Description: Objective STK33 has been reported to play an important role in cancer cell proliferation. We investigated the role of STK33 in hepatocellular carcinoma (HCC) and its underlying mechanisms. Design 251 patients with HCC were analysed for association between STK33 expression and clinical stage and survival rate. Tamoxifen (TAM)-inducible, hepatocyte-specific STK33 transgenic and knockout mice models were used to study the role of STK33 in liver tumorigenesis. HCC cell lines were used to study the role of STK33 in cell proliferation in vitro and in vivo. Results STK33 expression was found to be frequently upregulated in patients with HCC. Significant associations were found between increased expression of STK33 and advanced HCC staging and shorter disease-free survival of patients. Overexpression of STK33 increased HCC cell proliferation both in vitro and in vivo, whereas suppression of STK33 inhibited this effect. Using a TAM-inducible, hepatocyte-specific STK33 transgenic mouse model, we found that overexpression of STK33 resulted in increased hepatocyte proliferation, leading to tumour cell burst. Using a TAM-inducible, hepatocyte-specific STK33 knockout mouse model, we found that, when subjected to the diethylnitrosamine (DEN) liver cancer bioassay, STK33KO flox/flox, Alb-ERT2-Cre mice exhibited a markedly lower incidence of tumour formation compared with control mice. The underlying mechanism may be that STK33 binds directly to c-Myc and increases its transcriptional activity. In particular, the C-terminus of STK33 blocks STK33/c-Myc association, downregulates HCC cell proliferation, and reduces DEN-induced liver tumour cell number and tumour size. Conclusions STK33 plays an essential role in hepatocellular proliferation and liver tumorigenesis. The C-terminus of STK33 could be a potential therapeutic target in the treatment of patients with STK33-overexpressed HCC.

Description: Background Neighbourhood quality has been connected with an array of health issues, but neighbourhood research has been limited by the lack of methods to characterise large geographical areas. This study uses innovative computer vision methods and a new big data source of street view images to automatically characterise neighbourhood built environments. Methods A total of 430 000 images were obtained using Google’s Street View Image API for Salt Lake City, Chicago and Charleston. Convolutional neural networks were used to create indicators of street greenness, crosswalks and building type. We implemented log Poisson regression models to estimate associations between built environment features and individual prevalence of obesity and diabetes in Salt Lake City, controlling for individual-level and zip code-level predisposing characteristics. Results Computer vision models had an accuracy of 86%–93% compared with manual annotations. Charleston had the highest percentage of green streets (79%), while Chicago had the highest percentage of crosswalks (23%) and commercial buildings/apartments (59%). Built environment characteristics were categorised into tertiles, with the highest tertile serving as the referent group. Individuals living in zip codes with the most green streets, crosswalks and commercial buildings/apartments had relative obesity prevalences that were 25%–28% lower and relative diabetes prevalences that were 12%–18% lower than individuals living in zip codes with the least abundance of these neighbourhood features. Conclusion Neighbourhood conditions may influence chronic disease outcomes. Google Street View images represent an underused data resource for the construction of built environment features.

Description: We read with interest the paper by Todt et al 1 concerning the mutagenesis of Hepatitis E virus (HEV) caused by ribavirin treatment. HEV is a major cause of acute hepatitis worldwide and lacks a specific treatment. 1 2 It replicates in many extrahepatic sites (spleen, kidney, brain and muscle 3–5 ), but whether the testis is included is unknown. Active HEV has been detected in body fluids (blood, 2 urine 4 and milk 6 ), but no report exists for semen. Thus, HEV prevalence in the semen of infertile males (n=185) sexually abstinent for at least 2 days was investigated by reverse transcriptase-PCR. Ethical approval was obtained from the Institutional Ethics Committee. Unexpectedly, 28.11% (52/185) of the males were HEV RNA positive (HEV RNA+; detectable HEV ORF1 and ORF2 were considered as HEV RNA+, figure 1A )...

Description: Objective Gastric cancer (GC) is a deadly malignancy for which new therapeutic strategies are needed. Three transcription factors, KLF5, GATA4 and GATA6, have been previously reported to exhibit genomic amplification in GC. We sought to validate these findings, investigate how these factors function to promote GC, and identify potential treatment strategies for GCs harbouring these amplifications. Design KLF5 , GATA4 and GATA6 copy number and gene expression was examined in multiple GC cohorts. Chromatin immunoprecipitation with DNA sequencing was used to identify KLF5/GATA4/GATA6 genomic binding sites in GC cell lines, and integrated with transcriptomics to highlight direct target genes. Phenotypical assays were conducted to assess the function of these factors in GC cell lines and xenografts in nude mice. Results KLF5 , GATA4 and GATA6 amplifications were confirmed in independent GC cohorts. Although factor amplifications occurred in distinct sets of GCs, they exhibited significant mRNA coexpression in primary GCs, consistent with KLF5/GATA4/GATA6 cross-regulation. Chromatin immunoprecipitation with DNA sequencing revealed a large number of genomic sites co-occupied by KLF5 and GATA4/GATA6, primarily located at gene promoters and exhibiting higher binding strengths. KLF5 physically interacted with GATA factors, supporting KLF5/GATA4/GATA6 cooperative regulation on co-occupied genes. Depletion and overexpression of these factors, singly or in combination, reduced and promoted cancer proliferation, respectively, in vitro and in vivo. Among the KLF5/GATA4/GATA6 direct target genes relevant for cancer development, one target gene, HNF4α , was also required for GC proliferation and could be targeted by the antidiabetic drug metformin, revealing a therapeutic opportunity for KLF5/GATA4/GATA6 amplified GCs. Conclusions KLF5/GATA4/GATA6 may promote GC development by engaging in mutual crosstalk, collaborating to maintain a pro-oncogenic transcriptional regulatory network in GC cells.