Optimality of mutation and selection in germinal centers

The population dynamics theory of B cells in a typical germinal center could play an important role in revealing how affinity maturation is achieved. However, the existing models encountered some conflicts with experiments. To resolve these conflicts, we present a coarse-grained model to calculate the B cell population development in affinity maturation, which allows a comprehensive analysis of its parameter space to look for optimal values of mutation rate, selection strength, and initial antibody-antigen binding level that maximize the affinity improvement. With these optimized parameters, the model is compatible with the experimental observations such as the ~100-fold affinity improvements, the number of mutations, the hypermutation rate, and the "all or none" phenomenon. Moreover, we study the reasons behind the optimal parameters. The optimal mutation rate, in agreement with the hypermutation rate in vivo, results from a tradeoff between accumulating enough beneficial mutations and avoiding too many deleterious or lethal mutations. The optimal selection strength evolves as a balance between the need for affinity improvement and the requirement to pass the population bottleneck. These findings point to the conclusion that germinal centers have been optimized by evolution to generate strong affinity antibodies effectively and rapidly. In addition, we study the enhancement of affinity improvement due to B cell migration between germinal centers. These results could enhance our understandings to the functions of germinal centers.Comment: 5 figures in main text, and 4 figures in Supplementary Informatio

Performing meta-analysis with incomplete statistical information in clinical trials

<p>Abstract</p> <p>Background</p> <p>Results from clinical trials are usually summarized in the form of sampling distributions. When full information (mean, SEM) about these distributions is given, performing meta-analysis is straightforward. However, when some of the sampling distributions only have mean values, a challenging issue is to decide how to use such distributions in meta-analysis. Currently, the most common approaches are either ignoring such trials or for each trial with a missing SEM, finding a similar trial and taking its SEM value as the missing SEM. Both approaches have drawbacks. As an alternative, this paper develops and tests two new methods, the first being the prognostic method and the second being the interval method, to estimate any missing SEMs from a set of sampling distributions with full information. A merging method is also proposed to handle clinical trials with partial information to simulate meta-analysis.</p> <p>Methods</p> <p>Both of our methods use the assumption that the samples for which the sampling distributions will be merged are randomly selected from the same population. In the prognostic method, we predict the missing SEMs from the given SEMs. In the interval method, we define intervals that we believe will contain the missing SEMs and then we use these intervals in the merging process.</p> <p>Results</p> <p>Two sets of clinical trials are used to verify our methods. One family of trials is on comparing different drugs for reduction of low density lipprotein cholesterol (LDL) for Type-2 diabetes, and the other is about the effectiveness of drugs for lowering intraocular pressure (IOP). Both methods are shown to be useful for approximating the conventional meta-analysis including trials with incomplete information. For example, the meta-analysis result of Latanoprost versus Timolol on IOP reduction for six months provided in <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> was 5.05 ± 1.15 (Mean ± SEM) with full information. If the last trial in this study is assumed to be with partial information, the traditional analysis method for dealing with incomplete information that ignores this trial would give 6.49 ± 1.36 while our prognostic method gives 5.02 ± 1.15, and our interval method provides two intervals as Mean ∈ [4.25, 5.63] and SEM ∈ [1.01, 1.24].</p> <p>Conclusion</p> <p>Both the prognostic and the interval methods are useful alternatives for dealing with missing data in meta-analysis. We recommend clinicians to use the prognostic method to predict the missing SEMs in order to perform meta-analysis and the interval method for obtaining a more cautious result.</p

Reappraisal of Metformin Efficacy in the Treatment of Type 2 Diabetes: A Meta-Analysis of Randomised Controlled Trials

Catherine Cornu and colleagues performed a meta-analysis of randomised controlled trials of metformin efficacy on cardiovascular morbidity or mortality in patients with type 2 diabetes and showed that although metformin is considered the gold standard, its benefit/risk ratio remains uncertain

How and why community hospital clinicians document a positive screen for intimate partner violence: a cross-sectional study

BACKGROUND: This two-part study examines primary care clinicians' chart documentation and attitudes when confronted by a positive waiting room screen for intimate partner violence (IPV). METHODS: Patients at community hospital-affiliated health centers completed a screening questionnaire in waiting rooms that primary care providers (PCPs) were subsequently given at the time of the visit. We first reviewed the medical records of patients who screened positive for IPV, evaluating the presence and quality of documentation. Next we administered a survey to PCPs that measured their knowledge, attitudes and practice regarding IPV. RESULTS: Seventy-two percent of charts contained some documentation of IPV, however only 10% contained both a referral and safety plan. PCPs were more likely to refer patients (p < .05) who screened positively for mood or anxiety disorders, disclosed that they feared for their safety or were economically disadvantaged. Those that feared for their safety or endorsed mood or anxiety disorders were more likely to have notation of a safety plan in their records. When surveyed, 81.6% of clinicians strongly agreed that it is their role to inquire about IPV, but only 68% expressed confidence in their ability to manage it. In contrast, 93% expressed confidence in managing depression. Sixty-seven percent identified time constraints as a barrier to care. Predictors of PCP confidence in treating patients who have experienced IPV (p < .05) included hours of recent training and clinical experience with IPV. CONCLUSION: Mandatory waiting room screening for IPV does not result in high levels of referral or safety planning by PCPs. Despite the implementation of a screening process, clinicians lack confidence and time to address IPV in their patient populations suggesting that alternative methods of training and supporting PCPs need to be developed

