Co-directional replication-transcription conflicts lead to replication restart

August 24, 2011Head-on encounters between the replication and transcription machineries on the lagging DNA strand can lead to replication fork arrest and genomic instability1, 2. To avoid head-on encounters, most genes, especially essential and highly transcribed genes, are encoded on the leading strand such that transcription and replication are co-directional. Virtually all bacteria have the highly expressed ribosomal RNA genes co-directional with replication3. In bacteria, co-directional encounters seem inevitable because the rate of replication is about 10–20-fold greater than the rate of transcription. However, these encounters are generally thought to be benign2, 4, 5, 6, 7, 8, 9. Biochemical analyses indicate that head-on encounters10 are more deleterious than co-directional encounters8 and that in both situations, replication resumes without the need for any auxiliary restart proteins, at least in vitro. Here we show that in vivo, co-directional transcription can disrupt replication, leading to the involvement of replication restart proteins. We found that highly transcribed rRNA genes are hotspots for co-directional conflicts between replication and transcription in rapidly growing Bacillus subtilis cells. We observed a transcription-dependent increase in association of the replicative helicase and replication restart proteins where head-on and co-directional conflicts occur. Our results indicate that there are co-directional conflicts between replication and transcription in vivo. Furthermore, in contrast to the findings in vitro, the replication restart machinery is involved in vivo in resolving potentially deleterious encounters due to head-on and co-directional conflicts. These conflicts probably occur in many organisms and at many chromosomal locations and help to explain the presence of important auxiliary proteins involved in replication restart and in helping to clear a path along the DNA for the replisome.Biotechnology and Biological Sciences Research Council (Great Britain) (Grant BB/E006450/1)Wellcome Trust (London, England) (Grant 091968/Z/10/Z)National Institutes of Health (U.S.) (Grant GM41934)National Institutes of Health (U.S.) (Postdoctoral Fellowship GM093408)Biotechnology and Biological Sciences Research Council (Great Britain) (Sabbatical Visit

The Association between Depressive Symptoms and Non-Psychiatric Hospitalisation in Older Adults

Findings Hospital events from 1995 to 2006 were obtained from the Dutch National Medical Register and linked to participants of the Longitudinal Aging Study Amsterdam (LASA). Linkage was accomplished in 97% of the LASA sample by matching gender, year of birth and postal code. Depression was measured at each wave point of the LASA study using the Centre for Epidemiologic Studies Depression (CES-D). Hospital outcomes including admission, length of stay, readmission and death while in hospital were recorded at 6, 12 and 24 months intervals after each LASA interview. Generalised Estimating Equation models were also used to investigate potential confounders. After 12 months, 14% of depressed people were hospitalised compared to 10% of non-depressed individuals. There was a 2-fold increase in deaths while in hospital amongst the depressed (0.8% vs 0.4%), who also had longer total length of stay (2.6 days vs 1.4 days). Chronic illnesses and functional limitations had major attenuating effects, but depression was found to be an independent risk factor for length of stay after full adjustment (OR = 1.33, 95% CI: 1.22–1.46 after 12 months). Conclusions Depression in middle and old age is associated with non-psychiatric hospitalisation, longer length of stay and higher mortality in clinical settings. Targeting of this high-risk group could reduce the financial, medical and social burden related to hospital admission

High Degree of Heterogeneity in Alzheimer's Disease Progression Patterns

There have been several reports on the varying rates of progression among Alzheimer's Disease (AD) patients; however, there has been no quantitative study of the amount of heterogeneity in AD. Obtaining a reliable quantitative measure of AD progression rates and their variances among the patients for each stage of AD is essential for evaluating results of any clinical study. The Global Deterioration Scale (GDS) and Functional Assessment Staging procedure (FAST) characterize seven stages in the course of AD from normal aging to severe dementia. Each GDS/FAST stage has a published mean duration, but the variance is unknown. We use statistical analysis to reconstruct GDS/FAST stage durations in a cohort of 648 AD patients with an average follow-up time of 4.78 years. Calculations for GDS/FAST stages 4–6 reveal that the standard deviations for stage durations are comparable with their mean values, indicating the presence of large variations in the AD progression among patients. Such amount of heterogeneity in the course of progression of AD is consistent with the existence of several sub-groups of AD patients, which differ by their patterns of decline

Chronic Helminth Infections Protect Against Allergic Diseases by Active Regulatory Processes

Developed countries are suffering from an epidemic rise in immunologic disorders, such as allergy-related diseases and certain autoimmunities. Several studies have demonstrated a negative association between helminth infections and inflammatory diseases (eg, allergy), providing a strong case for the involvement of helminth infections in this respect. However, some studies point in the opposite direction. The discrepancy may be explained by differences in frequency, dose, time, and type of helminth. In this review, new studies are discussed that may support the concept that chronic helminth infections in particular—but not acute infections—are associated with the expression of regulatory networks necessary for downmodulating allergic immune responses to harmless antigens. Furthermore, different components of regulatory networks are highlighted, such as the role of regulatory T and B cells, modulation of dendritic cells, early innate signals from structural cells (eg, epithelial cells), and their individual contributions to protection against allergic diseases. It is of great interest to define and characterize specific helminth molecules that have profound immunomodulatory capacities as targets for therapeutic application in the treatment or prophylaxis of allergic manifestations

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe