Utilising Behavioural and Sensory Profiles and Associated Perinatal Factors to Identify Meaningful Subgroups in Autism Spectrum Disorder.

The heterogeneity of autism spectrum disorder (ASD) clinically and aetiologically hinders intervention matching and prediction of outcomes. This study investigated if the behavioural, sensory, and perinatal factor profiles of autistic children could be used to identify distinct subgroups. Participants on the autism spectrum aged 2 to 17 years and their families were sourced via the Australian Autism Biobank (AAB). Latent class analysis was used to identify subgroups within this cohort, utilising twenty-six latent variables representing child's behavioural and sensory features and perinatal factors. Four distinct subgroups within the sample (n = 1168) distinguished by sensory and behavioural autism traits and exposure to perinatal determinants were identified. Class 2 and Class 4, which displayed the greatest behavioural and sensory impairment respectively, were associated with the highest perinatal factor exposure. Class 1, labelled "Most behavioural concerns and moderate sensory and behavioural skills concerns" had mixed exposure to perinatal determinants while Class 3, named "Least sensory and behavioural skills concerns" had the least perinatal determinant exposure, indicating a directly proportional correlation between severity of clinical features and perinatal factor exposure. Additionally, association between specific exposures such as maternal mental illness in Class 1 and significant behavioural concerns was recognised. Identifying distinct subgroups among autistic children can lead to development of targeted interventions and supports. Close monitoring of children exposed to specific perinatal determinants for developmental differences could assist early intervention and supports.

2023 EULAR classification criteria for hand osteoarthritis.

OBJECTIVES: The objective of this study is to develop classification criteria for overall hand osteoarthritis (OA), interphalangeal OA and thumb base OA based on self-reported data and radiographic features. METHODS: The classification criteria sets were developed in three phases. In phase 1, we identified criteria that discriminated hand OA from controls. In phase 2, we used a consensus-based decision analysis approach to derive a clinician-based evaluation of the relative importance of the criteria. In phase 3, we refined the scoring system, determined the cut-offs for disease classification and compared the sensitivity and specificity of the European Alliance of Associations for Rheumatology (EULAR) criteria with the 1990 American College of Rheumatology (ACR) criteria. RESULTS: In persons with hand symptoms and no other disease (including psoriasis) or acute injury that can explain the hand symptoms (mandatory criteria), hand OA can be classified based on age, duration of morning stiffness, number of joints with osteophytes and joint space narrowing, and concordance between symptoms and radiographic findings. Using a sum of scores based on each diagnostic element, overall hand OA can be classified if a person achieves 9 or more points on a 0-15 scale. The cut-off for interphalangeal OA and thumb base OA is 8 points. While the EULAR criteria demonstrated better sensitivity than the ACR criteria in the phase 1 data set, the performance of the two criteria sets was similar in two external cohorts. CONCLUSIONS: International experts developed the EULAR criteria to classify overall hand OA, interphalangeal OA and thumb base OA in clinical studies using a rigorous methodology.

Difficult Toddler Temperament - Prevalence and Associated Factors at 18-Month Follow-Up of a Birth Cohort.

Purpose: Difficult temperament coupled with other risk factors may lead to mental health problems in childhood and have long-lasting effects in adolescence and adulthood. This study aimed to investigate the prevalence of parental perception of difficult temperament in toddlers and identify significant factors associated with individual and family-level sociodemographic risk factors. Patients and Methods: The prevalence of parental perception of difficult temperament was derived from items in the 18-month follow-up questionnaire within the Watch Me Grow (WMG) longitudinal birth cohort study in a multicultural and socioeconomically disadvantaged community in Sydney, Australia. Data was available for 500 children and their parents. Descriptive analysis was used to calculate the participant characteristics and the prevalence of parental perception of difficult temperament, whereas multivariable logistic regression analysis was used to assess significant risk factors associated with a difficult temperament. Results: Parental perception of difficult temperament in the cohort was 7.3% (n = 492). Findings of the multivariable logistic regression showed that screen time >2 hours a day (AOR 2.43, 95% CI: 1.2, 4.9), child not being read to (AOR 3.92, 95% CI: 1.8, 8.5), and family history of mental health problems (AOR 2.69, 95% CI: 1.1, 6.5) significantly increased the odds of having a difficult temperament. Conclusion: Toddlers with difficult temperament were less likely to have received stimulatory experiences, and their families were more likely to be under greater stress. The findings emphasize the importance of parental support and anticipatory guidance in promoting nurturing care to facilitate child health and development, particularly in disadvantaged communities.

