A collection of 2,209 isolates of six polysaccharide capsule types of Haemophi/us influenzoe, including 1,975 serotype b isolates recovered in 30 countries was characterized for electrophoretically demonstrable allele profiles at 17 metabolic enzyme loci. Two hundred eighty distinct multilocus genotypes were distinguished, and cluster analysis revealed two primary phylogenetic divisions. The population structure of encapsulated H. influenzae is clonal. Currently, most of the invasive disease worldwide is caused by serotype b strains of nine clones, Strains producing serotype c, e, and f capsules belong to single divisions and have no close genetic relationships to strains of other serotypes, Serotype a and b strains occur in both primary phylogenetic divisions, probably as a result of transfer and recombination of serotype-specific sequences of the cap region between clonal lineages. A close genetic relatedness between serotype d isolates and some strains of serotypes a and b was identified, There are strong patterns of geographic variation, on an intercontinental scale, in both the extent of genetic diversity and the clonal composition of populations of encapsulated strains, The analysis suggests that the present distribution of clones is, in part, related to patterns of racial or ethnic differentiation and historical demographic movements of the human host populations.

The clonal diversity of 105 Hemophilus isolates from the blood of children with lower respiratory tract infection in Pakistan was analyzed. Ten isolates were identified as H. parainfluenzae and 95 as H. influenzae. Of the H. influenzae isolates, 61 (64%) were serotype b and 34 (36%) were nontypable; 95% of the type b isolates were members of a single clonal group (as defined by multilocus enzyme electrophoresis, SDS-PAGE outer membrane protein profile, and biotype). This clone is rarely observed among type b strains recovered from patients with invasive type b disease in the USA or Europe. The nontypable isolates in Islamabad also were clonally restricted: 9 clonal groups were found among 34 isolates, with just 5 clonal groups accounting for most (82%) of the strains. Children infected with type b strains were hospitalized more often than those with nontypable H. influenzae disease (64% vs. 41%, P = .06), but no other clinical or demographic features distinguished children infected by type b and nontypable strains.

The US National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI) created the Cancer Genome Atlas (TCGA) Project in 2006. The TCGA’s goal was to sequence the genomes of 10,000 tumors to identify common genetic changes among different types of tumors for developing genetic-based treatments. TCGA offered great potential for cancer patients, but in reality has little impact on clinical applications. Recent reports place the past TCGA approach of testing a small tumor mass at a single time-point at a crossroads. This crossroads presents us with the conundrum of whether we should sequence more tumors or obtain multiple biopsies from each individual tumor at different time points. Sequencing more tumors with the past TCGA approach of single time-point sampling can neither capture the heterogeneity between different parts of the same tumor nor catch the heterogeneity that occurs as a function of time, error rates, and random drift. Obtaining multiple biopsies from each individual tumor presents multiple logistical and financial challenges. Here, we review current literature and rethink the utility and application of the TCGA approach. We discuss that the TCGA-led catalogue may provide insights into studying the functional significance of oncogenic genes in reference to non-cancer genetic background. Different methods to enhance identifying cancer targets, such as single cell technology, real time imaging of cancer cells with a biological global positioning system, and cross-referencing big data sets, are offered as ways to address sampling discrepancies in the face of tumor heterogeneity. We predict that TCGA landmarks may prove far more useful for cancer prevention than for cancer diagnosis and treatment when considering the effect of non-cancer genes and the normal genetic background on tumor microenvironment. Cancer prevention can be better realized once we understand how therapy affects the genetic makeup of cancer over time in a clinical setting. This may help create novel therapies for gene mutations that arise during a tumor’s evolution from the selection pressure of treatment.

Robotic surgery offers increased dexterity to the pediatric minimally invasive surgeon, but procedures require more time, and there is no defined patient benefit. The fact that robotic surgery digitalizes minimally invasive surgery creates exciting possibilities for training surgeons, planning operations, and performing surgery at great distances from the operator.