Prolonged and tunable residence time using reversible covalent kinase inhibitors.

Drugs with prolonged on-target residence times often show superior efficacy, yet general strategies for optimizing drug-target residence time are lacking. Here we made progress toward this elusive goal by targeting a noncatalytic cysteine in Bruton's tyrosine kinase (BTK) with reversible covalent inhibitors. Using an inverted orientation of the cysteine-reactive cyanoacrylamide electrophile, we identified potent and selective BTK inhibitors that demonstrated biochemical residence times spanning from minutes to 7 d. An inverted cyanoacrylamide with prolonged residence time in vivo remained bound to BTK for more than 18 h after clearance from the circulation. The inverted cyanoacrylamide strategy was further used to discover fibroblast growth factor receptor (FGFR) kinase inhibitors with residence times of several days, demonstrating the generalizability of the approach. Targeting of noncatalytic cysteines with inverted cyanoacrylamides may serve as a broadly applicable platform that facilitates 'residence time by design', the ability to modulate and improve the duration of target engagement in vivo

Mapping In Vivo Tumor Oxygenation within Viable Tumor by 19F-MRI and Multispectral Analysis

AbstractQuantifying oxygenation in viable tumor remains a major obstacle toward a better understanding of the tumor microenvironment and improving treatment strategies. Current techniques are often complicated by tumor heterogeneity. Herein, a novel in vivo approach that combines 19F magnetic resonance imaging (19F-MRI)R1 mapping with diffusionbased multispectral (MS) analysis is introduced. This approach restricts the partial pressure of oxygen (pO2) measurements to viable tumor, the tissue of therapeutic interest. The technique exhibited sufficient sensitivity to detect a breathing gas challenge in a xenograft tumor model, and the hypoxic region measured by MS 19F-MRI was strongly correlated with histologic estimates of hypoxia. This approach was then applied to address the effects of antivascular agents on tumor oxygenation, which is a research question that is still under debate. The technique was used to monitor longitudinal pO2 changes in response to an antibody to vascular endothelial growth factor (B20.4.1.1) and a selective dual phosphoinositide 3-kinase/mammalian target of rapamycin inhibitor (GDC-0980). GDC-0980 reduced viable tumor pO2 during a 3-day treatment period, and a significant reduction was also produced by B20.4.1.1. Overall, this method provides an unprecedented view of viable tumor pO2 and contributes to a greater understanding of the effects of antivascular therapies on the tumor's microenvironment

From Solvent-Free Microspheres to Bioactive Gradient Scaffolds

A solvent-free microsphere sintering technique was developed to fabricate scaffolds with pore size gradient for tissue engineering applications. Poly(D,L-Lactide) microspheres were fabricated through an emulsification method where TiO2 nanoparticles were employed both as particulate emulsifier in the preparation procedure and as surface modification agent to improve bioactivity of the scaffolds. A fine-tunable pore size gradient was achieved with a pore volume of 30±2.6%. SEM, EDX, XRD and FTIR analyses all confirmed the formation of bone-like apatite at the 14th day of immersion in Simulated Body Fluid (SBF) implying the ability of our scaffolds to bond to living bone tissue. In vitro examination of the scaffolds showed progressive activity of the osteoblasts on the scaffold with evidence of increase in its mineral content. The bioactive scaffold developed in this study has the potential to be used as a suitable biomaterial for bone tissue engineering and hard tissue regeneration

British Society for Sexual Medicine Guidelines on Adult Testosterone Deficiency, With Statements for UK Practice

BACKGROUND: Testosterone deficiency (TD) is an increasingly common problem with significant health implications, but its diagnosis and management can be challenging. AIM: To review the available literature on TD and provide evidence-based statements for UK clinical practice. METHODS: Evidence was derived from Medline, EMBASE, and Cochrane searches on hypogonadism, testosterone (T) therapy, and cardiovascular safety from May 2005 to May 2015. Further searches continued until May 2017. OUTCOMES: To provide a guideline on diagnosing and managing TD, with levels of evidence and grades of recommendation, based on a critical review of the literature and consensus of the British Society of Sexual Medicine panel. RESULTS: 25 statements are provided, relating to 5 key areas: screening, diagnosis, initiating T therapy, benefits and risks of T therapy, and follow-up. 7 statements are supported by level 1, 8 by level 2, 5 by level 3, and 5 by level 4 evidence. CLINICAL IMPLICATIONS: To help guide UK practitioners on effectively diagnosing and managing primary and age-related TD. STRENGTHS AND LIMITATIONS: A large amount of literature was carefully sourced and reviewed, presenting the best evidence available at the time. However, some statements provided are based on poor-quality evidence. This is a rapidly evolving area of research and recommendations are subject to change. Guidelines can never replace clinical expertise when making treatment decisions for individual patients, but rather help to focus decisions and take personal values and preferences and individual circumstances into account. Many issues remain controversial, but in the meantime, clinicians need to manage patient needs and clinical expectations armed with the best clinical evidence and the multidisciplinary expert opinion available. CONCLUSION: Improving the diagnosis and management of TD in adult men should provide somatic, sexual, and psychological benefits and subsequent improvements in quality of life. Hackett G, Kirby M, Edwards D, et al. British Society for Sexual Medicine Guidelines on Adult Testosterone Deficiency, With Statements for UK Practice. J Sex Med 2017;14:1504-1523

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense