Efectos sobre los procesos cognitivos del entrenamiento basado en doble tarea en personas con enfermedad de Parkinson: una revisión sistemática / Effects on cognitive processes of dual-task training in people with Parkinson’s disease: a systematic review

Introducción: La doble tarea es una intervención no farmacológica en personas con condiciones neurodegenerativas, utilizada en la enfermedad de Parkinson (EP), principalmente para favorecer el desempeño motor. El objetivo de esta revisión es reunir la evidencia actual sobre cómo el entrenamiento de doble tarea afecta a los procesos cognitivos en personas que presenten EP. Material y métodos. Se desarrolló una revisión sistemática, aplicando las directrices de PRISMA, incluyendo artículos obtenidos en las bases de datos de PubMed, Web of Science, Science Direct y Springer Link. La calidad metodológica se evaluó mediante PEDro y ROBINS-I. Resultados: Doce artículos cumplieron con los criterios de inclusión y exclusión: nueve de ellos corresponden a ensayos controlados aleatorizados y los tres restantes fueron estudios no aleatorizados. Se identificaron mejoras en la atención y las funciones ejecutivas, aunque la diversidad en enfoques y duración dificulta llegar a conclusiones definitivas. Conclusiones: Es crucial expandir la investigación, estandarizando los programas de intervención. Del mismo modo, es importante llevar a cabo estudios longitudinales y controlados aleatorizados en muestras representativas que permitan llegar a conclusiones aplicables a otros contextos.(AU)

Introduction: Dual-tasking is a non-pharmacological intervention in people with neurodegenerative conditions, and is used in Parkinson’s disease (PD), primarily to enhance motor performance. The aim of this review is to compile the current evidence on how dual-task training affects cognitive processes in people with PD. Material and methods: A systematic review was undertaken, applying PRISMA guidelines, which included articles obtained from the PubMed, Web of Science, Science Direct and Springer Link databases. Methodological quality was assessed using PEDro and ROBINS-I. Results: Twelve articles met the inclusion and exclusion criteria: nine of them were randomized controlled trials, and the remaining three were non-randomized studies. Improvements in attention and executive functions were identified, although the diversity of approaches and duration means that reaching definitive conclusions is difficult. Conclusions: Increased research and standardized intervention programmes are essential. Longitudinal and randomized controlled studies in representative samples which provide conclusions that are applicable to other contexts are also important.(AU)

Changed sleep according to weighted blanket adherence in a 16-week sleep intervention among children with attention-deficit/hyperactivity disorder.

STUDY OBJECTIVES: To examine differences in sample characteristics and longitudinal sleep outcomes according to weighted blanket adherence. METHODS: Children with attention-deficit/hyperactivity disorder (ADHD) (n =94), mean age 9.0 (sd 2.2, range 6-14) participated in a 16-week sleep intervention with weighted blankets (WB). Children were classified as WB adherent (use of WB ≥ 4 nights/week) or non-adherent (use of WB ≤ 3 nights/week). Changes in objectively measured sleep by actigraphy, parent-reported sleep problems (Children's Sleep Habits Questionnaire (CSHQ)) and child-reported Insomnia Severity Index (ISI) were evaluated according to adherence with mixed effect models. Gender, age, and ADHD subtype were examined as potential moderators. RESULTS: Children adherent to WBs (48/94) showed an early response in sleep outcomes and an acceptance of the WB after four weeks of use as well as a decrease in parent- (CSHQ) (-5.73, P = .000) and child-reported sleep problems (ISI) (-4.29, P = .005) after 16 weeks. The improvement in sleep was larger among WB adherent vs. non-adherent (between-group difference: CSHQ: -2.09, P = .038; ISI: -2.58, P =.007). Total sleep time was stable for children adherent to WB but decreased for non-adherent (between-group difference: +16.90, P = .019). CONCLUSIONS: An early response in sleep and acceptance of the WB predicted later adherence to WBs. Improvements in sleep were more likely among WB adherents vs. non-adherents. Children with ADHD may thus benefit from using WBs to handle their sleep problems.

Contextual cueing during lethal force training: How target design and repetition can alter threat assessments.

