Neurobiological correlates of antisociality across adolescence and young adulthood: a multi-sample, multi-method study.

BACKGROUND: Antisociality across adolescence and young adulthood puts individuals at high risk of developing a variety of problems. Prior research has linked antisociality to autonomic nervous system and endocrinological functioning. However, there is large heterogeneity in antisocial behaviors, and these neurobiological measures are rarely studied conjointly, limited to small specific studies with narrow age ranges, and yield mixed findings due to the type of behavior examined. METHODS: We harmonized data from 1489 participants (9-27 years, 67% male), from six heterogeneous samples. In the resulting dataset, we tested relations between distinct dimensions of antisociality and heart rate, pre-ejection period (PEP), respiratory sinus arrhythmia, respiration rate, skin conductance levels, testosterone, basal cortisol, and the cortisol awakening response (CAR), and test the role of age throughout adolescence and young adulthood. RESULTS: Three dimensions of antisociality were uncovered: 'callous-unemotional (CU)/manipulative traits', 'intentional aggression/conduct', and 'reactivity/impulsivity/irritability'. Shorter PEPs and higher testosterone were related to CU/manipulative traits, and a higher CAR is related to both CU/manipulative traits and intentional aggression/conduct. These effects were stable across age. CONCLUSIONS: Across a heterogeneous sample and consistent across development, the CAR may be a valuable measure to link to CU/manipulative traits and intentional aggression, while sympathetic arousal and testosterone are additionally valuable to understand CU/manipulative traits. Together, these findings deepen our understanding of the fundamental mechanisms underlying different components of antisociality. Finally, we illustrate the potential of using current statistical techniques for combining multiple datasets to draw robust conclusions about biobehavioral associations.

Effectiveness of an online self-help program, expert-patient support, and their combination for eating disorders: Results from a randomized controlled trial.

OBJECTIVE: Many individuals with an eating disorder do not receive appropriate care. Low-threshold interventions could help bridge this treatment gap. The study aim was to evaluate the effectiveness of Featback, a fully automated online self-help intervention, online expert-patient support and their combination. METHOD: A randomized controlled trial with a 12-month follow-up period was conducted. Participants aged 16 or older with at least mild eating disorder symptoms were randomized to four conditions: (1) Featback, a fully automated online self-help intervention, (2) chat or email support from a recovered expert patient, (3) Featback with expert-patient support and (4) a waiting list control condition. The intervention period was 8 weeks and there was a total of six online assessments. The main outcome constituted reduction of eating disorder symptoms over time. RESULTS: Three hundred fifty five participants, of whom 43% had never received eating disorder treatment, were randomized. The three active interventions were superior to a waitlist in reducing eating disorder symptoms (d = -0.38), with no significant difference in effectiveness between the three interventions. Participants in conditions with expert-patient support were more satisfied with the intervention. DISCUSSION: Internet-based self-help, expert-patient support and their combination were effective in reducing eating disorder symptoms compared to a waiting list control condition. Guidance improved satisfaction with the internet intervention but not its effectiveness. Low-threshold interventions such as Featback and expert-patient support can reduce eating disorder symptoms and reach the large group of underserved individuals, complementing existing forms of eating disorder treatment. PUBLIC SIGNIFICANCE STATEMENT: Individuals with eating-related problems who received (1) a fully automated internet-based intervention, (2) chat and e-mail support by a recovered individual or (3) their combination, experienced stronger reductions in eating disorder symptoms than those who received (4) usual care. Such brief and easy-access interventions play an important role in reaching individuals who are currently not reached by other forms of treatment.

Cost-effectiveness of three internet-based interventions for eating disorders: A randomized controlled trial.

