A Pilot Study Using Machine Learning Algorithms and Wearable Technology for the Early Detection of Postoperative Complications After Cardiothoracic Surgery.

OBJECTIVE: To evaluate whether a machine learning algorithm (i.e. the "NightSignal" algorithm) can be used for the detection of postoperative complications prior to symptom onset after cardiothoracic surgery. SUMMARY BACKGROUND DATA: Methods that enable the early detection of postoperative complications after cardiothoracic surgery are needed. METHODS: This was a prospective observational cohort study conducted from July 2021 to February 2023 at a single academic tertiary care hospital. Patients aged 18 years or older scheduled to undergo cardiothoracic surgery were recruited. Study participants wore a Fitbit watch continuously for at least 1 week preoperatively and up to 90-days postoperatively. The ability of the NightSignal algorithm-which was previously developed for the early detection of Covid-19-to detect postoperative complications was evaluated. The primary outcomes were algorithm sensitivity and specificity for postoperative event detection. RESULTS: A total of 56 patients undergoing cardiothoracic surgery met inclusion criteria, of which 24 (42.9%) underwent thoracic operations and 32 (57.1%) underwent cardiac operations. The median age was 62 (IQR: 51-68) years and 30 (53.6%) patients were female. The NightSignal algorithm detected 17 of the 21 postoperative events a median of 2 (IQR: 1-3) days prior to symptom onset, representing a sensitivity of 81%. The specificity, negative predictive value, and positive predictive value of the algorithm for the detection of postoperative events were 75%, 97%, and 28%, respectively. CONCLUSIONS: Machine learning analysis of biometric data collected from wearable devices has the potential to detect postoperative complications-prior to symptom onset-after cardiothoracic surgery.

Differential associations of adolescent versus young adult cannabis initiation with longitudinal brain change and behavior.

Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14-19 years) and young adulthood (19-22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.

Penalized deep partially linear cox models with application to CT scans of lung cancer patients.

Lung cancer is a leading cause of cancer mortality globally, highlighting the importance of understanding its mortality risks to design effective patient-centered therapies. The National Lung Screening Trial (NLST) employed computed tomography texture analysis, which provides objective measurements of texture patterns on CT scans, to quantify the mortality risks of lung cancer patients. Partially linear Cox models have gained popularity for survival analysis by dissecting the hazard function into parametric and nonparametric components, allowing for the effective incorporation of both well-established risk factors (such as age and clinical variables) and emerging risk factors (eg, image features) within a unified framework. However, when the dimension of parametric components exceeds the sample size, the task of model fitting becomes formidable, while nonparametric modeling grapples with the curse of dimensionality. We propose a novel Penalized Deep Partially Linear Cox Model (Penalized DPLC), which incorporates the smoothly clipped absolute deviation (SCAD) penalty to select important texture features and employs a deep neural network to estimate the nonparametric component of the model. We prove the convergence and asymptotic properties of the estimator and compare it to other methods through extensive simulation studies, evaluating its performance in risk prediction and feature selection. The proposed method is applied to the NLST study dataset to uncover the effects of key clinical and imaging risk factors on patients' survival. Our findings provide valuable insights into the relationship between these factors and survival outcomes.

Surgery for M1A Non-Small-Cell Lung Cancer With Additional Pulmonary Nodules in a Contralateral Lobe.

