First measurement of the K−n →Λπ−non-resonant transition amplitude below threshold

We present the analysis of K−absorption processes on He4 leading to Λπ−final states, measured with the KLOE spectrometer at the DAΦNE e+e−collider and extract, for the first time, the modulus of the non-resonant K−n →Λπ−direct production amplitude about 33 MeV below the K‾N threshold. This analysis also allows to disentangle the K−nuclear absorption at-rest from the in-flight capture, for K−momenta of about 120 MeV. The data are interpreted with the help of a phenomenological model, and the modulus of the non-resonant K−n →Λπ−amplitude for K−absorption at-rest is found to be |AK−n→Λπ−|=(0.334±0.018stat−0.058+0.034syst)fm

Quasispecies Theory and the Behavior of RNA Viruses

A large number of medically important viruses, including HIV, hepatitis C virus, and influenza, have RNA genomes. These viruses replicate with extremely high mutation rates and exhibit significant genetic diversity. This diversity allows a viral population to rapidly adapt to dynamic environments and evolve resistance to vaccines and antiviral drugs. For the last 30 years, quasispecies theory has provided a population-based framework for understanding RNA viral evolution. A quasispecies is a cloud of diverse variants that are genetically linked through mutation, interact cooperatively on a functional level, and collectively contribute to the characteristics of the population. Many predictions of quasispecies theory run counter to traditional views of microbial behavior and evolution and have profound implications for our understanding of viral disease. Here, we discuss basic principles of quasispecies theory and describe its relevance for our understanding of viral fitness, virulence, and antiviral therapeutic strategy

Height and timing of growth spurt during puberty in young people living with vertically acquired HIV in Europe and Thailand.

OBJECTIVE: The aim of this study was to describe growth during puberty in young people with vertically acquired HIV. DESIGN: Pooled data from 12 paediatric HIV cohorts in Europe and Thailand. METHODS: One thousand and ninety-four children initiating a nonnucleoside reverse transcriptase inhibitor or boosted protease inhibitor based regimen aged 1-10 years were included. Super Imposition by Translation And Rotation (SITAR) models described growth from age 8 years using three parameters (average height, timing and shape of the growth spurt), dependent on age and height-for-age z-score (HAZ) (WHO references) at antiretroviral therapy (ART) initiation. Multivariate regression explored characteristics associated with these three parameters. RESULTS: At ART initiation, median age and HAZ was 6.4 [interquartile range (IQR): 2.8, 9.0] years and -1.2 (IQR: -2.3 to -0.2), respectively. Median follow-up was 9.1 (IQR: 6.9, 11.4) years. In girls, older age and lower HAZ at ART initiation were independently associated with a growth spurt which occurred 0.41 (95% confidence interval 0.20-0.62) years later in children starting ART age 6 to 10 years compared with 1 to 2 years and 1.50 (1.21-1.78) years later in those starting with HAZ less than -3 compared with HAZ at least -1. Later growth spurts in girls resulted in continued height growth into later adolescence. In boys starting ART with HAZ less than -1, growth spurts were later in children starting ART in the oldest age group, but for HAZ at least -1, there was no association with age. Girls and boys who initiated ART with HAZ at least -1 maintained a similar height to the WHO reference mean. CONCLUSION: Stunting at ART initiation was associated with later growth spurts in girls. Children with HAZ at least -1 at ART initiation grew in height at the level expected in HIV negative children of a comparable age

Identification of TNF-α and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array

BACKGROUND: Several drugs are available to treat metastatic renal-cell carcinoma (MRCC), and predictive markers to identify the most adequate treatment for each patient are needed. Our objective was to identify potential predictive markers of sunitinib activity in MRCC. METHODS: We collected sequential serum samples from 31 patients treated with sunitinib. Sera of six patients with extreme phenotypes of either marked responses or clear progressions were analysed with a Human Cytokine Array which evaluates 174 cytokines before and after treatment. Variations in cytokine signal intensity were compared between both groups and the most relevant cytokines were assessed by ELISA in all the patients. RESULTS: Twenty-seven of the 174 cytokines varied significantly between both groups. Five of them (TNF-alpha, MMP-9, ICAM-1, BDNF and SDF-1) were assessed by ELISA in 21 evaluable patients. TNF-alpha and MMP-9 baseline levels were significantly increased in non-responders and significantly associated with reduced overall survival and time-to-progression, respectively. The area under the ROC curves for TNF-alpha and MMP-9 as predictive markers of sunitinib activity were 0.83 and 0.77. CONCLUSION: Baseline levels of TNF-alpha and MMP-9 warrant further study as predictive markers of sunitinib activity in MRCC. Selection of patients with extreme phenotypes seems a valid method to identify potential predictive factors of response

Strategies to design clinical studies to identify predictive biomarkers in cancer research

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework—the DESIGN guidelines—to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field