OBJECTIVE: The primary aim was assessing the cost-effectiveness of an internet-based self-help program, expert-patient support, and the combination of both compared to a care-as-usual condition. METHOD: An economic evaluation from a societal perspective was conducted alongside a randomized controlled trial. Participants aged 16 or older with at least mild eating disorder symptoms were randomly assigned to four conditions: (1) Featback, an online unguided self-help program, (2) chat or e-mail support from a recovered expert patient, (3) Featback with expert-patient support, and (4) care-as-usual. After a baseline assessment and intervention period of 8 weeks, five online assessments were conducted over 12 months of follow-up. The main result constituted cost-utility acceptability curves with quality-of-life adjusted life years (QALYs) and societal costs over the entire study duration. RESULTS: No significant differences between the conditions were found regarding QALYs, health care costs and societal costs. Nonsignificant differences in QALYs were in favor of the Featback conditions and the lowest societal costs per participant were observed in the Featback only condition (€16,741) while the highest costs were seen in the care-as-usual condition (€28,479). The Featback only condition had the highest probability of being efficient compared to the alternatives for all acceptable willingness-to-pay values. DISCUSSION: Featback, an internet-based unguided self-help intervention, was likely to be efficient compared to Featback with guidance from an expert patient, guidance alone and a care-as-usual condition. Results suggest that scalable interventions such as Featback may reduce health care costs and help individuals with eating disorders that are currently not reached by other forms of treatment. PUBLIC SIGNIFICANCE STATEMENT: Internet-based interventions for eating disorders might reach individuals in society who currently do not receive appropriate treatment at low costs. Featback, an online automated self-help program for eating disorders, was found to improve quality of life slightly while reducing costs for society, compared to a do-nothing approach. Consequently, implementing internet-based interventions such as Featback likely benefits both individuals suffering from an eating disorder and society as a whole.

The role of infant attention and parental sensitivity in infant cognitive development in the Netherlands and China.

Infant attention and parental sensitivity are important predictors of later child executive function (EF). However, most studies have investigated infant and parent factors in relation to child EF separately and included only mothers from Western samples. The current study examined whether both infant attention at 4 months and parental sensitivity at 4 and 14 months were related to infant EF (i.e., inhibition, working memory, and cognitive flexibility) at 14 months among 124 Dutch and 63 Chinese first-time mothers and fathers and their infants. Findings revealed that parental sensitivity at 4 months was not correlated with infant EF abilities at 14 months. However, infant attention at 4 months was significantly related to 14-month working memory, but not to inhibition and cognitive flexibility. Maternal sensitivity at 14 months was significantly related to 14-month inhibition, but not to working memory and cognitive flexibility. No country differences were found in the relation among 4-month infant attention, parental sensitivity, and EF outcomes. Results show that both infant and parent factors are associated with early EF development and that these correlates of early EF skills may be similar in Western and non-Western samples.

Rebutting Existing Misconceptions About Multiple Imputation as a Method for Handling Missing Data.

Missing data is a problem that occurs frequently in many scientific areas. The most sophisticated method for dealing with this problem is multiple imputation. Contrary to other methods, like listwise deletion, this method does not throw away information, and partly repairs the problem of systematic dropout. Although from a theoretical point of view multiple imputation is considered to be the optimal method, many applied researchers are reluctant to use it because of persistent misconceptions about this method. Instead of providing an(other) overview of missing data methods, or extensively explaining how multiple imputation works, this article aims specifically at rebutting these misconceptions, and provides applied researchers with practical arguments supporting them in the use of multiple imputation.

Significance Tests and Estimates for R2 for Multiple Regression in Multiply Imputed Datasets: A Cautionary Note on Earlier Findings, and Alternative Solutions.

Whenever multiple regression is applied to a multiply imputed data set, several methods for combining significance tests for R2 and the change in R2 across imputed data sets may be used: the combination rules by Rubin, the Fisher z-test for R2 by Harel, and F-tests for the change in R2 by Chaurasia and Harel. For pooling R2 itself, Harel proposed a method based on a Fisher z transformation. In the current article, it is argued that the pooled R2 based on the Fisher z transformation, the Fisher z-test for R2 , and the F-test for the change in R2 have some theoretical flaws. An argument is made for using Rubin's method for pooling significance tests for R2 instead, and alternative procedures for pooling R2 are proposed: simple averaging and a pooled R2 constructed from the pooled significance test by Rubin. Simulations show that the Fisher z-test and Chaurasia and Harel's F-tests generally give inflated type-I error rates, whereas the type-I error rates of Rubin's method are correct. Of the methods for pooling the point estimates of R2 no method clearly performs best, but it is argued that the average of R2 's across imputed data set is preferred.

Droplet digital PCR for detection and quantification of circulating tumor DNA in plasma of head and neck cancer patients.

