Hum Brain Mapp 38:2566–2579, 2017. © 2017 Wiley Periodicals, Inc.The relationship between the BOLD response and an applied force was quantified in the cerebellum using a power grip task. To investigate whether the cerebellum responds in an on/off way to motor demands or contributes to motor responses in a parametric fashion, similarly to the cortex, five grip force levels were investigated under visual feedback. Functional MRI data were acquired in 13 healthy volunteers and their responses were analyzed using a cerebellum‐optimized pipeline. This allowed us to evaluate, within the cerebellum, voxelwise linear and non‐linear associations between cerebellar activations and forces. We showed extensive non‐linear activations (with a parametric design), covering the anterior and posterior lobes of the cerebellum with a BOLD‐force relationship that is region‐dependent. Linear responses were mainly located in the anterior lobe, similarly to the cortex, where linear responses are localized in M1. Complex responses were localized in the posterior lobe, reflecting its key role in attention and executive processing, required during visually guided movement. Given the highly organized responses in the cerebellar cortex, a key question is whether deep cerebellar nuclei show similar parametric effects. We found positive correlations with force in the ipsilateral dentate nucleus and negative correlations on the contralateral side, suggesting a somatotopic organization of the dentate nucleus in line with cerebellar and cortical areas. Our results confirm that there is cerebellar organization involving all grey matter structures that reflect functional segregation in the cortex, where cerebellar lobules and dentate nuclei contribute to complex motor tasks with different BOLD response profiles in relation to the forces.  The ability to grip using the hands is one of the key functions allowing primates to use tools to act on the proximal environment. Object gripping is a complex motor act, because it requires the integration of visuo‐spatial and proprioceptive information, correct application, timing of different grip forces (GF) and coordination with other concurrent motor activities [Ulloa et al., psychometric functions in psychophysics—have received less attention. Several reasons may explain this, including difficulties in interpretation and also, importantly, detecting them. The rationale for our study of non‐linear neurometric functions is based on the non‐linearity inherent in neuronal dynamics and synaptic transmission, which define the relationship between neural activity and behavior; often found to be non‐linear—as shown by multiple neurophysiological studies [Ashe, Many neuroimaging studies test for linear relationships between signals that reflect activity at the neuronal level and experimental factors  Ashe, , while tes Ashe, . If we ces Ashe, , which hes Ashe, . These cTo date, however, the relative contributions of the different cerebellar lobules to gripping tasks (using fMRI) and the precise relationship between varying GFs and cerebellar activity have not been studied in detail apart from one careful study by Spraker et al.  where thTwo issues are clear from reviewing the literature: there seems to be some difficulty in detecting fMRI signals in the cerebellum and, when detected, there is little agreement on the relationship between GF and BOLD signal in the cerebellum. Different explanations may underlie the heterogeneity of published results on this topic, including differences in the types of grip task (power vs. precision), in grip patterns (static vs. dynamic) and importantly, the number and ranges of force levels used in the experimental setting [Alahmadi et al., In a recent visuomotor study [Alahmadi et al., t‐values increased similarly. Here, the SUIT and dentate nuclei (DN) templates [Diedrichsen, The fMRI analysis pipeline, optimized for whole brain analysis, however, is known to lead to suboptimal results in the cerebellum [Diedrichsen, Our study hypothesis was that the signal responses in the cerebellum would show extensive effects of GF, similar to those reported for the neo‐cortex, displaying: linear positive response to GF in motor regions, higher order non‐linear (parametric) forms in regions known to be involved in sensory, associative and cognitive processes, and negative response in visual areas as well as in motor areas. Furthermore, as the deep cerebellar nuclei are also key to motor and associative processing [Dimitrova et al., The subjects and acquisition protocol are the same as those described in [Alahmadi et al., Thirteen right‐handed healthy volunteers with no history of neurological disease  years) participated in this study. The handedness of subjects was tested using the Edinburgh handedness scaling questionnaire [Oldfield, 3, inter‐slice gap of 0.3 mm, SENSE = 2, number of slices = 46 acquired with descending order, FOV = 192 × 192 mm2, number of volumes = 200, flip angle = 90°, and a three dimensional (3D) anatomical T1‐weighted reference scan (3DT1): 3D inversion‐recovery prepared gradient‐echo (fast field echo) sequence with inversion time (TI) = 824 ms, TE/TR = 3.1/6.9 ms, flip angle = 8°, and voxel size = 1 mm isotropic.A 3.0 T MRI scanner  with a 32‐channel head coil was used. The imaging protocol comprised: A BOLD sensitive T2*‐weighted echo planar imaging (EPI) sequence: echo time (TE)/repetition time (TR) = 35/2,500 ms, voxel size = 3 × 3 × 2.7 mmhttp://www.surfer.nmr.mgh.harvard.edu/optseq) and comprised 75 active trials divided equally into 5 GF targets  interleaved with 75 rest trials. Each active trial lasted 3 sec and trials were specified in a randomized order. A visual cue was used to instruct the subject, defining the target force and providing interactive (live) feedback on the subject's performance for each trial [figure Subjects performed a dynamic power grip task with their right (dominant) hand, using an MR‐compatible squeeze ball [see Alahmadi et al., l figure . The vist‐statistics were used to test for the effects of each polynomial coefficient to generate contrast images and statistical maps for each polynomial order and for each subject that can then be used for the second level analysis. Then, the following SUIT steps were performed: (1) Extraction of each subject's cerebellum and brainstem from their corresponding whole brain 3DT1 anatomical image; (2) Normalization of the anatomical images to the SUIT template using a non‐linear deformation; (3) Re‐slicing of the functional contrast images produced from the first level analysis using the deformation produced from step 2 and masking out any activation outside the region of interest . The normalized cerebellum functional contrast images  from each subject were then smoothed with an 8mm isotropic full‐width half maximum (FWHM) Gaussian kernel and submitted to a (between‐subjects) standard second level random effects analysis, testing for increasingly higher order non‐linear effects within the cerebellum with one sample t‐test. In other words, the images of polynomial coefficients were then used as summary statistics for between subject (second level) random effects analysis . Significance was set at a corrected (FWE) cluster level using a threshold of P < 0.001; minimum extent ten voxels. This threshold corresponds to a t‐value of 3.92. The anatomical identification of the activations was defined using a high resolution probabilistic atlas defined by the SUIT template [Diedrichsen et al., Figure P < 0.001.In addition, signals from the DN, which appears hypointense on T2*‐weighted images, were analyzed differently as described in [Diedrichsen et al., Moreover, to highlight the predominant polynomial order effect from the force‐BOLD fitting at the single voxel level, we categorized the force related effects according to the greatest effect size  [Alahmadi et al., http://www.nitrc.org/projects/artifact_detect) to aid this analysis and help detect any obvious outliers in the functional volumes for each participant.In addition, to enhance the quality check of the data, we inspected the effects of head motion both visually and quantitatively. We used the Artifact Detection Tools (ART) , activations were found in the ipsilateral lobules (I‐VIII); as well as the contralateral lobule (VI) and part of the anterior and posterior vermis Fig. . Table 21st order positive linear effects were found in the ipsilateral cerebellum (lobules V‐VI and IX) Table . NegativHigher order positive non‐linear effects were mostly found bilaterally Table , especiaFurthermore, we found that the right DN showed a main effect of movement  and 4th order effects—with the 4th order having a wider spatial extent. A 4th order effect was also observed in the ipsilateral DRDN, covering only a small spatial extent. The ipsilateral VCDN mainly showed a positive 2nd effect and a small positive 1st effect. The 2nd order effect was also observed in the ipsilateral DRDN. In addition, activations dominated by negative 1st order behavior were localized in the contralateral VCDN and VRDN. Voxels displaying negative 3rd order effects were localized to the contralateral VCDN and DRDN.Moreover, results from ART showed that head motion was negligible as translations were one order of magnitude smaller than the voxel size and rotations a fraction of a degree (Supporting Information ‐figures 1). Also no outliers were detected . Furthermore, there were no significant correlations between any of the head motion parameters with each GF level. Figures that provide summaries of this analysis are shown in the Supporting Information (figures 1 and 2).It should be noted that Table A main effect of gripping using the dominant right hand  not only shows, as expected, clear involvement of the anterior lobe but also part of the posterior lobe  and the DN .An increase in task complexity  has a two‐fold effect: on the one hand, there is increased recruitment  of motor areas of the anterior lobe and, conversely, there is decreased recruitment  in the contralateral posterior lobe (area VII).Non‐linear BOLD responses to GF were observed in bilateral motor, cognitive and associative cerebellar areas as well as in the DN, suggesting that both cerebellar hemispheres may play a role in motor control during visually‐guided gripping, in synergy with the DN. These results also suggest that the DN shows a somatotopic organization that responds non‐linearly, consistent with empirical observations in the cerebellar cortex  and similarly to the cerebral neo‐cortex , indicating a consistency between functionally specific motor and associative areas [Alahmadi et al., In this work, we have characterized the cerebellar responses during a visually‐guided