Evidence-based brief interventions targeting acute mental health presentations for children and adolescents: systematic review.

BACKGROUND: Brief intervention services provide rapid, mobile and flexible short-term delivery of interventions to resolve mental health crises. These interventions may provide an alternative pathway to the emergency department or in-patient psychiatric services for children and young people (CYP), presenting with an acute mental health condition. AIMS: To synthesise evidence on the effectiveness of brief interventions in improving mental health outcomes for CYP (0-17 years) presenting with an acute mental health condition. METHOD: A systematic literature search was conducted, and the studies' methodological quality was assessed. Five databases were searched for peer-reviewed articles between January 2000 and September 2022. RESULTS: We synthesised 30 articles on the effectiveness of brief interventions in the form of (a) crisis intervention, (b) integrated services, (c) group therapies, (d) individualised therapy, (e) parent-child dyadic therapy, (f) general services, (g) pharmacotherapy, (h) assessment services, (i) safety and risk planning and (j) in-hospital treatment, to improve outcomes for CYP with an acute mental health condition. Among included studies, one study was rated as providing a high level of evidence based on the National Health and Medical Research Council levels of evidence hierarchy scale, which was a crisis intervention showing a reduction in length of stay and return emergency department visits. Other studies, of moderate-quality evidence, described multimodal brief interventions that suggested beneficial effects. CONCLUSIONS: This review provides evidence to substantiate the benefits of brief interventions, in different settings, to reduce the burden of in-patient hospital and readmission rates to the emergency department.

Evidence-based long term interventions targeting acute mental health presentations for children and adolescents: systematic review.

Background: Long term intervention services have proven to be effective in improving mental health (MH) outcomes and the quality of life for children and young people (CYP). Aim: To synthesize evidence on the effectiveness of long-term interventions in improving MH outcomes for CYP, 0-17 years, presenting with MH conditions. Methods: A systematic search was carried out and the methodological quality of included long term MH intervention studies were assessed. Six databases were searched for peer-reviewed articles between January 2000 and September 2022. Results: We found 30 studies that reported on the effectiveness of a range of long-term MH interventions in the form of (i) group therapy, (ii) multisystemic behavior therapy, (iii) general services, (iv) integrated services, (v) psychotherapy, (vi) intensive intervention services, (vii) comprehensive collaborative care, (viii) parent training, and (ix) home outreach service. Among the included studies, seven were rated as high level of evidence based on the National Health and Medical Research Council (NHMRC) levels of evidence hierarchy scale and seven were of moderate quality evidence. Others were rated as lower-quality evidence. Among the studies providing high quality evidence, most were reported for group therapy, general services, and psychotherapy studies demonstrating beneficial effects. Conclusion: This systematic review provides evidence to demonstrate the benefits of a range of long-term interventions, in a range of settings, can be effective in improving MH outcomes for CYP and their families. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022323324.

Blood-based microRNA profiling unveils complex molecular dynamics in breast cancer.