INTRODUCTION: Limited consensus exists on the optimal treatment strategy for clinical M1a non-small-cell lung cancer (NSCLC) presenting as a primary tumor with additional intrapulmonary nodules in a contralateral lobe ("M1a-Contra"). This study sought to compare long-term survival of patients with M1a-Contra tumors receiving multimodal therapy with versus without thoracic surgery. METHODS: Overall survival of patients with cT1-4, N0-3, M1a NSCLC with contralateral intrapulmonary nodules who received surgery as part of multimodal therapy ("Thoracic Surgery") versus systemic therapy with or without radiation ("No Thoracic Surgery") in the National Cancer Database from 2010 to 2015 was evaluated using Kaplan-Meier analysis, Cox proportional hazards modeling, and propensity score matching. RESULTS: Of the 5042 patients who satisfied study inclusion criteria, 357 (7.1%) received multimodal therapy including surgery. In multivariable-adjusted analysis, the Thoracic Surgery cohort had better overall survival than the No Thoracic Surgery cohort (HR: 0.66, 95% CI: 0.56-0.79, P < 0.001). In a propensity score-matched analysis of 386 patients, well-balanced on 12 common prognostic covariates, the Thoracic Surgery group had better 5-year overall survival than the No Thoracic Surgery group (P = 0.020). In propensity score-matched analyses stratified by clinical N status, Thoracic Surgery was associated with better overall survival than No Thoracic Surgery for patients with cN0 disease and cN1-2 disease. CONCLUSIONS: In this national analysis, multimodal treatment including surgery was associated with better overall survival than systemic therapy with or without radiation without surgery for patients with M1a-Contra tumors. These preliminary findings highlight the importance of further evaluation of surgery in a multidisciplinary treatment setting for M1a-Contra tumors.

Efficacy and Safety of Supraclavicular Thoracic Outlet Decompression.

OBJECTIVES: We aimed to report efficacy, safety, and health-related quality of life (HRQoL) outcomes of a multidisciplinary treatment approach including supraclavicular thoracic outlet decompression among patients with thoracic outlet syndrome (TOS). BACKGROUND: TOS is a challenging condition where controversy remains in diagnosis and treatment, primarily given a lack of data exploring various treatment approaches and associated patient outcomes. METHODS: Patients who underwent unilateral, supraclavicular thoracic outlet decompression, or pectoralis minor tenotomy for neurogenic, venous, or arterial TOS were identified from a prospectively maintained database. Demography, use of preoperative botulinum toxin injection, and participation in multidisciplinary evaluation were measured. The primary endpoints were composite postoperative morbidity and symptomatic improvement compared with baseline. RESULTS: Among 2869 patients evaluated (2007-2021), 1032 underwent surgery, including 864 (83.7%) supraclavicular decompressions and 168 (16.3%) isolated pectoralis minor tenotomies. Predominant TOS subtypes among surgical patients were neurogenic (75.4%) and venous TOS (23.4%). Most patients (92.9%) with nTOS underwent preoperative botulinum toxin injection; 56.3% reported symptomatic improvement. Before surgical consultation, few patients reported participation in physical therapy (10.9%). The median time from first evaluation to surgery was 136 days (interquartile range: 55, 258). Among 864 patients who underwent supraclavicular thoracic outlet decompression, complications occurred in 19.8%; the most common complication was chyle leak (8.3%). Four patients (0.4%) required revisional thoracic outlet decompression. At a median follow-up of 420 days (interquartile range: 150, 937) 93.3% reported symptomatic improvement. CONCLUSION: Based on low composite morbidity, need for very few revisional operations, and high rates of symptomatic improvement, a multidisciplinary treatment approach including primarily supraclavicular thoracic outlet decompression is safe and effective for patients with TOS.

Machine learning approaches linking brain function to behavior in the ABCD STOP task.

The stop-signal task (SST) is one of the most common fMRI tasks of response inhibition, and its performance measure, the stop-signal reaction-time (SSRT), is broadly used as a measure of cognitive control processes. The neurobiology underlying individual or clinical differences in response inhibition remain unclear, consistent with the general pattern of quite modest brain-behavior associations that have been recently reported in well-powered large-sample studies. Here, we investigated the potential of multivariate, machine learning (ML) methods to improve the estimation of individual differences in SSRT with multimodal structural and functional region of interest-level neuroimaging data from 9- to 11-year-olds children in the ABCD Study. Six ML algorithms were assessed across modalities and fMRI tasks. We verified that SST activation performed best in predicting SSRT among multiple modalities including morphological MRI (cortical surface area/thickness), diffusion tensor imaging, and fMRI task activations, and then showed that SST activation explained 12% of the variance in SSRT using cross-validation and out-of-sample lockbox data sets (n = 7298). Brain regions that were more active during the task and that showed more interindividual variation in activation were better at capturing individual differences in performance on the task, but this was only true for activations when successfully inhibiting. Cortical regions outperformed subcortical areas in explaining individual differences but the two hemispheres performed equally well. These results demonstrate that the detection of reproducible links between brain function and performance can be improved with multivariate approaches and give insight into a number of brain systems contributing to individual differences in this fundamental cognitive control process.

Small molecule RAF265 as an antiviral therapy acts against HSV-1 by regulating cytoskeleton rearrangement and cellular translation machinery.

Host-targeting antivirals (HTAs) have received increasing attention for their potential as broad-spectrum antivirals that pose relatively low risk of developing drug resistance. The repurposing of pharmaceutical drugs for use as antivirals is emerging as a cost- and time- efficient approach to developing HTAs for the treatment of a variety of viral infections. In this study, we used a virus titer method to screen 30 small molecules for antiviral activity against Herpes simplex virus-1 (HSV-1). We found that the small molecule RAF265, an anticancer drug that has been shown to be a potent inhibitor of B-RAF V600E, reduced viral loads of HSV-1 by 4 orders of magnitude in Vero cells and reduced virus proliferation in vivo. RAF265 mediated cytoskeleton rearrangement and targeted the host cell's translation machinery, which suggests that the antiviral activity of RAF265 may be attributed to a dual inhibition strategy. This study offers a starting point for further advances toward clinical development of antivirals against HSV-1.

Maternal perceived stress and infant behavior during the COVID-19 pandemic.

BACKGROUND: Maternal stress has negative consequences on infant behavioral development, and COVID-19 presented uniquely stressful situations to mothers of infants born during the pandemic. We hypothesized that mothers with higher levels of perceived stress during the pandemic would report higher levels of infant regulatory problems including crying and interrupted sleep patterns. METHODS: As part 6 sites of a longitudinal study, mothers of infants born during the pandemic completed the Perceived Stress Scale, the Brief Infant Sleep Questionnaire, and an Infant Crying survey at 6 (n = 433) and 12 (n = 344) months of infant age. RESULTS: Maternal perceived stress, which remained consistent at 6 and 12 months of infant age, was significantly positively correlated with time taken to settle infants. Although maternal perceived stress was not correlated with uninterrupted sleep length, time taken to put the infant to sleep was correlated. Perceived stress was also correlated with the amount of infant crying and fussiness reported at 6 months. CONCLUSIONS: Mothers who reported higher levels of perceived stress during the pandemic reported higher levels of regulatory problems, specifically at 6 months. Examining how varying levels of maternal stress and infant behaviors relate to overall infant developmental status over time is an important next step. IMPACT: Women giving birth during the COVID-19 pandemic who reported higher levels of stress on the Perceived Stress Scale also reported higher levels of infant fussiness and crying at 6 months old, and more disruptive sleep patterns in their infants at 6 months and 12 months old. Sleeping problems and excessive crying in infancy are two regulatory problems that are known risk factors for emotional and behavioral issues in later childhood. This paper is one of the first studies highlighting the associations between maternal stress and infant behaviors during the COVID-19 pandemic.

Wedge Resection Versus Segmentectomy for Older Patients With Stage IA Non-Small-Cell Lung Cancer.