Lethal force training requires individuals to make threat assessments, which involves holistic scenario processing to identify potential threats. Photorealistic targets can make threat/non-threat judgments substantially more genuine and challenging compared to simple cardboard or silhouette targets. Unfortunately, repeated target use also brings unintended consequences that could invalidate threat assessment processes conducted during training. Contextually rich or unique targets could be implicitly memorable in a way that allows observers to recall weapon locations rather than forcing observers to conduct a naturalistic assessment. Experiment 1 demonstrated robust contextual cueing effects in a well-established shoot/don't-shoot stimulus set, and Experiment 2 extended this finding from complex scene stimuli to simple actor-only stimuli. Experiment 3 demonstrated that these effects also occurred among trained professionals using rifles rather than computer-based tasks. Taken together, these findings demonstrate the potential for uncontrolled target repetition to alter the fundamental processes of threat assessment during lethal force training.

Gestational PBDE Concentrations, Persistent Externalizing, and Emerging Internalizing Behaviors in Adolescents: The HOME Study.

BACKGROUND: Polybrominated diphenyl ethers (PBDEs) are ubiquitous environmental chemicals used as flame retardants in commercial and consumer products. Gestational PBDE concentrations are associated with adverse behaviors in children; however, the persistence of these associations into adolescence remains understudied. OBJECTIVE: We estimated the association of gestational PBDE serum concentrations with early adolescent self- and caregiver-reported behaviors at age 12 years and determined the consistency with previously observed associations in childhood with caregiver-reported behaviors in a prospective pregnancy and birth cohort. METHODS: We measured maternal serum concentrations of five individual PBDE congeners and created a summary exposure variable (∑5BDE: -28, -47, -99, -100 and -153) during pregnancy. At age 12 years, we assessed behaviors for 237 adolescents using self- and caregiver-reports with the Behavioral Assessment System for Children-3 (BASC3). We used multivariable linear regression models to estimate covariate-adjusted associations of lipid standardized, log10-transformed gestational PBDE concentrations with BASC3 scores. We obtained estimates and 95% confidence intervals through a bootstrapping approach. We evaluated potential effect measure modification (EMM) of adolescent sex by examining sex-stratified regression models and estimating the EMM p-values. RESULTS: Gestational PBDE concentrations were positively associated with adolescent-reported BASC3 composite indices for inattention & hyperactivity (BDE-28, -47, -99, -100, ∑5BDE), internalizing problems (BDE-28, -47, -99), functional impairment (BDE-28, ∑5BDE), and emotional symptoms (BDE-28). Gestational PBDE concentrations were positively associated with caregiver-reported BASC3 composite indices for externalizing problems (BDE-28, -47, -99, -100, -153, ∑5BDE) and behavioral symptoms (BDE-99). For caregiver reported behaviors, we observed stronger associations with gestational BDE concentrations among males, especially for executive functioning (BDE-28, -47, -99, -100, ∑5BDE). DISCUSSION: Gestational PBDE serum concentrations were associated with self-reported internalizing and externalizing behavior problems in early adolescence. Caregiver-reported externalizing behaviors recognized during childhood remain associated with gestational PBDE concentrations and persist into early adolescence. Internalizing behaviors were less recognized by caregivers.

Neuropsychological functioning of pediatric patients with long COVID.

Objective: To determine the neurocognitive profile for youth with long COVID presenting with cognitive concerns. Method: This study is a case series of 54 pediatric patients (65% female, Mage = 13.48, SDage = 3.10, 5-19) with long COVID who were referred for neuropsychological testing from a post-COVID-19 multidisciplinary clinic. The outcomes of interest were neuropsychological test scores and parent ratings of mood, attention, and executive functioning. The percentage of patients with neuropsychological test scores below the 9th percentile (below average range) and those with at-risk or clinically significant scores (T-scores > 59) on parent-informant inventories were computed. Results: A portion of children with long COVID showed weaknesses in sustained attention (29%) and divided attention (35%). This portion of patients did not significantly differ when comparing patients with and without pre-existing attention and mood concerns. A high percentage of parents reported at-risk to clinically significant concerns for cognitive regulation (53%), depression (95%), anxiety (85%), and inattention (66%) on standardized questionnaires. Conclusions: The present case series showed that approximately a third of children with long COVID demonstrate objective weaknesses on sustained and divided attention tasks but were largely intact in other domains of neuropsychological functioning. Importantly, children with long COVID had similar difficulties in attention, regardless of pre-existing attention or mood concerns. Parents reported high rates of mood, anxiety, and executive functioning difficulties which likely impact daily functioning. Attention and emotional regulation should be closely monitored and treated as necessary in pediatric patients with long COVID to aid functional recovery.

Cannabis Use Characteristics Associated with Self-Reported Cognitive Function in a Nationally Representative U.S. sample.

BACKGROUND: With increases in cannabis use and potency, there is a need to improve our understanding of the impact of use on cognitive function. Previous research indicates long-term cannabis use may have a negative effect on executive function. Few studies have examined persistence of it in protracted abstinence, and there is limited evidence of predictors of worse cognitive function in current and former users. In this study, we aim to evaluate the associations between cannabis use status (current, former, and never use) and self-report cognition. Further, we investigate if cannabis use characteristics predict self-report cognitive function. METHODS: Cross-sectional cannabis use data from the National Epidemiological Survey on Alcohol and Related Conditions-III (NESARC-III), a national survey (N = 36,309) conducted in the USA between 2012 and 2013 were used alongside the Executive Function Index scales. The data were analyzed by using Ordinary Least Squares regression. RESULTS: Current (N = 3,681, Female = 37.7%) and former users (N = 7,448, Female = 45.4%) reported poorer cognition than never users (N = 24,956, Female = 56.6%). Self-reported cognition of former users was in-between that of current and never users. Several cannabis use characteristics were associated with self-reported cognition in current and former users. CONCLUSION: While prospective studies are required to confirm, findings suggest cannabis use is linked to worse cognition. There may be some limited recovery of cognition in former users and some cannabis use characteristics predict impairment. These findings add to our understanding of the cognitive impact of cannabis use. As worse cognitive function may impact relapse, findings have implications for personalization of cannabis use disorder treatment.

Acute effects of mango leaf extract on cognitive function in healthy adults: a randomised, double-blind, placebo-controlled crossover study.

Introduction: Extracts made from the leaves of the edible mango plant (Mangifera indica L., Anacardiaceae) have a long history of medicinal usage, most likely due to the presence of high levels of mangiferin, a polyphenol compound. Previous research has demonstrated that mango leaf extract (MLE) can beneficially modulate cognitive function in both animals and humans. This study aimed to assess the effects of an acute dose of 300 mg MLE (standardised to contain ≥60% mangiferin) on cognitive performance and mood in healthy adults. Methods: In this double-blind, placebo-controlled, crossover study, 114 healthy men and women (18-43 years) received either MLE or a matched placebo at each testing visit (separated by at least 7 days). Cognitive performance (including the cognitive demand battery) and mood were measured at 30, 180, and 300 min post-dose. Results: The results showed that, compared to placebo, the group taking MLE displayed a significant increase in serial 3 s and serial 7 s subtraction errors overall. There were no other significant effects on cognitive performance. Discussion: The results of the current study suggest that the consumption of 300 mg MLE in the absence of an observed multitasking psychological stressor does not improve cognitive performance or mood at up to 300 min post-dose. Due to the very limited nature of the effects and since they were observed among many analyses, these findings should be treated with caution.Clinical trial registration: http://ClinicalTrials.gov, identifier [NCT05182450].

Distractor inhibition by alpha oscillations is controlled by an indirect mechanism governed by goal-relevant information.

The role of alpha oscillations (8-13 Hz) in cognition is intensively investigated. While intracranial animal recordings demonstrate that alpha oscillations are associated with decreased neuronal excitability, it is been questioned whether alpha oscillations are under direct control from frontoparietal areas to suppress visual distractors. We here point to a revised mechanism in which alpha oscillations are controlled by an indirect mechanism governed by the load of goal-relevant information - a view compatible with perceptual load theory. We will outline how this framework can be further tested and discuss the consequences for network dynamics and resource allocation in the working brain.

