Sonographic evaluation of the shoulder in asymptomatic elderly subjects with diabetes

<p>Abstract</p> <p>Background</p> <p>The prevalence of rotator cuff tears increases with age and several studies have shown that diabetes is associated with symptomatic shoulder pathologies. Aim of our research was to evaluate the prevalence of shoulder lesions in a population of asymptomatic elderly subjects, normal and with non insulin - dependent diabetes mellitus.</p> <p>Methods</p> <p>The study was performed on 48 subjects with diabetes and 32 controls (mean age: 71.5 ± 4.8 and 70.7 ± 4.5, respectively), who did not complain shoulder pain or dysfunction. An ultrasound examination was performed on both shoulders according to a standard protocol, utilizing multiplanar scans.</p> <p>Results</p> <p>Tendons thickness was greater in diabetics than in controls (Supraspinatus Tendon: 6.2 ± 0.09 mm <it>vs </it>5.2 ± 0.7 mm, p < 0.001; Biceps Tendon: 4 ± 0.8 mm <it>vs </it>3.2 ± 0.4 mm, p < 0.001). Sonographic appearances of degenerative features in the rotator cuff and biceps were more frequently observed in diabetics (Supraspinatus Tendon: 42.7% <it>vs </it>20.3%, p < 0.003; Biceps Tendon: 27% <it>vs </it>7.8%, p < 0.002).</p> <p>Subjects with diabetes exhibited more tears in the Supraspinatus Tendon (Minor tears: 15 (15.8%) <it>vs </it>2 (3.1%), p < 0.03; Major tears: 15 (15.8%) <it>vs </it>5 (7.8%), p = ns), but not in the long head of Biceps. More effusions in subacromial bursa were observed in diabetics (23.9% <it>vs </it>10.9%, p < 0.03) as well as tenosynovitis in biceps tendon (33.3% <it>vs </it>10.9%, p < 0.001).</p> <p>In both groups, pathological findings were prevalent on the dominant side, but no difference related to duration of diabetes was found.</p> <p>Conclusions</p> <p>Our results suggest that age - related rotator cuff tendon degenerative changes are more common in diabetics.</p> <p>Ultrasound is an useful tool for discovering in pre - symptomatic stages the subjects that may undergo shoulder symptomatic pathologies.</p

Drug Resistance in Eukaryotic Microorganisms

Eukaryotic microbial pathogens are major contributors to illness and death globally. Although much of their impact can be controlled by drug therapy as with prokaryotic microorganisms, the emergence of drug resistance has threatened these treatment efforts. Here, we discuss the challenges posed by eukaryotic microbial pathogens and how these are similar to, or differ from, the challenges of prokaryotic antibiotic resistance. The therapies used for several major eukaryotic microorganisms are then detailed, and the mechanisms that they have evolved to overcome these therapies are described. The rapid emergence of resistance and the restricted pipeline of new drug therapies pose considerable risks to global health and are particularly acute in the developing world. Nonetheless, we detail how the integration of new technology, biological understanding, epidemiology and evolutionary analysis can help sustain existing therapies, anticipate the emergence of resistance or optimize the deployment of new therapies

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases