Socio-demographic variation in diagnosis of and prescribing for common mental illnesses among children and young people during the COVID-19 pandemic: time series analysis of primary care electronic health records.

BACKGROUND: The impact of the COVID-19 pandemic on the mental health of children and young people (CYP) has been widely reported. Primary care electronic health records were utilised to examine trends in the diagnosing, recording and treating of these common mental disorders by ethnicity and social deprivation in Greater Manchester, England. METHODS: Time-series analyses conducted using Greater Manchester Care Record (GMCR) data examined all diagnosed episodes of anxiety disorders and depression and prescribing of anxiolytics and antidepressants among patients aged 6-24 years. The 41-month observation period was split into three epochs: Pre-pandemic (1/2019-2/2020); Pandemic Phase 1 (3/2020-6/2021); Pandemic Phase 2 (7/2021-5/2022). Rate ratios for all CYP specific to sex, age, ethnicity, and neighbourhood-level Indices of Multiple Deprivation (IMD) quintile were modelled using negative binomial regression. RESULTS: Depression and anxiety disorder rates were highest in females, CYP aged 19-24, and White and 'Other' ethnic groups. During Pandemic Phase 1, rates for these diagnoses fell in all demographic subgroups and then rose to similar levels as those recorded pre-pandemic. In Pandemic Phase 2, rates in Black and Mixed-ethnicity females rose to a significantly greater degree (by 54% and 62%, respectively) than those in White females. Prescribing rates increased throughout the study period, with significantly greater rises observed in non-White females and males. The temporal trends were mostly homogeneous across deprivation quintiles. CONCLUSION: The observed fluctuations in frequency of recorded common mental illness diagnoses likely reflect service accessibility and patients' differential propensities to consult as well as changing levels of distress and psychopathology in the population. However, psychotropic medication prescribing increased throughout the observation period, possibly indicating a sustained decline in mental health among CYP, and also clinicians' responses to problems presented. The comparatively greater increases in frequencies of diagnosis recording and medication prescribing among ethnic minority groups warrants further investigation.

Loss of NF1 in Drosophila Larvae Causes Tactile Hypersensitivity and Impaired Synaptic Transmission at the Neuromuscular Junction.

Autism spectrum disorder (ASD) is a neurodevelopmental condition in which the mechanisms underlying its core symptomatology are largely unknown. Studying animal models of monogenic syndromes associated with ASD, such as neurofibromatosis type 1 (NF1), can offer insights into its etiology. Here, we show that loss of function of the Drosophila NF1 ortholog results in tactile hypersensitivity following brief mechanical stimulation in the larva (mixed sexes), paralleling the sensory abnormalities observed in individuals with ASD. Mutant larvae also exhibit synaptic transmission deficits at the glutamatergic neuromuscular junction (NMJ), with increased spontaneous but reduced evoked release. While the latter is homeostatically compensated for by a postsynaptic increase in input resistance, the former is consistent with neuronal hyperexcitability. Indeed, diminished expression of NF1 specifically within central cholinergic neurons induces both excessive neuronal firing and tactile hypersensitivity, suggesting the two may be linked. Furthermore, both impaired synaptic transmission and behavioral deficits are fully rescued via knock-down of Ras proteins. These findings validate NF1 -/- Drosophila as a tractable model of ASD with the potential to elucidate important pathophysiological mechanisms.SIGNIFICANCE STATEMENT Autism spectrum disorder (ASD) affects 1-2% of the overall population and can considerably impact an individual's quality of life. However, there are currently no treatments available for its core symptoms, largely because of a poor understanding of the underlying mechanisms involved. Examining how loss of function of the ASD-associated NF1 gene affects behavior and physiology in Drosophila may shed light on this. In this study, we identify a novel, ASD-relevant behavioral phenotype in NF1 -/- larvae, namely an enhanced response to mechanical stimulation, which is associated with Ras-dependent synaptic transmission deficits indicative of neuronal hyperexcitability. Such insights support the use of Drosophila neurofibromatosis type 1 (NF1) models in ASD research and may provide outputs for genetic or pharmacological screens in future studies.