dynamic grip task (with five different force targets) using a recently proposed pipeline that uses the optimized SUIT template for the cerebellum and DN. The main findings of this study are:In order to try to understand the implications of these results for the cerebellum's role in motor control and associative/cognitive functions, we now discuss the grip related effects localized in the anterior (V) and posterior lobes , as well as the DN.The anterior lobe of the cerebellum is known to play a key role in sensory‐motor integration and motor control [Stoodley and Schmahmann, The posterior cerebellum was initially thought to be mostly involved in higher level functions such as working memory, attention and executive functions [Stoodley and Schmahmann, One of the interesting findings of this study is the bilateral activation in lobule VI seen in the main effect of movement analysis; this is in line with previous GF studies [Halder et al., Interestingly, these cerebellar areas project to cortical areas  that show similar GF‐BOLD behavior [Alahmadi et al., One of the interesting findings of this study is the widespread evidence for a negative 3rd order BOLD‐GF effect within the posterior cerebellum (mainly in lobules VI and VII) and part of the anterior cerebellum (lobule V). The biophysical mechanisms behind such a relationship cannot be inferred from the present data, but two plausible explanations are as follows. When considering animal studies showing non‐linear neuronal responses as a function of applied force, it is possible to identify neurometric functions reflecting either saturation, or a reduced firing at high forces or firing patterns that follow an S‐shaped profile Ashe, . The negMoreover, it is interesting to note that the 1st, 2nd, and −3rd effects define an almost continuous area connecting the anterior and posterior lobules  were mainly localized in the ventral section of the DN matches the findings of the same parametric behavior in the posterior parietal lobule [Alahmadi et al., In addition, using a high field MRI scanner (7T) and in‐vivo sub‐millimetre structural diffusion MRI, Steele et al.  investigAlthough our current paradigm is a task specific fMRI study (a visuomotor task), the majority of our findings are in line with the aforementioned data, from a functional segregation point of view. For example, the 0th order (the main effect of gripping) was largely localized (with the largest effect sizes) to the dorsal part of the DN and the anterior lobe of the cerebellum as well as lobule VI. In line with the previous studies, this would be expected because of the motor nature of the task used in this study. The posterior cerebellum and the ventral portion of the DN showed some activations during the main effect of gripping that could be related to the use of the visual cue (a non‐motor domain). The activations in these non‐motor portions of the DN were smaller (in amplitude and extent) as compared to the motor regions in the cerebellum and the DN. Looking at the force related effects and the somatotopic organization of the DN—in relation to cerebellar findings—the organization is mostly in line with previous publications. For example, the −3rd order effect was largely restricted to functionally specific areas of the DN and the cerebellar cortex; that is, mainly within the anterior cerebellar lobe, lobule VI and the dorsal portion of the DN. These areas were shown in previous work to be structurally and functionally connected [Bernard et al., For a complete mapping of the deep cerebellar nuclei interactions, other cerebellar nuclei  could be investigated, but despite their important functions and roles, their size is too small to be examined using the images acquired in this study.In addition, there are methodological considerations that should be taken into account for this and other, similar studies. In our paradigm, an external visual cue was used by subjects to apply accurate forces while gripping. Such methodology has been commonly applied in previous studies [e.g., Alahmadi et al., It is believed that such paradigms mimic the functions of everyday life. Such networks are used daily, and are therefore worthy of investigation in their own right. Distinguishing visual and motor effects is not possible with these paradigms. To separate these contributions, an additional paradigm would probably be needed. For example, the visual cues could be presented without the need of gripping or the same paradigm could be used without the visual feedback. This, however, would have the drawback of making the interpretation of the GF‐BOLD relationships harder to achieve.Other studies have tried to separate visual from motor functions [e.g., Kuhtz‐Buschbeck et al., When comparing our results with previous studies, it should be noted that only a few studies have characterized non‐linear responses in vivo in humans and these non‐linearities were rarely fitted to specific functions or reported within the cerebellar lobules. For example, Keisker et al.  showed (One interesting issue—that could be further investigated—would be to assess differences in post stimuli time (PST) and reaction times, as well as characterizing haemodynamic delays using a temporal basis set for the HRF [Friston et al., It should be noted that areas showing a significant BOLD‐GF relationship do not necessarily have to show a 0th order effect. When this occurs, it means that the BOLD signal across all trials  is not significantly different from baseline, despite showing a specific modulation with respect to the applied different GFs. For example, if an area has a significant positive linear response but does not have a significant 0th order effect, it produces a negative BOLD response when applying low forces that becomes positive when applying high forces. Such a behavior may suggest an interplay between excitatory and inhibitory neurons, which is force‐dependent. Interestingly, inhibition and negative BOLD signal have been observed previously, although not in relation to variable applied GFs [Logothetis, In addition, head motion was shown to be negligible in this cohort and not correlated to any of the GF levels. Nevertheless, we adjusted the GLM regression model by entering motion parameters as regressors of no interest [Friston et al., The study demonstrates that, using a dedicated analysis protocol, linear and non‐linear BOLD responses to motor task performance are found in cerebellar grey matter structures—and that the parametric form of these responses can be characterized using a dedicated protocol. We have demonstrated linear and non‐linear BOLD responses to GF modulation with a clear and distributed regional specificity in the cerebellar lobules and nuclei. Crucially, these reflect our previous findings in the cerebral cortex, with 0th order and linear effects in motor regions and higher order parametric responses in associative and cognitive regions. These findings contribute substantially to our understanding of the cerebellum, beyond a simple motor controller and could have clinical implications if found to be systematically altered in neurological diseases. Our results indicate that cerbellar processing—even in motor tasks—goes beyond its traditional roles.Supporting InformationClick here for additional data file.


AD) have improved our understanding of the temporal sequence of biological events that lead to AD dementia  in the cerebrospinal fluid (CSF) or by binding of amyloid PET ligands, is thought to be a key initiating event in AD and begins many years prior to the onset of dementia. A rise in CSF tau and phosphorylated tau in the setting of Aβ deposition appears to reflect neurodegeneration and also begins years prior to the onset of dementia but after Aβ deposition has begun to accumulate. Individuals with “preclinical AD,” that is, normal cognition but abnormal AD biomarkers, have a much higher risk for developing AD dementia but may remain cognitively normal for years  that best predict the transition from cognitive normality to abnormality. A biomarker that is closely associated with the onset of cognitive decline could help us to understand the biological events that connect amyloid deposition and tangle formation to cognitive decline and could have significant practical value in AD diagnosis and clinical trial design.Biomarkers for Alzheimer's disease ( Current clinical CSF diagnostics evaluate levels of Aβ42, tau, and ptau. The combination of low CSF Aβ42 and high tau/ptau is consistent with the presence of AD pathology, but it is not specific—it may occur either in patients with dementia due to AD or preclinical AD. Addition of sTREM2 to CSF testing may improve our ability to determine whether mild cognitive problems are due to AD or other etiologies. CSF sTREM2 levels could also be helpful in AD drug trials. Biomarkers are being used as endpoints as well as enrollment criteria in some clinical trials. If CSF sTREM2 is reliably associated with the onset of cognitive decline, reduced sTREM2 levels in drug‐treated individuals with preclinical AD could indicate a favorable drug effect. Additionally, drugs for AD may be most effective when given at a particular stage of the AD process. Individuals who have abnormal biomarkers for amyloid, tau/ptau but normal CSF sTREM2 may be at an earlier stage of the AD process than individuals with abnormalities in all three biomarkers. If CSF sTREM2 further refines our ability to stage AD, this would allow us to evaluate which drugs are most appropriate for patients at various stages of the AD process. If additional studies confirm the results of Suárez‐Calvet et al , CSF sTR


At present a good number of bio‐based products  are derived from corn syrup and other sugar sources ; however, because of the food v fuel controversy new trends have been directed towards the production of bioproducts/biofuels from lignocellulosic biomass—the most abundant and important renewable source for alternative petrol derivatives. We discuss here the bases for sustainable bioenergy production.Currently the chemical industry is largely petroleum based and although the number of ongoing large‐scale biocatalytic processes are relatively low, a trend in growth is expected and the Organization for Economic Co‐operation and Development (OECD) and other agencies aim to have 30% of the total chemical industry based on renewable sources by 2050 (Philp  The advantages that MSW has over other sources of organic material are as follows it is available throughout the year, it is concentrated (supply locations), and it is less costly or even a direct source of revenues for processing companies due to the cost paid for its disposal (Arena et al. (Aracil et al.  assessedNone declared.


