Cross-cultural adaptation into Punjabi of the English version of the Hospital Anxiety and Depression Scale

BACKGROUND: We wanted to use a Punjabi version of the Hospital Anxiety and Depression Scale (HADS) to enable non-English speaking patients to participate in a clinical trial. The aim of the study was to translate and validate the Hospital Anxiety and Depression Scale into Punjabi. METHODS: The HADS was translated into Punjabi by a multidisciplinary team, verified against the original version, and administered to 73 bilingual patients attending an outpatient clinic. RESULTS: One sample t-tests and the Bland-Altman plots demonstrated acceptable linguistic agreement between the two versions of the HADS. Spearman's rank-order correlation coefficients (p < 0.0001) demonstrate excellent conceptual agreement between each item and its corresponding subscale score, for both versions. Concordance rates revealed that the Punjabi HADS adequately identified borderline cases of anxiety (80.8%), definite cases of anxiety (91.8%) and depression (91.8%), but was less reliable in identifying borderline cases of depression (65.8%). Cronbach alpha coefficients revealed high levels of internal consistency for both the Punjabi and English versions (0.81 and 0.86 for anxiety and 0.71 and 0.85 for depression, respectively). CONCLUSION: The Punjabi HADS is an acceptable, reliable and valid measure of anxiety and depression among physically ill Punjabi speaking people in the United Kingdom

Structure and Evolution of Streptomyces Interaction Networks in Soil and In Silico

Soil grains harbor an astonishing diversity of Streptomyces strains producing diverse secondary metabolites. However, it is not understood how this genotypic and chemical diversity is ecologically maintained. While secondary metabolites are known to mediate signaling and warfare among strains, no systematic measurement of the resulting interaction networks has been available. We developed a high-throughput platform to measure all pairwise interactions among 64 Streptomyces strains isolated from several individual grains of soil. We acquired more than 10,000 time-lapse movies of colony development of each isolate on media containing compounds produced by each of the other isolates. We observed a rich set of such sender-receiver interactions, including inhibition and promotion of growth and aerial mycelium formation. The probability that two random isolates interact is balanced; it is neither close to zero nor one. The interactions are not random: the distribution of the number of interactions per sender is bimodal and there is enrichment for reciprocity—if strain A inhibits or promotes B, it is likely that B also inhibits or promotes A. Such reciprocity is further enriched in strains derived from the same soil grain, suggesting that it may be a property of coexisting communities. Interactions appear to evolve rapidly: isolates with identical 16S rRNA sequences can have very different interaction patterns. A simple eco-evolutionary model of bacteria interacting through antibiotic production shows how fast evolution of production and resistance can lead to the observed statistical properties of the network. In the model, communities are evolutionarily unstable—they are constantly being invaded by strains with new sets of interactions. This combination of experimental and theoretical observations suggests that diverse Streptomyces communities do not represent a stable ecological state but an intrinsically dynamic eco-evolutionary phenomenon

Short interfering RNA against STAT1 attenuates cisplatin-induced ototoxicity in the rat by suppressing inflammation

Cisplatin is widely used for treating various solid tumors. However, this drug produces dose-limiting ototoxicity and nephrotoxicity, which significantly reduce the quality of life of cancer patients. While nephrotoxicity could be alleviated by diuresis, there is currently no approved treatment for hearing loss. Previous studies show that the ROS and inflammation are major contributors to cisplatin-induced hearing loss. In this study, we show that ROS trigger the inflammatory process in the cochlea by activating signal transducer and activator of transcription-1 (STAT1). Activation of STAT1 activation was dependent on ROS generation through NOX3 NADPH oxidase, knockdown of which by siRNA reduced STAT1 activation. Moreover, STAT1 siRNA protected against activation of p53, reduced apoptosis, reduced damage to OHCs and preserved hearing in rats. STAT1 siRNA attenuated the increase in inflammatory mediators, such as TNF-α, inhibition of which protected cells from cisplatin-mediated apoptosis. Finally, we showed that trans-tympanic administration of etanercept, a TNF-α antagonist, protected against OHC damage and cisplatin-induced hearing loss. These studies suggest that controlling inflammation by inhibition of STAT1-dependent pathways in the cochlea could serve as an effective approach to treat cisplatin ototoxicity and improve the overall quality of life for cancer patients

Coupling changes in cell shape to chromosome segregation

Animal cells undergo dramatic changes in shape, mechanics and polarity as they progress through the different stages of cell division. These changes begin at mitotic entry, with cell–substrate adhesion remodelling, assembly of a cortical actomyosin network and osmotic swelling, which together enable cells to adopt a near spherical form even when growing in a crowded tissue environment. These shape changes, which probably aid spindle assembly and positioning, are then reversed at mitotic exit to restore the interphase cell morphology. Here, we discuss the dynamics, regulation and function of these processes, and how cell shape changes and sister chromatid segregation are coupled to ensure that the daughter cells generated through division receive their fair inheritance

A review of data needed to parameterize a dynamic model of measles in developing countries