A transformer-based approach empowered by a self-attention technique for semantic segmentation in remote sensing.

Semantic segmentation of Remote Sensing (RS) images involves the classification of each pixel in a satellite image into distinct and non-overlapping regions or segments. This task is crucial in various domains, including land cover classification, autonomous driving, and scene understanding. While deep learning has shown promising results, there is limited research that specifically addresses the challenge of processing fine details in RS images while also considering the high computational demands. To tackle this issue, we propose a novel approach that combines convolutional and transformer architectures. Our design incorporates convolutional layers with a low receptive field to generate fine-grained feature maps for small objects in very high-resolution images. On the other hand, transformer blocks are utilized to capture contextual information from the input. By leveraging convolution and self-attention in this manner, we reduce the need for extensive downsampling and enable the network to work with full-resolution features, which is particularly beneficial for handling small objects. Additionally, our approach eliminates the requirement for vast datasets, which is often necessary for purely transformer-based networks. In our experimental results, we demonstrate the effectiveness of our method in generating local and contextual features using convolutional and transformer layers, respectively. Our approach achieves a mean dice score of 80.41%, outperforming other well-known techniques such as UNet, Fully-Connected Network (FCN), Pyramid Scene Parsing Network (PSP Net), and the recent Convolutional vision Transformer (CvT) model, which achieved mean dice scores of 78.57%, 74.57%, 73.45%, and 62.97% respectively, under the same training conditions and using the same training dataset.

High-intensity interval training (HIIT) and slow breathing interventions alleviate premature ejaculation (PE) symptoms.

Background: Physical exercise may alleviate premature ejaculation symptoms, a prevalent male sexual dysfunction linked to a series of negative outcomes for men and their partners. Objective: We investigated the effectiveness of high-intensity interval training (HIIT) and slow breathing interventions on premature ejaculation symptoms and their relation to autonomic activity and attention regulation. Method: Chinese adult men (N = 76, M = 21.89, SD = 3.32) with premature ejaculation completed one of the two-week interventions in their homes or as participants in a normal breathing control group; they reported their age, height, weight, physical activity level, premature ejaculation symptoms, and attention regulation. In the HIIT group, 26 participants engaged in a 7-minute HIIT each day. In the slow breathing group, 25 participants performed 7-minute slow breathing exercises per day while the 25 participants in the normal breathing group similarly performed normal breathing exercises. All participants measured their heart rate once before and five times (with one-minute intervals) after the intervention. When participants had penile-vaginal sex with their partners, they measured their heart rate once after ejaculation. Results: Time × Intervention interaction was significant with lower levels of premature ejaculation symptoms on Days 12, 13, and 14 in the HIIT group (M ± SD = 16.19 ± 3.45, 15.96 ± 3.43, and 15.15 ± 3.62) compared to the normal breathing group (M ± SD = 17.68 ± 3.06, 17.68 ± 3.15, and 17.44 ± 3.25). Higher levels of attention regulation were associated with fewer premature ejaculation symptoms. We also found that a larger increase in heart rate from resting to after sex was associated with fewer premature ejaculation symptoms. Conclusion: Compared to the control group, the efficacy of two weeks of HIIT exercise in mitigating PE symptoms suggests its potential as a novel treatment for PE.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading.

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

MMGAT: a graph attention network framework for ATAC-seq motifs finding.

BACKGROUND: Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths. GNN-based methods has the limitation of using the edge weight information directly, makes it difficult to aggregate the neighboring nodes' information more efficiently when representing node embedding. RESULTS: To address this challenge, we developed a novel graph attention network framework named MMGAT, which employs an attention mechanism to adjust the attention coefficients among different nodes. And then MMGAT finds multiple ATAC-seq motifs based on the attention coefficients of sequence nodes and k-mer nodes as well as the coexisting probability of k-mers. Our approach achieved better performance on the human ATAC-seq datasets compared to existing tools, as evidenced the highest scores on the precision, recall, F1_score, ACC, AUC, and PRC metrics, as well as finding 389 higher quality motifs. To validate the performance of MMGAT in predicting TFBSs and finding motifs on more datasets, we enlarged the number of the human ATAC-seq datasets to 180 and newly integrated 80 mouse ATAC-seq datasets for multi-species experimental validation. Specifically on the mouse ATAC-seq dataset, MMGAT also achieved the highest scores on six metrics and found 356 higher-quality motifs. To facilitate researchers in utilizing MMGAT, we have also developed a user-friendly web server named MMGAT-S that hosts the MMGAT method and ATAC-seq motif finding results. CONCLUSIONS: The advanced methodology MMGAT provides a robust tool for finding ATAC-seq motifs, and the comprehensive server MMGAT-S makes a significant contribution to genomics research. The open-source code of MMGAT can be found at https://github.com/xiaotianr/MMGAT , and MMGAT-S is freely available at https://www.mmgraphws.com/MMGAT-S/ .

The mediating effect of attentional impulsivity between mindfulness and problematic smartphone use.

OBJECTIVE: Problematic smartphone use has been linked to lower levels of mindfulness, impaired attentional function, and higher impulsivity. This study aimed to identify the psychological mechanisms of problematic smartphone use by exploring the relationship between addictive smartphone use, mindfulness, attentional function and impulsivity. METHODS: Ninety participants were evaluated with the smartphone addiction proneness scale and classified into the problematic smartphone use group (n = 42; 24 women; mean age: 27.6 ± 7.2 years) or normal use group (n = 48; 22 women; mean age: 30.1 ± 5.7 years). All participants completed self-report questionnaires evaluating their trait impulsivity and mindfulness and attention tests that assessed selective, sustained and divided attention. We compared the variables between the groups and explored the relationship between mindfulness, attentional function, impulsivity and addictive smartphone use through mediation analysis. RESULTS: The problematic smartphone use group showed higher trait impulsivity and lower mindfulness than the normal use group. There were no significant group differences in performance on attention tests. Levels of addictive smartphone use were significantly correlated with higher levels of trait impulsivity and lower levels of mindfulness, but not with performance on attention tests. Mediation analysis showed that acting with awareness, an aspect of mindfulness, reduces the degree of addictive smartphone use through attentional impulsivity, one of the trait impulsivity. CONCLUSION: Acting without sufficient awareness could influence addictive smartphone use by mediating attentional impulsivity. This supports that executive control deficits, reflected in high attentional impulsivity, contribute to problematic smartphone use. Our findings imply that mindfulness-based interventions can enhance executive control over smartphone use by promoting awareness.

Bidirectional brain-body interactions during natural story listening.

Narratives can synchronize neural and physiological signals between individuals, but the relationship between these signals, and the underlying mechanism, is unclear. We hypothesized a top-down effect of cognition on arousal and predicted that auditory narratives will drive not only brain signals but also peripheral physiological signals. We find that auditory narratives entrained gaze variation, saccade initiation, pupil size, and heart rate. This is consistent with a top-down effect of cognition on autonomic function. We also hypothesized a bottom-up effect, whereby autonomic physiology affects arousal. Controlled breathing affected pupil size, and heart rate was entrained by controlled saccades. Additionally, fluctuations in heart rate preceded fluctuations of pupil size and brain signals. Gaze variation, pupil size, and heart rate were all associated with anterior-central brain signals. Together, these results suggest bidirectional causal effects between peripheral autonomic function and central brain circuits involved in the control of arousal.

The time course of feature-selective attention inside and outside the focus of spatial attention.

Research on attentional selection of stimulus features has yielded seemingly contradictory results. On the one hand, many experiments in humans and animals have observed a "global" facilitation of attended features across the entire visual field, even when spatial attention is focused on a single location. On the other hand, several event-related potential studies in humans reported that attended features are enhanced at the attended location only. The present experiment demonstrates that these conflicting results can be explained by differences in the timing of attentional allocation inside and outside the spatial focus of attention. Participants attended to fields of either red or blue randomly moving dots on either the left or right side of fixation with the task of detecting brief coherent motion targets. Recordings of steady-state visual evoked potentials elicited by the flickering stimuli allowed concurrent measurement of the time course of feature-selective attention in visual cortex on both the attended and the unattended sides. The onset of feature-selective attentional modulation on the attended side occurred around 150 ms earlier than on the unattended side. This finding that feature-selective attention is not spatially global from the outset but extends to unattended locations after a temporal delay resolves previous contradictions between studies finding global versus hierarchical selection of features and provides insight into the fundamental relationship between feature-based and location-based (spatial) attention mechanisms.