BACKGROUND: Breast cancer, a genetically intricate disease with diverse subtypes, exhibits heightened incidence globally. In this study, we aimed to investigate blood-based microRNAs (miRNAs) as potential biomarkers for breast cancer. The primary objectives were to explore the role of miRNAs in cancer-related processes, assess their differential expression between breast cancer patients and healthy individuals, and contribute to a deeper understanding of the molecular underpinnings of breast cancer. METHODS: MiRNA extraction was performed on 40 breast cancer patients and adjacent normal tissues using a commercial RNA isolation kit. Total RNA quantification and quality assessment were conducted with advanced technologies. MiRNA profiling involved reverse transcription, labeling, and hybridization on Agilent human miRNA arrays (V2). Bioinformatics analysis utilized the DIANA system for target gene prediction and the DIANA-mirPath tool for pathway enrichment analysis. Selected miRNAs underwent validation through quantitative real-time PCR. RESULTS: Principal component analysis revealed overlapping miRNA expression patterns in primary and malignant breast tumors, underscoring the genetic complexity involved. Statistical analysis identified 54 downregulated miRNAs in malignant tumors and 38 in primary tumors compared to controls. Bioinformatics analysis implicated several pathways, including Wnt, TGF-b, ErbB, and MAPK signaling. Validation through qRT-PCR confirmed altered expression of hsa-miR-130a, hsa-miR-21, hsa-miR-223, and hsa-let-7c key miRNAs, highlighting their significance in breast cancer. The results from microarray were further validated by qPCR and the expression of which are downregulated in breast cancer was detected. CONCLUSION: This study provides significant insights into distinct miRNA expression patterns in normal and malignant breast tissues. The overlapping miRNA profiles in primary and malignant tumors underscore the complexity of genetic regulation in breast cancer. The identification of deregulated miRNAs and affected pathways contributes to our understanding of breast cancer pathogenesis. The validated miRNAs hold potential as diagnostic and prognostic markers, offering avenues for further clinical exploration in breast cancer research.

Analyzing the effectiveness of environmental impact assessment in Paraná, Brazil and California, United States with fuzzy-set qualitative comparative analysis and the analytical hierarchy process.

Environmental impact assessment (EIA) has become one of the most widespread environmental management instruments. Despite this, EIA is routinely criticized for being ineffective at impacting decision-making. This study compared the EIA systems of Paraná, Brazil and California, United States using the effectiveness dimensions from the EIA literature. This study formats the cases into contextual conditions using the fuzzy-set qualitative comparative analysis (fsQCA) to identify the necessary or sufficient conditions that cause effective outcomes. These effectiveness outcomes are then ranked by EIA stakeholders via the analytical hierarchy process (AHP) to identify stakeholder priorities and to improve stakeholder management. The results show that in Paraná stakeholders identified normative effectiveness as the most important dimension, while stakeholders in California identified this dimension as the second-most important following substantive effectiveness. Public participation was found to be a necessary condition for both substantive and normative effectiveness to occur. Early project definition was found to be sufficient for substantive effectiveness and necessary for normative effectiveness, for which stakeholder coordination was a sufficient condition. This suggests that in order for EIA to influence decision-making and foster sustainable development, greater care needs to be taken to actively engage stakeholders in public participation, with clear roles and project design communicated early on, and a clear role for regulatory authority to promote stakeholder coordination for acceptable outcomes. These findings suggest that some effectiveness dimensions are caused by similar conditions, which could help focus stakeholder management efforts and point to new avenues for future EIA effectiveness research.

Predicting Communication Skills Outcomes for Preschool Children with Autism Spectrum Disorder Following Early Intervention.

Purpose: This study aims to assess changes in the receptive and expressive language skills and to determine if the baseline characteristics such as communication, cognitive and motor skills, predict outcomes in preschool children with Autism Spectrum Disorder (ASD) following early intervention. Methods: We recruited 64 children participating in the Early Start Denver Model (ESDM) early intervention program at an Autism Specific Early Learning and Care Center (ASELCC) in Australia. Baseline characteristics across various developmental domains was measured using the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behaviour Scales, 2nd Edition (VABS-II), and the ESDM Curriculum Checklist. Linear mixed-effects models were used to examine the effects of the intervention on outcomes. Fixed-effects such as time, groups (verbal and minimally verbal), and time-by-group interactions were assessed whilst adjusting for covariates. Further, multiple linear regression models were used to determine if the baseline characteristics were significant predictors of the outcomes following the early intervention. Results: Among the 64 children who participated in this study, 38 children were verbal, whereas 26 were deemed to have minimal verbal skills. The mean age of the sample was 4.1 years with a significant male predilection (83%) and from a culturally and linguistically diverse (CALD) background (64%). Findings of the linear mixed effects model showed significant within and between group differences in the ESDM subscales, indicating higher magnitude of changes in the verbal group compared to the minimally verbal group. Finally, the multiple linear regression models suggested that baseline MSEL visual reception and expressive language scores were predictive of changes in the ESDM receptive and expressive communication scores. Conclusion: Understanding a child's baseline skill levels may provide valuable clues regarding what interventions would work best, or which interventions may be less suitable for individual preschool-aged children with ASD.

