Receiver Operating Characteristic AUC Research Articles

Retrospective Study Comparing WBC scan and 18F-FDG PET/CT in Patients with Suspected Prosthetic Vascular Graft Infection

Prosthetic vascular graft infections (PVGIs) are associated with high mortality rates. To improve treatment outcome, an early and definite diagnosis is critical, and current diagnostic criteria are often insufficient. The accuracy of 2-deoxy-2-[fluorine-18]-fluoro-d-glucose positron emission tomography integrated with computed tomography (18F-FDG PET/CT) and white blood cell (WBC) scan for the diagnosis of PVGI were compared. A retrospective single centre study was conducted on patients undergoing WBC scan and 18F-FDG PET/CT for a suspected PVGI between April 2013 and June 2016at the Bordeaux University Hospital, France. The diagnostic value of both imaging tests was assessed for all grafts, using receiver operating characteristic (ROC) curve analysis. Images were independently interpreted by two nuclear medicine physicians blinded to the patients' clinical and other imaging data. Thirty-nine patients were included, of whom 15 had PVGI. Antibiotic treatment was started before nuclear imaging for 16 patients, including nine patients with a PVGI. The 96 grafts of these patients were analysed, and 19 were infected. The diagnostic value of the WBC scan was significantly higher than 18F-FDG PET/CT (ROC AUC=0.902, 95% CI 0.824-0.980, and 0.759, CI 95% (0.659-0.858), respectively, p=.0071). Interobserver agreement was good for 18F-FDG PET/CT and excellent for WBC scan (kappa value of 0.76, 95% CI 0.62-0.9, and 0.97, 95% CI 0.92-1, respectively). Only one patient had a false negative 18F-FDG PET/CT result under antibiotic therapy. The WBC scan has a better diagnostic value than 18F-FDG PET/CT for PVGI diagnosis.

Susceptibility-Related Factor and Biomarkers of Dietary Supplement Polygonum multiflorum-Induced Liver Injury in Rats.

Polygonum multiflorum [PM, synonym Reynoutria multiflora (Thunb.) Moldenke.], a well-known and commonly used Traditional Chinese Medicine and herbal dietary supplement for nourishing the kidney and liver, etc., has aroused wide concern for its reported potential hepatotoxicity. Previous clinical cases and experimental studies have suggested that mild immune stress (MIS) may be one of the susceptibility-related factors of idiosyncratic drug-induced liver injury (IDILI) caused by PM. In this paper, we found that the same dose of PM caused abnormal liver biochemical indicators and liver tissue damage in MIS model rats, while it did not result in liver injury in normal rats, further confirming that MIS is a susceptibility factor for PM-IDILI. Plasma chemokine/cytokine profiling indicated that the MIS model group was significantly different from the other groups, showing a significant upregulation of plasma chemokines, while the MIS/PM group showed upregulated expression of chemokines or pro-inflammatory cytokines. Liver histopathological examination indicated a small amount of inflammatory cytokine infiltration in the MIS group, but no hepatocyte injury, consistent with the plasma profiles of increased chemokines and unchanged inflammatory cytokines. Notably, metabolomics characterization showed that MIS caused reprogramming of these metabolic pathways (such as phenylalanine and glutamate pathways), which was associated with acute phase reactions and inflammatory responses. These results suggested that MIS may promote an immune response to the initial cellular injury induced by PM in the liver, and MIS-induced upregulation of chemokines and metabolic reprogramming may an important mechanism that mediates the susceptibility to PM-IDILI. Furthermore, via receiver operating characteristic (ROC) curves analysis, we identified 12 plasma cytokines (e.g., IP-10, MCP-1 and MIP-1α) and nine metabolomics biomarkers (e.g., L-Phenylalanine, Creatinine, and L-glutamine) with differential capabilities (all ROC AUC > 0.9) of identifying susceptibility model animals from normal ones, which might be of referable value for the clinical recognition of PM-IDILI susceptible individuals.