INTRODUCTION: Anatomic lung resection remains the standard of care for early-stage non-small-cell lung cancer (NSCLC), but wedge resection may offer similar survival in older adult patients. The objective of this study was to evaluate the survival of patients aged 80 y and older undergoing wedge resection versus segmentectomy for stage IA NSCLC using a large clinical registry. METHODS: Patients aged 80 y and older in the National Cancer Database who underwent wedge resection or segmentectomy for cT1a-b N0 M0 NSCLC between 2004 and 2018 were identified for an analysis. Survival was assessed using multivariable Cox proportional hazards analysis, propensity-score matching, and inverse probability weighting. A subgroup analysis of patients who underwent lymph node evaluation with their wedge resection or segmentectomy was also performed. RESULTS: Of the 2690 patients identified, 2272 (84%) underwent wedge resection and 418 (16%) underwent segmentectomy. Wedge resection was associated with worse 5-year overall survival relative to segmentectomy in multivariable-adjusted (adjusted Hazard Ratio: 1.26, [1.06-1.51], P = 0.01) and propensity score-matched analysis (49% [95% confidence interval {CI}: 42%-55%] versus 59% [95% CI: 52%-65%], P = 0.02). Among a subgroup of 1221 wedge resection and 347 segmentectomy patients who also received intraoperative lymph node evaluation, however, there were no significant differences in 5-year survival in multivariable-adjusted (adjusted Hazard Ratio: 1.12, [0.90-1.39], P = 0.31) or propensity score-matched analysis (55% [95% CI: 48%-62%] versus 61% [95% CI: 54%-68%], P = 0.10). CONCLUSIONS: In this national analysis, there were no significant differences in survival between older adult patients with stage IA NSCLC who underwent wedge resection versus segmentectomy when a lymph node evaluation was performed.

Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD Study.

The use of predefined parcellations on surface-based representations of the brain as a method for data reduction is common across neuroimaging studies. In particular, prediction-based studies typically employ parcellation-driven summaries of brain measures as input to predictive algorithms, but the choice of parcellation and its influence on performance is often ignored. Here we employed preprocessed structural magnetic resonance imaging (sMRI) data from the Adolescent Brain Cognitive Development Study® to examine the relationship between 220 parcellations and out-of-sample predictive performance across 45 phenotypic measures in a large sample of 9- to 10-year-old children (N = 9,432). Choice of machine learning (ML) pipeline and use of alternative multiple parcellation-based strategies were also assessed. Relative parcellation performance was dependent on the spatial resolution of the parcellation, with larger number of parcels (up to ~4,000) outperforming coarser parcellations, according to a power-law scaling of between 1/4 and 1/3. Performance was further influenced by the type of parcellation, ML pipeline, and general strategy, with existing literature-based parcellations, a support vector-based pipeline, and ensembling across multiple parcellations, respectively, as the highest performing. These findings highlight the choice of parcellation as an important influence on downstream predictive performance, showing in some cases that switching to a higher resolution parcellation can yield a relatively large boost to performance.

The Risk of Postoperative Complications After Major Elective Surgery in Active or Resolved COVID-19 in the United States.

OBJECTIVE: To assess the association between the timing of surgery relative to the development of Covid-19 and the risks of postoperative complications. SUMMARY BACKGROUND DATA: It is unknown whether patients who recovered from Covid-19 and then underwent a major elective operation have an increased risk of developing postoperative complications. METHODS: The risk of postoperative complications for patients with Covid-19 undergoing 18 major types of elective operations in the Covid-19 Research Database was evaluated using multivariable logistic regression. Patients were grouped by time of surgery relative to SARS-CoV-2 infection; that is, surgery performed: (1) before January 1, 2020 ("pre-Covid-19"), (2) 0 to 4 weeks after SARS-CoV-2 infection ("peri-Covid-19"), (3) 4 to 8 weeks after infection ("early post-Covid-19"), and (4) ≥8 weeks after infection ("late post-Covid-19"). RESULTS: Of the 5479 patients who met study criteria, patients with peri-Covid-19 had an elevated risk of developing postoperative pneumonia [adjusted odds ratio (aOR), 6.46; 95% confidence interval (CI): 4.06-10.27], respiratory failure (aOR, 3.36; 95% CI: 2.22-5.10), pulmonary embolism (aOR, 2.73; 95% CI: 1.35-5.53), and sepsis (aOR, 3.67; 95% CI: 2.18-6.16) when compared to pre-Covid-19 patients. Early post-Covid-19 patients had an increased risk of developing postoperative pneumonia when compared to pre-Covid-19 patients (aOR, 2.44; 95% CI: 1.20-4.96). Late post-Covid-19 patients did not have an increased risk of postoperative complications when compared to pre-Covid-19 patients. CONCLUSIONS: Major, elective surgery 0 to 4 weeks after SARS-CoV-2 infection is associated with an increased risk of postoperative complications. Surgery performed 4 to 8 weeks after SARS-CoV-2 infection is still associated with an increased risk of postoperative pneumonia, whereas surgery 8 weeks after Covid-19 diagnosis is not associated with increased complications.

Commentary: Reply to 'Transgender and mental health' by Philip Graham.

The letter to the editor from Philip Graham regarding the manuscript 'Early adolescent gender diversity and mental health in the Adolescent Brain Cognitive Development study' (Potter et al., 2021) raises several points that highlight the complexity of the conversation around gender development in youth. While there is an agreement between the original manuscript and much of the letter, some of the issues raised warrant further discussion and clarification.

Geotemporal analysis of perinatal care changes and maternal mental health: an example from the COVID-19 pandemic.

Our primary objective was to document COVID-19 induced changes to perinatal care across the USA and examine the implication of these changes for maternal mental health. We performed an observational cross-sectional study with convenience sampling using direct patient reports from 1918 postpartum and 3868 pregnant individuals collected between April 2020 and December 2020 from 10 states across the USA. We leverage a subgroup of these participants who gave birth prior to March 2020 to estimate the pre-pandemic prevalence of specific birthing practices as a comparison. Our primary analyses describe the prevalence and timing of perinatal care changes, compare perinatal care changes depending on when and where individuals gave birth, and assess the linkage between perinatal care alterations and maternal anxiety and depressive symptoms. Seventy-eight percent of pregnant participants and 63% of postpartum participants reported at least one change to their perinatal care between March and August 2020. However, the prevalence and nature of specific perinatal care changes occurred unevenly over time and across geographic locations. The separation of infants and mothers immediately after birth and the cancelation of prenatal visits were associated with worsened depression and anxiety symptoms in mothers after controlling for sociodemographic factors, mental health history, number of pregnancy complications, and general stress about the COVID-19 pandemic. Our analyses reveal widespread changes to perinatal care across the US that fluctuated depending on where and when individuals gave birth. Disruptions to perinatal care may also exacerbate mental health concerns, so focused treatments that can mitigate the negative psychiatric sequelae of interrupted care are warranted.

Early adolescent gender diversity and mental health in the Adolescent Brain Cognitive Development study.

BACKGROUND: There are known associations between mental health symptoms and transgender identity among adults. Whether this relationship extends to early adolescents and to gender domains other than identity is unclear. This study measured dimensions of gender in a large, diverse, sample of youth, and examined associations between diverse gender experiences and mental health. METHODS: The ABCD study is an ongoing, longitudinal, US cohort study. Baseline data (release 2.0) include 11,873 youth age 9/10 (48% female); and the 4,951 1-year follow-up visits (age 10/11; 48% female) completed prior to data release. A novel gender survey at the 1-year visit assessed felt-gender, gender noncontentedness, and gender nonconformity using a 5-point scale. Mental health measures included youth- and parent-reports. RESULTS: Roughly half a percent of 9/10-year-olds (n = 58) responded 'yes' or 'maybe' when asked, 'Are you transgender' at baseline. Recurrent thoughts of death were more prevalent among these youth compared to the rest of the cohort (19.6% vs. 6.4%, χ2  = 16.0, p < .001). At the 1-year visit, when asked about the three dimensions of gender on a 5-point scale, 33.2% (n = 1,605) provided responses that were not exclusively and totally aligned with one gender. Significant relationships were observed between mental health symptoms and gender diversity for all dimensions assessed. CONCLUSIONS: Similar to adult studies, early adolescents identifying as transgender reported increased mental health symptoms. Results also point to considerable diversity in other dimensions of gender (felt-gender, gender noncontentedness, gender nonconformity) among 10/11-year-olds, and find this diversity to be related to critical mental health symptoms. These findings add to our limited understanding of the relationship between dimensions of gender and wellness for youth.

Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children.

The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems.

Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence.

Rates of cannabis use among adolescents are high, and are increasing concurrent with changes in the legal status of marijuana and societal attitudes regarding its use. Recreational cannabis use is understudied, especially in the adolescent period when neural maturation may make users particularly vulnerable to the effects of Δ-9-tetrahydrocannabinol (THC) on brain structure. In the current study, we used voxel-based morphometry to compare gray matter volume (GMV) in forty-six 14-year-old human adolescents (males and females) with just one or two instances of cannabis use and carefully matched THC-naive controls. We identified extensive regions in the bilateral medial temporal lobes as well as the bilateral posterior cingulate, lingual gyri, and cerebellum that showed greater GMV in the cannabis users. Analysis of longitudinal data confirmed that GMV differences were unlikely to precede cannabis use. GMV in the temporal regions was associated with contemporaneous performance on the Perceptual Reasoning Index and with future generalized anxiety symptoms in the cannabis users. The distribution of GMV effects mapped onto biomarkers of the endogenous cannabinoid system providing insight into possible mechanisms for these effects.SIGNIFICANCE STATEMENT Almost 35% of American 10th graders have reported using cannabis and existing research suggests that initiation of cannabis use in adolescence is associated with long-term neurocognitive effects. We understand very little about the earliest effects of cannabis use, however, because most research is conducted in adults with a heavy pattern of lifetime use. This study presents evidence suggesting structural brain and cognitive effects of just one or two instances of cannabis use in adolescence. Converging evidence suggests a role for the endocannabinoid system in these effects. This research is particularly timely as the legal status of cannabis is changing in many jurisdictions and the perceived risk by youth associated with smoking cannabis has declined in recent years.

Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood.

Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.

The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features.

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.

The effect of executive function on adherence with a cardiac secondary prevention program and its interaction with an incentive-based intervention.

Participation in secondary prevention programs such as cardiac rehabilitation (CR) reduces morbidity, mortality, and hospitalizations while improving quality of life. Executive function (EF) is a complex set of cognitive abilities that control and regulate behavior. EF predicts many health-related behaviors, but how EF interacts with interventions to improve treatment adherence is not well understood. The objective of this study is to examine if EF predicts CR treatment adherence and how EF interacts with an intervention to improve adherence. Data were collected from 2013 to 2018 in Vermont, USA. 130 Medicaid-enrolled individuals who had experienced a qualifying cardiac event were enrolled in a controlled clinical trial and randomized 1:1 to receive financial incentives for completing secondary prevention sessions or to usual care. In this secondary analysis, effects of EF on CR adherence (defined as completing ≥30/36 sessions) were examined in 112 participants (57 usual care, 55 intervention) who completed an EF battery. Delay-discounting, a measure of impulsivity, predicted CR adherence (p = 0.01) and interacted with the incentive intervention, such that those who exhibited greater discounting of future rewards benefitted more from the intervention than those who discounted less (F(1, 104) = 5.23, p = 0.02). Better cognitive flexibility, measured with the trail-making-task, also predicted CR adherence (p = 0.02). While EF has been associated with adherence to a variety of treatment regimens, this interaction between an incentive-based intervention to promote treatment adherence and EF is novel. This work illustrates the value of considering individual differences in EF when designing and implementing interventions to promote health-related behavior change.

Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology.

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.