Bone health assessment in adults with fragility fracture risk factors between 2002-2014: a retrospective cohort study.

BACKGROUND: Lifetime risk of fragility fractures is 50% in post-menopausal women and 20% in men aged >50 years. Identifying people at high risk facilitates early intervention and reduction of biopsychosocial morbidity associated with these fractures. AIM: To explore if bone health assessment (BHA) rates differ between women and men aged ≥50 years with fragility fracture risk factors. DESIGN & SETTING: A primary care-based cohort study in North Staffordshire, UK. METHOD: Patients were identified from the Consultations in Primary Care Archive (CiPCA) database between 2002 and 2014 with one or more fragility fracture risk factors (previous fractures, falls, and prolonged steroid use). Evaluation of BHA within 12 months of presentation of the first risk factor was carried out by searching for codes for fracture risk assessment tools (FRAX and QFracture), bone density measurement, specialist service referral, or if bone-protection medication was started. RESULTS: A total of 15 581 patients with risk factors were identified; men represented 40.4% of the cohort. The study found 1172 (7.5%) had BHA performed within 1 year of presentation, and 8.9% of women and 5.5% of men had BHAs, which was found with strong statistical evidence (χ2 = 59.88, P = 1 × 10-14). This relationship prevailed after adjusting for other covariates, such as comorbidity and number of consultations, with an odds ratio of 1.25 (95% confidence interval [CI] = 1.08 to 1.43). CONCLUSION: This study has shown that rates of BHA were generally low and even lower in men compared with women. Primary care clinicians should be alert to fragility fracture risk factors in both men and women to enable early assessment and intervention.

Combining multimodal magnetic resonance brain imaging and machine learning to unravel neurocognitive function in non-neuropsychiatric systemic lupus erythematosus.

OBJECTIVE: To study whether multimodal brain MRI comprising permeability and perfusion measures coupled with machine learning can predict neurocognitive function in young patients with SLE without neuropsychiatric manifestations. METHODS: SLE patients and healthy controls (HCs) (≤40 years of age) underwent multimodal structural brain MRI that comprised voxel-based morphometry (VBM), magnetization transfer ratio (MTR) and dynamic contrast-enhanced (DCE) MRI in this cross-sectional study. Neurocognitive function assessed by Automated Neuropsychological Assessment Metrics was reported as the total throughput score (TTS). Olfactory function was assessed. A machine learning-based model (i.e. glmnet) was constructed to predict TTS. RESULTS: Thirty SLE patients and 10 HCs were studied. Both groups had comparable VBM, MTR, olfactory bulb volume (OBV), olfactory function and TTS. While after correction for multiple comparisons the uncorrected increase in the blood-brain barrier (BBB) permeability parameters compared with HCs did not remain evident in SLE patients, DCE-MRI perfusion parameters, notably an increase in right amygdala perfusion, was positively correlated with TTS in SLE patients (r = 0.636, false discovery rate P < 0.05). A machine learning-trained multimodal MRI model comprising alterations of VBM, MTR, OBV and DCE-MRI parameters mainly in the limbic system regions predicted TTS in SLE patients (r = 0.644, P < 0.0005). CONCLUSION: Multimodal brain MRI demonstrated increased right amygdala perfusion that was associated with better neurocognitive performance in young SLE patients without statistically significant BBB leakage and microstructural abnormalities. A machine learning-constructed multimodal model comprising microstructural, perfusion and permeability parameters accurately predicted neurocognitive performance in SLE patients.

A robust evaluation of 49 high-dose-rate prostate brachytherapy treatment plans including all major uncertainties.

BACKGROUND: Uncertainties in radiotherapy cause deviation from the planned dose distribution and may result in delivering a treatment that fails to meet clinical objectives. The impact of uncertainties is unique to the patient anatomy and the needle locations in HDR prostate brachytherapy. Evaluating this impact during treatment planning is not common practice, relying on margins around the target or organs-at-risk to account for uncertainties. PURPOSE: A robust evaluation framework for HDR prostate brachytherapy treatment plans was evaluated on 49 patient plans, measuring the range of possible dosimetric outcomes to the patient due to 14 major uncertainties. METHODS: Patient plans were evaluated for their robustness to uncertainties by simulating probable uncertainty scenarios. Five-thousand probabilistic and 1943 worst-case scenarios per patient were simulated by changing the position and size of structures and length of dwell times from their nominal values. For each uncertainty scenario, the prostate D90 and maximum doses to the urethra, D0.01cc , and rectum, D0.1cc , were calculated. RESULTS: The D90 was an average 1.16 ± 0.51% (mean ± SD) below nominal values for the probabilistic scenarios; the D0.01cc metric was 2.24 ± 0.90% higher; and D0.1cc was greater by 0.48 ± 0.30%. The D0.01cc and D90 metrics were more sensitive to uncertainties than D0.1cc , with a median of 79.0% and 84.9% of probabilistic scenarios passing the constraints, compared to 96.5%. The median pass-rate for scenarios that passed all three metrics simultaneously was 63.4%. CONCLUSIONS: Assessing treatment plan robustness improves plan quality assurance, is achievable in less than 1-min, and identifies treatment plans with poor robustness, allowing re-optimization before delivery.

Technology-enhanced community forest management in tropical regions: A state of the art.

Tropical forests provide ecosystem services to around 2.7 billion people. Yet they are reaching tipping points due to social, economic, and environmental pressures. Technology is increasingly being leveraged to expand Community Forest Management (CFM) monitoring capabilities and to potentially increase its effectiveness, but a systematic accounting of this is lacking in the scientific literature. This study employed a mixed-methods approach combining a systematic literature review (SLR) with semi-structured interviews of technology-enhanced CFM (tech-CFM) case studies in tropical forests. From the SLR, evaluation criteria were identified and applied to 23 case studies that employed one or more novel technologies, 8 on the African continent, 9 in the Asia Pacific region, 5 in Latin America, and 1 in multiple regions. The results include classifying 22 monitoring technologies, with satellite remote sensing technology being the most common (17 case studies), followed by mobile devices (10 case studies), which are often integrated with geographic information system (8 case studies) analysis and data platforms. These technologies tend to be deployed in packages that augment each technology's capabilities, beyond their individual uses. Nonetheless, they are limited by poor internet coverage in remote regions, impeding the ability to develop real-time integrated monitoring systems. Tech-CFM shows potential for complementing and integrating with national monitoring system when adequate data collection protocols are in place. Practical social-cultural, technical, and project design recommendations are made for the integration of technology into CFM. Finally, a multi-criteria decision-making framework is developed from the literature-based evaluation criteria to assist practitioners in selecting appropriate technology suites.

Teleworking, Parenting Stress, and the Health of Mothers and Fathers.

This cross-sectional study examines the associations of telework during the COVID-19 pandemic with parents' general health, changes to mental health, and parenting stress.

Machine learning-based prediction for self-harm and suicide attempts in adolescents.

This study aimed to use machine learning (ML) models to predict the risk of self-harm and suicide attempts in adolescents. We conducted secondary analysis of cross-sectional data from the Longitudinal Study of Australian Children dataset. Several key variables at the age of 14-15 years were used to predict self-harm or suicide attempt at 16-17 years. Random forest classification models were used to select the optimal subset of predictors and subsequently make predictions. Among 2809 participants, 296 (10.54%) reported an act of self-harm and 145 (5.16%) reported attempting suicide at least once in the past 12 months. The area under the receiver operating curve was fair for self-harm (0.7397) and suicide attempt (0.7220), which outperformed the prediction strategy solely based on prior suicide or self-harm attempt (AUC: 0.6). The most important factors identified were similar, and included depressed feelings, strengths and difficulties questionnaire scores, perceptions of self, and school- and parent-related factors. The random forest classification algorithm, an ML technique, can effectively select the optimal subset of predictors from hundreds of variables to forecast the risks of suicide and self-harm among adolescents. Further research is needed to validate the utility and scalability of ML techniques in mental health research.