SJTs) measure.Despite their widespread use in medical school selection, there remains a lack of clarity on exactly what situational judgement tests  with an innovative deductive approach. The deductive approach guided the development of the SJT according to two established theoretical models, of which one was positively related to integrity (honesty–humility [HH]) and one was negatively related to integrity (cognitive distortions [CD]). The Integrity SJT covered desirable (HH‐based) and undesirable (CD‐based) response options. We examined the convergent and discriminant validity of the Integrity SJT and compared the validity of the HH‐based and CD‐based subscores.We aimed to develop an SJT was administered to 402 prospective applicants at a Dutch medical school. The Integrity SJT consisted of 57 scenarios, each followed by four response options, of which two represented HH facets and two represented CD categories. Three SJT scores were computed, including a total, an HH‐based and a CD‐based score. The validity of these scores was examined according to their relationships with external integrity‐related measures  and self‐efficacy .The Integrity SJT scores correlated significantly with all integrity‐related measures and not with self‐efficacy, indicating convergent and discriminant validity. In addition, the CD‐based SJT score correlated significantly more strongly than the HH‐based SJT score with two of the four integrity‐related measures.The three SJT that assesses the ability to correctly recognise CD‐based response options as inappropriate (i.e. what one should not do) seems to have stronger convergent validity than an SJT that assesses the ability to correctly recognise HH‐based response options as appropriate (i.e. what one should do). This finding might be explained by the larger consensus on what is considered inappropriate than on what is considered appropriate in a challenging situation. It may be promising to focus an SJT on the ability to recognise what one should not do.An  The authors demonstrate that an SJT score based on recognizing what not to do has stronger convergent validity than an SJT score based on recognizing what to do. In addition to the cognitive instruments used in selection for medical school, there is an increasing need for tools that assess non‐cognitive attributes (e.g. integrity). This growing need has led to the introduction of new medical school selection instruments such as multiple mini‐interviews, selection centres, personality and emotional intelligence assessments and situational judgement tests (SJTs).The application of an SJT in medical school selection necessitates the identification of what is measured by an SJT because this high‐stakes process requires clarity on the constructs used for selection. However, few studies elaborate on exactly what SJTs measure.By contrast, a deductive development approach bases the content of an SJT on a specific construct by using a literature review, a job analysis or an existing theory.To benefit from the strengths of both methods, we combined the inductive and deductive approaches to develop an SJT measuring applicants’ knowledge of appropriate and inappropriate responses to integrity‐related situations in medical school (henceforth: Integrity SJT). Integrity is considered a core competency for medical doctors across various medical specialtiesThe present study contributes to the existing research on two points. Firstly, we developed an SJT that covers appropriate and inappropriate responses. In this way, the SJT assesses the ability to identify appropriate responses, as well as the ability to identify inappropriate responses. We distinguished these two abilities because previous researchers suggested that they involve different skills.This study was conducted at the Erasmus Medical Centre (MC) Medical School, Rotterdam, the Netherlands. In the Netherlands, all entry to medical school is predominantly at the undergraduate level. Admission to the Erasmus MC Medical School at the time of the study was based on three aspects: pre‐university grade point average; extracurricular activities , and performance on five cognitive study skill tests (e.g. scientific reading) administered during three testing days.Six months before the testing days, the Erasmus MC Medical School organised a selection orientation day to inform medical school applicants about the selection process. Participation in the selection orientation day was voluntary and free of charge.The Integrity SJT was administered to the 402 participants at the 2015 selection orientation day. Participation in the SJT was voluntary. Participants were informed about the purpose of the administration and that their answers would not influence the admission decision. Informed consent was obtained from all participants. The data in this study were confidentially processed. The pencil‐and‐paper administration took place in a lecture hall at the Erasmus MC Medical School campus. The Ethics Committee of the Institute of Psychology, Erasmus University Rotterdam, deemed this study to have no need for further ethical approval by the Medical Ethics Committee.A demographic questionnaire was administered to determine the participants’ ethnic and socio‐economic backgrounds. An individual was classified as belonging to an ethnic minority if at least one of his or her parents had been born outside the Netherlands (i.e. the definition used by Statistics NetherlandsThe deductive development approach was guided by two integrity‐related models: the honesty–humility (HH) subscale of the HEXACO personality inventory, and the How I Think questionnaire measuring cognitive distortions (CDs). The HH dimension has been demonstrated to be positively related to integrityn = 41) to gather input for realistic response options. To stimulate the development of response options, scenarios were presented with a number of prompts (e.g. What would be the best/worst/most likely response to this situation?).The inductive development approach consisted of critical incident interviews with nine subject matter experts (SMEs), who were individuals directly involved in the assessment of professional behaviour of medical students . These SMEs described incidents in which a medical student behaved unprofessionally (e.g. by cheating). Further questions were asked to provide elaboration on these critical incidents following the technique described by Flanagan.The resulting Integrity SJT consisted of 57 scenarios. This pilot version of the Integrity SJT was randomly split into two versions (i.e. Version A and Version B) because of the large number of scenarios. Each scenario was followed by four response options, of which two represented HH facets and two represented CD categories. Table Box 1Z standardisation so each participant had a mean score of 0 and a standard deviation (SD) of 1.n = 63). These residents were chosen as a reference group because this group includes a relatively large number of residents who are trained as generalists. For the GP residents, the SJT was split into three versions of 19 scenarios  in order to reduce the time investment. The mean ± SD age of the GP residents was 28.6 ± 2.7 years and 52 (82.5%) of them were female. Fifty‐one (81.0%) GP residents were Dutch and 21 (33.0%) were first‐generation university students. Table Each SJT item was scored by calculating the squared distance between a participant's judgement and the average judgement across all other participants. To ensure that the SJT score was not influenced by responder tendencies to use the rating scale in a certain manner (e.g. extreme response style), this calculation was preceded by a within‐person Convergent validity was examined by the relationship between the Integrity SJT and the two integrity‐related measures used for assembling the response option categories: the HH subscale of the HEXACO Simplified Personality Inventory (HEXACO‐SPI)Discriminant validity was examined according to the relationship with the self‐efficacy subscale of the Motivated Strategies for Learning Questionnaire (MSLQ).spss Statistics for Windows Version 21.0 . r Version 3.1.0 (http://www.R-project.org) was used to meta‐analytically merge the correlation coefficients (‘metacor’ package) and to conduct the Williams’ test (‘psych’ package).Three SJT scores were computed by adding up scores across: (i) all items ; (ii) all HH‐based items, and (iii) all CD‐based items. Scores were reversed so that higher scores indicated better performance on the Integrity SJT. Pearson's correlation coefficients were calculated between the three SJT scores and the integrity‐related measures and self‐efficacy subscale. The correlation coefficients were merged across the two versions of the Integrity SJT using a random‐effects meta‐analytic approach. The difference between the HH‐based and CD‐based SJT scores in their correlations with the integrity‐related measures was analysed with the Williams’ test.t(354) = − 2.77, p = 0.006, d = 0.29). However, the effect size of this difference was small and both groups scored well below the average score of a normative sample of 412 youths (mean score: 2.39).The numbers of participants completing Versions A and B of the SJT were 186 (response rate: 92.5%) and 181 (response rate: 90.0%), respectively. There were no significant differences in age, gender, ethnicity or socio‐economic background between participants completing Versions A and B . All but three items had a correlation above 0.50 (i.e. large effect sizer ≤ 0.40). Appendix All SJT scores  correlated significantly with the four external integrity‐related measures Table. The cort(168) = 3.07, p = 0.003, d = 0.47) and with the ICB (t(171) = 2.69, p = 0.008, d = 0.41). The CD‐based SJT score correlated more strongly than the HH‐based SJT score with the honesty–humility subscale, but this difference was only marginally significant (t(173) =−2.54, p = 0.011, d = 0.39). No significant difference was found between the HH‐based and CD‐based SJT scores in their correlation with the workplace deviance measure (t(169) = 1.50, p = 0.130).All correlation coefficients with the integrity‐related measures were – in absolute terms – larger for the CD‐based SJT score than for the HH‐based SJT score Table. The WilAs expected, none of the SJT scores were significantly correlated to the self‐efficacy subscale Table.The results of this study indicate that the Integrity SJT had convergent and discriminant validity. This is evidenced by a significant correlation with integrity‐related measures and no correlation with a self‐efficacy subscale. Additionally, the findings indicate that an SJT score representing CD categories has stronger convergent validity than an SJT score representing HH facets. This is demonstrated by significantly higher correlations with two of the four integrity‐related measures for the CD‐based SJT score than for the HH‐based SJT score.The first finding implies that the use of a deductive development approach based on established theoretical models together with a traditional inductive approach generates an SJT that has convergent validity. The correlation with the HH subscale found in this study appears to be somewhat stronger than the correlation coefficient reported in the study by de Meijer et al.not do has stronger convergent validity than an SJT score based on the ability to identify what one should do. This finding is in line with that in a prior study on sales and management SJTs, which demonstrated stronger predictive validity for the ability to identify the worst response option than for the ability to identify the best response option.not do is also observed for the SJT in this study.The second finding of this study indicates that an SJT score based on the ability to identify what one should An important strength of this study lies in its combination of two development approaches, which allows us to benefit from the advantages of both methods and results in an SJT with realistic contextualised scenarios measuring an explicit construct. A second strength is the large number of integrity‐related measures used in this study, which supports the credibility of our statements regarding convergent validity. A third strength refers to the fact that, unlike most previous studies, the current work not only examined convergent validity, but also investigated discriminant validity, thereby indicating that the Integrity SJT is associated with theoretically related constructs and not associated with theoretically unrelated constructs.Despite its strengths, this study has some limitations. Firstly, the response options of the Integrity SJT were written to represent response option categories by aligning the wording and reasoning of response options belonging to the same category. Future research might improve the accuracy of this categorisation by performing an additional classification by an independent group. Secondly, the assumption that the HH facets reflect good responses and that CDs reflect bad responses may be too simplistic. For example, an HH‐based response might entail the betrayal of one's friend and a CD‐based response might seem to be made inevitable by group pressure. The influence of these subtleties on the functioning of an SJT should be further investigated. Thirdly, the investigation of systematic ethnic differences in the score on the Integrity SJT was beyond the scope of this paper, but future research is necessary to examine the ‘what to do’ versus ‘what not to do’ distinction with regard to adverse impact. Fourthly, critical incident interviews were conducted with only nine SMEs. Although the critical incident interviews produced a wealth of data, interviews with more SMEs may have led to a wider coverage of the professional issues encountered by medical students. Finally, the results of this study are derived solely from its administration within an admission context with undergraduate entry. As a result, the patient‐centredness of the SJT scenarios was limited, which may reduce the generalisability of the present results to SJTs used for graduate entry into medical school. Although the Integrity SJT involved some patient‐related scenarios, future research should investigate the generalisability of this study's findings to other settings.These findings elicit the following recommendations for future research. Firstly, the Integrity SJT showed stronger convergent validity for the CD‐based score than for the HH‐based score. However, it is possible that for other constructs (e.g. empathy), a score based on the correct identification of desirable responses will have stronger convergent validity than a score based on the correct identification of undesirable responses, perhaps because desirable responses are more obvious for certain constructs. Future research is necessary on the generalisability of the CD‐based score's stronger convergent validity to SJTs measuring other constructs. Finally, future research on the predictive validity is a necessary requirement before an SJT can be considered for inclusion in medical school selection.A first practical implication for medical schools using or planning to use a construct‐based SJT in their selection procedures is the use of established theoretical models to guide the deductive development of an SJT. The theoretical models may be related to integrity, but may also involve other constructs .not do in a challenging situation. This implication could support the proposal to use an SJT for screening out medical school applicantsA second practical implication is that an SJT might be used to assess the ability to correctly identify what one should not do).The combination of a traditional inductive and an innovative deductive development approach resulted in an Integrity SJT which had convergent and discriminant validity. Categorising the response options of the SJT according to two established theoretical models – one positively and one negatively related to integrity – resulted in a wide range of appropriate (HH‐based) and inappropriate (CD‐based) response options. The CD‐based SJT score had stronger convergent validity than the HH‐based SJT score. It may be promising to focus SJTs on the ability to correctly identify inappropriate response options . WEdL and APNT collected the data for the validation of the Integrity SJT. WEdL analysed the data and wrote the first draft of the paper. All authors contributed to the interpretation of the statistical analyses and the critical revision of the paper. All authors approved the final manuscript for publication and are accountable for this work.None.None.The study design was reviewed by the independent Ethical Committee of the Institute of Psychology, Erasmus University Rotterdam, which concluded that no further ethical approval by the Medical Ethics Committee was warranted.Table S1. Five example scenarios used in the integrity situational judgement test.Click here for additional data file.Table S2. Intraclass correlation coefficients for general practice residents for the total situational judgement test (SJT) score and the subscores based on the honesty–humility items and cognitive distortion items.Click here for additional data file.Table S3. Characteristics of the measures used to assess convergent and discriminant validity.Click here for additional data file.Appendix S1. Correlations between the individual response option categories, honesty–humility facets and cognitive distortion categories.Click here for additional data file.


This clinical image teaches readers that a rare finding such as intramedullary spinal metastasis could exist even in the rarest tumors. It adds to the literature how it was managed. It also might reflect the improvement of our cancer treatment allowing us to follow patients longer to find those rare findings in rare tumors. A 49‐year‐old female was diagnosed with stage 4 Merkel cell carcinoma of the vulva with pelvic and inguinal lymph node metastasis. She had received multiple chemotherapy and radiation therapy that failed, as only few months after diagnosis, the disease progressed and metastasized to the thoracic vertebrae and liver. She was waiting for a PET scan before starting her on immunotherapy as a final resort for treatment, but she presented with severe neck pain and left‐sided weakness of 10‐day duration. MRI of the spine revealed a 2.1 × 1.3 cm heterogeneous enhancing mass involving cervical spinal cord at C4–C5 level with expansion of the cord, that most likely be a metastasis of her disease, but another primary neoplastic disease could be ruled out (Fig. Intramedullary spinal cord metastasis remains a very rare entity for malignancies that are not breast or lung in origin Merkel cell carcinoma is a rare cutaneous malignancy that is almost always locally invasive and causes metastasis frequently, especially to lymph nodes, liver, lungs, bone, and brain To the best of our knowledge, this is the second case in the literature for Merkel cell carcinoma to cause intramedullary spinal cord metastasis None declared.TH: Primary Author, Original idea and manuscript writing. BT: Mentor and editor of the manuscript.