The seventh international RASopathies symposium: Pathways to a cure-expanding knowledge, enhancing research, and therapeutic discovery.

RASopathies are a group of genetic disorders that are caused by genes that affect the canonical Ras/mitogen-activated protein kinase (MAPK) signaling pathway. Despite tremendous progress in understanding the molecular consequences of these genetic anomalies, little movement has been made in translating these findings to the clinic. This year, the seventh International RASopathies Symposium focused on expanding the research knowledge that we have gained over the years to enhance new discoveries in the field, ones that we hope can lead to effective therapeutic treatments. Indeed, for the first time, research efforts are finally being translated to the clinic, with compassionate use of Ras/MAPK pathway inhibitors for the treatment of RASopathies. This biannual meeting, organized by the RASopathies Network, brought together basic scientists, clinicians, clinician scientists, patients, advocates, and their families, as well as representatives from pharmaceutical companies and the National Institutes of Health. A history of RASopathy gene discovery, identification of new disease genes, and the latest research, both at the bench and in the clinic, were discussed.

Risk factors for nonfatal self-harm and suicide among adolescents: two nested case-control studies conducted in the UK Clinical Practice Research Datalink.

BACKGROUND: The characteristics of adolescents who die by suicide have hitherto been examined in uncontrolled study designs, thereby precluding examination of risk factors. The degree to which antecedents of nonfatal self-harm and suicide at young age differ remains unknown. METHOD: We delineated two nested case-control studies of patients aged 10-19 years using the Clinical Practice Research Datalink with interlinked hospital and national mortality records. Cases were adolescents who between 1st January 2003 and 31st December 2018 had died from suicide (N = 324) - study 1; experienced their first self-harm episode (N = 56,008) - study 2. In both studies, cases were matched on sex, age and practice-level deprivation quintile to 25 controls. By fitting conditional logistic regression, we examined how risks varied according to psychiatric diagnoses, prescribed psychotropic medication, patterns of clinical contact and area-level deprivation. RESULTS: Suicides occurred more often among boys (66%), but self-harm was more common in girls (68%). Most individuals who self-harmed or died from suicide presented to their GP at least once in the preceding year (85% and 75% respectively). Only a third of cases had one of the examined diagnostic categories recorded. Depression was most strongly associated with elevated risks for both outcomes (self-harm: OR 7.9; 95% CI 7.8-8.2; suicide: OR 7.4; 95% CI 5.5-9.9). Except for autism spectrum disorder, all other diagnostic categories were linked with similar risk elevations for self-harm as for suicide. Whilst self-harm risk rose incrementally with increasing levels of area-level deprivation, suicide risks did not. CONCLUSIONS: We observed few marked differences in risk factor profiles for nonfatal self-harm versus suicide. As most adolescents who had harmed themselves or died by suicide were known to services in the preceding year, their underlying pathology may not be adequately identified and treated. Our findings highlight the need for a multiagency approach to treatment and prevention.

Development of the pupillary light reflex from 9 to 24 months: association with common autism spectrum disorder (ASD) genetic liability and 3-year ASD diagnosis.

