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Objective: To test the effect of a complex guideline-based intervention on agitation and psychotropic prescriptions.
Design, Setting, Participants: Cluster randomized controlled trial (VIDEANT) with blinded assessment of outcome in 18 nursing homes in Berlin, Germany, comprising 304 dementia patients.
Intervention: Training, support, and activity therapy intervention, delivered at the level of each nursing home, focusing on the management of agitation in dementia. Control group nursing homes received treatment as usual.
Measurements: Levels of agitated and disruptive behavior (Cohen-Mansfield agitation inventory [CMAI]) as the primary outcome. Number of neuroleptics, antidepressants, and cholinesterase inhibitors (ChEIs) prescribed in defined daily dosages (DDDs).
Results: Of 326 patients screened, 304 (93.3%) were eligible and cluster-randomized to 9 intervention (n = 163) and 9 control (n = 141) nursing homes. Data were collected from 287 (94.4%) patients at 10 months. At 10 months, compared with controls, nursing home residents with dementia in the intervention group exhibited significantly less agitation as measured with the CMAI (adjusted mean difference, 6.24; 95% CI 2.03-14.14; P = .009; Cohen's d = 0.43), received fewer neuroleptics (P < .05), more ChEIs (P < .05), and more antidepressants (P < .05).
Conclusion: Complex guideline-based interventions are effective in reducing agitated and disruptive behavior in nursing home residents with dementia. At the same time, increased prescription of ChEIs and antidepressants together with decreased neuroleptic prescription suggests an effect toward guideline-based pharmacotherapy.
Objectives: To investigate the efficacy of animal-assisted therapy (AAT) on symptoms of agitation/aggression and depression in nursing home residents with dementia in a randomized controlled trial. Previous studies have indicated that AAT has beneficial effects on neuropsychiatric symptoms in various psychiatric disorders but few studies have investigated the efficacy of AAT in patients suffering from dementia. Methods: Of 65 nursing home residents with dementia (mean [standard deviation] age: 81.8 [9.2] years; mean Mini-Mental State Examination score: 7.1 [0.7]), 27 matched pairs (N = 54) were randomly assigned to either treatment as usual or treatment as usual combined with AAT, administered over 10 weekly sessions. Blinded raters assessed cognitive impairment with the Mini-Mental State Examination, presence of agitation/aggression with the Cohen-Mansfield Agitation Inventory, and depression with the Dementia Mood Assessment Scale at baseline and during a period of 4 weeks after AAT intervention. Results: In the control group, symptoms of agitation/aggression and depression significantly increased over 10 weeks; in the intervention group, patients receiving combined treatment displayed constant frequency and severity of symptoms of agitation/aggression (F-1,F-48 = 6.43; p <0.05) and depression (F-1,F-48 = 26.54; p <0.001). Symptom amelioration did not occur in either group. Conclusions: AAT is a promising option for the treatment of agitation/aggression and depression in patients with dementia. Our results suggest that AAT may delay progression of neuropsychiatric symptoms in demented nursing home residents. Further research is needed to determine its long-time effects.
We explore the interaction between oculomotor control and language comprehension on the sentence level using two well-tested computational accounts of parsing difficulty. Previous work (Boston, Hale, Vasishth, & Kliegl, 2011) has shown that surprisal (Hale, 2001; Levy, 2008) and cue-based memory retrieval (Lewis & Vasishth, 2005) are significant and complementary predictors of reading time in an eyetracking corpus. It remains an open question how the sentence processor interacts with oculomotor control. Using a simple linking hypothesis proposed in Reichle, Warren, and McConnell (2009), we integrated both measures with the eye movement model EMMA (Salvucci, 2001) inside the cognitive architecture ACT-R (Anderson et al., 2004). We built a reading model that could initiate short Time Out regressions (Mitchell, Shen, Green, & Hodgson, 2008) that compensate for slow postlexical processing. This simple interaction enabled the model to predict the re-reading of words based on parsing difficulty. The model was evaluated in different configurations on the prediction of frequency effects on the Potsdam Sentence Corpus. The extension of EMMA with postlexical processing improved its predictions and reproduced re-reading rates and durations with a reasonable fit to the data. This demonstration, based on simple and independently motivated assumptions, serves as a foundational step toward a precise investigation of the interaction between high-level language processing and eye movement control.
Primary saccades are often followed by small secondary saccades, which are generally thought to reduce the distance between the saccade endpoint and target location. Accumulated evidence demonstrates that secondary saccades are subject to various influences, among which retinal feedback during postsaccadic fixation constitutes only one important signal. Recently, we reported that target eccentricity and an orientation bias influence the generation of secondary saccades. In the present study, we examine secondary saccades in the absence of postsaccadic visual feedback. Although extraretinal signals (e.g., efference copy) have received widespread attention in eye-movement studies, it is still unclear whether an extraretinal error signal contributes to the programming of secondary saccades. We have observed that secondary saccade latency and amplitude depend on primary saccade error despite the absence of postsaccadic visual feedback. Strong evidence for an extraretinal error signal influencing secondary saccade programming is given by the observation that secondary saccades are more likely to be oriented in a direction opposite to the primary saccade as primary saccade error shifts from target undershoot to overshoot. We further show how the functional relationship between primary saccade landing position and secondary saccade characteristics varies as a function of target eccentricity. We propose that initial target eccentricity and an extraretinal error signal codetermine the postsaccadic activity distribution in the saccadic motor map when no visual feedback is available.
Replicability of findings is at the heart of any empirical science. The aim of this article is to move the current replicability debate in psychology towards concrete recommendations for improvement. We focus on research practices but also offer guidelines for reviewers, editors, journal management, teachers, granting institutions, and university promotion committees, highlighting some of the emerging and existing practical solutions that can facilitate implementation of these recommendations. The challenges for improving replicability in psychological science are systemic. Improvement can occur only if changes are made at many levels of practice, evaluation, and reward.
Task demands and individual differences have been linked reliably to word skipping during reading. Such differences in fixation probability may imply a selection effect for multivariate analyses of eye-movement corpora if selection effects correlate with word properties of skipped words. For example, with fewer fixations on short and highly frequent words the power to detect parafoveal-on-foveal effects is reduced. We demonstrate that increasing the fixation probability on function words with a manipulation of the expected difficulty and frequency of questions reduces an age difference in skipping probability (i.e., old adults become comparable to young adults) and helps to uncover significant parafoveal-on-foveal effects in this group of old adults. We discuss implications for the comparison of results of eye-movement research based on multivariate analysis of corpus data with those from display-contingent manipulations of target words.
In many hydrological applications, ground-wave velocity measurements are increasingly used to map and monitor shallow soil water content. In this study, we propose an automated spectral velocity analysis method to determine the direct ground-wave (DGW) velocity from common midpoint (CMP) or multi-offset ground-penetrating radar (GPR) data. The method introduced in this paper is a variation of the well-known spectral velocity analysis for seismic and GPR reflection events where velocity spectra are computed using different coherency measures along hyperbolas following the normal moveout model. Here, the unnormalized cross-correlation is computed between waveforms across data gathers that are corrected with a linear moveout equation using a predefined range of velocities. Peaks in the resulting velocity spectra identify linear events in the GPR data gathers like DGW events and allow for estimating the corresponding velocities. In addition to obtaining a DGW velocity measurement, we propose a robust method to estimate the associated velocity uncertainties based on the width of the peak in the calculated velocity spectrum. Our proposed method is tested on synthetic data examples to evaluate the influence of subsurface velocity, surveying geometry and signal frequency on the accuracy of estimated ground-wave velocities. In addition, we investigate the influence of such velocity uncertainties on subsequent soil water content estimates using an established petrophysical relationship. Furthermore, we apply our approach to analyse field data, which were collected across a test site in Canada to monitor a wide range of seasonal soil moisture variations. A comparison between our spectral velocity estimates and results derived from manually picked ground-wave arrivals shows good agreement, which illustrates that our spectral velocity analysis is a feasible tool to analyse DGW arrivals in multi-offset GPR data gathers in an objective and more automated manner.
Haberlea rhodopensis is a resurrection species with extreme resistance to drought stress and desiccation but also with ability to withstand low temperatures and freezing stress. In order to identify biochemical strategies which contribute to Haberlea's remarkable stress tolerance, the metabolic reconfiguration of H. rhodopensis during low temperature (4 degrees C) and subsequent return to optimal temperatures (21 degrees C) was investigated and compared with that of the stress tolerant Thellungiella halophyla and the stress sensitive Arabidopsis thaliana. Metabolic analysis by GC-MS revealed intrinsic differences in the metabolite levels of the three species even at 21 degrees C. H. rhodopensis had significantly more raffinose, melibiose, trehalose, rhamnose, myo-inositol, sorbitol, galactinol, erythronate, threonate, 2-oxoglutarate, citrate, and glycerol than the other two species. A. thaliana had the highest levels of putrescine and fumarate, while T halophila had much higher levels of several amino acids, including alanine, asparagine, beta-alanine, histidine, isoleucine, phenylalanine, serine, threonine, and valine. In addition, the three species responded differently to the low temperature treatment and the subsequent recovery, especially with regard to the sugar metabolism. Chilling induced accumulation of maltose in H. rhodopensis and raffinose in A. thaliana but the raffinose levels in low temperature exposed Arabidopsis were still much lower than these in unstressed Haberlea. While all species accumulated sucrose during chilling, that accumulation was transient in H. rhodopensis and A. thaliana but sustained in T halophila after the return to optimal temperature. Thus, Haberlea's metabolome appeared primed for chilling stress but the low temperature acclimation induced additional stress-protective mechanisms. A diverse array of sugars, organic acids, and polyols constitute Haberlea's main metabolic defence mechanisms against chilling, while accumulation of amino acids and amino acid derivatives contribute to the low temperature acclimation in Arabidopsis and Thellungiella. Collectively, these results show inherent differences in the metabolomes under the ambient temperature and the strategies to respond to low temperature in the three species.