Performance of LC–MS/MS and immunoassay based 24-h urine free cortisol in the diagnosis of Cushing's syndrome

24-h urine free cortisol (UFC) is an indicator of integrated cortisol secretion and established screening tool for Cushing’s syndrome (CS). Doubts have been raised regarding specificity of immunoassays, and mass spectrometric techniques have been proposed as an alternative. In the present study we compared diagnostic accuracy of UFC measured with LC–MS/MS vs. immunoassay in patient with CS and patients where CS has been excluded. We examined 24-h urine samples from patients with surgically confirmed CS (n = 77; Cushing’s disease (n = 44), ectopic CS (n = 5), adrenal CS (n = 28)) and patients in whom Cushing’s syndrome was excluded (n = 97) by long-term follow up. UFC was first measured by automated chemiluminescence immunoassays (ADVIA Centaur, Siemens; LIAISON, DiaSorin). Aliquots of all samples were also analyzed by liquid chromatography-tandem mass spectrometry (LC–MS/MS). Statistics: Passing-Bablok Regression, Receiver operating characteristic (ROC) analysis with Youden’s index calculation. UFC of CS patients were higher with both immunoassays compared to LC–MS/MS (913 +/- 235 vs. 303 +/- 155 μg/24 h (ADVIA) and 898 +/-216 vs. 399 +/- 196 μg/24 h (LIAISON)). Similarly, UFC were higher with immunoassays than with LC–MS/MS in the control group (223 +/- 10 vs. 23 +/- 2 μg/24 h (ADVIA) and 105 +/- 6 vs. 27 +/- 4 ug/24 h for (LIAISON)). Passing-Bablok regression showed good correlation between LC–MS/MS and ADVIA as well as between LCMS/MS and LIAISON (r = 0.96 and r = 0.99, p < 000.1) but less correlation in controls (r = 0.83 and r = 0.74, respectively, p < 000.1). ROC calculation revealed the highest ROC AUC (0.89) for the LIAISON immunoassay, followed by LC–MS/MS (0.82) and the ADVIA (0.80). In direct comparison, AUCs from LC–MS/MS and immunoassays in the same patient were not statistically different (p < 0,001). Best cut-off concentration to identify patients with CS was 234 μg/24 h (LIAISON), 51 μg/24 h for LC–MS/MS and 330 μg/24 h (ADVIA Centaur).In summary, UFC values were measured substantially higher by both immunoassays compared to LC–MS/MS. This is most likely due to cross-reactivity from interfering glucocorticoid metabolites. Nevertheless, all three methods correlated well. ROC analysis revealed the highest AUC for one of the immunoassays, although differences between the three methods were not significant. Direct comparison with LC–MS/MS indicates that high diagnostic accuracy can be obtained with suitable immunoassays.

Integrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease

BackgroundThe diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently been recognized. MethodsWe investigated whether the joint data analysis of blood metabolomics and PET imaging by machine learning provides enhanced diagnostic discrimination and gives further pathophysiological insights. Blood plasma samples were collected from 60 PD patients and 15 age- and gender-matched healthy controls. We determined metabolomic profiles by gas chromatography coupled to mass spectrometry (GC–MS). In the same cohort and at the same time we performed FDOPA PET in 44 patients and 14 controls and FDG PET in 51 patients and 16 controls. 18 PD patients were available for a follow-up exam after one year. Both data sets were analysed by two machine learning approaches, applying either linear support vector machines or random forests within a leave-one-out cross-validation scheme and computing receiver operating characteristic (ROC) curves. ResultsIn the metabolomics data, the baseline comparison between cases and controls as well as the follow-up assessment of patients pointed to metabolite changes associated with oxidative stress and inflammation. For the FDOPA and FDG PET data, the diagnostic predictive performance (DPP) in the ROC analyses was highest when combining imaging features with metabolomics data (ROC AUC for best FDOPA + metabolomics model: 0.98; AUC for best FDG + metabolomics model: 0.91). DPP was lower when using only PET attributes or only metabolomics signatures. ConclusionIntegrating blood metabolomics data combined with PET data considerably enhances the diagnostic discrimination power. Metabolomic signatures also indicate interesting disease-inherent changes in cellular processes, including oxidative stress response and inflammation.

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood parameters on presentation to hospital. An SML algorithm was developed to classify cases into infection versus no infection using microbiology records and six available blood parameters (C-reactive protein, white cell count, bilirubin, creatinine, ALT and alkaline phosphatase) from 160203 individuals. A cohort of patients admitted to hospital over a 6 month period had their admission blood parameters prospectively inputted into the SML algorithm. They were prospectively followed up from admission to classify those who fulfilled clinical case criteria for a community-acquired bacterial infection within 72 h of admission using a pre-determined definition. Predictive ability was assessed using receiver operating characteristics (ROC) with cut-off values for optimal sensitivity and specificity explored. One hundred and four individuals were included prospectively. The median (range) cohort age was 65 (21-98) years. The majority were female (56/104; 54%). Thirty-six (35%) were diagnosed with infection in the first 72 h of admission. Overall, 44/104 (42%) individuals had microbiological investigations performed. Treatment was prescribed for 33/36 (92%) of infected individuals and 4/68 (6%) of those with no identifiable bacterial infection. Mean (SD) likelihood estimates for those with and without infection were significantly different. The infection group had a likelihood of 0.80 (0.09) and the non-infection group 0.50 (0.29) (P < 0.01; 95% CI: 0.20-0.40). ROC AUC was 0.84 (95% CI: 0.76-0.91). An SML algorithm was able to diagnose infection in individuals presenting to hospital using routinely available blood parameters.

Responsiveness and minimal important change for the quick-DASH in patients with shoulder disorders

BackgroundResponsiveness and minimal important change (MIC) are central measurement properties when interpreting scores from health questionnaires. The aim of the study was to evaluate the responsiveness and MIC of the Danish version of the shortened version the Disabilities of the Arm, Shoulder and Hand questionnaire (Quick-DASH) in patients with shoulder disorders referred to primary care physiotherapy treatment.MethodsThe study included 261 patients who completed questionnaires at baseline and 3 and 6 months follow up. Absolute and relative change scores was analysed using receiver-operating-characteristics (ROC) curve analysis with the Patient Global Impression of Change (PGIC) as external anchor.ResultsAt both 3 and 6 months follow up, the Area under the Curve (ROC AUC) exceeded 0.70 and MIC was 9.1 and 13.6 at 3 and 6 months respectively.ConclusionThe Danish version of the Quick-DASH demonstrated adequate ability to measure changes in disability over 3 and 6 months in patients with shoulder disorders undergoing primary care physiotherapy treatment.

Risk prediction model of dyslipidaemia over a 5-year period based on the Taiwan MJ health check-up longitudinal database

ObjectiveThis study aimed to provide an epidemiological model to evaluate the risk of developing dyslipidaemia within 5 years in the Taiwanese population.MethodsA cohort of 11,345 subjects aged 35–74 years and was non-dyslipidaemia in the initial year 1996 and followed in 1997–2006 to derive a risk score that could predict the occurrence of dyslipidaemia. Multivariate logistic regression was used to derive the risk functions using the check-up centre of the overall cohort. Rules based on these risk functions were evaluated in the remaining three centres as the testing cohort. We evaluated the predictability of the model using the area under the receiver operating characteristic (ROC) curve (AUC) to confirm its diagnostic property on the testing sample. We also established the degrees of risk based on the cut-off points of these probabilities after transforming them into a normal distribution by log transformation.ResultsThe incidence of dyslipidaemia over the 5-year period was 19.1%. The final multivariable logistic regression model includes the following six risk factors: gender, history of diabetes, triglyceride level, HDL-C (high-density lipoprotein cholesterol), LDL-C (low-density lipoprotein cholesterol) and BMI (body mass index). The ROC AUC was 0.709 (95% CI: 0.693–0.725), which could predict the development of dyslipidaemia within 5 years.ConclusionThis model can help individuals assess the risk of dyslipidaemia and guide group surveillance in the community.

Pharmacy Refill Data are Poor Predictors of Virologic Treatment Outcomes in Adolescents with HIV in Botswana.

In adults living with HIV, pharmacy refill data are good predictors of virologic failure (VF). The utility of pharmacy refill data for predicting VF in adolescents has not been reported. We evaluated data from 291 adolescents on antiretroviral therapy. The main outcome measure was VF, defined as two consecutive HIV viral load measurements ≥ 400 copies/mL during 24-months of follow-up. Pharmacy refill non-adherence was defined as two consecutive refill adherence measurements < 95% during the same period. Fifty-three (18%) adolescents experienced VF. One hundred twenty-eight (44%) adolescents had refill non-adherence. Refill non-adherence had poor discriminative ability for indicating VF (receiver operating characteristic AUC = 0.60). Sensitivity and specificity for predicting VF was poor (60% (95% CI 46-74%) and 60% (95% CI 53-66%), respectively). The lack of a viable surrogate for VF in adolescents highlights the urgent need for more access to virologic testing and novel methods of monitoring adolescent treatment adherence.

Detection of Brain Hypoxia Based on Noninvasive Optical Monitoring of Cerebral Blood Flow with Diffuse Correlation Spectroscopy.

Diffuse correlation spectroscopy (DCS) noninvasively permits continuous, quantitative, bedside measurements of cerebral blood flow (CBF). To test whether optical monitoring (OM) can detect decrements in CBF producing cerebral hypoxia, we applied the OM technique continuously to probe brain-injured patients who also had invasive brain tissue oxygen (PbO2) monitors. Comatose patients with a Glasgow Coma Score (GCS) < 8) were enrolled in an IRB-approved protocol after obtaining informed consent from the legally authorized representative. Patients underwent 6-8h of daily monitoring. Brain PbO2 was measured with a Clark electrode. Absolute CBF was monitored with DCS, calibrated by perfusion measurements based on intravenous indocyanine green bolus administration. Variation of optical CBF and mean arterial pressure (MAP) from baseline was measured during periods of brain hypoxia (defined as a drop in PbO2 below 19mmHg for more than 6min from baseline (PbO2 > 21mmHg). In a secondary analysis, we compared optical CBF and MAP during randomly selected 12-min periods of "normal" (> 21mmHg) and "low" (< 19mmHg) PbO2. Receiver operator characteristic (ROC) and logistic regression analysis were employed to assess the utility of optical CBF, MAP, and the two-variable combination, for discrimination of brain hypoxia from normal brain oxygen tension. Seven patients were enrolled and monitored for a total of 17days. Baseline-normalized MAP and CBF significantly decreased during brain hypoxia events (p < 0.05). Through use of randomly selected, temporally sparse windows of low and high PbO2, we observed that both MAP and optical CBF discriminated between periods of brain hypoxia and normal brain oxygen tension (ROC AUC 0.761, 0.762, respectively). Further, combining these variables using logistic regression analysis markedly improved the ability to distinguish low- and high-PbO2 epochs (AUC 0.876). The data suggest optical techniques may be able to provide continuous individualized CBF measurement to indicate occurrence of brain hypoxia and guide brain-directed therapy.

Temporal response profiles of serum ubiquitin C-terminal hydrolase-L1 and the 145-kDa alpha II-spectrin breakdown product after severe traumatic brain injury in children.

Traumatic brain injury (TBI) is the leading cause of acquired disability among children. Brain injury biomarkers may serve as useful diagnostic and prognostic indicators for TBI. Levels of ubiquitin C-terminal hydrolase-L1 (UCH-L1) and the 145-kDa alpha II-spectrin breakdown product (SBDP-145) correlate with outcome in adults after severe TBI. The authors conducted a pilot study of these biomarkers in children after severe TBI to inform future research exploring their utility in this population. The levels of UCH-L1 and SBDP-145 were measured in serum, and UCH-L1 in CSF from pediatric patients after severe TBI over 5 days after injury. Both biomarkers were also measured in age-matched control serum and CSF. Adequate numbers of samples were obtained in serum, but not CSF, to assess biomarker temporal response profiles. Using patients with samples from all time points, UCH-L1 levels increased rapidly and transiently, peaking at 12 hours after injury. SBDP-145 levels showed a more gradual and sustained response, peaking at 48 hours. The median serum UCH-L1 concentration was greater in patients with TBI than in controls (median [IQR] = 361 [187, 1330] vs 147 [50, 241] pg/ml, respectively; p < 0.001). Receiver operating characteristic (ROC) analysis revealed an AUC of 0.77. Similarly, serum SBDP-145 was greater in children with TBI than in controls (median [IQR] = 172 [124, 257] vs 69 [40, 99] pg/ml, respectively; p < 0.001), with an ROC AUC of 0.85. When only time points of peak levels were used for ROC analysis, the discriminability of each serum biomarker increased (AUC for UCH-L1 at 12 hours = 1.0 and for SBDP-145 at 48 hours = 0.91). Serum and CSF UCH-L1 levels correlated well in patients with TBI (r = 0.70, p < 0.001). Findings from this exploratory study reveal robust increases of UCH-L1 and SBDP-145 in serum and UCH-L1 in CSF obtained from children after severe TBI. In addition, important temporal profile differences were found between these biomarkers that can help guide optimal time point selection for future investigations of their potential to characterize injury or predict outcomes after pediatric TBI.

Ecological niche modeling re-examined: A case study with the Darwin's fox.