BACKGROUND: Although autism spectrum disorder (ASD) is heritable, the mechanisms through which genes contribute to symptom emergence remain unclear. Investigating candidate intermediate phenotypes such as the pupillary light reflex (PLR) prospectively from early in development could bridge genotype and behavioural phenotype. METHODS: Using eye tracking, we longitudinally measured the PLR at 9, 14 and 24 months in a sample of infants (N = 264) enriched for a family history of ASD; 27 infants received an ASD diagnosis at 3 years. We examined the 9- to 24-month developmental trajectories of PLR constriction latency (onset; ms) and amplitude (%) and explored their relation to categorical 3-year ASD outcome, polygenic liability for ASD and dimensional 3-year social affect (SA) and repetitive/restrictive behaviour (RRB) traits. Polygenic scores for ASD (PGSASD ) were calculated for 190 infants. RESULTS: While infants showed a decrease in latency between 9 and 14 months, higher PGSASD was associated with a smaller decrease in latency in the first year (ß = -.16, 95% CI = -0.31, -0.002); infants with later ASD showed a significantly steeper decrease in latency (a putative 'catch-up') between 14 and 24 months relative to those with other outcomes (typical: ß = .54, 95% CI = 0.08, 0.99; other: ß = .53, 95% CI = 0.02, 1.04). Latency development did not associate with later dimensional variation in ASD-related traits. In contrast, change in amplitude was not related to categorical ASD or genetics, but decreasing 9- to 14-month amplitude was associated with higher SA (ß = .08, 95% CI = 0.01, 0.14) and RRB (ß = .05, 95% CI = 0.004, 0.11) traits. CONCLUSIONS: These findings corroborate PLR development as possible intermediate phenotypes being linked to both genetic liability and phenotypic outcomes. Future work should incorporate alternative measures (e.g. functionally informed structural and genetic measures) to test whether distinct neural mechanisms underpin PLR alterations.

Temporal trends in annual incidence rates for psychiatric disorders and self-harm among children and adolescents in the UK, 2003-2018.

BACKGROUND: There has been growing concern in the UK over recent years that a perceived mental health crisis is affecting children and adolescents, although published epidemiological evidence is limited. METHODS: Two population-based UK primary care cohorts were delineated in the Aurum and GOLD datasets of the Clinical Practice Research Datalink (CPRD). We included data from 9,133,246 individuals aged 1-20 who contributed 117,682,651 person-years of observation time. Sex- and age-stratified annual incidence rates were estimated for attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) (age groups: 1-5, 6-9, 10-12, 13-16, 17-19), depression, anxiety disorders (6-9, 10-12, 13-16, 17-19), eating disorders and self-harm (10-12, 13-16, 17-19) during 2003-2018. We fitted negative binomial regressions to estimate incidence rate ratios (IRRs) to examine change in incidence between the first (2003) and final year (2018) year of observation and to examine sex-specific incidence. RESULTS: The results indicated that the overall incidence has increased substantially in both boys and girls in between 2003 and 2018 for anxiety disorders (IRR 3.51 95% CI 3.18-3.89), depression (2.37; 2.03-2.77), ASD (2.36; 1.72-3.26), ADHD (2.3; 1.73-3.25), and self-harm (2.25; 1.82-2.79). The incidence for eating disorders also increased (IRR 1.3 95% CI 1.06-1.61), but less sharply. The incidence of anxiety disorders, depression, self-harm and eating disorders was in absolute terms higher in girls, whereas the opposite was true for the incidence of ADHD and ASD, which were higher among boys. The largest relative increases in incidence were observed for neurodevelopmental disorders, particularly among girls diagnosed with ADHD or ASD. However, in absolute terms, the incidence was much higher for depression and anxiety disorders. CONCLUSION: The number of young people seeking help for psychological distress appears to have increased in recent years. Changes to diagnostic criteria, reduced stigma, and increased awareness may partly explain our results, but we cannot rule out true increases in incidence occurring in the population. Whatever the explanation, the marked rise in demand for healthcare services means that it may be more challenging for affected young people to promptly access the care and support that they need.

Haploinsufficiency of ATP6V0C possibly underlies 16p13.3 deletions that cause microcephaly, seizures, and neurodevelopmental disorder.

