgently needed

Methodology and implementation of the WHO European Childhood Obesity Surveillance Initiative (COSI)

Establishment of the WHO European Childhood Obesity Surveillance Initiative (COSI)has resulted in a surveillance system which provides regular, reliable, timely, andaccurate data on children's weight status—through standardized measurement ofbodyweight and height—in the WHO European Region. Additional data on dietaryintake, physical activity, sedentary behavior, family background, and schoolenvironments are collected in several countries. In total, 45 countries in the EuropeanRegion have participated in COSI. The first five data collection rounds, between 2007and 2021, yielded measured anthropometric data on over 1.3 million children. In COSI,data are collected according to a common protocol, using standardized instrumentsand procedures. The systematic collection and analysis of these data enables inter-country comparisons and reveals differences in the prevalence of childhood thinness,overweight, normal weight, and obesity between and within populations. Furthermore,it facilitates investigation of the relationship between overweight, obesity, and poten-tial risk or protective factors and improves the understanding of the development ofoverweight and obesity in European primary-school children in order to supportappropriate and effective policy responses.The authors gratefully acknowledge support through a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. The ministries of health of Austria, Croatia, Greece, Italy, Malta, Norway, and the Russian Federation provided financial support for the meetings at which the protocol, data collection procedures, and analyses were discussed. Data collection in countries was made possible through funding from the following: Albania: WHO through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health. Austria: Federal Ministry of Labor, Social Affairs, Health and Consumer Protection of Austria. Bulgaria: Ministry of Health, National Center of Public Health and Analyses, and WHO Regional Office for Europe. Bosnia and Herzegovina: WHO country office support for training and data management. Croatia: Ministry of Health, Croatian Institute of Public Health, and WHO Regional Office for Europe. Czechia: Ministry of Health of the Czech Republic, grant number 17-31670A and MZCR—RVO EU 00023761. Denmark: Danish Ministry of Health. Estonia: Ministry of Social Affairs, Ministry of Education and Research (IUT 42-2), WHO Country Office, and National Institute for Health Development. Finland: Finnish Institute for Health and Welfare. France: Santé publique France (the French Agency for Public Health). Georgia: WHO. Greece: International Hellenic University and Hellenic Medical Association for Obesity. Hungary: WHO Country Office for Hungary. Ireland: Health Service Executive. Italy: Ministry of Health. Kazakhstan: Ministry of Health of the Republic of Kazakhstan, WHO, and UNICEF. Kyrgyzstan: World Health Organization. Latvia: Ministry of Health and Centre for Disease Prevention and Control. Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO. Malta: Ministry of Health. Montenegro: WHO and Institute of Public Health of Montenegro. North Macedonia: Government of North Macedonia through National Annual Program of Public Health and implemented by the Institute of Public Health and Centers of Public Health; WHO country office provides support for training and data management. Norway: the Norwegian Ministry of Health and Care Services, the Norwegian Directorate of Health, and the Norwegian Institute of Public Health. Poland: National Health Programme, Ministry of Health. Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates, and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS). Romania: Ministry of Health. Russian Federation: WHO. San Marino: Health Ministry, Educational Ministry, and Social Security Institute and Health Authority. Serbia: WHO and the WHO Country Office (2015-540940 and 2018/873491-0). Slovakia: Biennial Collaborative Agreement between WHO Regional Office for Europe and Ministry of Health SR. Slovenia: Ministry of Education, Science and Sport of the Republic of Slovenia within the SLOfit surveillance system. Spain: Spanish Agency for Food Safety and Nutrition. Sweden: Public Health Agency of Sweden. Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection. Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health. Turkey: Turkish Ministry of Health and World Bank.info:eu-repo/semantics/publishedVersio

Framework and baseline examination of the German National Cohort (NAKO)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5