Epac inhibits migration and proliferation of human prostate carcinoma cells

BACKGROUND: It was recently found that cAMP mediates protein kinase A-independent effects through Epac proteins. The aim of this study was to investigate the role of Epac in migration and proliferation of prostate carcinoma cells. METHODS: The effect of Epac activation was determined by [(3)H] thymidine incorporation and scratch assays in PC-3 and DU 145 cells. Furthermore, cytoskeletal integrity was analysed by phalloidin staining. The participation of intracellular Epac effectors such as mitogen-activated protein (MAP) kinases, Rap1- and Rho-GTPases was determined by immunoblotting and pull-down assay. RESULTS: The specific Epac activator 8-pCPT-2'-O-Me-cAMP (8-pCPT) interfered with cytoskeletal integrity, reduced DNA synthesis, and migration. Although 8-pCPT activated Rap1, it inhibited MAP kinase signalling and RhoA activation. These findings were translated into functional effects such as inhibition of mitogenesis, cytoskeletal integrity, and migration. CONCLUSION: In human prostate carcinoma cells, Epac inhibits proliferative and migratory responses likely because of inhibition of MAP kinase and RhoA signalling pathways. Therefore, Epac might represent an attractive therapeutic target in the treatment of prostate cancer. British Journal of Cancer (2009) 101, 2038-2042. doi: 10.1038/sj.bjc.6605439 www.bjcancer.com Published online 17 November 2009 (C) 2009 Cancer Research U

Tumoral CD105 is a novel independent prognostic marker for prognosis in clear-cell renal cell carcinoma

International audienceBackground: Angiogenesis is essential for tumour growth and metastasis. There are conflicting reports as to whether microvessel density (MVD) using the endothelial marker CD105 (cluster of differentiation molecule 105) in clear-cell renal cell carcinomas (ccRCC) is associated with prognosis. Recently, CD105 has been described as a RCC cancer stem cell marker.Methods: A total of 102 ccRCC were analysed. Representative tumour sections were stained for CD105. Vascularity (endothelial CD105) was quantified by MVD. The immunohistochemistry analysis detected positive (if present) or negative (if absent) CD105 tumoral staining. This retrospective population-based study was evaluated using Kaplan–Meier method, t-test and Cox proportional hazard model.Results: We found that the expression of endothelial CD105 (MVD) negatively correlated with nuclear grade (P<0.001), tumour stage (P<0.001) and Leibovitch score (P<0.001), whereas the expression of tumoral CD105 positively correlated with these three clinicopathological factors (P<0.001). In multivariate analysis, tumoral CD105 was found to be an independent predictor of poor overall survival (P=0.002).Conclusions: We have shown for the first time that tumoral CD105 is an independent predictive marker for death risk and unfavourable prognosis in patients with ccRCC after curative resection

Petunia Floral Defensins with Unique Prodomains as Novel Candidates for Development of Fusarium Wilt Resistance in Transgenic Banana Plants

Antimicrobial peptides are a potent group of defense active molecules that have been utilized in developing resistance against a multitude of plant pathogens. Floral defensins constitute a group of cysteine-rich peptides showing potent growth inhibition of pathogenic filamentous fungi especially Fusarium oxysporum in vitro. Full length genes coding for two Petunia floral defensins, PhDef1 and PhDef2 having unique C- terminal 31 and 27 amino acid long predicted prodomains, were overexpressed in transgenic banana plants using embryogenic cells as explants for Agrobacterium–mediated genetic transformation. High level constitutive expression of these defensins in elite banana cv. Rasthali led to significant resistance against infection of Fusarium oxysporum f. sp. cubense as shown by in vitro and ex vivo bioassay studies. Transgenic banana lines expressing either of the two defensins were clearly less chlorotic and had significantly less infestation and discoloration in the vital corm region of the plant as compared to untransformed controls. Transgenic banana plants expressing high level of full-length PhDef1 and PhDef2 were phenotypically normal and no stunting was observed. In conclusion, our results suggest that high-level constitutive expression of floral defensins having distinctive prodomains is an efficient strategy for development of fungal resistance in economically important fruit crops like banana