We recently contributed to the description of eight individuals with a novel condition caused by 16p13.3 microdeletions encompassing TBC1D24, ATP6V0C, and PDPK1 and resulting in epilepsy, microcephaly and neurodevelopmental problems. The phenotypic spectrum, the minimum overlapping region and the underlying disease mechanism for this disorder remain to be clarified. Here we report a 3.5-year-old male, with microcephaly, autism spectrum disorder and a de novo 16p13.3 microdeletion. We performed detailed in silico analysis to show that the minimum overlapping region for the condition is ~80Kb encompassing five protein coding genes. Analysis of loss of function constraint metrics, transcript-aware evaluation of the population variants, GeVIR scores, analysis of reported pathogenic point variants, detailed review of the known functions of gene products and their animal models showed that the haploinsufficiency of ATP6V0C likely underlies the phenotype of this condition. Protein-protein interaction network, gene phenology and analysis of topologically associating domain showed that it was unlikely that the disorder has an epistatic or regulatory basis. 16p13.3 deletions encompassing ATP6V0C cause a neurodevelopmental disorder. Our results broaden the phenotypic spectrum of this disorder and clarify the likely underlying disease mechanism for the condition.

Perceived fatigue in children and young adults with neurofibromatosis type 1.

AIM: This study describes the prevalence and severity of perceived fatigue in a young neurofibromatosis type 1 (NF1) population. METHODS: Ethical approval was obtained and NF1 affected Individuals aged 2-18 years from the Manchester's NF1 clinic invited along with any unaffected siblings. The PedsQL Multidimensional Fatigue Scale Parental and child report was used. This validated measure explores cognitive, physical and sleep/rest domains on a 0-100 scale. Higher scores indicate less fatigue. Fatigue scores in affected children were compared to unaffected siblings after adjusting for age, sex and Index of Multiple Deprivation and with published population standards using z-scores. RESULTS: A total of 286 families were invited and 75 affected and 16 siblings participated. There were significant differences between NF1 and controls in the aggregated fatigue core (child report 55 ± 19 vs. 75 (14), P < 0.001; parent 54 ± 20 vs. 73 ± 18, P = 0.001) and the three sub-domains: cognitive (child 48 ± 27 vs. 75 ± 23, P < 0.001), physical (child 59 ± 19 vs. 82 ± 14, P < 0.001) and sleep/rest (child 59 ± 19 vs. 71 ± 15, P = 0.018). Similar differences were seen when compared with published controls (aggregated child z-score -1.9 ± 1.4, P < 0.001; parent -3.2 ± 1.8, P < 0.001). Prevalence of severe fatigue indicated by scores <2 standard deviation below published means for healthy controls were also higher for children with NF on both parent and child reports. Agreement between child and parent reports were limited as is frequently seen in the literature. CONCLUSION: This study suggests that children with NF1 are affected by perceived fatigue when compared with healthy children who do not have NF1.

Annual Research Review: The state of autism intervention science: progress, target psychological and biological mechanisms and future prospects.

BACKGROUND: There has been recent systematic review of key evidence in psychosocial intervention in autism but little review of biological treatments. METHODS: We analyse the current literature from the perspective of intervention and mechanism targets across social and biological development. RESULTS: The overall quality of trials evidence in autism intervention remains relatively low, despite some recent progress. Many treatments in common use have little or no evidence base. This is very concerning in such an important disorder. A variety of psychosocial interventions can show effect to improve some short-term effects on children's immediate dyadic social interactions, for instance with caregivers. But showing true effectiveness in this developmental disorder requires generalisation of such effects into wider social contexts, on autism symptoms and in long-term progress in development. Only a few interventions so far have begun to show this. A number of early phase interventions on biological targets have shown real promise, but none has yet progressed to larger scale effectiveness trials on behavioural or symptom outcomes. CONCLUSIONS: There has been enough progress in psychosocial intervention research now to be able to begin to identify some evidence-based practice in autism treatment. To consolidate and improve outcomes, the next phase of intervention research needs improved trial design, and an iterative approach building on success. It may also include the testing of potential synergies between promising biological and psychosocial interventions.

Autism spectrum disorder and other neurobehavioural comorbidities in rare disorders of the Ras/MAPK pathway.