Mage = 17.58) in addition to the target adolescent (Mage = 11.79), and both adolescents’ externalizing behaviors were used as moderators for the link between PSE and parenting of the target adolescent. Path analysis in Mplus showed that higher PSE was linked to more promotive parenting but only among parents who had an older adolescent with lower levels of externalizing behaviors. Among parents of adolescents with higher levels of externalizing behaviors, whose promotive parenting was significantly lower than other parents overall, PSE did not predict promotive parenting. The link between PSE and parenting did not differ depending on the target adolescents’ behavior. Findings suggest that the link between parents’ beliefs and parenting depends on the broader family context. More specifically, how PSE is linked to parenting practices depends at least partly on the experiences that parents bring from parenting an older adolescent to their interactions with a later-born adolescent. From a clinical perspective, parents might need guidance in how to think about their earlier parenting experiences when parenting a younger adolescent.Based on theory that parents with higher levels of self-efficacy (PSE) should find it easier to parent effectively in the face of challenging child behaviors than should parents with lower levels of PSE, this study examines the link between PSE and parenting using children’s behaviors as potential moderators. Participants were 130 parents who had an older adolescent ( Parental self-efficacy (PSE) describes parents’ beliefs about being able to influence their child in a way that fosters his or her positive development and adjustment Bandura , 1997. PWhen moderators of the link between PSE and parenting practices have been examined, results have been consistent with Bandura’s suggestion Bandura , showingThe type of child behaviors that parents are faced with might also influence the link between PSE and parenting. In fact, it has been argued that parents with higher levels of PSE should find it easier to parent effectively in the face of difficult and challenging child behaviors than should parents with lower levels of PSE  higher levels of PSE should be linked to more promotive parenting only when parents have experienced difficult behaviors in their older adolescent, or (2) among parents who experienced difficult behaviors in their older adolescent, such negative experiences would be transferred into less promotive parenting practices of the target adolescent, regardless of their level of PSE. We also had hypotheses concerning the combination of both adolescents’ behavior. We expected that among parents who experienced less difficult behavior in their older adolescent and more difficult behaviors in the target adolescent, higher levels of PSE would be linked to higher levels of promotive parenting. On the contrary, PSE should not be a strong predictor of parenting when parents faced more difficult behaviors in the older adolescent than in the target adolescent or when parents faced similar behaviors in both of their adolescents.Mage = 17.58, SD = 3.19) in addition to the target adolescent , and they reported on all study variables.The sample was drawn from a longitudinal project involving 398 parents (284 mothers and 114 fathers) of a target adolescent child in sixth or seventh grade. We used reports from a sample of 130 parents (89 mothers and 41 fathers) from the first time point of the data collection in 1999–2000. These parents were eligible for the current study because they had an older adolescent ; 55 % of the sibling pairs were of the same sex and 44 % were of the opposite sex. Concerning parents’ ethnicity, 67 % were European American, 32 % were African American, and 1 % was Hispanic. This ethnic distribution is similar to the current national and state ethnic breakdown  of the sibling pairs were within three to six years of one another in age (Parents were recruited through two public middle schools located in the southeastern United States. Some of the parents came from the same families (48 %), whereas in other families, only the mother (48 %) or only the father (4 %) participated. In families with two participating parents, they were instructed to fill out the surveys separately. Once parents agreed to participate, they were mailed response scales that were used during a telephone interview, which lasted approximately one hour. Each parent was compensated $50 for his or her participation in the project.Very little) to 7 . Cronbach’s alpha for this scale was .80.Parents completed a five-item scale of parental self-efficacy  to 2 (Very true or often true). The CBCL has demonstrated strong associations with other measures of child externalizing behaviors as well as positive and negative parenting behaviors  to 7 (Strongly disagree). Cronbach’s alpha for this scale was .90.We used the “risk-taking/rebellious” and “problem behaviors” subscales from Whiteman and Buchanan  to measuNever)–5 (Always). A recent examination of the factor structure of the APQ among parents of adolescents ages 11–18 , and in order to use the same approach as the measurement of the older adolescent’s externalizing behaviors and to follow the suggestion by Zlomke et al.  on the one hand and promotive parenting practices on the other. Additionally, as noted earlier, in some families, both parents participated whereas in other families only one parent participated. To avoid potential biases in the results because of this inter-family dependency, we used this dichotomized variable (whether one or two parents from the same family participated in the project) as a covariate in the path analysis . The analytical model is illustrated in Fig. To evaluate the model fit, three indices were used: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). CFI and TLI values above .90 and RMSEA values of .06 or lower are considered indicators of an acceptable fit between the hypothesized model and the observed data , p = .599; RMSEA = .00; CFI = 1.00; TLI = 1.04. The results from this analysis are presented in Table The path analysis see Fig.  showed a = 18.78 1, p = .5B = .15, SE = .05, p = .006), but the slope set at one SD above the mean was not significant .Of the interactions, the “PSE*Older adolescent externalizing” was the only significant predictor of promotive parenting. The interaction is depicted in Fig. In this study, we examined adolescents’ externalizing behavior as a moderator of the link between PSE and promotive parenting practices. Consistent with theory and previous research , which might result in different parenting practices  that parents have with multiple children, as this has been suggested to be important (Glatz and Stattin This study brings together theory on PSE Bandura , 1997 an


Vibrio cholerae and the invasive pathogen Salmonella enterica serovar Typhimurium. Both possess clusters of A + T‐rich horizontally acquired virulence genes that are silenced by the nucleoid‐associated protein H‐NS and regulated positively or negatively by wHTH TFs: for example, ToxR and LeuO in V. cholerae; HilA, LeuO, SlyA and OmpR in S. Typhimurium. Because of their relatively relaxed base sequence requirements for target recognition, indirect readout mechanisms have the potential to engage regulatory proteins with many more targets than might be the case using direct readout, making indirect readout an important, yet often ignored, contributor to the expression of pathogenic phenotypes.Indirect readout mechanisms of transcription control rely on the recognition of DNA shape by transcription factors (TFs). TFs may also employ a direct readout mechanism that involves the reading of the base sequence in the DNA major groove at the binding site. TFs with winged helix–turn–helix (wHTH) motifs use an alpha helix to read the base sequence in the major groove while inserting a beta sheet ‘wing’ into the adjacent minor groove. Such wHTH proteins are important regulators of virulence gene transcription in many pathogens; they also control housekeeping genes. This article considers the cases of the non‐invasive Gram‐negative pathogen  The poirae Fig.  and Salmium Fig. . These oet al., et al., Transcription factors that select their binding sites by detecting specific base sequences are said to use a direct readout mechanism for the regulation of their target genes  is a cytoplasmic membrane located sensor kinase and SsrB is a response regulator   is well established, but the potential for the changing transcriptional landscape to modulate the binding of proteins is sometimes overlooked in studies of gene control. Here we have emphasised the connection between DNA supercoiling and the binding to DNA of wHTH TFs. The principles that have been outlined concerning the impact of altered DNA twist on major and minor groove width, especially in A + T‐rich DNA illustrate the potential of DNA supercoiling to act allosterically on TF function (Fig. et al., et al., et al., et al., et al., Variable DNA topology is, perhaps, an under‐appreciated contributor to the collective control of transcription in bacteria of all kinds, including pathogens (Dorman ion Fig. . The linion Fig. . We sugg


The remaining values were higher or lower than those from the long‐used Medasys system. These differences might have changed cancer patient chemotherapy clinical decisions. As a result, our institution elected not to implement either new system.Before implementing one of two new LVEF radionuclide gated ventriculogram (MUGA) systems, the results from 312 consecutive parallel patient studies were evaluated. Each gamma‐camera acquisition was simultaneously processed by semi‐automatic Medasys Pinnacle and by fully automatic and semiautomatic Philips nuclear medicine computer systems. The Philips systems yielded LVEF results within PACS: 87.57.U‐ Nuclear medicine imaging The company later became Medasys and produced the Pinnacle MUGA system. While other imaging techniques such as quantitative gated SPECT (QGS) and volumetric ultrasound have subsequently been developed for LVEF determination, planar radionuclide ventriculography remains a generally accepted standard against which other LVEF measurement techniques are evaluated.(–) In particular, at institutions with active cancer treatment centers, this study is frequently performed on patients receiving chemotherapy regimens with various cardiotoxic drugs.(–)The MUGA (multigated acquisition) study has long been used as a non‐invasive method for quantification of left ventricular ejection fraction (LVEF).