Molecular mechanisms of desiccation tolerance in the resurrection glacial relic Haberlea rhodopensis
(2013)
Haberlea rhodopensis is a resurrection plant with remarkable tolerance to desiccation. Haberlea exposed to drought stress, desiccation, and subsequent rehydration showed no signs of damage or severe oxidative stress compared to untreated control plants. Transcriptome analysis by next-generation sequencing revealed a drought-induced reprogramming, which redirected resources from growth towards cell protection. Repression of photosynthetic and growth-related genes during water deficiency was concomitant with induction of transcription factors (members of the NAC, NF-YA, MADS box, HSF, GRAS, and WRKY families) presumably acting as master switches of the genetic reprogramming, as well as with an upregulation of genes related to sugar metabolism, signaling, and genes encoding early light-inducible (ELIP), late embryogenesis abundant (LEA), and heat shock (HSP) proteins. At the same time, genes encoding other LEA, HSP, and stress protective proteins were constitutively expressed at high levels even in unstressed controls. Genes normally involved in tolerance to salinity, chilling, and pathogens were also highly induced, suggesting a possible cross-tolerance against a number of abiotic and biotic stress factors. A notable percentage of the genes highly regulated in dehydration and subsequent rehydration were novel, with no sequence homology to genes from other plant genomes. Additionally, an extensive antioxidant gene network was identified with several gene families possessing a greater number of antioxidant genes than most other species with sequenced genomes. Two of the transcripts most abundant during all conditions encoded catalases and five more catalases were induced in water-deficient samples. Using the pharmacological inhibitor 3-aminotriazole (AT) to compromise catalase activity resulted in increased sensitivity to desiccation. Metabolome analysis by GC or LC-MS revealed accumulation of sucrose, verbascose, spermidine, and gamma-aminobutyric acid during drought, as well as particular secondary metabolites accumulating during rehydration. This observation, together with the complex antioxidant system and the constitutive expression of stress protective genes suggests that both constitutive and inducible mechanisms contribute to the extreme desiccation tolerance of H. rhodopensis.
Natural genetic diversity provides a powerful tool to study the complex interrelationship between metabolism and growth. Profiling of metabolic traits combined with network-based and statistical analyses allow the comparison of conditions and identification of sets of traits that predict biomass. However, it often remains unclear why a particular set of metabolites is linked with biomass and to what extent the predictive model is applicable beyond a particular growth condition. A panel of 97 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions was grown in near-optimal carbon and nitrogen supply, restricted carbon supply, and restricted nitrogen supply and analyzed for biomass and 54 metabolic traits. Correlation-based metabolic networks were generated from the genotype-dependent variation in each condition to reveal sets of metabolites that show coordinated changes across accessions. The networks were largely specific for a single growth condition. Partial least squares regression from metabolic traits allowed prediction of biomass within and, slightly more weakly, across conditions (cross-validated Pearson correlations in the range of 0.27-0.58 and 0.21-0.51 and P values in the range of <0.001-<0.13 and <0.001-<0.023, respectively). Metabolic traits that correlate with growth or have a high weighting in the partial least squares regression were mainly condition specific and often related to the resource that restricts growth under that condition. Linear mixed-model analysis using the combined metabolic traits from all growth conditions as an input indicated that inclusion of random effects for the conditions improves predictions of biomass. Thus, robust prediction of biomass across a range of conditions requires condition-specific measurement of metabolic traits to take account of environment-dependent changes of the underlying networks.
