The effect of a selective CXCR2 antagonist (AZD5069) on human blood neutrophil count and innate immune functions.

Abstract AIMS: The aim of the present study was to investigate whether selective antagonism of the cysteine-X-cysteine chemokine receptor-2 (CXCR2) receptor has any adverse effects on the key innate effector functions of human neutrophils for defence against microbial pathogens. METHODS: In a double-blind, crossover study, 30 healthy volunteers were randomized to treatment with the CXCR2 antagonist AZD5069 (100 mg) or placebo, twice daily orally for 6 days. The peripheral blood neutrophil count was assessed at baseline, daily during treatment and in response to exercise challenge and subcutaneous injection of granulocyte-colony stimulating factor (G-CSF). Neutrophil function was evaluated by phagocytosis of Escherichia coli and by the oxidative burst response to E. coli. RESULTS: AZD5069 treatment reversibly reduced circulating neutrophil count from baseline by a mean [standard deviation (SD)] of -1.67 (0.67) ×10(9) l(-1) vs. 0.19 (0.78) ×10(9) l(-1) for placebo on day 2, returning to baseline by day 7 after the last dose. Despite low counts on day 4, a 10-min exercise challenge increased absolute blood neutrophil count, but the effect with AZD5069 was smaller and not sustained, compared with placebo treatment. Subcutaneous G-CSF on day 5 caused a substantial increase in blood neutrophil count in both placebo- and AZD5069-treated subjects. Superoxide anion production in E. coli-stimulated neutrophils and phagocytosis of E. coli were unaffected by AZD5069 (P = 0.375, P = 0.721, respectively vs. baseline, Day 4). AZD5069 was well tolerated. CONCLUSIONS: CXCR2 antagonism did not appear adversely to affect the mobilization of neutrophils from bone marrow into the peripheral circulation, phagocytosis or the oxidative burst response to bacterial pathogens. This supports the potential of CXCR2 antagonists as a treatment option for diseases in which neutrophils play a pathological role.

Image quality optimization, via application of contextual contrast sensitivity and discrimination functions

What is the best luminance contrast weighting-function for image quality optimization? Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. We suggest contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant. In this investigation, test images are weighted with a traditional CSF, cCSF, cVPF and a constant function. Controlled mutations of these functions are also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness are then assessed in two-alternative forced-choice psychophysical tests. We show that maximal quality for our test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.

Program slice metrics and their potential role in DSL design, position paper

The advantages a DSL and the benefits its use potentially brings imply that informed decisions on the design of a domain specific language are of paramount importance for its use. We believe that the foundations of such decisions should be informed by analysis of data empirically collected from systems to highlight salient features that should then form the basis of a DSL. To support this theory, we describe an empirical study of a large OSS called Barcode, written in C, and from which we collected two well-known 'slice' based metrics. We analyzed multiple versions of the system and sliced its functions in three separate ways (i.e., input, output and global variables). The purpose of the study was to try and identify sensitivities and traits in those metrics that might inform features of a potential slice-based DSL. Results indicated that cohesion was adversely affected through the use of global variables and that appreciation of the role of function inputs and outputs can be revealed through slicing. The study presented is motivated primarily by the problems with current tools and interfaces experienced directly by the authors in extracting slicing data and the need to promote the benefits that analysis of slice data and slicing in general can offer.

What is universal and what differs in language development?

Goldin-Meadow (2015) presents an exceptional synthesis of work from studies of children acquiring language under variable circumstances of input or processing abilities. Deaf children who acquire homesign without any well- formed model from which to learn language represent a powerful example. Goldin-Meadow argues that the resilient properties of language that nevertheless emerge include simple syntactic structures, hierarchical organisa- tion, markers modulating the meaning of sentences, and social-communicative functions. Among the fragile or input-dependent properties are the orders that the language follows, the parts into which words are decomposed, and the features that distinguish nominals from predicates. Separation of these two types of properties poses questions concerning the innate constraints on language acquisition (perhaps these equate to the resilient properties) and con‐ cerning the specificity of processes to language (e.g., whether properties such as hierarchical organisation are specific to language or originate in the structure of thought). The study of the resilient properties of human language in the face of adversity and the relation of these properties to the information that is encoded in the human genome represent a research strategy that draws inferences about species universals (properties that all humans share) from data about individual differences (IDs; factors that make humans different from one another). In the following, we suggest three reasons to be cautious about this approach.