AIM: To investigate the cognitive and behavioural phenotype in rare disorders of the Ras/MAPK pathway, namely Noonan, cardiofaciocutaneous (CFC), and Costello syndromes, particularly prevalence of autism spectrum disorder (ASD) and attention-deficit-hyperactivity disorder (ADHD). METHOD: Fifty children were recruited over 10 months through the regional genetics service and advertisements. A range of parent, child, and observational measures were administered including Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Scale. RESULTS: Using the Collaborative Programme for Excellence in Autism criteria, 12 out of 40 children with Noonan syndrome (30%) showed ASD, and 12 out of 40 (30%) with partial ASD features and 16 out of 40 (40%) showed non-ASD. The Noonan syndrome ASD group showed male dominance in a ratio of 5:1. In the CFC group, eight out of nine children met the criteria for ASD, with equal sex distribution. Additionally 19 out of 40 (48%) of the Noonan syndrome group and eight out of nine (88.9%) of the CFC group scored met clinical criteria for ADHD. Only one child was in the Costello syndrome group. INTERPRETATION: This is the first systematic study to suggest a high prevalence of ASD in Noonan and CFC syndromes, and thus offers crucial evidence to support the importance of the Ras/MAPK pathway in the aetiology of ASD. Limitations include the inevitable possibility of a sampling bias in a rare disorder study of this kind.

Cognition in children with neurofibromatosis type 1: data from a population-based study.

AIM: This study aimed to investigate the core cognitive deficits in children with neurofibromatosis type 1 (NF1). METHOD: The study recruited 49 children with NF1 (25 males, 24 females; mean age 11y 9mo [SD 3y 2mo]), 19 healthy siblings of children with NF1 (sibling comparisons; mean age 12y 7mo [SD 2y 7mo], 9 males, 10 females) and 29 healthy children from the community (community comparisons; mean age 11y [SD 2y 7mo], 12 males, 17 females). Participants completed a battery of cognitive tests including tests of intelligence, academic achievement, attention, visuoperceptual functioning, visual learning, executive functioning, and non-verbal working memory tests. RESULTS: Our study, using a population-based sample, confirmed previous findings from studies using variable sampling methods. Children with NF1 had significantly lower Full-scale IQs (p=0.04) and lower academic achievement (p=0.026-0.005) than their siblings. Compared with their siblings, they also had significantly poorer visuospatial processing (p=0.007), visual associate learning (p=0.014), non-verbal working memory (p=0.023), and executive function (p<0.001). Data from the community comparisons were not included because they were subject to significant selection bias. INTERPRETATION: Population-based frequencies for cognitive deficits in children with NF1 are similar to the frequencies in non-population based samples. This study highlights the heterogeneous nature of cognitive problems in children with NF1 and the need for monitoring and support at school.

Production of thermo-alkali-stable laccase and xylanase by co-culturing of Bacillus sp. and B. halodurans for biobleaching of kraft pulp and deinking of waste paper.

To reduce pollution and cost of treatment for fresh and recycled paper, co-production of xylanase and laccase was carried out in the same production medium using two compatible species of Bacillus. These co-produced enzymes were used for deinking of old newsprint (ONP) and biobleaching of eucalyptus Kraft pulp. Solid-state co-cultivation of Bacillus sp. and B. halodurans FNP135 was optimized statistically by response surface methodology for the co-production of xylanase (X) and laccase (L). A significant increase in production of xylanase (2.1-fold, 1,685 IU/g) and laccase (2.04-fold, 2,270 nkat/g) was observed under optimized conditions viz. pH (10.5), inoculum size (10 + 10 %) and moisture:substrate ratio (0.8:1). Both the enzymes showed identical temperature and pH optima of 70 °C and 9, respectively, and were used for deinking of ONP pulp and biobleaching of kraft pulp. In case of ONP pulp deinking, the XL treatment increased brightness (11.8 %), freeness (17.8 %), breaking length (34.8 %), burst factor (2.77 %) and tear factor (2.4 %). In case of kraft pulp biobleaching, XL treatment showed a significant increase in brightness (13 %), whiteness (106.15 %) breaking length (49 %), burst factor (6.9 %), tear factor (23 %), and viscosity (11.68 %) and reduction in kappa number (15 %) after alkali extraction and peroxide stage. This enhancement of pulp properties revealed a synergistic effect of xylanase and laccase produced in one setup.

