Effects of a training program after surgically treated ankle fracture: a prospective randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Despite conflicting results after surgically treated ankle fractures few studies have evaluated the effects of different types of training programs performed after plaster removal. The aim of this study was to evaluate the effects of a 12-week standardised but individually suited training program (training group) versus usual care (control group) after plaster removal in adults with surgically treated ankle fractures.</p> <p>Methods</p> <p>In total, 110 men and women, 18-64 years of age, with surgically treated ankle fracture were included and randomised to either a 12-week training program or to a control group. Six and twelve months after the injury the subjects were examined by the same physiotherapist who was blinded to the treatment group. The main outcome measure was the Olerud-Molander Ankle Score (OMAS) which rates symptoms and subjectively scored function. Secondary outcome measures were: quality of life (SF-36), timed walking tests, ankle mobility tests, muscle strength tests and radiological status.</p> <p>Results</p> <p>52 patients were randomised to the training group and 58 to the control group. Five patients dropped out before the six-month follow-up resulting in 50 patients in the training group and 55 in the control group. Nine patients dropped out between the six- and twelve-month follow-up resulting in 48 patients in both groups. When analysing the results in a mixed model analysis on repeated measures including interaction between age-group and treatment effect the training group demonstrated significantly improved results compared to the control group in subjects younger than 40 years of age regarding OMAS (p = 0.028), muscle strength in the plantar flexors (p = 0.029) and dorsiflexors (p = 0.030).</p> <p>Conclusion</p> <p>The results of this study suggest that when adjusting for interaction between age-group and treatment effect the training model employed in this study was superior to usual care in patients under the age of 40. However, as only three out of nine outcome measures showed a difference, the beneficial effect from an additional standardised individually suited training program can be expected to be limited. There is need for further studies to elucidate how a training program should be designed to increase and optimise function in patients middle-aged or older.</p> <p>Trial Registration</p> <p>Current Controlled Trials ACTRN12609000327280</p

Reference values of whole-blood fatty acids by age and sex from European children aged 3-8 years

OBJECTIVES: To establish reference values for fatty acids (FA) especially for n-3 and n-6 long-chain polyunsaturated FAs (LC PUFA) in whole-blood samples from apparently healthy 3-8-year-old European children. The whole-blood FA composition was analysed and the age-and sex-specific distribution of FA was determined. DESIGN AND SUBJECTS: Blood samples for FA analysis were taken from 2661 children of the IDEFICS (identification and prevention of dietary-and lifestyle-induced health effects in children and infants) study cohort. Children with obesity (n = 454) and other diseases that are known to alter the FA composition (n = 450) were excluded leaving 1653 participants in the reference population. MEASUREMENTS: The FA composition of whole blood was analysed from blood drops by a rapid, validated gas chromatographic method. RESULTS: Pearson correlation coefficients showed an age-dependent increase of C18:2n-6 and a decrease of C18:1n-9 in a subsample of normal weight boys and girls. Other significant correlations with age were weak and only seen either in boys or in girls, whereas most of the FA did not show any age dependence. For age-dependent n-3 and n-6 PUFA as well as for other FA that are correlated with age (16:0, C18:0 and C18:1n-9) percentiles analysed with the general additive model for location scale and shape are presented. A higher median in boys than in girls was observed for C20:3n-6, C20:4n-6 and C22:4n-6. CONCLUSIONS: Given the reported associations between FA status and health-related outcome, the provision of FA reference ranges may be useful for the interpretation of the FA status of children in epidemiological and clinical studies

Six-week high-intensity exercise program for middle-aged patients with knee osteoarthritis: a randomized controlled trial [ISRCTN20244858]