<p>Abstract</p> <p>Background</p> <p>Dynamic models of infection transmission can project future disease burden within a population. Few dynamic measles models have been developed for low-income countries, where measles disease burden is highest. Our objective was to review the literature on measles epidemiology in low-income countries, with a particular focus on data that are needed to parameterize dynamic models.</p> <p>Methods</p> <p>We included age-stratified case reporting and seroprevalence studies with fair to good sample sizes for mostly urban African and Indian populations. We emphasized studies conducted before widespread immunization. We summarized age-stratified attack rates and seroprevalence profiles across these populations. Using the study data, we fitted a "representative" seroprevalence profile for African and Indian settings. We also used a catalytic model to estimate the age-dependent force of infection for individual African and Indian studies where seroprevalence was surveyed. We used these data to quantify the effects of population density on the basic reproductive number <it>R</it>₀.</p> <p>Results</p> <p>The peak attack rate usually occurred at age 1 year in Africa, and 1 to 2 years in India, which is earlier than in developed countries before mass vaccination. Approximately 60% of children were seropositive for measles antibody by age 2 in Africa and India, according to the representative seroprevalence profiles. A statistically significant decline in the force of infection with age was found in 4 of 6 Indian seroprevalence studies, but not in 2 African studies. This implies that the classic threshold result describing the critical proportion immune (<it>p</it>_c) required to eradicate an infectious disease, <it>p</it>_c= 1-1/<it>R</it>₀, may overestimate the required proportion immune to eradicate measles in some developing country populations. A possible, though not statistically significant, positive relation between population density and <it>R</it>₀for various Indian and African populations was also found. These populations also showed a similar pattern of waning of maternal antibodies. Attack rates in rural Indian populations show little dependence on vaccine coverage or population density compared to urban Indian populations. Estimated <it>R</it>₀values varied widely across populations which has further implications for measles elimination.</p> <p>Conclusions</p> <p>It is possible to develop a broadly informative dynamic model of measles transmission in low-income country settings based on existing literature, though it may be difficult to develop a model that is closely tailored to any given country. Greater efforts to collect data specific to low-income countries would aid in control efforts by allowing highly population-specific models to be developed.</p

Functional selectivity of adenosine receptor ligands

Adenosine receptors are plasma membrane proteins that transduce an extracellular signal into the interior of the cell. Basically every mammalian cell expresses at least one of the four adenosine receptor subtypes. Recent insight in signal transduction cascades teaches us that the current classification of receptor ligands into agonists, antagonists, and inverse agonists relies very much on the experimental setup that was used. Upon activation of the receptors by the ubiquitous endogenous ligand adenosine they engage classical G protein-mediated pathways, resulting in production of second messengers and activation of kinases. Besides this well-described G protein-mediated signaling pathway, adenosine receptors activate scaffold proteins such as β-arrestins. Using innovative and sensitive experimental tools, it has been possible to detect ligands that preferentially stimulate the β-arrestin pathway over the G protein-mediated signal transduction route, or vice versa. This phenomenon is referred to as functional selectivity or biased signaling and implies that an antagonist for one pathway may be a full agonist for the other signaling route. Functional selectivity makes it necessary to redefine the functional properties of currently used adenosine receptor ligands and opens possibilities for new and more selective ligands. This review focuses on the current knowledge of functionally selective adenosine receptor ligands and on G protein-independent signaling of adenosine receptors through scaffold proteins

Frequently asked questions about chlorophyll fluorescence, the sequel

[EN] Using chlorophyll (Chl) a fluorescence many aspects of the photosynthetic apparatus can be studied, both in vitro and, noninvasively, in vivo. Complementary techniques can help to interpret changes in the Chl a fluorescence kinetics. Kalaji et al. (Photosynth Res 122: 121-158, 2014a) addressed several questions about instruments, methods and applications based on Chl a fluorescence. Here, additionalChl a fluorescence-related topics are discussed again in a question and answer format. 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Optimal Diffeomorphic Matching in Biomedical Image Processing

We consider optimal matching of submanifolds such as curves and surfaces by a variational approach based on Hilbert spaces of diffeomorphic transformations. In an abstract setting, the optimal matching is formulated as a minimization problem involving actions of diffeomorphisms on regular Borel measures considered as supporting measures of the reference and the target submanifolds. The objective functional consists of two parts measuring the elastic energy of the dynamically deformed surfaces and the quality of the matching. To make the problem computationally accessible, we use reproducing kernel Hilbert spaces with radial kernels and weighted sums of Dirac measures which gives rise to diffeomorphic point matching and amounts to the solution of a finite dimensional minimization problem. We present a matching algorithm based on the first order necessary optimality conditions which include an initial-value problem for a dynamical system in the trajectories describing the deformation of the surfaces and a final-time problem associated with the adjoint equations. The performance of the algorithm is illustrated by numerical results for examples from medical image analysis

Diffeomorphic Matching and Dynamic Deformable Surfaces in 3D Medical Imaging

We consider optimal matching of submanifolds such as curves and surfaces by a variational approach based on Hilbert spaces of diffeomorphic transformations. In an abstract setting, the optimal matching is formulated as a minimization problem involving actions of diffeomorphisms on regular Borel measures considered as supporting measures of the reference and the target submanifolds. The objective functional consists of two parts measuring the elastic energy of the dynamically deformed surfaces and the quality of the matching. To make the problem computationally accessible, we use reproducing kernel Hilbert spaces with radial kernels and weighted sums of Dirac measures which gives rise to diffeomorphic point matching and amounts to the solution of a finite dimensional minimization problem. We present a matching algorithm based on the first order necessary optimality conditions which include an initial-value problem for a dynamical system in the trajectories describing the deformation of the surfaces and a final-time problem associated with the adjoint equations. The performance of the algorithm is illustrated by numerical results for examples from medical image analysis