BACKGROUND: During posttreatment surveillance of head and neck cancer patients, imaging is insufficiently accurate for the early detection of relapsing disease. Free circulating tumor DNA (ctDNA) may serve as a novel biomarker for monitoring tumor burden during posttreatment surveillance of these patients. In this exploratory study, we investigated whether low level ctDNA in plasma of head and neck cancer patients can be detected using Droplet Digital PCR (ddPCR). METHODS: TP53 mutations were determined in surgically resected primary tumor samples from six patients with high stage (II-IV), moderate to poorly differentiated head and neck squamous cell carcinoma (HNSCC). Subsequently, mutation specific ddPCR assays were designed. Pretreatment plasma samples from these patients were examined on the presence of ctDNA by ddPCR using the mutation-specific assays. The ddPCR results were evaluated alongside clinicopathological data. RESULTS: In all cases, plasma samples were found positive for targeted TP53 mutations in varying degrees (absolute quantification of 2.2-422 mutational copies/ml plasma). Mutations were detected in wild-type TP53 background templates of 7667-156,667 copies/ml plasma, yielding fractional abundances of down to 0.01%. CONCLUSIONS: Our results show that detection of tumor specific TP53 mutations in low level ctDNA from HNSCC patients using ddPCR is technically feasible and provide ground for future research on ctDNA quantification for the use of diagnostic biomarkers in the posttreatment surveillance of HNSCC patients.

Liquid Biopsy: A Future Tool for Posttreatment Surveillance in Head and Neck Cancer?

The prognosis of head and neck squamous cell carcinoma (HNSCC) is largely based on disease stage. Despite improvements in treatment, recurrence rates are still considered high. Currently, disease progression or regression after curative treatment is monitored by clinical evaluation combined with flexible endoscopy and/or imaging. However, specificity of imaging is low due to the posttreatment effects. Detection of circulating tumor DNA (ctDNA) from blood samples of HNSCC patients is a minimally invasive technique that could lead to an earlier detection of recurrence. In addition, digital droplet PCR (ddPCR) could be used to sensitively detect these mutational targets. Future study on ctDNA using ddPCR in blood samples of HNSCC patients is recommended during the follow-up stage to detect recurrences in a timely manner.

The perception of emotion and focus prosody with varying acoustic cues in cochlear implant simulations with varying filter slopes.

This study aimed to find the optimal filter slope for cochlear implant simulations (vocoding) by testing the effect of a wide range of slopes on the discrimination of emotional and linguistic (focus) prosody, with varying availability of F0 and duration cues. Forty normally hearing participants judged if (non-)vocoded sentences were pronounced with happy or sad emotion, or with adjectival or nominal focus. Sentences were recorded as natural stimuli and manipulated to contain only emotion- or focus-relevant segmental duration or F0 information or both, and then noise-vocoded with 5, 20, 80, 120, and 160 dB/octave filter slopes. Performance increased with steeper slopes, but only up to 120 dB/octave, with bigger effects for emotion than for focus perception. For emotion, results with both cues most closely resembled results with F0, while for focus results with both cues most closely resembled those with duration, showing emotion perception relies primarily on F0, and focus perception on duration. This suggests that filter slopes affect focus perception less than emotion perception because for emotion, F0 is both more informative and more affected. The performance increase until extreme filter slope values suggests that much performance improvement in prosody perception is still to be gained for CI users.

Do internationally adopted children in the Netherlands use more medication than their non-adopted peers?

UNLABELLED: Empirical evidence has shown that international adoptees present physical growth delays, precocious puberty, behavioral problems, and mental health referrals more often than non-adoptees. We hypothesized that the higher prevalence of (mental) health problems in adoptees is accompanied by elevated consumption of prescription drugs, including antidepressants, attention deficit hyperactivity disorder (ADHD) medication, and medication for growth inhibition/stimulation. In an archival, population-based Dutch cohort study, data on medication use were available from the Health Care Insurance Board by Statistics Netherlands from 2006 to 2011. The Dutch population born between 1994 and 2005 and alive during the period of measurement was included (2,360,450 including 10,602 international adoptees, of which 4447 from China). Their mean age was 6.5 years at start (range 1-12 years) and 11.5 years at the end of the measurement period (range 6-17 years). Chinese female adoptees used less medication for precocious puberty (as treatment for precocious puberty; odds ratio (OR) = 0.57, effect size Cohen's d = -0.31) and contraception (OR = 0.65, d = -0.24) than non-adoptees. For both males and females, non-Chinese adoptees used more medication for ADHD than non-adoptees (males: OR = 1.22, females: OR = 1.32), but the effect was small (males: d = 0.11, females: d = 0.15). CONCLUSIONS: Adoptees in the Netherlands generally do not use more medication than their non-adopted peers. WHAT IS KNOWN: • Meta-analytical evidence shows that international adoptees present physical growth delays and mental health referrals more often than non-adopted controls. • With the exception of one Swedish study on ADHD medication, there is no other systematic research on medication use of international adoptees. What is New: • All differences in medication use between international adoptees in the Netherlands and non-adopted controls were below the threshold of a small effect with the exception of medication for precocious puberty, but this effect was in the opposite direction with female adoptees using less medication for precocious puberty than non-adoptees. • International adoptees in the Netherlands do not use more medication despite experiences of preadoption adversity and higher rates of mental health referrals during childhood and adolescence.

