Impact of childhood trauma on antipsychotic effectiveness in schizophrenia spectrum disorders: A prospective, pragmatic, semi-randomized trial

Antipsychotic medications are generally effective in ameliorating psychotic symptoms in schizophrenia spectrum disorders (SSDs). Identifying predictors associated with poor treatment response is important for a personalized treatment approach. Childhood trauma (CT) may have a general and differential effect on the effectiveness of different types of antipsychotics in SSDs. The Bergen-Stavanger-Trondheim-Innsbruck (BeSt InTro) study is a pragmatic, researcher-initiated, semi-randomized trial. The present study aimed to investigate symptom change (the Positive and Negative Syndrome Scale) from baseline to 1, 3, 6, 12, 26, 39 and 52 weeks of antipsychotic treatment (amisulpride, aripiprazole and olanzapine) by group (CT/no CT). Participants (n = 98) with diagnoses within the schizophrenia spectrum (F20–29 in the International Classification of Diseases — 10th Revision) were randomized to receive amisulpride, aripiprazole or olanzapine, and for this study categorized into groups of none and low CT, and moderate to severe CT according to thresholds defined by the Childhood Trauma Questionnaire Short-Form manual. CT in SSDs predicted an overall slower treatment response and less antipsychotic effectiveness after 26 weeks of treatment, which was statistically nonsignificant at 52 weeks. Secondary analyses showed a differential effect of CT related to type of antipsychotic medication: patients with SSDs and CT who received olanzapine showed less antipsychotic effectiveness throughout 52 weeks of treatment. The intention-to-treat and per-protocol analyses were convergent. Our findings indicate that in patients with SSD and CT, delayed response to antipsychotics could be expected, and a longer evaluation period before considering change of medication may be recommended.publishedVersio

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

Methods for biogeochemical studies of sea ice: the state of the art, caveats, and recommendations

Over the past two decades, with recognition that the ocean’s sea-ice cover is neither insensitive to climate change nor a barrier to light and matter, research in sea-ice biogeochemistry has accelerated significantly, bringing together a multi-disciplinary community from a variety of fields. This disciplinary diversity has contributed a wide range of methodological techniques and approaches to sea-ice studies, complicating comparisons of the results and the development of conceptual and numerical models to describe the important biogeochemical processes occurring in sea ice. Almost all chemical elements, compounds, and biogeochemical processes relevant to Earth system science are measured in sea ice, with published methods available for determining biomass, pigments, net community production, primary production, bacterial activity, macronutrients, numerous natural and anthropogenic organic compounds, trace elements, reactive and inert gases, sulfur species, the carbon dioxide system parameters, stable isotopes, and water-ice-atmosphere fluxes of gases, liquids, and solids. For most of these measurements, multiple sampling and processing techniques are available, but to date there has been little intercomparison or intercalibration between methods. In addition, researchers collect different types of ancillary data and document their samples differently, further confounding comparisons between studies. These problems are compounded by the heterogeneity of sea ice, in which even adjacent cores can have dramatically different biogeochemical compositions. We recommend that, in future investigations, researchers design their programs based on nested sampling patterns, collect a core suite of ancillary measurements, and employ a standard approach for sample identification and documentation. In addition, intercalibration exercises are most critically needed for measurements of biomass, primary production, nutrients, dissolved and particulate organic matter (including exopolymers), the CO2 system, air-ice gas fluxes, and aerosol production. We also encourage the development of in situ probes robust enough for long-term deployment in sea ice, particularly for biological parameters, the CO2 system, and other gases

Controlled human malaria infection with graded numbers of Plasmodium falciparum NF135.C10- or NF166.C8-infected mosquitoes

Controlled human malaria infections (CHMIs) with Plasmodium falciparum (Pf) parasites are well established. Exposure to five Pf (NF54)-infected Anopheles mosquitoes results in 100% infection rates in malaria-näive volunteers. Recently Pf clones NF135.C10 and NF166.C8 were generated for application in CHMIs. Here, we tested the clinical infection rates of these clones, using graded numbers of Pf-infected mosquitoes. In a double-blind randomized trial, we exposed 24 malaria-näive volunteers to bites from one, two, or five mosquitoes infected with NF135.C10 or NF166.C8. The primary endpoint was parasitemia by quantitative polymerase chain reaction. For both strains, bites by five infected mosquitoes resulted in parasitemiain4/4 volunteers; 3/4 volunteers developed parasitemia after exposure to one or two infected mosquitoes infected with either clone. The prepatent period was 7.25 ± 4.0 days (median ± range). There were no serious adverse events and comparable clinical symptoms between all groups. These data confirm the eligibility of NF135.C10 and NF166.C8 for use in CHMI studies

Spadek fotosyntetycznej wydajności nie wyjaśnia zamykania szparek u roślin pomidora w warunkach stresu zalewania

Stomata begin to close within 24 h of imposing soil flooding. We investigated whether the stomatal response was triggered by reduced photosynthetic efficiency in young, fully expanded leaves of flooded plants. Chlorophyll fluorescence measurements indicated that ФpsII the effective quantum yield of PS II,decreased after stomata began to close in flooded plants. Changes in qP mirrored those of ФpsII, ФpsII was not affected by daytime patterns of stomatal conductance in well-drained plants but was reduced by stomatal closure in flooded plants. Fv/Fm a measure of the overall photosynthetic efficiency of dark- adapted plants, decreased after 57 h of flooding. Therefore, prolonged soil flooding adversely affected the thylakoid membranes. QN, a measure of the amount of captured energy dissipated as heat and therefore, unused by the photosynthetic machinery, began to increase after 32 h of flooding and continued to rise thereafter. The interdependence of the changes in chlorophyll fluorescence parameters and the flooding-induced closure of stomata is discussed.W warunkach nadmiaru wody w glebie szparki u roślin pomidora zamykają się w czasie 24 h. W prezentowanych eksperymentach badano czy ta reakcja szparek była inicjowana przez spadek fotosyntetycznej wydajności młodych, rozwiniętych liści pomidora. Pomiary fluorescencji chlorofilu wykazały, że ФpsII, efektywna wydajność transportu elektronów PSII, spadała dopiero po rozpoczęciu zamykania szparek u zalewanych roślin. Zmiany qP, fotochemicznego wygaszania fluorescencji, odzwierciedlały przebieg ФpsII Na ФpsII nie wpływał okołodobowy rytm szparek u roślin kontrolnych. Natomiast, u roślin zalewanych, ÖpsII spadało wskutek zamykania szparek. Fv/Fm, miara całkowitej wydajności fotosyntetycznej roślin zaadaptowanych do ciemności, spadał po 57 h zalewania roślin. Wskazuje to na niekorzystny wpływ wydłużonego stresu zalewania na membrany tylakoidowe. Niefotochemiczne wygaszanie fluorescencji (NQ), która jest miarą rozpraszania niewykorzystanej energii w postaci ciepła, wzrastała po 32 h od rozpoczęcia stresu zalewania. W pracy dyskutowana jest niezależność zmian parametrów fluorescencji chlorofilu a i indukowanego stresem zalewania zamykania się szparek

The regulation of sweet cherry fruit abscission by polar auxin transport

Inconsistency of cropping is an important problem for UK sweet cherry production. Premature fruit abscission in Prunus can reduce yields severely, however, the environmental cues and hormonal signals that trigger abscission have not been identified. Auxin (IAA) is known to delay abscission by reducing the sensitivity of cells in the abscission zone to ethylene, a promoter of abscission. Therefore, the capacity for polar auxin transport (PAT) through sweet cherry pedicels was examined in relation to fruit abscission. Cherry ‘spurs’ (short shoots) with similar leaf areas and different fruit numbers were phloem-girdled to restrict assimilate movement. Abscission from spurs with many fruit (eight or more) occurred within 14 days of girdling, whereas abscission from spurs with few (two) fruit was minimal. The pedicels’ capacity for PAT in spurs with different fruit numbers was determined 1, 3 and 9 days after girdling (DAG). Fruit were analysed for endogenous IAA concentration 3, 5, 7 and 9 DAG. PAT inhibitors 2,3,5-triiodobenzoic acid or 1-N-naphthylphtalamic acid were applied to pedicels of fruit not expected to abscise, i.e. on spurs with few fruit. The effect of these inhibitors on fruit abscission was determined 14 DAG. The proportion of the transported [3H]-IAA was lower from the outset in pedicels from spurs with many fruit. By 9 DAG, symptoms of fruit abscission were apparent and 40% less [3H] -IAA was transported through pedicels on spurs with many fruit. Fruit endogenous IAA concentrations were similar in the two groups of spurs. Application of PAT inhibitors shortly after girdling increased fruit abscission by 30%. The results suggest that although a decline in PAT is not the only cause of fruit abscission, the maintenance of PAT contributes to fruit retention