Brain-region specific autism prediction from electroencephalogram signals using graph convolution neural network.

BACKGROUND: Brain variations are responsible for developmental impairments, including autism spectrum disorder (ASD). EEG signals efficiently detect neurological conditions by revealing crucial information about brain function abnormalities. OBJECTIVE: This study aims to utilize EEG data collected from both autistic and typically developing children to investigate the potential of a Graph Convolutional Neural Network (GCNN) in predicting ASD based on neurological abnormalities revealed through EEG signals. METHODS: In this study, EEG data were gathered from eight autistic children and eight typically developing children diagnosed using the Childhood Autism Rating Scale at the Central Institute of Psychiatry, Ranchi. EEG recording was done using a HydroCel GSN with 257 channels, and 71 channels with 10-10 international equivalents were utilized. Electrodes were divided into 12 brain regions. A GCNN was introduced for ASD prediction, preceded by autoregressive and spectral feature extraction. RESULTS: The anterior-frontal brain region, crucial for cognitive functions like emotion, memory, and social interaction, proved most predictive of ASD, achieving 87.07% accuracy. This underscores the suitability of the GCNN method for EEG-based ASD detection. CONCLUSION: The detailed dataset collected enhances understanding of the neurological basis of ASD, benefiting healthcare practitioners involved in ASD diagnosis.

5-year mental health outcomes for children and adolescents presenting with psychiatric symptoms to general practitioners in England: a retrospective cohort study.

BACKGROUND: Little information is available on the clinical trajectories of children and adolescents who attend general practice (GP) with psychiatric symptoms. We aimed to examine 5-year service use in English primary care for children and adolescents with neurodevelopmental or mental health symptoms or diagnoses. METHODS: In this retrospective cohort study, we used anonymised primary care health records from the Clinical Practice Research Datalink Aurum database (CPRD-Aurum). We identified children and adolescents (aged 3-18 years) presenting to primary care in England between Jan 1, 2000, and May 9, 2016, with a symptom or diagnosis of a mental health, behavioural, or neurodevelopmental condition. Participants were excluded if they had less than 1 year of follow-up. We followed up participants from their index date until either death, transfer out of the practice, or the end of data collection on May 5, 2021, and for trajectory analysis we limited follow-up to 5 years. We used group-based multi-trajectory models to identify clusters with similar trajectories over 5 years of follow-up for three primary outcomes: mental health-related GP contacts, psychotropic medication prescriptions, and specialist mental health-care contact. We did survival analysis to examine the associations between trajectory-group membership and hospital admission for self-harm or death by suicide, as indicators of severe psychiatric distress. FINDINGS: We included 369 340 children and adolescents, of whom 180 863 (49·0%) were girls, 188 438 (51·0%) were boys, 39 (<0·1%) were of indeterminate gender, 290 125 (78·6%) were White, 9161 (2·5%) were South Asian, 10 418 (2·8%) were Black, 8115 (2·2%) were of mixed ethnicity, and 8587 (2·3%) were other ethnicities, and the median age at index presentation was 13·6 years (IQR 8·4-16·7). In the best-fitting, seven-group, group-based multi-trajectory model, over a 5-year period, the largest group (low contact; 207 985 [51·2%]) had low rates of additional service contact or psychotropic prescriptions. The other trajectory groups were moderate, non-pharmacological contact (43 836 [13·0%]); declining contact (25 469 [8·7%]); year-4 escalating contact (18 277 [6·9%]); year-5 escalating contact (18 139; 5·2%); prolonged GP contact (32 147 [8·6%]); and prolonged specialist contact (23 487 [6·5%]). Non-White ethnicity and presentation in earlier study years (eg, 2000-2004) were associated with low-contact group membership. The prolonged specialist-contact group had the highest risk of hospital admission for self-harm (hazard ratio vs low-contact group 2·19 [95% CI 2·03-2·36]) and suicide (2·67 [1·72-4·14]). INTERPRETATION: Most children and adolescents presenting to primary care with psychiatric symptoms or diagnoses have low or declining rates of ongoing contact. If these trajectories reflect symptomatic improvement, these findings provide reassurance for children and adolescents and their caregivers. However, these trajectories might reflect an unmet need for some children and adolescents. FUNDING: National Institute for Health and Care Research and the Wellcome Trust.