Web-Based Fully Automated Self-Help With Different Levels of Therapist Support for Individuals With Eating Disorder Symptoms: A Randomized Controlled Trial.

BACKGROUND: Despite the disabling nature of eating disorders (EDs), many individuals with ED symptoms do not receive appropriate mental health care. Internet-based interventions have potential to reduce the unmet needs by providing easily accessible health care services. OBJECTIVE: This study aimed to investigate the effectiveness of an Internet-based intervention for individuals with ED symptoms, called "Featback." In addition, the added value of different intensities of therapist support was investigated. METHODS: Participants (N=354) were aged 16 years or older with self-reported ED symptoms, including symptoms of anorexia nervosa, bulimia nervosa, and binge eating disorder. Participants were recruited via the website of Featback and the website of a Dutch pro-recovery-focused e-community for young women with ED problems. Participants were randomized to: (1) Featback, consisting of psychoeducation and a fully automated self-monitoring and feedback system, (2) Featback supplemented with low-intensity (weekly) digital therapist support, (3) Featback supplemented with high-intensity (3 times a week) digital therapist support, and (4) a waiting list control condition. Internet-administered self-report questionnaires were completed at baseline, post-intervention (ie, 8 weeks after baseline), and at 3- and 6-month follow-up. The primary outcome measure was ED psychopathology. Secondary outcome measures were symptoms of depression and anxiety, perseverative thinking, and ED-related quality of life. Statistical analyses were conducted according to an intent-to-treat approach using linear mixed models. RESULTS: The 3 Featback conditions were superior to a waiting list in reducing bulimic psychopathology (d=-0.16, 95% confidence interval (CI)=-0.31 to -0.01), symptoms of depression and anxiety (d=-0.28, 95% CI=-0.45 to -0.11), and perseverative thinking (d=-0.28, 95% CI=-0.45 to -0.11). No added value of therapist support was found in terms of symptom reduction although participants who received therapist support were significantly more satisfied with the intervention than those who did not receive supplemental therapist support. No significant differences between the Featback conditions supplemented with low- and high-intensity therapist support were found regarding the effectiveness and satisfaction with the intervention. CONCLUSIONS: The fully automated Internet-based self-monitoring and feedback intervention Featback was effective in reducing ED and comorbid psychopathology. Supplemental therapist support enhanced satisfaction with the intervention but did not increase its effectiveness. Automated interventions such as Featback can provide widely disseminable and easily accessible care. Such interventions could be incorporated within a stepped-care approach in the treatment of EDs and help to bridge the gap between mental disorders and mental health care services. TRIAL REGISTRATION: Netherlands Trial Registry: NTR3646; http://www.trialregister.nl/trialreg/admin/ rctview.asp?TC=3646 (Archived by WebCite at http://www.webcitation.org/6fgHTGKHE).

Epidemiology and outcome of infections with carbapenem-resistant Gram-negative bacteria treated with polymyxin B-based combination therapy.

INTRODUCTION: Infections with carbapenem-resistant Gram-negative bacteria (CRGNB) are increasing and are associated with a high mortality. Synergistic effects of combination therapy with a polymyxin, carbapenem, and rifampin have been observed in in vitro studies. Clinical data are limited to retrospective studies. METHODS: We performed an observational cohort study of patients over 18 y of age who were treated with polymyxin B combination therapy. RESULTS: One hundred and four patients were studied. The mean age was 77 y; 73% had recently received antibiotics, 67% had recently been hospitalized, and 47% lived in a nursing facility. The most common infections were pneumonia and urinary tract infection due to Acinetobacter baumannii (33%), Klebsiella pneumoniae (24%), and Pseudomonas aeruginosa (11%). Treatment regimens included polymyxin B with a carbapenem in 48%, with additional rifampin in 23%. Clinical success was achieved in 50% and reinfection occurred in 25%. Treatment-related acute renal failure occurred in 14.4%. No treatment-related hemodialysis was needed. All-cause hospital mortality was 47% and mortality after 6 months was 77%. No significant difference was found between treatment regimens. Age (odds ratio (OR) 10.4 per 10 y, p = 0.04), severity of acute illness (OR 2.2 per point, p < 0.001), and Charlson score (OR 1.12 per point, p = 0.04) were associated with hospital mortality. K. pneumoniae was associated with increased hospital survival compared to other CRGNB (p = 0.03). CONCLUSION: CRGNB infections are associated with previous antibiotic and health care exposure. Mortality is related to age and the severity of chronic and acute illness.

Analysis of Variance of Multiply Imputed Data.

As a procedure for handling missing data, Multiple imputation consists of estimating the missing data multiple times to create several complete versions of an incomplete data set. All these data sets are analyzed by the same statistical procedure, and the results are pooled for interpretation. So far, no explicit rules for pooling F-tests of (repeated-measures) analysis of variance have been defined. In this paper we outline the appropriate procedure for the results of analysis of variance for multiply imputed data sets. It involves both reformulation of the ANOVA model as a regression model using effect coding of the predictors and applying already existing combination rules for regression models. The proposed procedure is illustrated using three example data sets. The pooled results of these three examples provide plausible F- and p-values.

A comparison of different measures of the proportion of explained variance in multiply imputed data sets.

The proportion of explained variance is an important statistic in multiple regression for determining how well the outcome variable is predicted by the predictors. Earlier research on 20 different estimators for the proportion of explained variance, including the exact Olkin-Pratt estimator and the Ezekiel estimator, showed that the exact Olkin-Pratt estimator produced unbiased estimates, and was recommended as a default estimator. In the current study, the same 20 estimators were studied in incomplete data, with missing data being treated using multiple imputation. In earlier research on the proportion of explained variance in multiply imputed data sets, an estimator called R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ was shown to be the preferred pooled estimator for regular R 2 $$ {R}^2 $$ . For each of the 20 estimators in the current study, two pooled estimators were proposed: one where the estimator was the average across imputed data sets, and one where R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ was used as input for the calculation of the specific estimator. Simulations showed that estimates based on R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ performed best regarding bias and accuracy, and that the Ezekiel estimator was generally the least biased. However, none of the estimators were unbiased at all times, including the exact Olkin-Pratt estimator based on R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ .

Role of knowledge and reasoning processes as predictors of resident physicians' susceptibility to anchoring bias in diagnostic reasoning: a randomised controlled experiment.

BACKGROUND: Diagnostic errors have been attributed to reasoning flaws caused by cognitive biases. While experiments have shown bias to cause errors, physicians of similar expertise differed in susceptibility to bias. Resisting bias is often said to depend on engaging analytical reasoning, disregarding the influence of knowledge. We examined the role of knowledge and reasoning mode, indicated by diagnosis time and confidence, as predictors of susceptibility to anchoring bias. Anchoring bias occurs when physicians stick to an incorrect diagnosis triggered by early salient distracting features (SDF) despite subsequent conflicting information. METHODS: Sixty-eight internal medicine residents from two Dutch university hospitals participated in a two-phase experiment. Phase 1: assessment of knowledge of discriminating features (ie, clinical findings that discriminate between lookalike diseases) for six diseases. Phase 2 (1 week later): diagnosis of six cases of these diseases. Each case had two versions differing exclusively in the presence/absence of SDF. Each participant diagnosed three cases with SDF (SDF+) and three without (SDF-). Participants were randomly allocated to case versions. Based on phase 1 assessment, participants were split into higher knowledge or lower knowledge groups. MAIN OUTCOME MEASUREMENTS: frequency of diagnoses associated with SDF; time to diagnose; and confidence in diagnosis. RESULTS: While both knowledge groups performed similarly on SDF- cases, higher knowledge physicians succumbed to anchoring bias less frequently than their lower knowledge counterparts on SDF+ cases (p=0.02). Overall, physicians spent more time (p<0.001) and had lower confidence (p=0.02) on SDF+ than SDF- cases (p<0.001). However, when diagnosing SDF+ cases, the groups did not differ in time (p=0.88) nor in confidence (p=0.96). CONCLUSIONS: Physicians apparently adopted a more analytical reasoning approach when presented with distracting features, indicated by increased time and lower confidence, trying to combat bias. Yet, extended deliberation alone did not explain the observed performance differences between knowledge groups. Success in mitigating anchoring bias was primarily predicted by knowledge of discriminating features of diagnoses.