BACKGROUND: Studies on exercise in knee osteoarthritis (OA) have focused on elderly subjects. Subjects in this study were middle-aged with symptomatic and definite radiographic knee osteoarthritis. The aim was to test the effects of a short-term, high-intensity exercise program on self-reported pain, function and quality of life. METHODS: Patients aged 36–65, with OA grade III (Kellgren & Lawrence) were recruited. They had been referred for radiographic examination due to knee pain and had no history of major knee injury. They were randomized to a twice weekly supervised one hour exercise intervention for six weeks, or to a non-intervention control group. Exercise was performed at ≥ 60% of maximum heart rate (HR max). The primary outcome measure was the Knee injury and Osteoarthritis Outcome Score (KOOS). Follow-up occurred at 6 weeks and 6 months. RESULTS: Sixty-one subjects (mean age 56 (SD 6), 51 % women, mean BMI 29.5 (SD 4.8)) were randomly assigned to intervention (n = 30) or control group (n = 31). No significant differences in the KOOS subscales assessing pain, other symptoms, or function in daily life or in sport and recreation were seen at any time point between exercisers and controls. In the exercise group, an improvement was seen at 6 weeks in the KOOS subscale quality of life compared to the control group (mean change 4.0 vs. -0.7, p = 0.05). The difference between groups was still persistent at 6 months (p = 0.02). CONCLUSION: A six-week high-intensive exercise program had no effect on pain or function in middle-aged patients with moderate to severe radiographic knee OA. Some effect was seen on quality of life in the exercise group compared to the control group

Mechanisms Establishing TLR4-Responsive Activation States of Inflammatory Response Genes

Precise control of the innate immune response is required for resistance to microbial infections and maintenance of normal tissue homeostasis. Because this response involves coordinate regulation of hundreds of genes, it provides a powerful biological system to elucidate the molecular strategies that underlie signal- and time-dependent transitions of gene expression. Comprehensive genome-wide analysis of the epigenetic and transcription status of the TLR4-induced transcriptional program in macrophages suggests that Toll-like receptor 4 (TLR4)-dependent activation of nearly all immediate/early- (I/E) and late-response genes results from a sequential process in which signal-independent factors initially establish basal levels of gene expression that are then amplified by signal-dependent transcription factors. Promoters of I/E genes are distinguished from those of late genes by encoding a distinct set of signal-dependent transcription factor elements, including TATA boxes, which lead to preferential binding of TBP and basal enrichment for RNA polymerase II immediately downstream of transcriptional start sites. Global nuclear run-on (GRO) sequencing and total RNA sequencing further indicates that TLR4 signaling markedly increases the overall rates of both transcriptional initiation and the efficiency of transcriptional elongation of nearly all I/E genes, while RNA splicing is largely unaffected. Collectively, these findings reveal broadly utilized mechanisms underlying temporally distinct patterns of TLR4-dependent gene activation required for homeostasis and effective immune responses

The Fecal Viral Flora of Wild Rodents

The frequent interactions of rodents with humans make them a common source of zoonotic infections. To obtain an initial unbiased measure of the viral diversity in the enteric tract of wild rodents we sequenced partially purified, randomly amplified viral RNA and DNA in the feces of 105 wild rodents (mouse, vole, and rat) collected in California and Virginia. We identified in decreasing frequency sequences related to the mammalian viruses families Circoviridae, Picobirnaviridae, Picornaviridae, Astroviridae, Parvoviridae, Papillomaviridae, Adenoviridae, and Coronaviridae. Seventeen small circular DNA genomes containing one or two replicase genes distantly related to the Circoviridae representing several potentially new viral families were characterized. In the Picornaviridae family two new candidate genera as well as a close genetic relative of the human pathogen Aichi virus were characterized. Fragments of the first mouse sapelovirus and picobirnaviruses were identified and the first murine astrovirus genome was characterized. A mouse papillomavirus genome and fragments of a novel adenovirus and adenovirus-associated virus were also sequenced. The next largest fraction of the rodent fecal virome was related to insect viruses of the Densoviridae, Iridoviridae, Polydnaviridae, Dicistroviriade, Bromoviridae, and Virgaviridae families followed by plant virus-related sequences in the Nanoviridae, Geminiviridae, Phycodnaviridae, Secoviridae, Partitiviridae, Tymoviridae, Alphaflexiviridae, and Tombusviridae families reflecting the largely insect and plant rodent diet. Phylogenetic analyses of full and partial viral genomes therefore revealed many previously unreported viral species, genera, and families. The close genetic similarities noted between some rodent and human viruses might reflect past zoonoses. This study increases our understanding of the viral diversity in wild rodents and highlights the large number of still uncharacterized viruses in mammals

