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Background: Modern gene therapy methods have limited control over where a therapeutic viral vector inserts into the host genome. Vector integration can activate local gene expression, which can cause cancer if the vector inserts near an oncogene. Viral integration hot-spots or 'common insertion sites' (CIS) are scrutinized to evaluate and predict patient safety. CIS are typically defined by a minimum density of insertions (such as 2-4 within a 30-100 kb region), which unfortunately depends on the total number of observed VIS. This is problematic for comparing hot-spot distributions across data sets and patients, where the VIS numbers may vary.Results: We develop two new methods for defining hot-spots that are relatively independent of data set size. Both methods operate on distributions of VIS across consecutive 1 Mb 'bins' of the genome. The first method 'z-threshold' tallies the number of VIS per bin, converts these counts to z-scores, and applies a threshold to define high density bins. The second method 'BCP' applies a Bayesian change-point model to the z-scores to define hot-spots. The novel hot-spot methods are compared with a conventional CIS method using simulated data sets and data sets from five published human studies, including the X-linked ALD (adrenoleukodystrophy), CGD (chronic granulomatous disease) and SCID-X1 (X-linked severe combined immunodeficiency) trials. The BCP analysis of the human X-linked ALD data for two patients separately (774 and 1627 VIS) and combined (2401 VIS) resulted in 5-6 hot-spots covering 0.17-0.251% of the genome and containing 5.56-7.74% of the total VIS. In comparison, the CIS analysis resulted in 12-110 hot-spots covering 0.018-0.246% of the genome and containing 5.81-22.7% of the VIS, corresponding to a greater number of hot-spots as the data set size increased. Our hot-spot methods enable one to evaluate the extent of VIS clustering, and formally compare data sets in terms of hot-spot overlap. Finally, we show that the BCP hot-spots from the repopulating samples coincide with greater gene and CpG island density than the median genome density.Conclusions: The z-threshold and BCP methods are useful for comparing hot-spot patterns across data sets of disparate sizes. The methodology and software provided here should enable one to study hot-spot conservation across a variety of VIS data sets and evaluate vector safety for gene therapy trials. © 2011 Presson et al; licensee BioMed Central Ltd.

Background and Purpose: Chronic obstructive pulmonary disease (COPD) is proposed to hasten lung aging. Erythromycin protects against oxidative stress and inflammatory responses. However, the potential anti-senescence effect of erythromycin remains disclosed. In the present study, we investigated whether erythromycin influenced oxidative stress-induced cellular senescence and investigated its related mechanisms. Methods: A cigarrete smoke (CS) -induced emphysema mouse model and a H 2 O 2 -induced premature senescence model in human bronchial epithelial cell line (BEAS-2B) were established. Senescence-related markers (P53, P21 and SA-β-Gal activity), and levels of oxidative stress biomarkers (MDA, SOD and ROS) were measured. Additionally, cells were pretreated with rapamycin (mTOR inhibitor) or erythromycin, and the expression levels of components of the PI3K-mTOR signaling pathway were measured in BEAS-2B cells. Results: Exposed to H 2 O 2 , increased SA-β-gal activity was observed in BEAS-2B cells suggesting premature senescence. Erythromycin inhibited the expression of P53 and P21 in the CS-induced emphysema mouse model. MDA levels significantly increased and SOD levels decreased in the CS-exposed mice and H 2 O 2 -induced BEAS-2B cells. Rapamycin and erythromycin significantly suppressed the expression of P53 and P21. Additionally, rapamycin and erythromycin inhibited the PI3K-mTOR signaling pathway. Conclusion: Our findings suggest that erythromycin ameliorates oxidative stress-induced cellular senescence via the PI3K-mTOR signaling pathway. Hence, we establish a theoretical foundation for the clinical application of erythromycin for COPD prevention and treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Xiaofei, Tingting, Xuan and Zhiyi.)

Objective: To investigate the short-term efficacy and safety outcomes following a sequential treatment with clearing heat and eliminating phlegm (CHEP) formula and tonifying Qi and activating blood circulation (TQABC) formula in patients with acute ischemic stroke (AIS) within a 72 h time window., Methods: In this randomized, multicenter, double-blinded, placebo-controlled trial, 500 participants will be randomly assigned in a ratio of 1∶1 to the CHEP+ TQABC group or control group. In addition to guideline-based standard medical care, participants in the treatment group will receive the CHEP formula for the first 5 consecutive days followed by the TQABC formula for another 10 consecutive days, while those in the control group will receive CHEP formula placebo and TQABC formula placebo consecutively. The primary outcome measure will be the comparison of the change in the National Institutes of Health Stroke Scale score from baseline to 15 days after randomization. The secondary outcome measures will include the scores on the modified Rankin Scale, Barthel Index, Patient-Reported Outcomes, TCM symptom pattern (Zheng-hou) evaluation Scale, and the incidence of in-hospital complications. Safety assessment will include the physical examination, laboratory detection, any adverse events or serious adverse events, and the proportion of any complications during hospitalization., Discussion: The results of this study will provide objective and scientific data with which to assess the efficacy and safety of a sequential treatment based on "integrating disease and symptom pattern" for patients with AIS.