Discrepancies between dimensions of interoception in autism: implications for emotion and anxiety

Emotions and affective feelings are influenced by one's internal state of bodily arousal via interoception. Autism Spectrum Conditions (ASC) are associated with difficulties in recognising others' emotions, and in regulating own emotions. We tested the hypothesis that, in people with ASC, such affective differences may arise from abnormalities in interoceptive processing. We demonstrated that individuals with ASC have reduced interoceptive accuracy (quantified using heartbeat detection tests) and exaggerated interoceptive sensibility (subjective sensitivity to internal sensations on self-report questionnaires), reflecting an impaired ability to objectively detect bodily signals alongside an over-inflated subjective perception of bodily sensations. The divergence of these two interoceptive axes can be computed as a trait prediction error. This error correlated with deficits in emotion sensitivity and occurrence of anxiety symptoms. Our results indicate an origin of emotion deficits and affective symptoms in ASC at the interface between body and mind, specifically in expectancy-driven interpretation of interoceptive information

Serum HCoV-spike specific antibodies do not protect against subsequent SARS-CoV-2 infection in children and adolescents

SARS-CoV-2 infections in children are generally asymptomatic or mild and rarely progress to severe disease and hospitalization. Why this is so remains unclear. Here we explore the potential for protection due to pre-existing cross-reactive seasonal coronavirus antibodies and compare the rate of antibody decline for nucleocapsid and spike protein in serum and oral fluid against SARS-CoV-2 within the pediatric population. No differences in seasonal coronaviruses antibody concentrations were found at baseline between cases and controls, suggesting no protective effect from pre-existing immunity against seasonal coronaviruses. Antibodies against seasonal betacoronaviruses were boosted in response to SARS-CoV-2 infection. In serum, anti-nucleocapsid antibodies fell below the threshold of positivity more quickly than anti-spike protein antibodies. These findings add to our understanding of protection against infection with SARS-CoV-2 within the pediatric population, which is important when considering pediatric SARS-CoV-2 immunization policies

Evidence-based practice in a multicultural world: changing with the times

Evidence-based practice (EBP), which is commonly implemented in high-income countries (HICs), integrates the best research evidence, clinical expertise and patient preferences in the planning and provision of healthcare for both physical and mental health conditions. Although the same principles of EBP apply in low- and middle-income countries (LMICs), research into and implementation of such interventions in these countries remains significantly behind compared with HICs. This article presents a brief overview of the global mental health agenda and initiatives aiming to address this pressing gap through the promotion of research and scaling up services, identification of barriers to developing and implementing EBP in LMICs, and possible solutions to overcome them.</p

Associations between Smoking and Alcohol and Follicular Lymphoma Incidence and Survival: A Family-Based Case-Control Study in Australia

The association between smoking and alcohol consumption and follicular lymphoma (FL) incidence and clinical outcome is uncertain. We conducted a population-based family case-control study (709 cases: 490 controls) in Australia. We assessed lifetime history of smoking and recent alcohol consumption and followed-up cases (median = 83 months). We examined associations with FL risk using unconditional logistic regression and with all-cause and FL-specific mortality of cases using Cox regression. FL risk was associated with ever smoking (OR = 1.38, 95%CI = 1.08–1.74), former smoking (OR = 1.36, 95%CI = 1.05–1.77), smoking initiation before age 17 (OR = 1.47, 95%CI = 1.06–2.05), the highest categories of cigarettes smoked per day (OR = 1.44, 95%CI = 1.04–2.01), smoking duration (OR = 1.53, 95%CI = 1.07–2.18) and pack-years (OR = 1.56, 95%CI = 1.10–2.22). For never smokers, FL risk increased for those exposed indoors to >2 smokers during childhood (OR = 1.84, 95%CI = 1.11–3.04). For cases, current smoking and the highest categories of smoking duration and lifetime cigarette exposure were associated with elevated all-cause mortality. The hazard ratio for current smoking and FL-specific mortality was 2.97 (95%CI = 0.91–9.72). We found no association between recent alcohol consumption and FL risk, all-cause or FL-specific mortality. Our study showed consistent evidence of an association between smoking and increased FL risk and possibly also FL-specific mortality. Strengthening anti-smoking policies and interventions may reduce the population burden of FL