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

Health Behaviours, Socioeconomic Status, and Mortality: Further Analyses of the British Whitehall II and the French GAZEL Prospective Cohorts

Background: Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study.Methods and Findings: We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p < 0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p < 0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results.Conclusions: Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours

CpG binding protein (CFP1) occupies open chromatin regions of active genes, including enhancers and non-CpG islands

Additional file 1. Fig. S1: Analysis of CFP1 binding at individual loci and CpG islands (CGIs). (A-B) Analysis of CFP1 binding at the human α-globin locus in expressing and non-expressing cells. (A) Real-Time PCR analysis of immunoprecipitated chromatin using CFP1 antibody in human erythroblasts (red) and B-lymphocytes (blue). The y-axis represents enrichment over the input DNA, normalised to a control sequence in the human 18S gene. The x-axis represents the positions of Taqman probes used. The coding sequence is represented by the three exons (Promoter/Ex1, Ex2, Ex3) of the α-globin genes. 218 and hBact denote control sequences adjacent to the CpG islands of the human LUC7L (218) and ACTB promoters. Error bars correspond to ± 1 SD from at least two independent ChIPs. (B) Real-Time PCR analysis of immunoprecipitated chromatin using the CFP1 antibody indicated in humanised erythroblasts (normal, +MCS-R2 (left) and mutant, MCS-R2 (right). The y-axis represents enrichment over the input DNA, normalised to a control sequence in the mouse GAPDH gene. CpG Act denotes additional control sequence at the CGI of the mouse ACTB gene. The amplicons highlighted in red represent deleted regions in the humanised mice, for which no PCR signal is observed. Error bars correspond to ± 1 SD from at least two independent ChIPs. (C) CFP1 ChIP signal intensity in the top 200 peaks, by antibody and by cell type. Abcam, ab56035 antibody. Roeder, main antibody used in this study. (D) Analysis of CGI (green) and non-CGI (blue) transcription start sites (1-kb window, centred on TSS). Gene symbols shown with CpG content of individual loci in parentheses. Greek letters represent individual globin genes. Fig. S2: Peak overlaps of CFP1 and marks of active and repressed chromatin in transcription start sites (TSSs). Peaks were detected by MACS2. Venn diagrams show that CFP1 peaks within 1-kb of TSSs are strongly associated with H3K4me3 histone mark and poorly associated with H3K27me3 repressive histone mark. Cell types are (A) ERY and (B) EBV. Public data sets: * NCBI GEO GSE36985, ** NCBI GEO GSE50893. Fig. S3: UCSC tracks showing CFP1 and other ChIP signals in gene loci in erythroblasts (ERY) and EBV-transformed B-lymphoblasts (EBV). Hg38 coordinates for multiple genes, CpG islands (CGI, green boxes), and putative regulatory regions (blue boxes) are shown. CFP1 signals are shown in dark reds, inputs in grey, histone H3 signals in blues and open chromatin marks in greens. All ChIP pileups are scaled to 1x coverage genome-wide and shown in a range 0–50, except CFP1 (Roeder) is shown with extended range and H3K27me3 graphs scaled by 2x. (A) Tissue-specific binding of CFP1 to CGI promoters of tissue-specifically expressed genes. Left (chr16), CGI promoters of active genes in alpha globin locus are CFP1-bound in ERY, and unbound in EBV. Flanking