Patients with cirrhosis and very early iCCA may become candidates for liver transplantation; a prospective multicenter clinical trial is needed to further confirm these results. (Hepatology 2016;64:1178-1188).

ABSTRACT:The TNC gene has previously been associated with Achilles tendinopathy (AT) in a South African population. The aims of this study were (i) to investigate the association of single nucleotide polymorphisms within the TNC gene, and the additional candidate gene, COL27A1, with AT in two populations, and (ii) to identify if there is a risk haplotype for AT in both populations. Three hundred and thirty nine healthy control participants (CON) and 179 participants clinically diagnosed with AT (TEN) from South Africa and Australia, were genotyped for variants: rs4143245, rs1249744, rs753085, rs946053 (COL27A1) and rs13321, rs2104772, rs1330363 (TNC). Haplotypes were inferred using the genotype data. The rs2104772 (p ¼ 0.017) and rs1330363 (p ¼ 0.020) variants within TNC showed a significant allele association with AT. The GCA haplotype (rs946053-rs13321-rs2104772) occurred significantly more frequently in TEN participants compared to CON (27% vs. 18%; p ¼ 0.019). This study further implicates the genomic region containing the TNC and COL27A1 genes in influencing risk of AT, and maps the potential risk allele to a genetic interval flanked by rs946053 and rs2104772. This region may have functional effects on the transcription, structure and properties of tenascin-C and the alpha-1 chain of type XXVII collagen. ß

We have previously shown that the insertion allele of the angiotensin-converting enzyme (ACE) gene was over-represented in the fastest South-African-born finishers of the South African Ironman Triathlons. As ACE is a component of the skeletal muscle kallikrein-kinin system (KKS), the aim of this study is to determine if there are any further associations between polymorphisms within the BDKRB2 and NOS3 genes, which encode for the KKS components, bradykinin beta(2) receptor and nitric oxide synthase, respectively, and ultra-endurance performance during the Ironman Triathlons. Four-hundred and forty-three male Caucasian triathletes who completed the 2000 and/or 2001 South African Ironman Triathlons and 203 healthy Caucasian male control subjects were genotyped for the functional -9/+9 polymorphism within exon 1 of the BDKRB2 gene and the G894T NOS3 gene polymorphisms. The BDKRB2 -9/-9 genotype occurred at a significantly higher frequency when the triathlete group (27.0%) was compared with the control group (19.3%, P=0.035). When divided into tertiles, there was also a significant linear trend for the NOS3 GG genotype distribution among the fastest (35.0%), middle (40.4%) and slowest (46.9%) finishers (P=0.039). The overall finishing times of the triathletes with an NOS3 GG genotype together with a BDKRB2 +9 allele were significantly slower than those with other genotype combinations (P=0.001). The NOS3/BDKRB2 genotype (beta=-0.150, B=-31.48, P=0.002), together with body mass index and age, accounted for 14.6% of the variance in the overall race time for the triathlon. In conclusion, both the NOS3 and BDKRB2 genes are associated with the actual performance during the Ironman Triathlons.

Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge “Introduction to Bioinformatics” course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery–mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online “question and discussion” forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings.