177 research outputs found

    Distribution of antibiotic resistance genes in the saliva of healthy omnivores, ovo-lacto-vegetarians, and vegans

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    Food consumption allows the entrance of bacteria and their antibiotic resistance (AR) genes into the human oral cavity. To date, very few studies have examined the influence of diet on the composition of the salivary microbiota, and even fewer investigations have specifically aimed to assess the impact of different long-term diets on the salivary resistome. In this study, the saliva of 144 healthy omnivores, ovo-lacto-vegetarians, and vegans were screened by nested PCR for the occurrence of 12 genes conferring resistance to tetracyclines, macrolide-lincosamide-streptogramin B, vancomycin, and \u3b2-lactams. The tet(W), tet(M), and erm(B) genes occurred with the highest frequencies. Overall, no effect of diet on AR gene distribution was seen. Some differences emerged at the recruiting site level, such as the higher frequency of erm(C) in the saliva of the ovo-lacto-vegetarians and omnivores from Bologna and Turin, respectively, and the higher occurrence of tet(K) in the saliva of the omnivores from Bologna. A correlation of the intake of milk and cheese with the abundance of tet(K) and erm(C) genes was seen. Finally, when the occurrence of the 12 AR genes was evaluated along with geographical location, age, and sex as sources of variability, high similarity among the 144 volunteers was seen

    Post-mortem histopathology underlying β-amyloid PET imaging following flutemetamol F 18 injection

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    In vivo imaging of fibrillar β-amyloid deposits may assist clinical diagnosis of Alzheimer's disease (AD), aid treatment selection for patients, assist clinical trials of therapeutic drugs through subject selection, and be used as an outcome measure. A recent phase III trial of [(18)F]flutemetamol positron emission tomography (PET) imaging in 106 end-of-life subjects demonstrated the ability to identify fibrillar β-amyloid by comparing in vivo PET to post-mortem histopathology. Post-mortem analyses demonstrated a broad and continuous spectrum of β-amyloid pathology in AD and other dementing and non-dementing disease groups. The GE067-026 trial demonstrated 91% sensitivity and 90% specificity of [(18)F]flutemetamol PET by majority read for the presence of moderate or frequent plaques. The probability of an abnormal [(18)F]flutemetamol scan increased with neocortical plaque density and AD diagnosis. All dementia cases with non-AD neurodegenerative diseases and those without histopathological features of β-amyloid deposits were [(18)F]flutemetamol negative. Majority PET assessments accurately reflected the amyloid plaque burden in 90% of cases. However, ten cases demonstrated a mismatch between PET image interpretations and post-mortem findings. Although tracer retention was best associated with amyloid in neuritic plaques, amyloid in diffuse plaques and cerebral amyloid angiopathy best explain three [(18)F]flutemetamol positive cases with mismatched (sparse) neuritic plaque burden. Advanced cortical atrophy was associated with the seven false negative [(18)F]flutemetamol images. The interpretation of images from pathologically equivocal cases was associated with low reader confidence and inter-reader agreement. Our results support that amyloid in neuritic plaque burden is the primary form of β-amyloid pathology detectable with [(18)F]flutemetamol PET imaging

    Pair-Wise Regulation of Convergence and Extension Cell Movements by Four Phosphatases via RhoA

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    Various signaling pathways regulate shaping of the main body axis during early vertebrate development. Here, we focused on the role of protein-tyrosine phosphatase signaling in convergence and extension cell movements. We identified Ptpn20 as a structural paralogue of PTP-BL and both phosphatases were required for normal gastrulation cell movements. Interestingly, knockdowns of PTP-BL and Ptpn20 evoked similar developmental defects as knockdown of RPTPα and PTPε. Co-knockdown of RPTPα and PTP-BL, but not Ptpn20, had synergistic effects and conversely, PTPε and Ptpn20, but not PTP-BL, cooperated, demonstrating the specificity of our approach. RPTPα and PTPε knockdowns were rescued by constitutively active RhoA, whereas PTP-BL and Ptpn20 knockdowns were rescued by dominant negative RhoA. Consistently, RPTPα and PTP-BL had opposite effects on RhoA activation, both in a PTP-dependent manner. Downstream of the PTPs, we identified NGEF and Arhgap29, regulating RhoA activation and inactivation, respectively, in convergence and extension cell movements. We propose a model in which two phosphatases activate RhoA and two phosphatases inhibit RhoA, resulting in proper cell polarization and normal convergence and extension cell movements

    Amyloid imaging in the differential diagnosis of dementia: review and potential clinical applications

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    In the past decade, positron emission tomography (PET) with carbon-11-labeled Pittsburgh Compound B (PIB) has revolutionized the neuroimaging of aging and dementia by enabling in vivo detection of amyloid plaques, a core pathologic feature of Alzheimer's disease (AD). Studies suggest that PIB-PET is sensitive for AD pathology, can distinguish AD from non-AD dementia (for example, frontotemporal lobar degeneration), and can help determine whether mild cognitive impairment is due to AD. Although the short half-life of the carbon-11 radiolabel has thus far limited the use of PIB to research, a second generation of tracers labeled with fluorine-18 has made it possible for amyloid PET to enter the clinical era. In the present review, we summarize the literature on amyloid imaging in a range of neurodegenerative conditions. We focus on potential clinical applications of amyloid PET and its role in the differential diagnosis of dementia. We suggest that amyloid imaging will be particularly useful in the evaluation of mildly affected, clinically atypical or early age-at-onset patients, and illustrate this with case vignettes from our practice. We emphasize that amyloid imaging should supplement (not replace) a detailed clinical evaluation. We caution against screening asymptomatic individuals, and discuss the limited positive predictive value in older populations. Finally, we review limitations and unresolved questions related to this exciting new technique

    A Comprehensive Approach to Evaluate Durum Wheat–Faba Bean Mixed Crop Performance.

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    Plant breeding for intercropping is lagging because most varieties currently available in the market are selected for sole cropping systems. The present study analyzed the response of durum wheat (12 varieties) and faba bean (3 varieties) in pure and mixed cropping. Field trials were conducted in 2019 and 2020. The performance of each variety in mixed and pure cropping was evaluated using both univariate and multivariate analyses of the grain yield and land equivalent ratio (LER). For durum wheat, grain protein content was also evaluated. Durum wheat varieties were characterized by good performance in both years, whereas faba bean varieties were more affected by the growing season, suggesting that much breeding effort is warranted to improve the latter as a pure and mixed crop. Moreover, the relative performance of all varieties was affected by their combination in mixed cropping, as evaluated based on the ratio (LERratio) between LER for wheat (LERw) and LER for faba bean (LERfb). To further evaluate the overall performance of wheat and faba bean in mixed cropping, total yield, LERtotal (LERw + LERfb), and ln(LERratio) were subjected to principal component and cluster analyses. The first principal component combined the total yield and LERtotal in a single index of the overall performance of each mixed crop combination. The second principal component, based on ln(LERratio), highlighted the relative performance of varieties in each mixed crop combination. The proposed multivariate approach can be applied in the breeding programs for intercropping to identify variety combinations based on crop performance and the relative importance of the proportion of cereal and legume grains in the total harvest
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