230 research outputs found

    Diversity of Lecidea (Lecideaceae, Ascomycota) species revealed by molecular data and morphological characters

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    The diversity of lichens, especially crustose species, in continental Antarctica is still poorly known. To overcome difficulties with the morphology based species delimitations in these groups, we employed molecular data (nuclear ITS and mitochondrial SSU rDNA sequences) to test species boundaries within the genus Lecidea. Sampling was done along a north–south transect at five different areas in the Ross Sea region (Cape Hallett, Botany Bay to Mount Suess, Taylor Valley, Darwin Area and Mount Kyffin). A total of 153 specimens were collected from 13 localities. Phylogenetic analyses also include specimens from other regions in Antarctica and non-Antarctic areas. Maximum parsimony, maximum likelihood and Bayesian analyses agreed in placing the samples from continental Antarctica into four major groups. Based on this phylogenetic estimate, we restudied the micromorphology and secondary chemistry of these four clades to evaluate the use of these characters as phylogenetic discriminators. These clades are identified as the following species Lecidea cancriformis, L. andersonii as well as the new species L. polypycnidophora Ruprecht & Türk sp. nov. and another previously unnamed clade of uncertain status, referred to as Lecidea sp. (L. UCR1)

    Early reconstitution of effector memory CD4+ CMV-specific T cells protects against CMV reactivation following allogeneic SCT.

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    Reactivation of CMV is a common complication following allogeneic haematopoietic SCT and is associated with significant morbidity and mortality. The relative importance of the CD4+ and CD8+ components of the CMV-specific immune response in protection from reactivation is unclear. The CMV-specific CD4+ and CD8+ immune response was measured at serial time points in 32 patients following allogeneic HSCT. Intracellular cytokine staining following CMV lysate stimulation and HLA-peptide tetramers were used to determine CMV-specific CD4+ and CD8+ responses, respectively. A deficient CMV-specific CD4+ T-cell immune response within the first 30-50 days post transplant was associated with high risk of viral reactivation. Patients with combined impairment of the CD4+ and CD8+ immune response within the first 100 days were susceptible to late viral reactivation. The frequency of CMV-specific CD4+ T cells correlated with CMV-specific CD8+ T cells, comprising 10% of the whole T-cell repertoire. Early CMV-specific CD4+ T-cell reconstitution was dominated by effector memory cells with normal levels of IL-2 resuming 6 months following transplantation. In summary, both CD4 and CD8 CMV-specific immune reconstitution is required for protection from recurrent activation. Measurement of the magnitude of the CMV-specific CD4+ immune response is useful in managing viral reactivation following HSCT

    Dose Transition Pathways::The missing link between complex dose-finding designs and simple decision-making

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    The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. Clin Cancer Res; 23(24); 7440-7. ©2017 AACR

    Stratified medicine in European Medicines Agency licensing : a systematic review of predictive biomarkers

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    OBJECTIVES: Stratified medicine is often heralded as the future of clinical practice. Key part of stratified medicine is the use of predictive biomarkers, which identify patient subgroups most likely to benefit (or least likely to experience harm) from an intervention. We investigated how many and what predictive biomarkers are currently included in European Medicines Agency (EMA) licensing. SETTING: EMA licensing. PARTICIPANTS: Indications and contraindications of all drugs considered by the EMA and published in 883 European Public Assessment Reports and Pending Decisions. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected on: the type of the biomarker, whether it selected a subgroup of patients based on efficacy or toxicity, therapeutic area, marketing status, date of licensing decision, date of inclusion of the biomarker in the indication or contraindication and on orphan designation. RESULTS: 49 biomarker–indication–drug (B-I-D) combinations were identified over 16 years, which included 37 biomarkers and 41 different drugs. All identified biomarkers were molecular. Six drugs (relating to 10 B-I-D combinations) had an orphan designation at the time of licensing. The identified B-I-D combinations were mainly used in cancer and HIV treatment, and also in hepatitis C and three other indications (cystic fibrosis, hyperlipoproteinaemia type I and methemoglobinaemia). In 45 B-I-D combinations, biomarkers were used as predictive of drug efficacy and in four of drug toxicity. It appeared that there was an increase in the number of B-I-D combinations introduced each year; however, the numbers were too small to identify any trends. CONCLUSIONS: Given the large body of literature documenting research into potential predictive biomarkers and extensive investment into stratified medicine, we identified relatively few predictive biomarkers included in licensing. These were also limited to a small number of clinical areas. This might suggest a need for improvement in methods of translation from laboratory findings to clinical practice