The human immunodeficiency virus (HIV) epidemic and dual infection of tuberculosis (TB) and HIV are now altering the role of chest radiography (CR) in TB control. The role has been gaining increasing importance, especially as HIV-associated TB and childhood TB are less likely to show positive smears. However, CR with poor image quality can cause misdiagnoses or require repeated examinations, wasting economic resources and exposing patients to unnecessary radiation. In order to improve the image quality of CR, the Tuberculosis Coalition for Technical Assistance (TBCTA) developed an assessment tool for CR categorized on the basis of six factors as “excellent,” “good,” “fair,” and “poor.” With the aim of disseminating the assessment tool, five-day international training sessions were held in Cambodia and Kenya in 2009. This field report summarizes the international training activities and documents the findings after the trainings.
A total of thirty-four participants from 14 countries were trained and assigned to conduct an assessment upon their return. The results from nine countries showed that the quality of CR ranged from 90% excellent or good in Bangladesh to over 90% fair or poor in Afghanistan. Of 69 health facilities, only 4 apply more than 120kV and above. This is one of the considerable factors behind the sub-optimal quality of CR in these countries.

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer's disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P < 0.05) with highest significance for miR-532-5p (Benjamini- Hochberg adjusted P = 4.8 × 10 -30). Machine learning models reached an area under the curve (AUC) value of 87.6％ in differentiating AD patients from controls. Further, ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted P = 0.0002). Interestingly, the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells, while those up-regulated in AD were enriched in serum, exosomes, cytotoxic t-cells, and B-cells. Our study represents the next important step in translational research for a miRNA-based AD test.