Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

This is the final version. Available from the publisher via the DOI in this record.The data that support the findings of this study are available from University of Exeter Medical School/Oxford University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of University of Exeter Medical School/Oxford University. R code is made available in supplementary file (see Additional file 2).Background: There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense of classic statistical models. Previous studies have compared performance between these two approaches but their findings are inconsistent and many have limitations. We aimed to compare the discrimination and calibration of seven models built using logistic regression and optimised machine learning algorithms in a clinical setting, where the number of potential predictors is often limited, and externally validate the models. Methods: We trained models using logistic regression and six commonly used machine learning algorithms to predict if a patient diagnosed with diabetes has type 1 diabetes (versus type 2 diabetes). We used seven predictor variables (age, BMI, GADA islet-autoantibodies, sex, total cholesterol, HDL cholesterol and triglyceride) using a UK cohort of adult participants (aged 18–50 years) with clinically diagnosed diabetes recruited from primary and secondary care (n = 960, 14% with type 1 diabetes). Discrimination performance (ROC AUC), calibration and decision curve analysis of each approach was compared in a separate external validation dataset (n = 504, 21% with type 1 diabetes). Results: Average performance obtained in internal validation was similar in all models (ROC AUC ≥ 0.94). In external validation, there were very modest reductions in discrimination with AUC ROC remaining ≥ 0.93 for all methods. Logistic regression had the numerically highest value in external validation (ROC AUC 0.95). Logistic regression had good performance in terms of calibration and decision curve analysis. Neural network and gradient boosting machine had the best calibration performance. Both logistic regression and support vector machine had good decision curve analysis for clinical useful threshold probabilities. Conclusion: Logistic regression performed as well as optimised machine algorithms to classify patients with type 1 and type 2 diabetes. This study highlights the utility of comparing traditional regression modelling to machine learning, particularly when using a small number of well understood, strong predictor variables.National Institute for Health Research (NIHR

Seasonal changes and population dynamics of the ctenophore Mnemiopsis leidyi after its first year of invasion in the Kiel Fjord, Western Baltic Sea

We analyzed the seasonal variations of the ctenophore Mnemiopsis leidyi weekly collected since its first record in the western Baltic Sea in October 2006. The distribution pattern together with the seasonal dynamics and population outbreaks in late summer 2007 indicate recent successfully establishment of M. leidyi in this area. Seasonal changes showed two periods of high reproductive activity characterized by a population structure dominated by small size classes, followed by an increase of larger ones. These results further revealed that the bulk of the population remains in deep layers during the periods of low population density, whereas it appeared situated in upper layers during the proliferation of the species. We further emphasized the strength of the population outbreaks, which can reach abundances >10-fold higher in time periods shorter than a week. The predatory impact this species may have in pelagic ecosystems warns on the importance of its recent range of expansion

Correlates of self-reported offending in children with a first police contact from distinct socio-demographic and ethnic groups

<p>Abstract</p> <p>Background</p> <p>This study aims to identify risk factors for level of offending among childhood offenders from different socio-economic status (SES) neighborhoods and ethnic origins.</p> <p>Method</p> <p>Three groups of childhood first time police arrestees were studied using standardized instruments for individual and parental characteristics: native Dutch offenders from moderate to high SES neighborhoods, native Dutch offenders from low SES neighborhoods, and offenders of non-Western origin from low SES neighborhoods.</p> <p>Results</p> <p>All subgroups showed high rates of externalizing disorders (27.2% to 41.8%) and familial difficulties (25.7% to 50.5%). Few differences between neighborhoods were found in the prevalence and impact of risk factors. However, the impact of some family risk factors on offending seemed stronger in the low SES groups. Regarding ethnical differences, family risk factors were more prevalent among non-Western childhood offenders. However, the association of these factors with level of offending seemed lower in the non-Western low SES group, while the association of some individual risk factors were stronger in the non-Western low SES group. Turning to the independent correlation of risk factors within each of the groups, in the Dutch moderate to high SES group, 23.1% of the variance in level of offending was explained by ADHD and behavioral problems; in the Dutch low SES group, 29.0% of the variance was explained by behavioral problems and proactive aggression; and in the non-Western low SES group, 41.2% of the variance was explained by substance use, sensation seeking, behavioral peer problems, and parental mental health problems.</p> <p>Conclusions</p> <p>Thereby, the study indicates few neighborhood differences in the impact of individual and parental risk factors on offending, while individual and parental risk factors may differ between ethnic groups.</p

Revisiting Lynam's notion of the "fledgling psychopath": are HIA-CP children truly psychopathic-like?