Elements of the water - food - environment nexus for integrated sustainability analysis.

Water and food security are constantly on the sustainable development agenda since they are interrelated with anthropogenic and ecosystemic issues present in the economic, environmental, and social spheres. The non-integrative management of these issues points to unsustainable futures. In this context, nexus approaches deserve considerable attention in the search for integrative management solutions capable of contributing to leveraging synergies that increase agricultural productivity, while simultaneously reducing environmental impacts, including water resources. This systematic literature review article aims to analyze the integration factors from the perspective of the water - food - environment nexus in the context of water and agricultural sustainability. The systematic methodology, including a content analysis, allowed the identification of analytical categories composed of the most present integrating factors and discussed in the scientific scope and how they are correlated from the perspective of the nexus. Among the extensive number of factors, the systemic management inserted in the integrated management of watersheds, the sustainable intensification from the perspective of food security and the demand for water resources, categorized in water security, presented higher frequency of occurrence when compared with the other factors. It is proposed that these factors can be considered as indicators of sustainability in the context of integrated water resources management and agricultural food production, since their synergistic effects have consequences in the water, agricultural and environmental management sectors. Thus, this study stands out for identifying trends and gaps in the water - food - environment nexus that can contribute to the development of innovative decision-making tools, in order to assist in the management of the watershed, where agriculture plays a key role in socio-environmental issues.

Blowfly-derived mammal DNA as mammal diversity assessment tool: Determination of dispersal activity and flight range of tropical blowflies.

Mammalian DNA extracted from the invertebrates, especially blowfly-derived DNA, has been suggested as a useful tool to complement traditional field methods for terrestrial mammal monitoring. However, the accuracy of the estimated location of the target mammal detected from blowfly-derived DNA is largely dependent on the knowledge of blowflies' dispersal range. Presently, published data on adult blowfly dispersal capabilities remain scarce and mostly limited to temperate and subtropical regions, with no published report on the adult blowfly dispersal range in the Tropics. We seek to determine the blowfly flight range and dispersal activity in a tropical plantation in Malaysia by mark-release-recapture of approximately 3000 wild blowflies by use of rotten fish-baited traps for nine consecutive days. Out of the 3000 marked Chrysomya spp., only 1.5% (43) were recaptured during the 9-day sampling period. The majority of the blowflies (79%) were recaptured 1 km from the release point, while 20.9% were caught about 2-3 km from the release point. One individual blowfly travelled as far as 3 km and before being recaptured, which was the maximum dispersal distance recorded in this study. This result suggests that the estimated locations of the mammals detected from blowfly-derived iDNA is likely to be within 1-2 km radius from the origin of the blowfly sampling location. However, a more accurate estimated distance between the target mammal and the blowfly sampling location requires further investigation due to various factors, such as blowfly species, wind speed and direction that may potentially affect the blowfly dispersal activities. This study contributes further understanding on the development of a blowfly-derived DNA method as a mammalian monitoring tool in the tropical forests.

The Effects of Whole-body Cold-water Immersion on Brain Connectivity Related to the Affective State in Adults Using fMRI: A Protocol of a Pre-post Experimental Design.

