Gut and Whole-Body Microbiota of the Honey Bee Separate Thriving and Non-thriving Hives

The recent worldwide decline of honey bee colonies is a major ecological problem which also threatens pollinated crop production. Several interacting stressors such as environmental pressures and pathogens are suspected. Recently, the gut microbiota has emerged as a critical factor affecting bee health and fitness. We profiled the bacterial communities associated with the gut and whole body of worker bees to assess whether non-thriving colonies could be separated from thriving hives based on their microbial signature. The microbiota of thriving colonies was characterised by higher diversity and higher relative abundance of bacterial taxa involved in sugar degradation that were previously associated with healthy bees (e.g. Commensalibacter sp. and Bartonella apis). In contrast, the microbiota of non-thriving bees was depleted in health-associated species (e.g. Lactobacillus apis), and bacterial taxa associated with disease states (e.g. Gilliamella apicola) and pollen degradation (e.g. G. apicola and Bifidobacterium asteroides) were present in higher abundance compared to thriving colonies. Gut and whole-body microbiota shared a similar dominant core but their comparison showed differences in composition and relative abundance. More differences in taxon relative abundance between gut and whole body were observed in non-thriving bees, suggesting that microbiota associated with other bee organs might also be different. Thus, microbiota profiling could be used as a diagnostic tool in beekeeping practices to predict hive health and guide hive management.

APOE genotype influences the gut microbiome structure and function in humans and mice: relevance for Alzheimer's disease pathophysiology

Apolipoprotein E (APOE) genotype is the strongest prevalent genetic risk factor for Alzheimer's disease (AD). Numerous studies have provided insights into the pathologic mechanisms. However, a comprehensive understanding of the impact of APOE genotype on microflora speciation and metabolism is completely lacking. In this study, we investigated the association between APOE genotype and the gut microbiome composition in human and APOE-targeted replacement (TR) transgenic mice. Fecal microbiota amplicon sequencing from matched individuals with different APOE genotypes revealed no significant differences in overall microbiota diversity in group-aggregated human APOE genotypes. However, several bacterial taxa showed significantly different relative abundance between APOE genotypes. Notably, we detected an association of Prevotellaceae and Ruminococcaceae and several butyrate-producing genera abundances with APOE genotypes. These findings were confirmed by comparing the gut microbiota of APOE-TR mice. Furthermore, metabolomic analysis of murine fecal water detected significant differences in microbe-associated amino acids and short-chain fatty acids between APOE genotypes. Together, these findings indicate that APOE genotype is associated with specific gut microbiome profiles in both humans and APOE-TR mice. This suggests that the gut microbiome is worth further investigation as a potential target to mitigate the deleterious impact of the APOE4 allele on cognitive decline and the prevention of AD.-Tran, T. T. T., Corsini, S., Kellingray, L., Hegarty, C., Le Gall, G., Narbad, A., Müller, M., Tejera, N., O'Toole, P. W., Minihane, A.-M., Vauzour, D. APOE genotype influences the gut microbiome structure and function in humans and mice: relevance for Alzheimer's disease pathophysiology.

Accuracy of 64-section MDCT in the diagnosis of cruciate ligament tears

AIM

To evaluate the accuracy of non-arthrographic 64-section multidetector computed tomography (CT) in the assessment of cruciate ligament tears. A secondary goal was to determine its accuracy in the diagnosis of additional soft-tissue injuries around the knee.

MATERIALS AND METHODS

Forty consecutive outpatients underwent same-day magnetic resonance imaging (MRI) and 64-slice multidetector CT (MDCT) of the knee in this prospective study. MDCT images were independently evaluated for integrity of the anterior (ACL) and posterior cruciate ligaments (PCL), medial and lateral menisci, and medial and lateral collateral ligaments. Recognised secondary signs of ACL tears were also documented. MRI images were subsequently assessed by two radiologists and a consensus reached.

RESULTS

The sensitivity of MDCT for ACL tears was 87.5-100%, with a specificity of 100%. The presence of one or more secondary signs of ACL tears on MDCT had a sensitivity of 50-87.5% with a specificity of 100%. The sensitivity of MDCT for PCL tears was 0-25% with a specificity of 100%. The sensitivity for meniscal tears was 9.1-23.1% with a specificity of 96.3-100%.

CONCLUSION

64-section MDCT has very high sensitivity and specificity for ACL tears and, as on MRI, secondary signs, such as buckling of the PCL, are also useful in their diagnosis. MDCT has a low sensitivity for other soft-tissue injuries at the knee; however, its high specificity indicates that apparent PCL, meniscal, and collateral ligament tears can reliably be treated as true-positive findings.

PET/CT and breast cancer

This paper summarises the current status of PET/CT in relation to breast cancer.

The effect of central corneal thickness on estimates of the anterior chamber depth

BACKGROUND

The slitlamp can be used to estimate the anterior chamber depth (ACD). The length of a slit object is increased until the corneal and iris/lens images appear to just touch. Multiplying the just-touching-slit-length (JTSL) by a conversion factor gives an estimate of the ACD as measured by ultrasonography. The purpose of this study was to determine if central corneal thickness (CCT) affects the accuracy of this technique.

METHODS

The ACD of 50 subjects was measured by A-scan ultrasonography and estimated by the slitlamp technique. CCT was measured by ultrasonic pachometry. The refractive error was determined subjectively.

RESULTS

The average ultrasonographic ACD for all subjects was 3.32 +/- 0.65 mm. The average JTSL was 2.46 +/- 0.38 mm. The conversion ratio between the ultrasonographic ACD and the average JTSL was 1.35. The predicted ACD using the regression equation of JTSL on the ultrasound anterior chamber depth (USACD) was 3.32 +/- 0.54 mm. The corresponding value using the regression equation of JTSL and CCT on USACD was exactly the same, that is, 3.32 +/- 0.54 mm.

CONCLUSION

Incorporation of CCT into a regression equation does not improve the accuracy of the Smith technique.