Early detection of salt stress is vital for plant survival and growth. Still, the molecular processes controlling early salt stress perception and signaling are not fully understood. Here, we identified SALT-RESPONSIVE ERF1 (SERF1), a rice (Oryza sativa) transcription factor (TF) gene that shows a root-specific induction upon salt and hydrogen peroxide (H2O2) treatment. Loss of SERF1 impairs the salt-inducible expression of genes encoding members of a mitogen-activated protein kinase (MAPK) cascade and salt tolerance-mediating TFs. Furthermore, we show that SERF1-dependent genes are H2O2 responsive and demonstrate that SERF1 binds to the promoters of MAPK KINASE KINASE6 (MAP3K6), MAPK5, DEHYDRATION-RESPONSIVE ELEMENT BINDING2A (DREB2A), and ZINC FINGER PROTEIN179 (ZFP179) in vitro and in vivo. SERF1 also directly induces its own gene expression. In addition, SERF1 is a phosphorylation target of MAPK5, resulting in enhanced transcriptional activity of SERF1 toward its direct target genes. In agreement, plants deficient for SERF1 are more sensitive to salt stress compared with the wild type, while constitutive overexpression of SERF1 improves salinity tolerance. We propose that SERF1 amplifies the reactive oxygen species-activated MAPK cascade signal during the initial phase of salt stress and translates the salt-induced signal into an appropriate expressional response resulting in salt tolerance.
Developmental senescence is a coordinated physiological process in plants and is critical for nutrient redistribution from senescing leaves to newly formed sink organs, including young leaves and developing seeds. Progress has been made concerning the genes involved and the regulatory networks controlling senescence. The resulting complex metabolome changes during senescence have not been investigated in detail yet. Therefore, we conducted a comprehensive profiling of metabolites, including pigments, lipids, sugars, amino acids, organic acids, nutrient ions, and secondary metabolites, and determined approximately 260 metabolites at distinct stages in leaves and siliques during senescence in Arabidopsis (Arabidopsis thaliana). This provided an extensive catalog of metabolites and their spatiotemporal cobehavior with progressing senescence. Comparison with silique data provides clues to source-sink relations. Furthermore, we analyzed the metabolite distribution within single leaves along the basipetal sink-source transition trajectory during senescence. Ceramides, lysolipids, aromatic amino acids, branched chain amino acids, and stress-induced amino acids accumulated, and an imbalance of asparagine/aspartate, glutamate/glutamine, and nutrient ions in the tip region of leaves was detected. Furthermore, the spatiotemporal distribution of tricarboxylic acid cycle intermediates was already changed in the presenescent leaves, and glucosinolates, raffinose, and galactinol accumulated in the base region of leaves with preceding senescence. These results are discussed in the context of current models of the metabolic shifts occurring during developmental and environmentally induced senescence. As senescence processes are correlated to crop yield, the metabolome data and the approach provided here can serve as a blueprint for the analysis of traits and conditions linking crop yield and senescence.
Growth regulation is an important aspect of plant adaptation during environmental perturbations. Here, the role of MULTIPASS (OsMPS), an R2R3-type MYB transcription factor of rice, was explored. OsMPS is induced by salt stress and expressed in vegetative and reproductive tissues. Over-expression of OsMPS reduces growth under non-stress conditions, while knockdown plants display increased biomass. OsMPS expression is induced by abscisic acid and cytokinin, but is repressed by auxin, gibberellin and brassinolide. Growth retardation caused by OsMPS over-expression is partially restored by auxin application. Expression profiling revealed that OsMPS negatively regulates the expression of EXPANSIN (EXP) and cell-wall biosynthesis as well as phytohormone signaling genes. Furthermore, the expression of OsMPS-dependent genes is regulated by auxin, cytokinin and abscisic acid. Moreover, we show that OsMPS is a direct upstream regulator of OsEXPA4, OsEXPA8, OsEXPB2, OsEXPB3, OsEXPB6 and the endoglucanase genes OsGLU5 and OsGLU14. The multiple responses of OsMPS and its target genes to various hormones suggest an integrative function of OsMPS in the cross-talk between phytohormones and the environment to regulate adaptive growth.
Understanding metabolic acclimation of plants to challenging environmental conditions is essential for dissecting the role of metabolic pathways in growth and survival. As stresses involve simultaneous physiological alterations across all levels of cellular organization, a comprehensive characterization of the role of metabolic pathways in acclimation necessitates integration of genome-scale models with high-throughput data. Here, we present an integrative optimization-based approach, which, by coupling a plant metabolic network model and transcriptomics data, can predict the metabolic pathways affected in a single, carefully controlled experiment. Moreover, we propose three optimization-based indices that characterize different aspects of metabolic pathway behavior in the context of the entire metabolic network. We demonstrate that the proposed approach and indices facilitate quantitative comparisons and characterization of the plant metabolic response under eight different light and/or temperature conditions. The predictions of the metabolic functions involved in metabolic acclimation of Arabidopsis thaliana to the changing conditions are in line with experimental evidence and result in a hypothesis about the role of homocysteine-to-Cys interconversion and Asn biosynthesis. The approach can also be used to reveal the role of particular metabolic pathways in other scenarios, while taking into consideration the entirety of characterized plant metabolism.