<p>Abstract</p> <p>Background</p> <p>In his developmental model of emerging psychopathy, Lynam proposed that the "fledgling psychopath" is most likely to be located within a subgroup of children elevated in both hyperactivity/inattention/impulsivity (HIA) and conduct problems (CP). This approach has garnered some empirical support. However, the extent to which Lynam's model captures children who resemble psychopathy with regard to the core affective and interpersonal features remains unclear.</p> <p>Methods</p> <p>In the present study, we investigated this issue within a large community sample of youth (<it>N </it>= 617). Four groups (non-HIA-CP, HIA-only, CP-only, and HIA-CP), defined on the basis of teacher reports of the Strengths and Difficulties Questionnaire (SDQ), were compared with respect to parent-reported psychopathic-like traits and subjective emotional reactivity in response to unpleasant, emotionally-laden pictures from the International Affective Pictures System (IAPS).</p> <p>Results</p> <p>Results did not support Lynam's model. HIA-CP children did not appear most psychopathic-like on dimensions of callous-unemotional and narcissistic personality, nor did they report reduced emotional reactivity to the IAPS relative to the other children. Post-hoc regression analyses revealed a significant moderation such that elevated HIA weakened the association between CP and emotional underarousal.</p> <p>Conclusions</p> <p>Implications of these findings with regard to the development of psychopathy are discussed.</p

Intricate macrophage-colorectal cancer cell communication in response to radiation

Both cancer and tumour-associated host cells are exposed to ionizing radiation when a tumour is subjected to radiotherapy. Macrophages frequently constitute the most abundant tumour-associated immune population, playing a role in tumour progression and response to therapy. The present work aimed to evaluate the importance of macrophage-cancer cell communication in the cellular response to radiation. To address this question, we established monocultures and indirect co-cultures of human monocyte-derived macrophages with RKO or SW1463 colorectal cancer cells, which exhibit higher and lower radiation sensitivity, respectively. Mono- and co-cultures were then irradiated with 5 cumulative doses, in a similar fractionated scheme to that used during cancer patients' treatment (2 Gy/fraction/day). Our results demonstrated that macrophages sensitize RKO to radiation-induced apoptosis, while protecting SW1463 cells. Additionally, the co-culture with macrophages increased the mRNA expression of metabolism- and survival-related genes more in SW1463 than in RKO. The presence of macrophages also upregulated glucose transporter 1 expression in irradiated SW1463, but not in RKO cells. In addition, the influence of cancer cells on the expression of pro- and anti-inflammatory macrophage markers, upon radiation exposure, was also evaluated. In the presence of RKO or SW1463, irradiated macrophages exhibit higher levels of pro-inflammatory TNF, IL6, CCL2 and CCR7, and of anti-inflammatory CCL18. However, RKO cells induce an increase of macrophage pro-inflammatory IL1B, while SW1463 cells promote higher pro-inflammatory CXCL8 and CD80, and also anti-inflammatory VCAN and IL10 levels. Thus, our data demonstrated that macrophages and cancer cells mutually influence their response to radiation. Notably, conditioned medium from irradiated co-cultures increased non-irradiated RKO cell migration and invasion and did not impact on angiogenesis in a chicken embryo chorioallantoic membrane assay. Overall, the establishment of primary human macrophage-cancer cell co-cultures revealed an intricate cell communication in response to ionizing radiation, which should be considered when developing therapies adjuvant to radiotherapy

Specific Cognitive Deficits in ADHD: A Diagnostic Concern in Differential Diagnosis

We present a critical account of existing tools used to diagnose children with Attention Deficit Hyperactivity Disorder and to make a case for the assessment of cognitive impairments as a part of diagnostic system. Surveys have shown that clinicians rely almost entirely upon subjective reports or their own clinical judgment when arriving at diagnostic decisions relating to this prevalent disorder. While information from parents and teachers should always be carefully considered, they are often influenced by a host of emotional and perceptual factors. It increases the possibility for misdiagnosis of a condition like ADHD. Recent experimental literature on ADHD has identified unique underlying cognitive dysfunction, specific to ADHD. Therefore, we propose that there is a need to incorporate information on cognitive mechanisms underlying ADHD and inculcate such information in the diagnostic system, which will provide a more sensitive as well as specific tool in differential diagnosis of ADHD

Unpacking the relationships between impulsivity, neighborhood disadvantage, and adolescent violence : an application of a neighborhood-based group decomposition

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement no. 615159 (ERC Consolidator Grant DEPRIVEDHOODS, Socio-spatial inequality, deprived neighbourhoods, and neighbourhood effects); and from the Marie Curie programme under the European Union’s Seventh Framework Programme (FP/2007–2013)/Career Integration Grant no. PCIG10-GA-2011-303728 (CIG Grant NBHCHOICE, Neighbourhood choice, neighbourhood sorting, and neighbourhood effects).Scholars have become increasingly interested in how social environments condition the relationships between individual risk-factors and adolescent behavior. An appreciable portion of this literature is concerned with the relationship between impulsivity and delinquency across neighborhood settings. The present article builds upon this growing body of research by considering the more nuanced pathways through which neighborhood disadvantage shapes the development of impulsivity and provides a situational context for impulsive tendencies to manifest in violent and aggressive behaviors. Using a sample of 12,935 adolescent from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (mean age = 15.3, 51% female; 20% Black, 17% Hispanic), we demonstrate the extent to which variation in the association between impulsivity and delinquency across neighborhoods can be attributed to (1) differences in mean-levels of impulsivity and violence and (2) differences in coefficients across neighborhoods. The results of a series of multivariate regression models indicate that impulsivity is positively associated with self-reported violence, and that this relationship is strongest among youth living in disadvantaged neighborhoods. The moderating effect of neighborhood disadvantage can be attributed primarily to the stronger effect of impulsivity on violence in these areas, while differences in average levels of violence and impulsivity account for a smaller, yet nontrivial portion of the observed relationship. These results indicate that the differential effect of impulsivity on violence can be attributed to both developmental processes that lead to the greater concentration of violent and impulsive adolescents in economically deprived neighborhoods as well as the greater likelihood of impulsive adolescents engaging in violence when they reside in economically disadvantaged communities.Publisher PDFPeer reviewe

Neural responses to others’ pain vary with psychopathic traits in healthy adult males

Disrupted empathic processing is a core feature of psychopathy. Neuroimaging data have suggested that individuals with high levels of psychopathic traits show atypical responses to others' pain in a network of brain regions typically recruited during empathic processing (anterior insula, inferior frontal gyrus, and mid- and anterior cingulate cortex). Here, we investigated whether neural responses to others' pain vary with psychopathic traits within the general population in a similar manner to that found in individuals at the extreme end of the continuum. As predicted, variation in psychopathic traits was associated with variation in neural responses to others' pain in the network of brain regions typically engaged during empathic processing. Consistent with previous research, our findings indicated the presence of suppressor effects in the association of levels of the affective-interpersonal and lifestyle-antisocial dimensions of psychopathy with neural responses to others' pain. That is, after controlling for the influence of the other dimension, higher affective-interpersonal psychopathic traits were associated with reduced neural responses to others' pain, whilst higher lifestyle-antisocial psychopathic traits were associated with increased neural responses to others' pain. Our findings provide further evidence that atypical function in this network might represent neural markers of disrupted emotional and empathic processing; that the two dimensions of psychopathy might tap into distinct underlying vulnerabilities; and, most importantly, that the relationships observed at the extreme end of the psychopathy spectrum apply to the nonclinical distribution of these traits, providing further evidence for continuities in the mechanisms underlying psychopathic traits across the general population

Expression of Mir-21 and Mir-143 in Cervical Specimens Ranging from Histologically Normal through to Invasive Cervical Cancer

MicroRNA expression is severely disrupted in carcinogenesis, however limited evidence is available validating results from cell-line models in human clinical cancer specimens. MicroRNA-21 (mir-21) and microRNA-143 (mir-143) have previously been identified as significantly deregulated in a range of cancers including cervical cancer. Our goal was to investigate the expression patterns of several well-studied microRNA species in cervical samples and compare the results to cell line samples.We measured the expression of mir-21 and mir-143 in 142 formalin-fixed, paraffin embedded (FFPE) cervical biopsy tissue blocks, collected from Dantec Oncology Clinic, Dakar, Senegal. MicroRNA expression analysis was performed using Taqman-based real-time PCR assays. Protein immunohistochemical staining was also performed to investigate target protein expression on 72 samples. We found that mir-21 expression increased with worsening clinical diagnosis but that mir-143 was not correlated with histology. These observations were in stark contrast to previous reports involving cervical cancer cell lines in which mir-143 was consistently down-regulated but mir-21 largely unaffected. We also identified, for the first time, that cytoplasmic expression of Programmed Cell Death Protein 4 PDCD4; a known target of mir-21) was significantly lower in women with invasive cervical carcinoma (ICC) in comparison to those with cervical intraepithelial neoplasia (2-3) or carcinoma in situ (CIN2-3/CIS), although there was no significant correlation between mir-21 and PDCD4 expression, despite previous studies identifying PDCD4 transcript as a known mir-21 target.Whilst microRNA biomarkers have a number of promising features, more studies on expression levels in histologically defined clinical specimens are required to investigate clinical relevance of discovery-based studies. Mir-21 may be of some utility in predictive screening, given that we observed a significant correlation between mir-21 expression level and worsening histological diagnosis of cervical cancer