Cysteine-rich Domain 1 of CD40 Mediates Receptor Self-assembly.

The activation of CD40 on B cells, macrophages, and dendritic cells by its ligand CD154 (CD40L) is essential for the development of humoral and cellular immune responses. CD40L and other TNF superfamily ligands are noncovalent homotrimers, but the form under which CD40 exists in the absence of ligand remains to be elucidated. Here, we show that both cell surface-expressed and soluble CD40 self-assemble, most probably as noncovalent dimers. The cysteine-rich domain 1 (CRD1) of CD40 participated to dimerization and was also required for efficient receptor expression. Modelization of a CD40 dimer allowed the identification of lysine 29 in CRD1, whose mutation decreased CD40 self-interaction without affecting expression or response to ligand. When expressed alone, recombinant CD40-CRD1 bound CD40 with a KD of 0.6 μm. This molecule triggered expression of maturation markers on human dendritic cells and potentiated CD40L activity. These results suggest that CD40 self-assembly modulates signaling, possibly by maintaining the receptor in a quiescent state.

Calculation of correction factors for ionization chamber measurements with small fields in low-density media.

The quantity of interest for high-energy photon beam therapy recommended by most dosimetric protocols is the absorbed dose to water. Thus, ionization chambers are calibrated in absorbed dose to water, which is the same quantity as what is calculated by most treatment planning systems (TPS). However, when measurements are performed in a low-density medium, the presence of the ionization chamber generates a perturbation at the level of the secondary particle range. Therefore, the measured quantity is close to the absorbed dose to a volume of water equivalent to the chamber volume. This quantity is not equivalent to the dose calculated by a TPS, which is the absorbed dose to an infinitesimally small volume of water. This phenomenon can lead to an overestimation of the absorbed dose measured with an ionization chamber of up to 40% in extreme cases. In this paper, we propose a method to calculate correction factors based on the Monte Carlo simulations. These correction factors are obtained by the ratio of the absorbed dose to water in a low-density medium □D(w,Q,V1)(low) averaged over a scoring volume V₁ for a geometry where V₁ is filled with the low-density medium and the absorbed dose to water □D(w,QV2)(low) averaged over a volume V₂ for a geometry where V₂ is filled with water. In the Monte Carlo simulations, □D(w,QV2)(low) is obtained by replacing the volume of the ionization chamber by an equivalent volume of water, according to the definition of the absorbed dose to water. The method is validated in two different configurations which allowed us to study the behavior of this correction factor as a function of depth in phantom, photon beam energy, phantom density and field size.

Do brief alcohol motivational interventions work like we think they do?

BACKGROUND: Questions remain about how brief motivational interventions (BMIs) for unhealthy alcohol use work, and addressing these questions may be important for improving their efficacy. Therefore, we assessed the effects of various characteristics of BMIs on drinking outcomes across 3 randomized controlled trials (RCTs). METHODS: Audio recordings of 314 BMIs were coded. We used the global rating scales of the Motivational Interviewing Skills Code (MISC) 2.1: counselor's acceptance, empathy, and motivational interviewing (MI) spirit, and patient's self-exploration were rated. MI proficiency was defined as counselor's rating scale scores ≥5. We also used the structure, confrontation, and advice subscale scores of the Therapy Process Rating Scale and the Working Alliance Inventory. We examined these process characteristics in interventions across 1 U.S. RCT of middle-aged medical inpatients with unhealthy alcohol use (n = 124) and 2 Swiss RCTs of young men with binge drinking in a nonclinical setting: Swiss-one (n = 62) and Swiss-two (n = 128). We assessed the associations between these characteristics and drinks/d reported by participants 3 to 6 months after study entry. RESULTS: In all 3 RCTs, mean MISC counselor's rating scales scores were consistent with MI proficiency. In overdispersed Poisson regression models, most BMI characteristics were not significantly associated with drinks/d in follow-up. In the U.S. RCT, confrontation and self-exploration were associated with more drinking. Giving advice was significantly associated with less drinking in the Swiss-one RCT. Contrary to expectations, MI spirit was not consistently associated with drinking across studies. CONCLUSIONS: Across different populations and settings, intervention characteristics viewed as central to efficacious BMIs were neither robust nor consistent predictors of drinking outcome. Although there may be alternative reasons why the level of MI processes was not predictive of outcomes in these studies (limited variability in scores), efforts to understand what makes BMIs efficacious may require attention to factors beyond intervention process characteristics typically examined.

Steady-state expression of self-regulated genes.

MOTIVATION: Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations. METHODOLOGY: In this study, we provide new exact formulas and efficient numerical algorithms for computing/modeling the steady-state of a class of self-regulated genes, and we use it to model/compute the stochastic expression of a gene of interest in an engineered network introduced in mammalian cells. The behavior of the genetic network is then analyzed experimentally in living cells. RESULTS: Stochastic models often reveal counter-intuitive experimental behaviors, and we find that this genetic architecture displays a unimodal behavior in mammalian cells, which was unexpected given its known bimodal response in unicellular organisms. We provide a molecular rationale for this behavior, and we implement it in the mathematical picture to explain the experimental results obtained from this network.