–3 OnFor over 17 years, the standard planar radionuclide ventriculogram at our institution had been the Medasys Pinnacle MUGA study. However, when Medasys went out of business several years ago and stopped supporting their hardware and software, our institution sought a replacement system. No universally accepted gold standard exists for left ventricular ejection fraction.To understand why we decided to clinically test the two systems, it is important to discuss briefly how each processing algorithm works. The Medasys Pinnacle system is semiautomated: the operator positions a box defining the search limits for the algorithm to find the edges of the left ventricular (LV) chamber using standard second‐derivative search criteria. The operator employs Fourier phase data to help position this box accurately to exclude left atrial (LA) activity. The operator then visually evaluates the data to exclude right ventricular (RV) activity and non‐cardiac (e.g. splenic) activity from the area being searched. The sensitivity of the edge‐detection algorithm can be manually adjusted if necessary in the four quadrants of the LV chamber to maximize edge tracking accuracy. This system has demonstrated reproducible results at our institution for over 17 years and thus serves as a reasonable standard for testing the new algorithms.At the onset of this project, Philips Medical Systems Odyssey systems had two available planar radionuclide ventriculography software packages; we elected to test both. The first system, the Philips GBP‐Dual system (GBP‐D), was written to emulate the Medasys program on the more modern Odyssey computer platform. One notable difference is that this system is fully automatic. As a result, the operator cannot define or limit the LV search area or adjust edge‐detection sensitivity. Likewise, Fourier phase data is available but cannot be used by the technologist to define the search area for the LV. The second system is the Philips GBP‐Multi software (GBP‐M) package. This software does not directly emulate the Medasys system, but its semiautomated algorithm permits the operator to define a search area for the LV.Our goal was to determine how closely the left ventricular ejection fractions calculated by the newer systems reproduced the calculation of the Medasys system. In particular, we wanted to see how often discrepancies in the calculated LVEF might affect treatment decisions.The study group included all patients who underwent gated planar left ventriculography (MUGA) at our institution in the two‐year period from May 2004 through April 2006. Three hundred and fifteen (315) total examinations were performed, including repeat examinations on 37 patients. Of these examinations, three examinations processed only with the Medasys system  were excluded from the analysis.in vivo with intravenous stannous pyrophosphate followed by Tc‐99m sodium pertechnetate . The patients were then imaged in the best LAO projection to separate RV and LV with a Siemens Orbiter gamma camera, which had already undergone acceptance testing. The raw data from the gamma camera were sent to the Medasys and Philips hardware simultaneously and processed by all three software systems independently. This simultaneous acquisition and processing method was the same as that employed by Carpentier for the original validation of the GBP‐D system. All three systems provided LVEF data for analysis; only the Medasys results were reported to clinicians for therapy decisions.Red blood cell labeling was performed ±5 ejection fraction percentage points difference between the test systems and Medasys were selected based on our institutional standard that such a difference represents a clinically significant change in LVEF. The mean difference and 95% confidence intervals were calculated to determine whether the test systems’ results generally fell within the clinic limits with respect to the Medasys results.The data were then analyzed using a least‐squares fit comparing the Medasys LVEFs to the test systems’ LVEFs to determine degree of correlation, forcing the fit through . In all of the tests, the Medasys results were used as the basis for comparison. In addition, we performed a Bland‐Altman analysis(–) For this reason, we also collected data of LV end diastolic volume (LVEDV) to evaluate whether small volumes might contribute to different results between the Medasys and the test systems. Only Medasys and GBP‐D provided this data, not the GBP‐M system.LVEF determination by Quantitative Gated SPECT (QGS) from stress sestamibi perfusion myocardial scans is known to cause false‐high measurements in patients with very small LV volumes.–17 F±5 ejection fraction percentage points. Overall, only 168 calculations (54%) of the GBP‐D system and 116 calculations (37%) of GBP‐M system agreed with Medasys to within ±5LVEF percentage points. Nineteen (7%) of the GBP‐D system and 4 (1%) of the GBP‐M system data were more than 5 percentage points lower, while 125 (40%) of the GBP‐D system and 192 (62%) of the GBP‐M system were more than 5 percentage points higher.Figure These figures also demonstrate a number of cases with markedly different values of LVEF obtained by the test systems than by the Medasys system. We assessed these differences by visually inspecting the left ventricular contour determined by each algorithm. The cases with the worst correlation typically showed that the search algorithm had extended the boundaries well outside the visualized LV boundary. In particular, for the fully automated GBP‐D system, the search algorithm sometimes included one or more extraneous structures in addition to the LV, or entirely excluded the LV from the calculation. Figure Unlike the QGS system of LVEF measurement, the LVEDV value for the GBP‐D system has no significant influence on LVEF measurements. As illustrated in Fig. Our data indicate that the LVEFs calculated by the Medasys and GBP‐D methods lie within 5 LVEF percentage points in approximately half of the cases, with less agreement between the Medasys and GBP‐M systems. The remaining cases were significantly disparate, both higher and lower, with some GBP‐D and GBP‐M results markedly diverging from the Medasys calculation. These data show both a systematic trend – the test systems’ LVEFs were on average higher than those from the Medasys system – as well individual failures of the test systems in certain cases.(–) In practice, however, many software programs are not extensively tested prior to clinical use. One of the most comprehensive and recent studies by De Bondt et al.,With regard to the systematic differences between the test systems and Medasys, it is difficult to determine which system correctly calculates the LVEF. First, there is no true gold standard for clinical determination of left ventricular ejection fraction, and therefore no definite reference technique.–20 IWithout detailed access to manufacturers’ processing algorithms, it is not possible to determine precisely which features of the algorithm contribute to the discrepancies. One likely source of systematic difference observed in our study may be differences in background subtraction: relative oversubtraction of background counts elevates the calculated LVEF, while undersubtraction decreases it.Such systematic differences could be identified by testing all new LVEF algorithms with a validated left ventricular phantom; however, such phantoms are not widely or commercially available. In the particular case of planar radionuclide ventriculography (MUGA), phantom studies present a challenge because a dynamic phantom  is not commercially available. Individual centers may not have access to such a phantom to do this testing. This type of testing may be best accomplished by manufacturers working with institutions with access to such a phantom.in vivo RBC labeling may influence determination of LVEF in real patients compared to mechanical phantoms. In particular, such variability in real patients may overwhelm the capabilities of the left ventricular edge‐detection algorithms. Importantly, the phantom designed by De Bondt, modeled only the left ventricle. The marked variability observed in our study was in some cases attributable to inclusion of erroneous structures in the test systems’ left ventricular volume calculation, which cannot happen in this phantom.More troubling than the overall systematic differences were the marked differences between some of the LVEFs calculated by the test programs and those calculated in the Medasys system. The observed variability may stem in part from significant patient variables in this patient population. Body habitus, difficulties in patient positioning, and medicines that interfere with To identify errors that arise in live patients, pre‐market validation of new algorithms should include testing in an adequate number of live patients, in addition to testing in phantoms. Our study in over 300 patients suggests that the initial clinical testing on 30 patients may not have adequately sampled the variabilities that live patients present. Additionally, smaller centers may not have adequate case volumes, experience, trained nuclear medicine specialists, or medical physicists necessary to do clinical testing on large numbers of patients. This effectively puts the onus of doing such testing on the manufacturers, likely in conjunction with a large institution.As a result of this study, our institution decided not to implement these new software programs. The manufacturer was informed of our findings and pulled the product from the market. They further used our test data for validation of a new product now being sold.This study illustrates the importance of a large‐scale clinical evaluation of any new medical imaging tool that generates quantitative clinical values important to patient care. In this particular case, one of the newer software packages introduced fully automated functions to generate these values. Before purchasing a new system, we recommend seeking out all previous clinical evaluations of the equipment. If no such study has been performed, then the purchasing institution should strongly consider conducting such a study, particularly in comparison with a clinically tested system.More generally, our results suggest that adequate testing of new software packages should include phantom studies, when possible, and clinical testing on a reasonable number of patients.


Social media reviews contained fewer serious AEs  and concentrated on fewer types of AEs  compared with FAERS. While social media sibutramine reviews mentioning cardiac issues helped predict those in FAERS 11 months later (p < 0.001), social media atorvastatin reviews did not help predict FAERS reports.We analyzed 998 and 270 social media postings between 2001 and 2014, 69 003 and 7383 FAERS reports between 1997 and 2014 for atorvastatin and sibutramine, respectively. Social media reporters were younger (atorvastatin: 53.9 vs. 64.0 years, Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.Social media AE reporters were younger and focused on less‐serious and fewer types of AEs than FAERS reporters. The potential for social media to provide earlier indications of AEs compared with FAERS is uncertain. Our findings highlight some of the promises and limitations of online social media versus conventional pharmacovigilance sources and the need for careful interpretation of the results. © 2016 The Authors.  Regulators have shown increasing interest in mining data from support group websites and social media postings as potential new sources for analyzing drug safety, patient‐reported outcomes, and drug use experiences.®, a lipid‐lowering agent first approved in the USA in December 1996, manufactured by Pfizer, New York City, New York, United States) and sibutramine , in a social media data source with those in FDA FAERS reports.Leveraging social media data for pharmacovigilance requires an understanding of their strengths and weaknesses relative to conventional data sources, such as the FDA Adverse Event Reporting System (FAERS).stata  version 14 or sas  version 9.3.All statistical analyses were performed using Atorvastatin  and sibutramine  were selected for this study to provide comparative evidence from the perspectives of a relatively safe versus an unsafe drug. Despite some known side effects, atorvastatin is generally viewed as having a favorable risk‐benefit profile.AskaPatient.com is a patient support group website in which patients share and rate their experiences with different medications. We selected this social media data source because of the compatibility of this study with the website's terms of use.When creating a new review, users are required to enter basic demographic information (gender and age), medication dosage, duration and reason for use, and a satisfaction rating of 1 to 5, where 1 is defined as “I would not recommend taking this medicine” and 5 as “this medicine cured me or helped me a great deal.” In addition, users can enter free text in “side effects” and “comments” fields. We extracted data from these fields for reviews posted from 2001, when the website was established, to December 2014.FDA Adverse Event Reporting System is a database that contains information on adverse event and medication error reports submitted to FDA.We excluded social media reviews that: (i) provided insufficient information for use in our analyses ; (ii) contained only irrelevant, speculative, or hearsay information; and (iii) were obvious duplicates. To make the FAERS reports more comparable with the social media data, we excluded those with clinical trials or literature as their source  and included only those in which atorvastatin or sibutramine was the primary suspect drug. We carried out sensitivity analyses including reports from clinical trials and literature.We screened all social media reviews and categorized them into the following: (i) positive or negative overall sentiment; and (ii) AE categories. AE categories were generated by the reviewer during the screening process with the objective of capturing all user‐reported AE types and facilitating a reasonable degree of differentiation between AEs. The same social media review could contribute to multiple AE categories.Our analyses also utilized specific, clinically important AEs for each drug , the extent of overlap in the most commonly mentioned AEs, and the extent of heterogeneity in AEs (assessed by the fraction of unique reports that contribute to the top 10 and 20 AEs) between the two data sources. MedDRA High Level Term terms for AEs in FAERS were used for comparisons with the reviewer‐generated AE categories in the social media data; High‐Level Group Terms were used in a sensitivity analysis.We compared the gender distribution and mean age of AE reporters in the two data sources. Within social media reviews, we also compared the average user ratings for both drugs from all users and from the subset of users who experienced specific, clinically important AEs (user ratings were not available in FAERS). We presented xis said to “Granger‐cause” another variableyif y can be better‐predicted with all available prior information on both x and y than with prior information on y alone.We used Granger causality tests to assess the association between the numbers of FAERS reports in a given month and social media postings in prior months, conditional on other available prior information . A variableCarrying out the Granger analyses first required us to model the relationship between FAERS reports and social media postings as a system of linear equations explaining the evolution of each variable as a function of the other variables in the system . The VAR equations took the following form:yt) as a function of the numbers of FAERS reports in the prior months (yt − i) and prior social media postings (xt − i) in each of T prior months. As sensitivity analyses, we also modeled the proportional reporting ratio (PRR) for muscle pain and cardiac issues in FAERS in a given month (yt) as a function of the PRR for muscle pain and cardiac issues in FAERS in the prior months (yt − i) and prior social media postings (xt − i) in each of T prior months.We modeled the number of FAERS reports in a given month  of social media postings and its potential linkage to specific AEs.P. We then executed the Granger causality tests on the equation representing the number of FAERS reports in a given month as a function of the numbers of past FAERS reports and social media postings in each of one through P prior months. This amounted to testing the null hypothesis of β1 = β2 = ⋅ ⋅ ⋅ = βp = 0 in the previous equation, with T = p. When a two‐sided p‐value is 0.05 or less, we conclude that series tx Granger cause series ty.For each VAR, we used likelihood‐ratio tests based on maximum lag lengths of up to 12 months to determine the optimal lag length There were 998 social media postings for atorvastatin from April 2001 to December 2014 and 270 postings for sibutramine from June 2001 to October 2012. Our final FAERS dataset contained 69 003 atorvastatin from November 1997 to December 2014 and 7 383 sibutramine reports from March 1998 to May 2014.p = 0.096). Social media reporters were on average younger than FAERS patients .Table p < 0.001). The pattern is reversed for the subset of pain‐related AEs classified as serious: only 2.5% of pain‐related social media reports were serious compared with 38.2% of pain‐related FAERS reports (p < 0.001).A larger proportion of social media reviews were related to pain compared with FAERS reports ; those who reported serious pain tended to give even lower ratings.Three positive sentiment categories  were identified among social media reviews of atorvastatin. Compared with all social media atorvastatin reporters, those who reported pain gave atorvastatin lower average ratings , and social media reporters were on average younger than FAERS reporters .Table p = 0.160). However, a smaller fraction of cardiovascular‐related social media reports were serious compared with cardiovascular‐related FAERS reports .The share of reports related to cardiovascular issues was similar across the two data sources , and those who reported serious cardiovascular issues tended to rate sibutramine even lower.Compared with all social media sibutramine reporters, those who reported any cardiovascular issues gave sibutramine lower average ratings . This finding contradicted the clinical understanding of the efficacy and safety profiles of the two drugs: atorvastatin is generally considered efficacious and safe in the clinical community, and yet, patients gave it a lower average rating than sibutramine, which was withdrawn from the market by the FDA.Six positive sentiment categories  were identified among social media sibutramine reviews. Consistent with the larger number of positive sentiment categories identified for sibutramine than for atorvastatin, the average rating for sibutramine in AskaPatient.com was higher than for atorvastatin . The predictive power of social media postings for sibutramine appears to be at least in‐part explained by social media reviews mentioning cardiac‐related AEs, which Granger‐cause FAERS reports for cardiac issues . Sensitivity analyses using PRRs for muscle pain and cardiac issues showed similar pattern for both atorvastatin and sibutramine. Including reports from clinical trials and literature does not have any substantial impact on the Granger causality analyses.For sibutramine, social media reviews mentioning cardiovascular events did not mention vascular events. Hence, our analyses of the time series of specific AEs excluded vascular events from the FAERS data. The optimal lag length for the all‐reports equation was 4 months. The total number of social media postings Granger‐cause FAERS reports 4 months later . To the extent that overall social media utilization  are higher for younger patients, the drivers of social media AE reports over time may tend to mirror those for conventional pharmacovigilance sources to a greater extent for medications utilized more frequently by younger patients.et al.et al.In addition, despite some similarities between the two data sources , our results suggest that social media sources contain different information and are used by a different demographic group compared with conventional pharmacovigilance data sources such as FAERS. Compared with FAERS, social media reporters of drug‐related AEs tended to be younger, and their reviews focused on fewer and less‐serious AEs affecting their quality of life rather than clinically‐significant AEs. These results were consistent across two drugs with very different safety profiles. Moreover, our results are consistent with the conclusions from the literature. Pages et al. reached a similar conclusion in their 2014 study of the extent of concordance between Twitter posts mentioning AEs and FAERS reports, noting that “…a human curation step was the most efficient way to understand the nature of the problems reported.”Context provided in social media reviews was important to our study. For example, social media reviews expressed both positive and negative sentiments, and some postings in the raw data appeared to be based on hearsay rather than actual experiences by the social media reviewer. Our manual review process was well‐suited to identifying and appropriately interpreting this context. Freifeld et al. study discussed previously, is that AE reports from social media sources should not be pooled together with those from conventional pharmacovigilance sources . Clinically important signals that the current FAERS system is designed to capture could be diluted by the large influx of non‐life‐threatening AEs that seem to be prevalent in social media sources. Hence, it is important that pharmacovigilance regulations provide clear guidance about what constitutes a reportable event to ensure the quality of the data . In addition, regulators should maintain detailed data on the source of AE reports and make these data available to researchers.Researchers and regulators should be attentive to potential differences in the information contained in social media versus conventional pharmacovigilance data sources. One policy implication of our findings, consistent with the conclusions of the Freifeld Social media adverse event reporters were younger and focused on fewer and less‐serious adverse events compared with FAERS reporters.The potential for social media sources to give earlier indications of adverse events compared with FAERS is uncertain.Appropriate interpretation and methods of analyses of adverse events from various data sources are crucial to properly evaluate hypothesis‐generating drug safety signals.This study has several limitations. First, the generalizability of our findings to other medications and data sources is uncertain. We focused on only two medications based on their divergent risk‐benefit profiles and hence abilities to provide different perspectives on social media versus conventional pharmacovigilance sources. Second, AskaPatient.com is only one social media site. The number of postings is small, which is likely to result in volatile time series. It may not be representative of all social media sources, such as open discussion forum or major social networks. Third, AskaPatient.com was established in 2000 and the first reports for atorvastatin and sibutramine were not available until 2001, several years after the approval of these two drugs. Also, the Internet use was not as prevalent. Because the majority of spontaneous reports usually occur during the first few years following the approval of a new drug, AskaPatient.com might not capture the full AE profiles of these two drugs. Hence, inferences from this study may not apply equally to other social media sources or to more recently approved drugs. Fourth, both FAERS and AskaPatient.com data consist of unvalidated patient self‐reports possibly containing errors and duplicates. Fifth, as with all spontaneous AE report sources, neither AskaPatient.com nor FAERS have information on the total number of users of a specific drug needed to calculate AE rates. Both are numerator‐based reports which may be subject to the influences of news media, herd effects, and hindsight bias. Sixth, because of the lack of data on patient characteristics, our Granger causality tests did not control for confounding factors that might affect the reporting patterns in each data source. Seventh, the total number of reports and changes in the number of reports over time are imperfect measures of a drug's potential safety issue. They not only contain true safety signals, but also noises that are subject to stimuli such as media reports, legal actions and FDA safety communications. Exploring and comparing the patterns of safety signals using appropriate metrics  between these data sources is an important topic for future research.The paper is self‐initiated by the authors, who are all employees of Analysis Group. No outside funding was provided. Analysis Group is a consulting company that has provided professional services to various government agencies and industries, including the pharmaceutical, computer IT, energy, and banking industries. The authors thank AskaPatient.com for providing their data for use in this study.Preliminary results of this study were presented at the International Conference on Pharmacoepidemiology  and the Epidemiology Seminar Series at the Harvard T.H. Chan School of Public Health (2015).