Autism and other psychiatric comorbidity in neurofibromatosis type 1: evidence from a population-based study.

AIM: To investigate psychopathology in children with neurofibromatosis type 1 (NF1), particularly the prevalence of autism spectrum disorder (ASD) and attention-deficit-hyperactivity disorder (ADHD) symptomatology, using a population-based sampling approach. METHOD: Standard questionnaire screen reports were analysed for ASD (Social Responsiveness Scale, SRS), ADHD (Conners' Parent Rating Scale- Revised, CPRS-R), and other psychiatric morbidity (Strengths and Difficulties Questionnaire, SDQ) from parents and teachers of children aged from 4 to 16 years (112 females, 95 males) on the UK North West Regional Genetic Service register for NF1. RESULTS: Parental response rate was 52.7% (109/207 children; 59 females, 50 males, mean age 9 y 11 mo, SD 3 y 3 mo). The SRS showed that in 29.4% (32/109) of children, autism was in the severe, clinical range (T-score>75) and in 26.6% (29/109) in the mild to moderate range (T-score 60-75). CPRS-R scores showed that in 53.8% (57/106) of children autism was in the clinical ADHD range (ADHD index T-score>65). Based on their scores on the SDQ total difficulties scale, 41.5% (44/106) of children were in the abnormal range and 14.2% (15/106) were in the borderline range. Twenty-five per cent (26/104) of children met criteria for both clinical autism and ADHD. INTERPRETATION: This representative population-based sample of children with NF1 indicates a high prevalence of ASD symptoms associated with NF1 as well as substantial co-occurrence with ADHD symptoms. The findings clarify the psychopathology of NF1 and show the disorder as a potentially important single-gene cause for autism symptoms.

S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram.

Purpose: Human emotion recognition using electroencephalograms (EEG) is a critical area of research in human-machine interfaces. Furthermore, EEG data are convoluted and diverse; thus, acquiring consistent results from these signals remains challenging. As such, the authors felt compelled to investigate EEG signals to identify different emotions. Methods: A novel deep learning (DL) model stacked long short-term memory with attention (S-LSTM-ATT) model is proposed for emotion recognition (ER) in EEG signals. Long Short-Term Memory (LSTM) and attention networks effectively handle time-series EEG data and recognise intrinsic connections and patterns. Therefore, the model combined the strengths of the LSTM model and incorporated an attention network to enhance its effectiveness. Optimal features were extracted from the metaheuristic-based firefly optimisation algorithm (FFOA) to identify different emotions efficiently. Results: The proposed approach recognised emotions in two publicly available standard datasets: SEED and EEG Brainwave. An outstanding accuracy of 97.83% in the SEED and 98.36% in the EEG Brainwave datasets were obtained for three emotion indices: positive, neutral and negative. Aside from accuracy, a comprehensive comparison of the proposed model's precision, recall, F1 score and kappa score was performed to determine the model's applicability. When applied to the SEED and EEG Brainwave datasets, the proposed S-LSTM-ATT achieved superior results to baseline models such as Convolutional Neural Networks (CNN), Gated Recurrent Unit (GRU) and LSTM. Conclusion: Combining an FFOA-based feature selection (FS) and an S-LSTM-ATT-based classification model demonstrated promising results with high accuracy. Other metrics like precision, recall, F1 score and kappa score proved the suitability of the proposed model for ER in EEG signals.