Enhancement of Room Temperature Ethanol Sensing by Optimizing the Density of Vertically Aligned Carbon Nanofibers Decorated with Gold Nanoparticles.

An ethanol gas sensor based on carbon nanofibers (CNFs) with various densities and nanoparticle functionalization was investigated. The CNFs were grown by means of a Plasma-Enhanced Chemical Vapor Deposition (PECVD), and the synthesis conditions were varied to obtain different number of fibers per unit area. The devices with a larger density of CNFs lead to higher responses, with a maximal responsivity of 10%. Furthermore, to simultaneously improve the sensitivity and selectivity, CNFs were decorated with gold nanoparticles by an impaction printing method. After metal decoration, the devices showed a response 300% higher than pristine devices toward 5 ppm of ethanol gas. The morphology and structure of the different samples deposited on a silicon substrate were characterized by TEM, EDX, SEM, and Raman spectroscopy, and the results confirmed the presence of CNF decorated with gold. The influence of operating temperature (OT) and humidity were studied on the sensing devices. In the case of decorated samples with a high density of nanofibers, a less-strong cross-sensitivity was observed toward a variation in humidity and temperature.

The diagnostic process from primary care to child and adolescent mental healthcare services: the incremental value of information conveyed through referral letters, screening questionnaires and structured multi-informant assessment.

BACKGROUND: A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined. AIMS: To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians' remote evaluations in predicting mental health disorders. METHOD: Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed. RESULTS: Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value. CONCLUSIONS: Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary-secondary care interface should now be quantified in prospective studies.

Accurate detection of circulating tumor DNA using nanopore consensus sequencing.

Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant ctDNA molecules based on somatic variants, extremely sensitive sequencing methods are required. Here, we describe a new technique, CyclomicsSeq, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule. Consensus calling of the DNA copies increased the base-calling accuracy ~60×, enabling accurate detection of TP53 mutations at frequencies down to 0.02%. We demonstrate that a TP53-specific CyclomicsSeq assay can be successfully used to monitor tumor burden during treatment for head-and-neck cancer patients. CyclomicsSeq can be applied to any genomic locus and offers an accurate diagnostic liquid biopsy approach that can be implemented in clinical workflows.

Standardized Regression Coefficients and Newly Proposed Estimators for [Formula: see text] in Multiply Imputed Data.

Whenever statistical analyses are applied to multiply imputed datasets, specific formulas are needed to combine the results into one overall analysis, also called combination rules. In the context of regression analysis, combination rules for the unstandardized regression coefficients, the t-tests of the regression coefficients, and the F-tests for testing [Formula: see text] for significance have long been established. However, there is still no general agreement on how to combine the point estimators of [Formula: see text] in multiple regression applied to multiply imputed datasets. Additionally, no combination rules for standardized regression coefficients and their confidence intervals seem to have been developed at all. In the current article, two sets of combination rules for the standardized regression coefficients and their confidence intervals are proposed, and their statistical properties are discussed. Additionally, two improved point estimators of [Formula: see text] in multiply imputed data are proposed, which in their computation use the pooled standardized regression coefficients. Simulations show that the proposed pooled standardized coefficients produce only small bias and that their 95% confidence intervals produce coverage close to the theoretical 95%. Furthermore, the simulations show that the newly proposed pooled estimates for [Formula: see text] are less biased than two earlier proposed pooled estimates.

Dataset on maternal attitudes about child maltreatment in nine countries using a Q-sort methodology.

Analyses of the present data are reported in the article "Crossing Boundaries: A Pilot Study of Maternal Attitudes about Child Maltreatment in Nine Countries" [8]. Data were collected during home visits using the Maltreatment Q-Sort (MQS). A total of 466 mothers from nine different countries gave their opinion about child maltreatment by sorting 90 cards with parenting behaviors taken from the literature that reflect four types of child maltreatment, into 9 evenly distributed stacks (with 10 cards each) from least to most harmful for the child. This data article provides an overview of the content of the 90 items, which type of maltreatment they reflect, and the source of the items. The percentage of mothers labelling each of the MQS items as maltreatment is also presented. In addition, instructions are included about the administration of the MQS as well as data-entry and analyses of Q-sort data, accompanied by example datasets and syntaxes. This can serve as a manual for researchers interested in using Q-sort data.