HLC) assay will enable us to evaluate the changes in the concentrations of iHLC and uHLC separately and to better identify whether the change observed is clonal or reactive. It would therefore aid in decision making for earlier implementation or discontinuation of treatment for patients with intact immunoglobulin multiple myeloma (MM).Heavy/light chain ( It has been a consensus to utilize both serum protein electrophoretic measurement and nephelometric measurement of monoclonal immunoglobulin (M‐Ig) κ/Ig'λ) that provides an indication of clonality Recently, a novel polyclonal antibody‐based serum immunoassay has been developed that separately identifies and quantifies the different heavy/light chain (HLC) types of each Ig class, providing a precise measurement of both monoclonal (involved) Ig and polyclonal (uninvolved) Ig. An important merit in clinical practice lies with the ability of this serum immunoassay to generate a HLC ratio , immunofixation electrophoresis (IFE), total Ig measurements by nephelometry, serum free light chain (FLC) assay, and the HLC immunoassay in patients with IgG MM who obtained deep responses composed of complete response (CR) and very good partial response (VGPR). We analyzed the clinical relevance of the HLC assay by taking all of the results and clinical information into consideration.κ, IgGλ, IgAκ, IgAλ, IgMκ, and IgMλ), FLC , total Ig , and M‐protein concentrations. Each serum sample was stored at −20°C and was thawed before testing for total Ig and M‐protein concentrations measured as in routine practice and for FLC and HLC concentrations quantified using Freelite and Hevylite reagents provided by the manufacturer  by immunoturbidimetry . Written informed consent was obtained from each patient before study enrollment. The IMWG  criteria were used for response assessment Inclusion criteria for this study were limited to MM patients who achieved at least a VGPR to therapy and whose M‐Ig was suitable for monitoring by the HLC immunoassays. Therefore, patients with light chain MM and IgD MM were excluded, and because there were no patients with IgA MM who attained a deep response at our community hospital, the study cohort was limited to the patients with IgG MM only. Serial serum samples were collected at each clinic visit from six patients with IgG MM who achieved a deep response (two patients who achieved a VGPR and four that achieved a CR). Serum samples were retrospectively evaluated for HLC  and polyclonal HLC (uHLC) into a graphic form. By utilizing Microsoft Excel, we formulated a pattern of the changes of the HLC data and made it easy for clinicians to observe at a glance whether the results are indicative of an increment, decrement, or no change, as shown in the figures.We also elaborated a schematic diagram that may help us to better understand the changes in iHLC and uHLC levels and the HLC ratio to guide patient management Table .λ symptomatic MM treated with HDM/ASCT  had attained a CR in January 2016, which has been sustained up until the patient's most recent visit in 2017. HLC assay was helpful to evaluate the disease status in two occasions indicated by the arrow case 1–1 and arrow case 1–2 in the Figure κ (uHLC) and IgGλ (iHLC) concentrations, and the ratios of IgG HLC, IgA HLC, and IgM HLC are all normal.Case #1  until April 2017. Over the time period from January 2015 until March 2016, the sequential HLC assay disclosed a gradual increase in the iHLC levels along with a gradual decrease in the uHLC levels as indicated by the arrow case 4–1, implicating the development of IgG pair suppression Case #4 Fig. : A 69‐yeκ MM obtained a VGPR with salvage VTd  regimen. The HLC ratios as well as FLC ratios had been in the normal range since March 2016. However, due to neurotoxicity of the VTd regimen, treatment was switched to KRd  in October 2016, with which his M‐protein levels and the iHLC levels started to decrease further without a change in the uHLC levels as indicated by the arrow case 5–1 and the patient obtained a sCR in February 2017. These combinations of the changes in the HLC data were interpreted as indicating a remission according to Table Case #5 Fig. : A 75‐yeκ symptomatic MM with past medical history of cerebral infarction with resultant left hemiplegia was treated with VMP  and obtained a VGPR which was maintained with monthly bortezomib. The patient developed a trend of increment in the M‐protein levels in July 2014 as indicated by the arrow case 6–1. However, by observing HLC trend, the HLC assay disclosed that both of the iHLC and uHLC levels were also increasing which resulted in a normal HLC ratio as indicated by the arrow case 6–2 in October 2014. These combinations of the changes in the HLC data were interpreted as indicating a remission according to Table Case #6 Fig. : A 66‐yeλ value in patients with IgGκ MM) separately, to define clonality using the HLC ratio and also to measure nonmyeloma polyclonal Ig isotypes  The value of the heavy/light chain (HLC) assay is considered to lie in its capacity of quantifying M‐Ig and polyclonal Ig of the same isotype separately in a situation where either electrophoretic or nephelometric measurements are not informative. Accordingly, this assay will enable us to evaluate the changes in the concentration of involved HLC (iHLC) and suppressed uninvolved HLC pair  alone associated with a decrease in uHLC (IgGλ) which would then indicate the development of so‐called pair suppression We were able to identify that an increase in serum total Ig concentration could result from two phenomena by the HLC assay: 1) In case of progression after CR as with the case #4, increase in the IgG concentration would be identified as clonal by the HLC assay by demonstrating the exclusive increase in iHLC  have enjoyed their symptom‐free life for more than 19 months (#1), 12 months (#2), and 25 months (#3) until the patient's most recent visit in the clinic now, respectively, and 60 months until relapse (#4). This is in line with previous studies that have shown that after treatment normalization of the FLC ratio Although long‐term follow‐up and a larger‐scale study are needed, we have an impression that the HLC assay can be prognostic, in line with previous studies We would consider that the HLC assay could help us make decision to implement or delay treatment in patients who had obtained a deep response. In the case of minimal or no change in Ig concentrations of the same class with M‐protein, if there is an increasing iHLC level either alone or along with a decreasing uHLC level (pair suppression There is a possibility that the HLC ratios may be predictive of remission as with case #3 (arrow case 3–4 vs. arrow case 3–3, Fig. There might be another possibility that a normal HLC ratio in a patient who obtained a deep response but presenting with M‐protein and abnormal FLC ratios may implicate that the patient has become a “revert to MGUS.”KS: planned and led the investigation and wrote the manuscript. YK: analyzed the results, depicted the figures, and discussed the interpretation of the results. JI and JO: did the measurements of the heavy/light chain assay. ML: analyzed and discussed the results, indicated the references, and reviewed the manuscript. SS: analyzed and discussed the results and reviewed the manuscript.None declared.


A major barrier to the achievement of Millennium Development Goals (MDGs) for reducing maternal and child mortality by three quarters and two–thirds respectively, related to lack of access to care by millions living in abject poverty in rural populations and urban slums . NotwithThese gains in global maternal and child health and survival are by no means equal and wide global disparities persist. Sub–Saharan Africa continues to have the highest under–five mortality rate among all regions, with 83 deaths per 1000 live births annually. Although Millennium Development Goal 4 was achieved in some high–mortality countries in Sub–Saharan Africa and South Asia, there are still 58 low– and middle–income countries (LMICs) who are still to reach this target. Barriers to access and equitable care are related to poverty and compounded by lack of trained human resources for health and poorly functional health systems.In 2015, the world transitioned from the MDGs to the Sustainable Development Goals (SDGs). Although the maternal, neonatal, child and adolescent health issues remain central, the SDGs are all encompassing and the health goal (SDG3) will require close linkages with other contributing SDGs. Although lack of skilled birth attendants and qualified health workers is a large part of the problem, poor health outcomes also related to complex issues such as maternal empowerment, sociocultural taboos, and care–seeking practices and behaviors during pregnancy and child–birth . Given tThe global evidence base for strategies and interventions for newborn care in community settings has substantially improved, with a range of interventions that can be potentially packaged for delivery at different times during pregnancy, childbirth, and after birth, through various health–care providers, especially community health workers (CHWs). These CHWs were tasked with improving maternal and child health outcomes in a range of research settings and shown to be effective . A fundaMuch of the global evidence for community based strategies for care has been collated in systematic reviews with an undue reliance on randomized controlled trials . This suAs we move toward accelerating action for achieving the SDGs, the role of community based platforms will become more important. These strategies are needed to ensure that several of the key themes of the SDGs such as reducing inequities and reaching marginalized populations, are achieved within the next 15 years. Some 40 years following the Alma Ata declaration of “health for all”, this might yet become a reality.