Segmentation of bone surface from ultrasound using a lightweight network UBS-Net.

Objective. Ultrasound-assisted orthopaedic navigation held promise due to its non-ionizing feature, portability, low cost, and real-time performance. To facilitate the applications, it was critical to have accurate and real-time bone surface segmentation. Nevertheless, the imaging artifacts and low signal-to-noise ratios in the tomographical B-mode ultrasound (B-US) images created substantial challenges in bone surface detection. In this study, we presented an end-to-end lightweight US bone segmentation network (UBS-Net) for bone surface detection.Approach. We presented an end-to-end lightweight UBS-Net for bone surface detection, using the U-Net structure as the base framework and a level set loss function for improved sensitivity to bone surface detectability. A dual attention (DA) mechanism was introduced at the end of the encoder, which considered both position and channel information to obtain the correlation between the position and channel dimensions of the feature map, where axial attention (AA) replaced the traditional self-attention (SA) mechanism in the position attention module for better computational efficiency. The position attention and channel attention (CA) were combined with a two-class fusion module for the DA map. The decoding module finally completed the bone surface detection.Main Results. As a result, a frame rate of 21 frames per second (fps) in detection were achieved. It outperformed the state-of-the-art method with higher segmentation accuracy (Dice similarity coefficient: 88.76% versus 87.22%) when applied the retrospective ultrasound (US) data from 11 volunteers.Significance. The proposed UBS-Net for bone surface detection in ultrasound achieved outstanding accuracy and real-time performance. The new method out-performed the state-of-the-art methods. It had potential in US-guided orthopaedic surgery applications.

Multi-branch myocardial infarction detection and localization framework based on multi-instance learning and domain knowledge.

Objective. Myocardial infarction (MI) is a serious cardiovascular disease that can cause irreversible damage to the heart, making early identification and treatment crucial. However, automatic MI detection and localization from an electrocardiogram (ECG) remain challenging. In this study, we propose two models, MFB-SENET and MFB-DMIL, for MI detection and localization, respectively.Approach. The MFB-SENET model is designed to detect MI, while the MFB-DMIL model is designed to localize MI. The MI localization model employs a specialized attention mechanism to integrate multi-instance learning with domain knowledge. This approach incorporates handcrafted features and introduces a new loss function called lead-loss, to improve MI localization. Grad-CAM is employed to visualize the decision-making process.Main Results.The proposed method was evaluated on the PTB and PTB-XL databases. Under the inter-patient scheme, the accuracy of MI detection and localization on the PTB database reached 93.88% and 67.17%, respectively. The accuracy of MI detection and localization on the PTB-XL database were 94.89% and 85.83%, respectively.Significance. Our method achieved comparable or better performance than other state-of-the-art algorithms. The proposed method combined deep learning and medical domain knowledge, demonstrates effectiveness and reliability, holding promise as an efficient MI diagnostic tool to assist physicians in formulating accurate diagnoses.

Switch to Lisdexamfetamine in the Treatment of Attention-Deficit Disorder at a Psychiatric Outpatient Clinic for School-Aged Children: A Danish Cohort Study.

Objectives: This study aimed to examine switch from first-line methylphenidate (MPH) to lisdexamfetamine (LDX) in school-aged children with attention-deficit/hyperactivity disorder (ADHD). Methods: This is a retrospective observational study based on systematic review of patient records of all children (7-13 years) diagnosed with ADHD and referred to a Danish specialized outpatient clinic. The study included 394 children switching from MPH to LDX as either second-line or third-line treatment (atomoxetine [ATX] as second-line treatment) during the study period from April 1, 2013, to November 5, 2019. Results: One in five children switched from MPH to LDX at some point during the study period. The most frequent reasons for switching to LDX were adverse effects (AEs; 70.0% for MPH, 68.3% for ATX) and lack of efficiency (52.0% for MPH, 72.7% for ATX). Top five AEs of LDX were decreased appetite (62.4%), insomnia (28.7%), irritability/aggression (26.1%), weight decrease (21.1%), and mood swings (13.9%). MPH and LDX had similar AE profiles, yet most AEs were less frequent after switching to LDX. At the end of the study period, the majority were prescribed LDX as second-line rather than third-line treatment (86.1% in 2019). However, the likelihood of LDX as second-line treatment decreased with the number of psychiatric comorbidities, ADHD symptom severity as assessed by parents, and if AEs were a reason for MPH discontinuation. Among children observed for at least 1 year after initiation of LDX, 41.3% continued LDX treatment for a year or longer. LDX continuation was less likely if AEs were a reason for MPH discontinuation. Similarly to MPH and ATX, the most frequent reasons for LDX discontinuation were AEs (74.4%) and lack of efficiency (34.7%). Implications: The findings support LDX as an important option in the personalized treatment of children with ADHD and may support prescribers in the clinical decision-making on switching medication.

Activator of KAT3 histone acetyltransferase family ameliorates a neurodevelopmental disorder phenotype in the syntaxin 1A ablated mouse model.

Syntaxin-1A (stx1a) repression causes a neurodevelopmental disorder phenotype, low latent inhibition (LI) behavior, by disrupting 5-hydroxytryptaminergic (5-HTergic) systems. Herein, we discovered that lysine acetyltransferase (KAT) 3B increases stx1a neuronal transcription and TTK21, a KAT3 activator, induces stx1a transcription and 5-HT release in vitro. Furthermore, glucose-derived CSP-TTK21 could restore decreased stx1a expression, 5-HTergic systems in the brain, and low LI in stx1a (+/-) mice by crossing the blood-brain barrier, whereas the KAT3 inhibitor suppresses stx1a expression, 5-HTergic systems, and LI behaviors in wild-type mice. Finally, in wild-type and stx1a (-/-) mice treated with IKK inhibitors and CSP-TTK21, respectively, we show that KAT3 activator-induced LI improvement is a direct consequence of KAT3B-stx1a pathway, not a side effect. In conclusion, KAT3B can positively regulate stx1a transcription in neurons, and increasing neuronal stx1a expression and 5-HTergic systems by a KAT3 activator consequently improves the low LI behavior in the stx1a ablation mouse model.

Assessment and report of individual symptoms in studies of delirium in postoperative populations: a systematic review.

OBJECTIVES: Delirium is most often reported as present or absent. Patients with symptoms falling short of the diagnostic criteria for delirium fall into 'no delirium' or 'control' groups. This binary classification neglects individual symptoms and may be hindering identification of the pathophysiology underlying delirium. This systematic review investigates which individual symptoms of delirium are reported by studies of postoperative delirium in adults. METHODS: Medline, EMBASE and Web of Science databases were searched on 03 June 2021 and 06 April 2023. Two reviewers independently examined titles and abstracts. Each paper was screened in duplicate and conflicting decisions settled by consensus discussion. Data were extracted, qualitatively synthesised and narratively reported. All included studies were quality assessed. RESULTS: These searches yielded 4,367 results. After title and abstract screening, 694 full-text studies were reviewed, and 62 deemed eligible for inclusion. This review details 11,377 patients including 2,049 patients with delirium. In total, 78 differently described delirium symptoms were reported. The most reported symptoms were inattention (N = 29), disorientation (N = 27), psychomotor agitation/retardation (N = 22), hallucination (N = 22) and memory impairment (N = 18). Notably, psychomotor agitation and hallucinations are not listed in the current Diagnostic and Statistical Manual for Mental Disorders-5-Text Revision delirium definition. CONCLUSIONS: The 78 symptoms reported in this systematic review cover domains of attention, awareness, disorientation and other cognitive changes. There is a lack of standardisation of terms, and many recorded symptoms are synonyms of each other. This systematic review provides a library of individual delirium symptoms, which may be used to inform future reporting.