Low pre-death growth rates of oak (Quercus robur L.)—Is oak death a long-term process induced by dry years?

Background and purpose A complex interplay between biotic and abiotic factors is believed to be responsible for several oak declines in pedunculate oak (Quercus robur L.). This study aims to clarify the temporal process of oak declines, as well as identifying individual tree and environmental variables that affects growth rate and that may increase the risk of mortality. The study was performed in southern Sweden at three sites. Findings Cross-dating revealed that most trees had died during the last decade and that the growth rates of the dead oaks were affected long before death. Averaged growth chronologies of dead and control trees reaching 150 years back in time illustrated an excellent match up until around 1992, when a severe drought occurred after which the dead trees started to express reduced growth. Precipitation the previous year during August-September and during March-June this current year was of significant importance for oak growth. Site-specific results that showed that dead trees: included fewer small-sized trees, grew on non-clay soils, were more likely to have shelf fungus and cavities and were exposed to less sunshine. Conclusion The results support the theories that oak mortality is a long process that may be induced decades before the actual death.</p

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Data Availability Statement: The raw data supporting the conclusions of this article and code used for analysis will be made available by the authors on reasonable request pending appropriate study approvals and data transfer agreements between participating institutions.Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/brainsci14070669/s1, Table S1: Inclusion/exclusion criteria for each data source; Table S2: Deficit in words recalled for each clinical condition relative to matched controls. Refs. [61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100] are cited in the Supplementary Materials.Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.This research was funded by the Psychological Health/Traumatic Brain Injury Research Program Long-Term Impact of Military Relevant Brain Injury Consortium (LIMBIC), Grant/Award Numbers: W81XWH18PH, TBIRPLIMBIC under Awards Numbers: W81XWH1920067 and W81XWH1320095; US Department of Defense, Grant/Award Number: AZ150145; US Department of Veterans Affairs, Grant/Award Numbers: I01 CX002097, I01 CX002096, I01 HX003155, I01 RX003444, I01 RX003443, I01 RX003442, I01 CX001135, I01 CX001246, I01 RX001774, I01 RX001135, I01 RX002076, I01 RX001880, I01 RX002172, I01 RX002173, I01 RX002171, I01 RX002174, I01 RX002170, 1I01 RX003444; National Institutes of Health (NIH), Grant/Award Number(s): RF1NS115268, RF1NS128961, U01NS086625, U01MH124639, P50MH115846, R01MH113827, R25MH080663, K08MH068540, R01NS100973, R01EB006841, P20GM103472, RO1MH083553, T32MH019535, R01 HD061504, RO1MH083553, R01AG050595, R01AG076838, R01AG060470, R01AG064955, P01AG055367, K23MH095661, R01MH094524, R01MH121246, T32MH019535, R01NS124585, R01NS122827, R61NS120249, R01NS122184, U54EB020403, R01MH116147, R56AG058854, P41EB015922, R01MH111671, P41RR14075, M01RR01066, R01EB006841, R01EB005846, R01 EB000840, RC1MH089257, U24 RR021992, and NCRR 5 month-RR001066 (MGH General Clinical Research Center); National Institute of Mental Health (NIMH), Grant/Award Number: 1P20RR021938; Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III, Grant/Award Numbers: PI15-00852, PI18-00945, JR19-00024, PI17-00481, PI20-00721; Sara Borrell contract, Grant/Award Number: CD19-00149; German Research Foundation DFG grant FOR2107, Grant/Award Numbers: JA 1890/7-1, JA 1890/7-2, NE2254/1-2, NE2254/2-1, NE2254/3-1, NE2254/4-1, KI588/14-1, KI588/14-2, DA1151/5-1, DA1151/5-2, SFB-TRR58, Projects C09 and Z02; European Union, NextGenerationEU, Grant/Award Numbers: PMP21/00051, PI19/01024; Structural Funds; Seventh Framework Program; H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2, Grant/Award Number: 101034377; Project AIMS-2-TRIALS, Grant/Award Number: 777394; Horizon Europe; NSF, Grant/Award Number: 2112455; Madrid Regional Government, Grant/Award Number: B2017/BMD-3740 AGES-CM-2; Dalhousie Medical Research Foundation; Research Nova Scotia, Grant/Award Number: RNS-NHIG-2021-1931; NJ Commission on TBI Research Grants, Grant/Award Numbers: CBIR11PJT020, CBIR13IRG026; Department of Psychology, University of Oslo; Sunnaas Rehabilitation Hospital, Grant/Award Number: HF F32NS119285; Canadian Institutes of Health Research, Grant/Award Number: 166098; Neurological Foundation of New Zealand, Grant/Award Number: 2232 PRG; Canterbury Medical Research Foundation, University of Otago; Biogen US Investigator-initiated grant; Italian Ministry of Health, Grant/Award Number: RF-2019-12370182 and Ricerca Corrente RC 23; National Institute on Aging; National Health and Medical Research Council, Investigator Grant/Award Number: APP1176426; PA Health Research, Grant/Award Number: 4100077082; La Caixa Foundation, Grant/Award Number: 100010434, fellowship code: LCF/BQ/PR22/11920017; Research Council of Norway, Grant/Award Number: 248238; Health Research Council of New Zealand Sir Charles Hercus Early Career Development, Grant/Award Numbers: 17/039 and 14-440; Health Research Council of New Zealand, Grant/Award Numbers: 20/538 and 14/440; Research and Education Trust Pacific Radiology, Grant/Award Number: MRIJDA; South-Eastern Norway Regional Health Authority, Grant/Award Number: 2018076; Norwegian ExtraFoundation for Health and Rehabilitation, Grant/Award Numbers: 2015/FO5146; South-Eastern Norway Regional Health Authority, Grant/Award Number: 2015044; Stiftelsen K.G. Jebsen, Grant/Award Number: SKGJ MED-02; The Liaison Committee between Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology (NTNU), Grant/Award Number: 2020/39645; National Health and Medical Research Council, Grant/Award Number: APP1020526; Brain Foundation; Wicking Trust; Collie Trust; Sidney and Fiona Myer Family Foundation; U.S. Army Medical Research and Materiel Command (USAMRMC), Grant/Award Number: 13129004; Department of Energy, Grant/Award Number: DE-FG02-99ER62764; Mind Research Network; National Association for Research in Schizophrenia and Affective Disorders, Young Investigator Award; Blowitz Ridgeway and Essel Foundations; Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster; NOW ZonMw TOP, Grant/Award Number: 91211021; UCLA Easton Clinic for Brain Health; UCLA Brain Injury Research Center; Stan and Patty Silver; Clinical and Translational Research Center, Grant/Award Numbers: UL1RR033176, UL1TR000124; Mount Sinai Institute for NeuroAIDS Disparities; VA Rehab SPIRE; CDMRP PRAP; VA RR&D, Grant/Award Number: IK2RX002922; Veski Fellowship; Femino Foundation grant; Fundación Familia Alonso; Fundación Alicia Koplowitz; CIBERSAM, Madrid Regional Government, Grant/Award Numbers: B2017/BMD-3740 AGES-CM-2, 2019R1C1C1002457, 21-BR-03-01, 2020M3E5D9079910, 21-BR-03-01; Deutsche Forschungsgemeinschaft (DFG), Grant/Award Numbers: NE2254/1-2, NE2254/2-1, NE2254/3-1, NE2254/4-1