Many previous studies have attempted to assess ecological niche modeling performance using receiver operating characteristic (ROC) approaches, even though diverse problems with this metric have been pointed out in the literature. We explored different evaluation metrics based on independent testing data using the Darwin's Fox (Lycalopex fulvipes) as a detailed case in point. Six ecological niche models (ENMs; generalized linear models, boosted regression trees, Maxent, GARP, multivariable kernel density estimation, and NicheA) were explored and tested using six evaluation metrics (partial ROC, Akaike information criterion, omission rate, cumulative binomial probability), including two novel metrics to quantify model extrapolation versus interpolation (E‐space index I) and extent of extrapolation versus Jaccard similarity (E‐space index II). Different ENMs showed diverse and mixed performance, depending on the evaluation metric used. Because ENMs performed differently according to the evaluation metric employed, model selection should be based on the data available, assumptions necessary, and the particular research question. The typical ROC AUC evaluation approach should be discontinued when only presence data are available, and evaluations in environmental dimensions should be adopted as part of the toolkit of ENM researchers. Our results suggest that selecting Maxent ENM based solely on previous reports of its performance is a questionable practice. Instead, model comparisons, including diverse algorithms and parameterizations, should be the sine qua non for every study using ecological niche modeling. ENM evaluations should be developed using metrics that assess desired model characteristics instead of single measurement of fit between model and data. The metrics proposed herein that assess model performance in environmental space (i.e., E‐space indices I and II) may complement current methods for ENM evaluation.

Performance of existing risk scores around heart transplantation: validation study in a 4-year cohort.

Several risk scores exist to help identify best candidate recipients for heart transplantation (HTx). This study describes the performance of five heart failure risk scores and two post-HTx mortality risk scores in a French single-centre cohort. All patients listed for HTx through a 4-year period were included. Waiting-list risk scores [Heart Failure Survival Score (HFSS), Seattle Heart Failure Model (SHFM), Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC), Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) and Get With The Guidelines-Heart Failure (GWTG-HF)] and post-HTx scores Index for Mortality Prediction After Cardiac Transplantation (IMPACT and CARRS) were computed. Main outcomes were 1-year mortality on waiting list and after HTx. Performance was assessed using receiver operator characteristic (ROC), calibration and goodness-of-fit analyses. The cohort included 414 patients. Waiting-list mortality was 14.0%, and post-HTx mortality was 16.3% at 1-year follow-up. Heart failure risk scores had adequate discrimination regarding waiting-list mortality (ROC AUC for HFSS=0.68, SHFM=0.74, OPTIMIZE-HF=0.72, MAGGIC= 0.70 and GWTG=0.77; all P-values <0.05). On the contrary, post-HTx risk scores did not discriminate post-HTx mortality (AUC for IMPACT=0.58, and CARRS=0.48, both P-values >0.50). Subgroup analysis on patients undergoing HTx after ventricular assistance device (VAD) implantation (i.e. bridge-to-transplantation) (n=36) showed an IMPACT AUC=0.72 (P<0.001). In this single-centre cohort, existing heart failure risk scores were adequate to predict waiting-list mortality. Post-HTx mortality risk scores were not, except in the VAD subgroup.

A type 1 diabetes genetic risk score can discriminate monogenic autoimmunity with diabetes from early-onset clustering of polygenic autoimmunity with diabetes

Aims/hypothesisIdentifying individuals suitable for monogenic autoimmunity testing and gene discovery studies is challenging: early-onset type 1 diabetes mellitus can cluster with additional autoimmune diseases due to shared polygenic risk and islet- and other organ-specific autoantibodies are present in both monogenic and polygenic aetiologies. We aimed to assess whether a type 1 diabetes genetic risk score (GRS) could identify monogenic autoimmune diabetes and be useful to prioritise individuals for gene discovery studies.MethodsWe studied 79 individuals with diabetes and at least one additional autoimmune disease diagnosed before the age of 5 years. We screened all participants for the seven genes known to cause monogenic autoimmunity that can include diabetes (AIRE, IL2RA, FOXP3, LRBA, STAT1, STAT3, STAT5B). We genotyped the top ten risk alleles for type 1 diabetes, including HLA and non-HLA loci, to generate a type 1 diabetes GRS.ResultsOf the 79 individuals studied, 37 (47%) had mutations in the monogenic autoimmunity genes. The type 1 diabetes GRS was lower in these individuals than in those without mutations in these genes (median 9th vs 49th centile of type 1 diabetes controls, p < 0.0001). Age of diabetes diagnosis and type 1 diabetes GRS combined to be highly discriminatory of monogenic autoimmunity (receiver operating characteristic AUC: 0.88). Most individuals without a mutation in a known gene had a high type 1 diabetes GRS, suggesting that they have polygenic clustering of type 1 diabetes and additional autoimmunity and should not be included in gene discovery studies.Conclusions/interpretationWe have shown that the type 1 diabetes GRS can identify individuals likely to have monogenic autoimmunity, helping both diagnostic testing and novel monogenic autoimmunity gene discovery. Individuals with monogenic autoimmunity have a different clinical course to those with polygenic type 1 diabetes and can respond well to therapies targeting the underlying genetic defect.

A 3D Human Airway Model Enables Prediction of Respiratory Toxicity of Inhaled Drugs In Vitro.

Respiratory tract toxicity represents a significant cause of attrition of inhaled drug candidates targeting respiratory diseases. One of the key issues to allow early detection of respiratory toxicities is the lack of reliable and predictive in vitro systems. Here, the relevance and value of a physiologically relevant 3D human airway in vitro model (MucilAir) were explored by repeated administration of a set of compounds with (n = 8) or without (n = 7) respiratory toxicity following inhalation in vivo. Predictability for respiratory toxicity was evaluated by readout of cytotoxicity, barrier integrity, viability, morphology, ciliary beating frequency, mucociliary clearance and cytokine release. Interestingly, the data show that in vivo toxicity can be predicted in vitro by studying cell barrier integrity by transepithelial electrical resistance (TEER), and cell viability determined by the Resazurin method. Both read-outs had 88% sensitivity and 100% specificity, respectively, while the former was more accurate with receiver operating characteristic (ROC) AUC of 0.98 (p = .0018) compared with ROC AUC of 0.90 (p = .0092). The loss of cell barrier integrity could mainly, but not fully, be attributed to a loss of cell coverage in 6 out of 7 compounds with reduced TEER. Notably, these effects occurred only at 400 µM, at concentration levels significantly above primary target cell potency, suggesting that greater attention to high local lung concentrations should be taken into account in safety assessment of inhaled drugs. Thus, prediction of respiratory toxicity in 3D human airway in vitro models may result in improved animal welfare and reduced attrition in inhaled drug discovery projects.

Structure based drug design of Pim-1 kinase followed by pharmacophore guided synthesis of quinolone-based inhibitors

Over expression of Human phosphatidyl inositol mannoside kinases isoform 1 (Pim-1 kinase) has been reported in several leukemia and solid tumors. Our continuous interest to reveal the secrecies of the mysterious Pim-1 kinase binding pocket has led us to employ a structure based drug design procedure based on receptor-ligand pharmacophore generation protocol implemented in Discovery Studio 4.5 (DS 4.5). Subsequently, we collected 104 crystal structures of Pim-1 kinase from the Protein Data Bank (PDB) and used them to generate pharmacophores based on the anticipated co-crystallized ligand-Pim 1 kinase receptor interactions. All selected pharmacophoric features were enumerated and only those that had corresponding valuable receptor-ligand interactions were retained. This was followed by modeling all pharmacophore combinations and scoring them according to their Receiver Operating Characteristic (ROC) curve analysis parameters as well as a DS.4.5 built-in Genetic Function Algorithm (GFA) validating model. Accordingly, 111 pharmacophores resulted with acceptable ROC performances; 1XWS_2_04, 2BIK_2_06, and 1XWS_2_06 (ROC AUC value of: 0.770, 0.743 and 0.741 respectively) were the best pharmacophores. These pharmacophores were employed to guide the synthesis of new series of 7-[(2-Carboxyethyl)amino]-1-substituted-6-fluoro-8-nitro-4-oxo-1,4-dihydro-quinoline-3-carboxylic acid and their reduced 8-amino derivatives. The synthesized compounds were later evaluated for their Pim-1 kinase inhibitory potencies. Of which the most potent illustrated an IC50 value of 0.29µM against Pim-1 kinase.

Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades : ACross-Sectional Observational Study.

To assess the role of perfusion-related signal decay on diffusion kurtosis imaging (DKI) estimates for in vivo stratification of glioma according to the integrated approach of the 2016 World Health Organization classification of tumors of the central nervous system (2016 CNS WHO). In this study 77 patients with histopathologically confirmed glioma were retrospectively assessed between January 2013 and February 2017 in aprospective trial. Mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were assessed by two physicians blinded to the study from avolume of interest around the entire solid tumor. Wilcoxon's signed-rank test compared perfusion-biased and perfusion-corrected MK (MKpb and MKpc) and MD (MDpb, MDpc) values. One-way ANOVA was used to compare MKpb&pc and MDpb&pc values between 2016 WHO glioma grades. Spearman's correlation coefficient was used to correlate them with 2016 WHO glioma grades. Receiver operating characteristic (ROC) analysis was performed on MKpb&pc and MDpb&pc for the significant results. The MKpc values were significantly higher than MKpb values (p< 0.001), whereas MDpc values were significantly lower than MDpb values (p< 0.001). For stratifying gliomas, MKpb values (ROC AUC range, 0.818-0.979) showed ahigher diagnostic performance than MKpc values (ROC AUC range, 0.773-0.975), whereas MDpb values (ROC AUC range, 0.744-0.928) showed less diagnostic performance than MDpc values (ROC AUC range, 0.753-0.934). The diagnostic accuracy of MKpb was 80.0%. The MK and MD estimates of DKI are influenced by microcapillary blood perfusion; however, taking the effect of perfusion on DKI metrics into account does not substantially impact their overall diagnostic performance in classifying glioma according to the 2016 CNS WHO.

The impact of reconstruction and scanner characterisation on the diagnostic capability of a normal database for [123I]FP-CIT SPECT imaging

BackgroundThe use of a normal database for [123I]FP-CIT SPECT imaging has been found to be helpful for cases which are difficult to interpret by visual assessment alone, and to improve reproducibility in scan interpretation. The aim of this study was to assess whether the use of different tomographic reconstructions affects the performance of a normal [123I]FP-CIT SPECT database and also whether systems benefit from a system characterisation before a database is used.Seventy-seven [123I]FP-CIT SPECT studies from two sites and with 3-year clinical follow-up were assessed quantitatively for scan normality using the ENC-DAT normal database obtained in well-documented healthy subjects. Patient and normal data were reconstructed with iterative reconstruction with correction for attenuation, scatter and septal penetration (ACSC), the same reconstruction without corrections (IRNC), and filtered back-projection (FBP) with data quantified using small volume-of-interest (VOI) (BRASS) and large VOI (Southampton) analysis methods. Test performance was assessed with and without system characterisation, using receiver operating characteristics (ROC) analysis for age-independent data and using sensitivity/specificity analysis with age-matched normal values. The clinical diagnosis at follow-up was used as the standard of truth.ResultsThere were no significant differences in the age-independent quantitative assessment of scan normality across reconstructions, system characterisation and quantitative methods (ROC AUC 0.866–0.924). With BRASS quantification, there were no significant differences between the values of sensitivity (67.4–83.7%) or specificity (79.4–91.2%) across all reconstruction and calibration strategies. However, the Southampton method showed significant differences in sensitivity between ACSC (90.7%) vs IRNC (76.7%) and FBP (67.4%) reconstructions with calibration. Sensitivity using ACSC reconstruction with this method was also significantly better with calibration than without calibration (65.1%). Specificity using the Southampton method was unchanged across reconstruction and calibration choices (82.4–88.2%).ConclusionsThe ability of a normal [123I]FP-CIT SPECT database to assess clinical scan normality is equivalent across all reconstruction, system characterisation, and quantification strategies using BRASS quantification. However, when using the Southampton quantification method, performance is sensitive to the reconstruction and calibration strategy used.

A Comparative Study to Evaluate C-Reactive Protein and Procalcitonin as a Marker of Bacterial Infection in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Introduction: Exacerbations of chronic obstructive pulmonary disease (COPD) can be precipitated by several factors. The most common causes appear to be respiratory tract infections. The overuse of antibiotics is common and accelerates the development of drug resistance and hospital-acquired infections. In some recent studies, both C-reactive proteins (CRP), as well as procalcitonin (PCT) levels, have been shown to be useful in differentiating bacterial etiology of exacerbations and thus helping in guiding the treatment as well as in prediction of outcome. This study aims to evaluate the sensitivity and specificity of CRP and procalcitonin as a marker of bacterial infection in patients with acute exacerbation of COPD. Material and Methods: A total of 50 patients from patients of COPD with acute exacerbation attending/admitted to pulmonary OPD/IPD were included in the study, excluding those below 40 years old or presenting with acute breathlessness due to comorbid conditions. Demographic information, relevant clinical data, and lab investigations were recorded from all patients, including C-reactive protein and procalcitonin, on admission following which the patients have started antibiotics as per guidelines. Reassessment of S. procalcitonin and CRP was done on the 3rd and 7th day of hospitalization. Receiveroperating characteristic (ROC) curve was applied to compare sensitivity and specificity. Results: Sputum culture was found positive in 27 (54%) patients. At all the three intervals, CRP levels had ROC area under curve (ROC AUC) values above 0.70. The area under curve value was maximum on day 3. For PCT, the area under curve values was &gt; 0.8 on day 1 and 3, but on day 7 this value was only 0.624. On evaluating the correlation between S. C-reactive protein and PCT levels, a mild positive and significant correlation was observed at day 1 and 7 intervals, whereas on day 3 a moderate positive and significant correlation was observed between the two markers. Conclusion: The CRP is a good marker when tested early and late, while PCT is better when tested early.

Volatile organic compound markers of psychological stress in skin: a pilot study

The forehead was studied as a possible sampling site for capturing changes in volatile organic compound (VOC) profiles associated with psychological-stress. Skin-VOCs were sampled with a polydimethylsilicone (PDMS)-coupon and the resulting VOCs were recovered and analysed with two-stage thermal desorption gas chromatography-mass spectrometry.Fifteen young adult volunteers (19 years–26 years) participated in two interventions run in a randomised crossover design. One intervention, termed ‘Neutral’, required the participants to listen to peaceful music, the other, termed a ‘paced audio serial addition task’, required the participants to undertake a series of rapid mental arithmetic calculations in a challenging environment that induced a stress response. Skin-VOC samples were taken during each intervention. The resultant data were processed with dynamic background compensation, deconvolved, and registered to a common retention index scale.The importance of freezing skin patch samplers to −80 °C was determined during the method development phase of this study. The cumulative distribution function of the GC-MS data indicates the possibility that PDMS-coupons are selective towards the lower volatility VOC components in skin. The frequency distribution of the GC-MS data was observed to be approximately log-normal, and on the basis of this study, a further two-orders of magnitude reduction in sensitivity may be required before the complete skin-VOC profile may be characterised.Multi-variate analysis involving Pareto-scaling prior to partial least squares discriminant analysis identified four VOCs with the highest probability of contributing to the variance between the two states, and the responses to these VOCs were modelled with principle components analysis (PCA). Two VOCs, benzoic acid and n-decanoic acid were upregulated (14 and 8 fold respectively) and appear to be PASAT sensitive, with areas under (AUC) their receiver operator characteristic (ROC) curves of 0.813 and 0.852 respectively. A xylene isomer and 3-carene were down regulated 75% and 97% respectively, and found to be predictive of the neutral intervention (ROC AUC values of 0.898 and 0.929 respectively). VOC profiles in skin appear to change with stress either due to increased elimination, elevated bacterial activity, or perhaps increased oxidative pathways.

Diagnostic accuracy of presepsin (sCD14-ST) as a biomarker of infection and sepsis in the emergency department

BackgroundPresepsin is a promising biomarker for the diagnosis and prognosis of sepsis. However, results reported about its value to diagnose sepsis in an emergency department (ED) are controversial, probably due to differences in the design of the studies. We have evaluated the diagnostic accuracy of presepsin for infection and sepsis, compared with procalcitonin (PCT) and C-reactive protein (CRP), in patients presenting to the emergency department (ED) with suspected infection. Methods223 patients with suspected infection were enrolled for the study. Blood samples were collected on admission for measurement of biomarkers. Definitive diagnosis was obtained afterwards by analysis of digital medical records. Receiver operating characteristic (ROC) curve analysis was conducted to determine the diagnostic accuracy. ResultsInfection was confirmed in 200 patients, including 130 with non-complicated infection and 70 with sepsis. Median CRP, PCT and presepsin levels were significantly higher in patients with infection and sepsis. PCT was the biomarker with the highest performance for infection (ROC AUC: 0.910); for sepsis, PCT (ROC AUC: 0.815) and presepsin (ROC AUC: 0.775) shown a similar performance. ConclusionAlthough presepsin is a valuable biomarker for diagnosis of infection and sepsis, its diagnostic accuracy in our study does not improve that of PCT. Its introduction in clinical practice is not justified.