regions are included, with known tissue-specific enhancers. Right (chr6), first seven exons of IRF4 locus, active in EBV and inactive in ERY, with CFP1 binding to CGI promoter in EBV only. (B) CGI promoters of housekeeping genes are CFP1 bound and unmarked by H3K27me3. Left (chr7), ACTB locus. Right (chr16), LUC7L locus. (C) CGI promoter of RHBDF1 locus (chr16) has H3K27me3 mark and the absence of CFP1 binding in both ERY and EBV. Fig. S4: Western blot analysis of CGBP (CFP1) expression in mouse and human erythroid and human lymphoid cell types. Whole cell extracts (20 µg) were loaded in each lane (1) mouse ES, (2) U-MEL, (3) I-MEL, (4) mouse primary erythroblasts and (5) human primary T lymphocytes and (6) human primary erythroblasts and separated on a 10% SDS-polyacrylamide gel. CFP1 antibody was used at a 1:1000 dilution. Fig. S5: Similar cell type-specific CFP1 read depth at CGI TSS of HBA1 gene and non-CGI TSS of HBB gene. Upper two tracks use the main antibody, and second two tracks use the commercial antibody. Coordinates are from the hg38 human genome build. Read depths are averaged in 50 bp bins and normalised to 1x genome-wide coverage. Blue boxes, known regulatory regions; green box, CGI. Fig. S6: Distribution of TrxG components in erythroid cells. Green indicates CGI and blue indicates other putative regulatory regions. All loci transcribed right to left. Pileups are shown scaled to 1x genome coverage, with full scale 0–50x depth. (A) Housekeeping genes ACTB, left (chr7), and LUC7L, right (chr16). (B) β-globin locus (chr11), (C) Non-expressed RHBDF1 locus (chr16). Fig. S7: Overlap of TrxG subunit ChIP peaks in a high-confidence subset of regions. SET1A complexes are represented by CFP1-SET1A colocalisation. MLL1/2 complexes are represented by Menin, and MLL3/4 complexes are represented by UTX, respectively. HCF1 is found in SET1A/B and MLL1/2 complexes, and RBBP5 is a member of SET1A/B and MLL1/2/3/4 complexes. Red outline (4220 peaks) shows strong colocalisation of Menin and CFP1-SET1A, accounting for the vast majority (99.5%) of 4242 CFP1-SET1A and half (50.0%) of 8432 Menin peak regions. Majority (87.0%, 2089/2400 peaks) of HCF1 (blue region) is accounted for by approximately half (49.5%, 2089/4220) of regions of Menin-SET1A-CFP1 colocalisation. Regions where either SET1A-CFP1 or Menin or both are colocalised with HCF1 (blue dashed line) accounts for nearly all (99.6%, 2390/2400) HCF1 regions, suggesting that HCF1 bound to DNA is primarily present as part of SET1A/B or MLL1/2 complexes. Fig. S8: Chromatin accessibility in TSSs and enhancers in erythroid cells as measured by ATAC-seq and DNase-seq. 1x-normalised, input-subtracted signals from ATAC-seq and DNase were averaged in a 2-kb window about TSSs and putative enhancers. Z-score transformed values for ATAC-seq and DNase-seq at a given locus were averaged. Fig. S9: Relationship of CFP1 signal to three predictive factors in top-decile open chromatin regions. A linear combination of CpG density and SET1A and H3K4me3 ChIP signals explains a substantial fraction of variation in CFP1 ChIP signal. Table S1: Bias of CFP1 for CGI TSSs in cell types and gene classes. Table S2: Bias of CFP1 for housekeeping gene TSSs. Table S3: Motifs associated with CFP1 peaks. Table S4: Dependence of CFP1 ChIP signal in erythroid cells on covariates putatively associated with its binding. Table S5: Analysis of variance of CFP1 signal in top-decile open chromatin regions surrounding TSSs and putative enhancers