CCL3L1 copy number, CCR5 genotype and susceptibility to tuberculosis

Background: Tuberculosis is a major infectious disease and functional studies have provided evidence that both the chemokine MIP-1α and its receptor CCR5 play a role in susceptibility to TB. Thus by measuring copy number variation of CCL3L1, one of the genes that encode MIP-1α, and genotyping a functional promoter polymorphism -2459A > G in CCR5 (rs1799987) we investigate the influence of MIP-1α and CCR5, independently and combined, in susceptibility to clinically active TB in three populations, a Peruvian population (n = 1132), a !Xhosa population (n = 605) and a South African Coloured population (n = 221). The three populations include patients with clinically diagnosed pulmonary TB, as well as other, less prevalent forms of extrapulmonary TB. Methods and results: Copy number of CCL3L1 was measured using the paralogue ratio test and exhibited ranges between 0–6 copies per diploid genome (pdg) in Peru, between 0–12 pdg in !Xhosa samples and between 0–10 pdg in South African Coloured samples. The CCR5 promoter polymorphism was observed to differ significantly in allele frequency between populations (*A; Peru f = 0.67, !Xhosa f = 0.38, Coloured f = 0.48). Conclusions: The case–control association studies performed however find, surprisingly, no evidence for an influence of variation in genes coding for MIP-1α or CCR5 individually or together in susceptibility to clinically active TB in these populations

Switching to letrozole or exemestane improves hot flushes, mood and quality of life in tamoxifen intolerant women

We report an open-label, prospective, crossover study involving 184 post-menopausal women experiencing hot flushes on adjuvant tamoxifen (T). Six weeks after switching to an AI, the primary end point, hot flush score, improved by 47.3% (P<0.001) compared to those reported on T. The mean mood rating scale (MRS) score improved by 9.7% (P=0.01). The total mean combined FACT (b+es) score improved from 134.2 (95% CI ±2.96) to 143.5 (95% CI ±2.96 <0.001), and the endocrine subscale improved by 9.8% from 51.73 (95% CI ±1.38) to 57.34 (CI ±1.38, P<0.001). At 6 weeks, significantly more women chose to remain on an AI: 133 (72%), vs 40 (22%) (P<0.001) preferring T. At 3 months, 107 (58%) preferred to remain on an AI, 55(30%) on T, and 22 (12%) withdrew. The overall arthralgia rate at 3 months was 47% on AI and 30% on T (P=0.001). In all 182 (99%) women reported appreciating the opportunity to experience both drugs. These data suggest that if patients suffering significant adverse effects on T are given the opportunity to try an AI, this empowers them to prioritise relative side-effects, improving wellbeing in a significant proportion. These data also highlight the need for hospital follow-up in this intolerant cohort

A Stable Biologically Motivated Learning Mechanism for Visual Feature Extraction to Handle Facial Categorization

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task

Heterogeneous nuclear ribonucleoprotein K: altered pattern of expression associated with diagnosis and prognosis of prostate cancer

Using proteomic analysis of the nuclear matrix (NM), we found that heterogeneous nuclear ribonucleoprotein K (hnRNP K), a member of the hnRNP family with pleiotropic functions, was differentially expressed in prostate cancer (PCa) tissues. This study aimed to characterise the expression of hnRNP K and its subcellular localisation in PCa, utilising immunohistochemical and quantitative western blot techniques. Furthermore, the hnRNP K expression was studied in human PCa cell lines in order to determine its modulation by bicalutamide, the anti-androgen widely used in PCa therapy. Immunohistochemical staining of paraffin-embedded tissues showed that hnRNP K was overexpressed in PCa, where it was localised both in the cytoplasm and in the nucleus. Staining of non-tumour tissues showed exclusively nuclear localisation and a less intense or absent signal. Immunoblot analysis demonstrated that the hnRNP K level within the NM was higher in PCa compared with non-tumour tissues and closely correlated with Gleason score (P=0.008). Higher expression within the NM was significantly (P=0.032) associated with poor prognosis. In two-dimensional western blot analysis hnRNP K presented several isoforms; the one with pI 5.1 was the most differently expressed between non-tumour and PCa tissues. Preliminary results indicate that hnRNP K can be modulated in vitro by a non-steroidal anti-androgen. Taken together, our findings suggest that hnRNP K has potential implications at the diagnostic, prognostic and therapeutic levels in PCa

The Method for Assigning Priority Levels (MAPLe): A new decision-support system for allocating home care resources

<p>Abstract</p> <p>Background</p> <p>Home care plays a vital role in many health care systems, but there is evidence that appropriate targeting strategies must be used to allocate limited home care resources effectively. The aim of the present study was to develop and validate a methodology for prioritizing access to community and facility-based services for home care clients.</p> <p>Methods</p> <p>Canadian and international data based on the Resident Assessment Instrument – Home Care (RAI-HC) were analyzed to identify predictors for nursing home placement, caregiver distress and for being rated as requiring alternative placement to improve outlook.</p> <p>Results</p> <p>The Method for Assigning Priority Levels (MAPLe) algorithm was a strong predictor of all three outcomes in the derivation sample. The algorithm was validated with additional data from five other countries, three other provinces, and an Ontario sample obtained after the use of the RAI-HC was mandated.</p> <p>Conclusion</p> <p>The MAPLe algorithm provides a psychometrically sound decision-support tool that may be used to inform choices related to allocation of home care resources and prioritization of clients needing community or facility-based services.</p

Thermodynamics of mixing in diopside-jadeite, CaMgSi2O6-NaAlSi2O6, solid solution from staticlattice energy calculations

Static lattice energy calculations (SLEC), based on empirical interatomic potentials, have beenperformed for a set of 800 different structures in a 2 2 4 supercell of C2/c diopside with compositionsbetween diopside and jadeite, and with different states of order of the exchangeable Na/Ca and Mg/Al cations. Excess static energies of these structures have been cluster expanded in a basis set of 37 pair-interaction parameters. These parameters have been used to constrain Monte Carlo simulations of temperature-dependent properties in the range of 273?2,023 K and to calculate a temperature?composition phase diagram. The simulations predict the order?disorder transition in omphacite at1,150 20C in good agreement with the experimental data of Carpenter (Mineral Petrol 78:433?440, 1981). The stronger ordering of Mg/Al within the M1 site than of Ca/Na in the M2 site is attributed to the shorter M1?M1 nearest-neighbor distance, and, consequently, the stronger ordering force. The comparison of the simulated relationship between the order parameters corresponding to M1 and M2 sites with the X-ray refinement data on natural omphacites (Boffa Ballaran et al. in Am Mineral83:419?433, 1998) suggests that the cation ordering becomes kinetically ineffective at about 600C

Positive Feedbacks in Seagrass Ecosystems – Evidence from Large-Scale Empirical Data

Positive feedbacks cause a nonlinear response of ecosystems to environmental change and may even cause bistability. Even though the importance of feedback mechanisms has been demonstrated for many types of ecosystems, their identification and quantification is still difficult. Here, we investigated whether positive feedbacks between seagrasses and light conditions are likely in seagrass ecosystems dominated by the temperate seagrass Zostera marina. We applied a combination of multiple linear regression and structural equation modeling (SEM) on a dataset containing 83 sites scattered across Western Europe. Results confirmed that a positive feedback between sediment conditions, light conditions and seagrass density is likely to exist in seagrass ecosystems. This feedback indicated that seagrasses are able to trap and stabilize suspended sediments, which in turn improves water clarity and seagrass growth conditions. Furthermore, our analyses demonstrated that effects of eutrophication on light conditions, as indicated by surface water total nitrogen, were on average at least as important as sediment conditions. This suggests that in general, eutrophication might be the most important factor controlling seagrasses in sheltered estuaries, while the seagrass-sediment-light feedback is a dominant mechanism in more exposed areas. Our study demonstrates the potentials of SEM to identify and quantify positive feedbacks mechanisms for ecosystems and other complex systems

Persistent inequalities in 90-day colon cancer mortality: an English cohort study.

BACKGROUND: Variation in colon cancer mortality occurring shortly after diagnosis is widely reported between socio-economic status (SES) groups: we investigated the role of different prognostic factors in explaining variation in 90-day mortality. METHODS: National cancer registry data were linked with national clinical audit data and Hospital Episode Statistics records for 69 769 adults diagnosed with colon cancer in England between January 2010 and March 2013. By gender, logistic regression was used to estimate the effects of SES, age and stage at diagnosis, comorbidity and surgical treatment on probability of death within 90 days from diagnosis. Multiple imputations accounted for missing stage. We predicted conditional probabilities by prognostic factor patterns and estimated the effect of SES (deprivation) from the difference between deprivation-specific average predicted probabilities. RESULTS: Ninety-day probability of death rose with increasing deprivation, even after accounting for the main prognostic factors. When setting the deprivation level to the least deprived group for all patients and keeping all other prognostic factors as observed, the differences between deprivation-specific averaged predicted probabilities of death were greatly reduced but persisted. Additional analysis suggested stage and treatment as potential contributors towards some of these inequalities. CONCLUSIONS: Further examination of delayed diagnosis, access to treatment and post-operative care by deprivation group may provide additional insights into understanding deprivation disparities in mortality