An emerging body of behavioural studies indicates that regular swimming in cold water has positive effects on mental health and wellbeing, such as reducing fatigue, improving mood, and lessening depressive symptoms. Moreover, some studies reported immediate effects of cold-water immersion (CWI) on elevating mood and increasing a positive emotional state. However, the neural mechanisms underlying these effects remain largely unknown. The lack of studies using neuroimaging techniques to investigate how a whole-body CWI affects neural processes has partly resulted from the lack of a tested experimental protocol. Previous protocols administered tonic limb cooling (1-10 °C) while recording functional magnetic resonance (fMRI) signals. However, using very low water temperature constitutes points of contrast to painful experiences that are different from what we experience after a whole-body head-out CWI. In our protocol, healthy adults unhabituated to cold water were scanned twice: immediately before (pre-CWI) and after (post-CWI) immersion in cold water (water temperature 20 °C) for 5 min. We recorded cardiac and ventilatory responses to CWI and assessed self-reported changes in positive and negative affects. Our protocol showed reliable changes in brain connectivity after a short exposure to cold water, thus enabling its use as a tested experimental framework in future studies.

Sociocultural factors associated with detection of autism among culturally and linguistically diverse communities in Australia.

BACKGROUND: The age at which parents or caregivers first develop concerns about their child's development has significant implications on formal diagnosis and intervention. This study aims to determine the sociocultural factors that are associated with the age and type of first concern reported by parents of autistic children among culturally and linguistically diverse (CALD) communities in Australia. We also assessed whether sociocultural factors predict autism traits measured in terms of social affect (SA), restricted and repetitive behaviours (RRB), and calibrated severity scores (CSS). METHODS: This study is a secondary data analysis of the data collected from six Autism Specific Early Learning and Care Centres (ASELCCs) as part of the Autism Co-operative Research Centre (CRC) program between 2015 and 2019. Data analysed in this study included a family history questionnaire with sociodemographic and sociocultural information, parent-reported age and type of first concern, and clinician/researcher administered Autism Diagnostic Observation Schedule - Second Edition (ADOS-2) which includes standardised domain-wise scores of social affect (SA) and restricted and repetitive behaviours (RRB) as well as calibrated severity scores (CSS), a measure of severity of autism. Primary analysis included multivariable linear regression models to examine the predictive influence of sociodemographic and sociocultural factors on the dependant variables of age of concern (AOC) and the autism traits (SA, RRB, and CSS). RESULTS: The mean AOC in the sample was 18.18 months and the most common concerns were speech/language delay, limited social interaction, and hyperactivity/behavioural changes. The multivariable linear regression models showed factors such as increase in age of child, those from a CALD background, annual family income, sibling's autism diagnosis, and developmental concerns to be significantly associated with parental AOC. Additionally, we also found that increase in child's age and CALD status to be significant predictors of autism trait (RRB) and severity measured in terms of the CSS score. Further, females (compared to males) were associated with higher difficulties with social communication and interaction skills. CONCLUSION: Understanding key factors that contribute to early identification of autism can help tailor awareness programs for parents and caregivers, whilst also informing the development of services focused on serving all CALD communities.

Immune cell ratio and coagulation markers in assessing prognosis of asthma: a cross-sectional study from Saudi Arabia.

Asthma affects a significant number of individuals in Saudi Arabia, with increasing prevalence worldwide, leading to a considerable impact on their quality of life and frequent hospitalizations. In this study, we aimed to explore the relationship between the immune cell ratio and coagulation markers, specifically to identify the occurrence of coagulation abnormalities associated with asthma. To achieve this, we assessed asthma history and severity using a questionnaire while analyzing coagulation biomarkers through venous blood samples. The biomarkers examined included d-dimer, prothrombin time (PT), partial thromboplastin time (PTT), and the international normalized ratio (INR). In addition, we evaluated various hematological parameters such as blood cell counts and hemoglobin (HGB) levels. Our findings revealed compelling evidence, showing significantly elevated levels of d-dimer and the eosinophil-to-neutrophil (ENR) ratio in asthma cases compared to the controls. Moreover, we observed a positive correlation between d-dimer levels and the ENR, with each unit increase in d-dimer associated with a 0.0006 increase in the ENR among asthma cases. These results highlight the potential of assessing ENR and d-dimer levels as predictive indicators for disease prognosis and the development of coagulation abnormalities in individuals with asthma. By shedding light on the relationship between immune cell ratios and coagulation markers in the context of asthma, our study contributes to a better understanding of disease progression and the associated complications. These insights can potentially lead to improved management strategies and better outcomes for asthma patients.