Calcium inhibits promotion by hot dog of 1,2‐dimethylhydrazine‐induced mucin‐depleted foci in rat colon

Epidemiology suggests that processed meat is associated with colorectal cancer risk, but few experimental studies support this association. We have shown that a model of cured meat made in a pilot workshop promotes preneoplastic lesions, mucin‐depleted foci (MDF) in the colon of rats. This study had two aims: to check if real store‐bought processed meats also promote MDF, and to test if calcium carbonate, which suppresses heme‐induced promotion, can suppress promotion by processed meat. A 14‐day study was done to test the effect of nine purchased cured meats on fecal and urinary biomarkers associated with heme‐induced carcinogenesis promotion. Fecal water from rats given hot dog or fermented raw dry sausage was particularly cytotoxic. These two cured meats were thus given to rats pretreated with 1,2‐dimethylhydrazine, to evaluate their effect on colorectal carcinogenesis. After a 100‐days feeding period, fecal apparent total N‐nitroso compounds (ATNC) were assayed and colons were scored for MDF. Hot dog diet increased fecal ATNC and the number of MDF per colon compared with the no‐meat control diet (3.0 ± 1.7 vs. 1.2 ± 1.4, p < 0.05). In a third study, addition of calcium carbonate (150 µmol/g) to the hot dog diet decreased the number of MDF/colon and fecal ATNC compared with the hot dog diet without calcium carbonate (1.2 ± 1.1 vs. 2.3 ± 1.4, respectively, p < 0.05). This is the first experimental evidence that a widely consumed processed meat promotes colon carcinogenesis in rats. It also shows that dietary prevention of this detrimental effect is possible.     

Face recognition in schizophrenia: do individual and average ROCs tell the same story?

Introduction. Many studies have shown that recollection process is impaired in patients with schizophrenia, whereas familiarity is generally spared. However, in these studies, the Receiver Operating Characteristic (ROC) presented is average ROC likely to mask individual differences.

Methods. In the present study using a face-recognition task, we computed the individual ROC of patients with schizophrenia and control participants. Each group was divided into two subgroups on the basis of the type of recognition processes implemented: recognition based on familiarity only and recognition based on familiarity and recollection.

Results. The recognition performance of the schizophrenia patients was below that of the control participants only when recognition was based solely on familiarity. For the familiarity-alone patients, the score obtained on the Scale for the Assessment of Positive Symptoms (SAPS) was correlated with the variance of the old-face familiarity. For the familiarity-recollection patients, the score obtained on the Scale for the Assessment of Negative Symptoms (SANS) was correlated with the decision criterion and with the old-face recollection probability.

Conclusions. These results show that one cannot ascribe the impaired recognition observed in patients with schizophrenia to a recollection deficit alone. These results show that individual ROC can be used to distinguish between subtypes of schizophrenia and could serve as a basis for setting up specific cognitive remediation therapy for individuals with schizophrenia.     

Individual QT–R‐R Relationship: Average Stability over Time Does Not Rule Out an Individual Residual Variability: Implication for the Assessment of Drug Effect on the QT Interval

Background: Universal QT correction formulae have been shown to under or overcorrect the QT interval duration. Individual QT–R‐R modeling has been proposed as a preferable solution for heart rate correction of QT intervals. However, the QT–R‐R relationship stability over time needs to be evaluated. Methods: The present report is part of randomized, double‐dummy, and placebo‐controlled 4‐way crossover phase 1 study (48 healthy volunteers). Each randomized period included a run‐in placebo day followed the day after by drug administration, with moxifloxacin as a positive control for QT interval measurement. Digital Holter ECG data were analyzed using the “bin” approach. For each period, individual QT–R‐R relationship were calculated using two different models (linear and parabolic log–log models). Results: The mean intrasubject variability for the α coefficient of the linear modeling (SDintra = 0.011 ± 0.005) reached 28.6 ± 10.2%. When the parabolic model was considered, the SDintra was 0.026 ± 0.009 for the α coefficient. The QT–R‐R relationship variability was in part related to long‐term RR changes (R²= 30%, P < 0.05). However, no significant time effect (ANOVA) was evidenced for QT–R‐R coefficients. Moxifloxacin significantly increased the α coefficient of the QT–R‐R relationship from 0.07 ± 0.018 to 0.085 ± 0.019, P < 0.05 (linear model). Conclusions: The individual QT–R‐R relationship shows a residual variability in part related to long‐term autonomic changes. In addition, the QT–R‐R relationship might be modulated by the drug tested. As a consequence, pretherapy QT–R‐R relationship obtained in a given patient cannot be used as a fingerprint throughout a drug trial.     

Comparison of non-invasive liver fibrosis biomarkers in HIV/HCV co-infected patients: the fibrovic study--ANRS HC02

BACKGROUND/AIMS: To compare non-invasive biological liver fibrosis scores, as alternatives to liver biopsy, in HIV/HCV co-infected patients. METHODS: Two hundred and seventy-two HIV/HCV patients, nai ve for HCV treatment, underwent liver biopsy [197 (72%) men, 39.9 years, fibrosis stage (Metavir) F1 (25%), F2 (40%), F3 (25%), F4 (10%), median CD4 486/mm(3) and median HIV viral load 3.5log. Fibrotest (FT), Hepascore (HS), Fibrometer (FM), SHASTA, APRI, Forns index, and Fib-4 were tested in order to differentiate patients with mild to moderate fibrosis (F2) and those with advanced fibrosis (F3). The AUROC and the rate of well-classified patients were compared to liver biopsy. RESULTS: FT, HS, and FM were able to stage liver fibrosis in all patients with AUROCs of 0.78, 0.84 and 0.89 for the diagnosis of F2, respectively. The correlation coefficient indexes were 0.37, 0.46 and 0.48, respectively. The rates of well-classified patients were 62%, 68% and 71%, respectively. Fib-4, APRI and the Forn's index were only able to stage 37-61% of patients and showed lower accuracies. Using a combination of FT, HS and FM did not significantly increase the performance of each test. CONCLUSIONS: In HIV/HCV co-infected patients, Fibrometer, Hepascore and Fibrotest outperformed other non-invasive liver fibrosis biomarkers for the prediction of significant liver fibrosis.