Occupational exposure to extremely low-frequency magnetic fields and follicular lymphoma risk: a family case-control study

Objectives: We aimed to examine the relationship between occupational exposure to extremely low-frequency magnetic fields (ELF-MFs) and follicular lymphoma (FL) risk. Methods: We conducted a family case-control study between 2011 and 2016 in Australia and included 681 cases. Controls were either a family member of cases (related (n=294), unrelated (n=179)) or were unrelated recruited for a similarly designed Australian multiple myeloma study (n=711). We obtained detailed job histories using lifetime work calendars. We assigned exposure to ELF-MFs using an enhanced job exposure matrix, with a lag period of 10 years. We examined associations with FL risk using logistic regression accounting for relatedness between cases and controls. We performed sensitivity analyses including by control type, by sex, complete case analyses, ELF-MF exposure percentiles in addition to quartiles, ELF-MF exposure in the maximum exposed job, a shorter lag period (1 year) and the cumulative exposure in the most recent time period (1-9 years). Results: We observed no association with the average intensity, duration or lifetime cumulative exposure to occupational ELF-MF exposure in the primary or sensitivity analyses. Conclusions: Our findings do not support an association between occupational ELF-MF exposure and FL risk. Although the inclusion of family members as part of the larger control group may have biased our risk estimates towards the null, findings were similar in sensitivity analyses restricted to cases and unrelated controls. Further research incorporating enhanced exposure assessment to ELF-MF is warranted to inform occupational safety regulations and any potential role in lymphomagenesis.This study was supported by the National Health and Medical Research Council of Australia (ID 1006707). The National Health and Medical Research Council also supported MTvL (ID 1012141). MKO is supported by an International Postgraduate Award Scholarship through the Australian Government Research Training Program (ID 5188838) and a Cancer Institute NSW Translational Cancer Research Network PhD Scholarship Top-up award. MCT is funded by a Ramón y Cajal fellowship (RYC-2017-01892) from the Spanish Ministry of Science, Innovation and Universities and co-funded by the European Social Fund. ISGlobal acknowledges support from the Spanish Ministry of Science and Innovation through the 'Centro de Excelencia Severo Ochoa 2019–2023' Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. The INTEROCC Study was supported by the NIH (grant no. 1R01CA124759)

Supplementary Tables 1a-3d from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk

Supplementary Tables 1a-3d. Supplementary Table 1a: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours. Supplementary Table 1b: Average posterior probability value and odds of correct classification for outdoor hours trajectory groups. Supplementary Table 1c: Estimated probability and the proportion of study members classified in each group according to the maximum posterior probability assignment rule. Supplementary Table 2a: Odds ratios and 95% confidence intervals for FL risk in relation to total lifetime outdoor hours during decade years among cases and related controls.Supplementary Table 2b: Odds ratios and 95% confidence intervals for FL risk in relation to outdoor hours on weekdays, weekends, and holidays at each decade year among cases and related controls. Supplementary Table 2c: Odds ratios and 95% confidence intervals for FL risk in relation to trajectories of outdoor hours across the decade years among cases and related controls. Supplementary Table 2d: Odds ratios and 95% confidence intervals for FL risk in relation to total lifetime outdoor hours during decade years among cases and unrelated controls. Supplementary Table 2e: Odds ratios and 95% confidence intervals for FL risk in relation to outdoor hours on weekdays, weekends, and holidays at each decade year among cases and unrelated controls. Supplementary Table 2f: Odds ratios and 95% confidence intervals for FL risk in relation to trajectories of outdoor hours across the decade years among cases and unrelated controls. Supplementary Table 3a: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours – cases and related controls. Supplementary Table 3b: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours – cases and unrelated controls. Supplementary Table 3c: Average posterior probability value and odds of correct classification for outdoor hours trajectory groups. Supplementary Table 3d: Estimated probability and the proportion of study members classified in each group according to the maximum posterior probability assignment rule.</p

Supplementary Figure 5 from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk

Supplementary Figure 4 shows the estimated trajectories of outdoor hours by control type for warmer months (A and B), cooler months (C and D) and total (E and F)</p

Supplementary Figure 3 from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk

Supplementary Figure 3 shows the distribution of total hours per week at four decade years</p