A novel convolution bi-directional gated recurrent unit neural network for emotion recognition in multichannel electroencephalogram signals.

BACKGROUND: Recognising emotions in humans is a great challenge in the present era and has several applications under affective computing. Deep learning (DL) is found as a successful tool for prediction of human emotions in different modalities. OBJECTIVE: To predict 3D emotions with high accuracy in multichannel physiological signals, i.e. electroencephalogram (EEG). METHODS: A hybrid DL model consisting of convolutional neural network (CNN) and gated recurrent units (GRU) is proposed in this work for emotion recognition in EEG data. CNN has the capability of learning abstract representation, whereas GRU can explore temporal correlation. A bi-directional variation of GRU is used here to learn features in both directions. Discrete and dimensional emotion indices are recognised in two publicly available datasets SEED and DREAMER, respectively. A fused feature of energy and Shannon entropy (𝐸𝑛𝑆𝐸→) and energy and differential entropy (𝐸𝑛𝐷𝐸→) are fed in the proposed classifier to improve the efficiency of the model. RESULTS: The performance of the presented model is measured in terms of average accuracy, which is obtained as 86.9% and 93.9% for SEED and DREAMER datasets, respectively. CONCLUSION: The proposed convolution bi-directional gated recurrent unit neural network (CNN-BiGRU) model outperforms most of the state-of-the-art and competitive hybrid DL models, which indicates the effectiveness of emotion recognition using EEG signals and provides a scientific base for the implementation in human-computer interaction (HCI).

Efficacy of novel attention-based gated recurrent units transformer for depression detection using electroencephalogram signals.

Purpose: Depression is a global challenge causing psychological and intellectual problems that require efficient diagnosis. Electroencephalogram (EEG) signals represent the functional state of the human brain and can help build an accurate and viable technique for the early prediction and treatment of depression. Methods: An attention-based gated recurrent units transformer (AttGRUT) time-series model is proposed to efficiently identify EEG perturbations in depressive patients. Statistical, spectral and wavelet features were first extracted from the 60-channel EEG signal data. Then, two feature selection techniques, recursive feature elimination and the Boruta algorithm, both with Shapley additive explanations, were utilised for selecting essential features. Results: The proposed model outperformed the two baseline and two hybrid time-series models-long short-term memory (LSTM), gated recurrent units (GRU), convolutional neural network-LSTM (CNN-LSTM), and CNN-GRU-achieving an accuracy of up to 98.67%. Feature selection considerably increased the performance across all time-series models. Conclusion: Based on the obtained results, novel feature selection greatly affected the results of the baseline and hybrid time-series models. The proposed AttGRUT can be implemented and tested in other domains by using different modalities for prediction. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-022-00205-8.

A Review on Opportunities and Limitations of Membrane Bioreactor Configuration in Biofuel Production.

Biofuels are a clean and renewable source of energy that has gained more attention in recent years; however, high energy input and processing cost during the production and recovery process restricted its progress. Membrane technology offers a range of energy-saving separation for product recovery and purification in biorefining along with biofuel production processes. Membrane separation techniques in combination with different biological processes increase cell concentration in the bioreactor, reduce product inhibition, decrease chemical consumption, reduce energy requirements, and further increase product concentration and productivity. Certain membrane bioreactors have evolved with the ability to deal with different biological production and separation processes to make them cost-effective, but there are certain limitations. The present review describes the advantages and limitations of membrane bioreactors to produce different biofuels with the ability to simplify upstream and downstream processes in terms of sustainability and economics.