Pilot study: potential transcription markers for adult attention-deficit hyperactivity disorder in whole blood

Attention-deficit hyperactivity disorder (ADHD) is a common behavioural disorder that affects not only children and adolescents but also adults; however, diagnosis of adult ADHD is difficult because patients seem to have reduced externalized behaviour. ADHD is a multifactorial disorder in which many genes, all with small effects, are thought to cause the disorder in the presence of unfavourable environmental conditions. Therefore, in this pilot study, we explored the expression profile of a list of previously established candidate genes in peripheral blood samples from adult ADHD subjects (n = 108) and compared these results with those of healthy controls (n = 35). We demonstrate that combining the gene expression levels of dopamine transporter (SLC6A3), dopamine D5 receptor, tryptophan hydroxylase-1, and SNAP25 as predictors in a regression model resulted in sensitivity and specificity of over 80 % (ROC: max R(2) = 0.587, AUC = 0.917, P < 0.001, 95 % CI: 0.900-0.985). In conclusion, the combination of these four genes could represent a potential method for estimating risk and could be of diagnostic value for ADHD. Nevertheless, further investigation in a larger independent population including different subtypes of ADHD (inattentive, hyperactive, or combined type) patients is required to obtain more specific sets of biomarkers for each subtype as well as to differentiate between child, adolescent, and adulthood forms