Oligoclonal expansion of TCR <Emphasis Type="Italic">V</Emphasis>δ T cells may be a potential immune biomarker for clinical outcome of acute myeloid leukemia

Background

Recent data have shown that γδ T cells can act as mediators for immune defense against tumors. Our previous study has demonstrated that persisting clonally expanded TRDV4 T cells might be relatively beneficial for the outcome of patients with T cell acute lymphoblastic leukemia after hematopoietic stem cell transplantation (HSCT). However, little is known about the distribution and clonality of the TRDV repertoire in T cell receptor (TCR) of γδ T cells and their effects on the clinical outcome of patients with acute myeloid leukemia (AML). The aim of this study was to assess whether the oligoclonal expansion of TCR Vδ T cells could be used as an immune biomarker for AML outcome.

Findings

γδ T cells were sorted from the peripheral blood of 30 patients with untreated AML and 12 healthy donors. The complementarity-determining region 3 (CDR3) sizes of eight TCR Vδ subfamily genes (TRDV1 to TRDV8) were analyzed in sorted γδ T cells using RT-PCR and GeneScan. The most frequently expressed TRDV subfamilies in the AML patients were TRDV8 (86.67 %) and TRDV2 (83.33 %), and the frequencies for TRDV1, TRDV3, TRDV4, and TRDV6 were significantly lower than those in healthy individuals. The most frequent clonally expanded TRDV subfamilies in the AML patients included TRDV8 (56.67 %) and TRDV4 (40 %). The clonal expansion frequencies of the TRDV2 and TRDV4 T cells were significantly higher than those in healthy individuals, whereas a significantly lower TRDV1 clonal expansion frequency was observed in those with AML. Moreover, the oligoclones of TRDV4 and TRDV8 were independent protective factors for complete remission. Furthermore, the oligoclonal expansion frequencies of TRDV5 and TRDV6 in patients with relapse were significantly higher than those in non-recurrent cases.

Conclusions

To the best of our knowledge, we characterized for the first time a significant alteration in the distribution and clonality of the TRDV subfamily members in γδ T cells sorted from AML patients. Clonally expanded TRDV4 and TRDV8 T cells might contribute to the immune response directed against AML, while oligoclonal TRDV5 and TRDV6 might occur in patients who undergo relapse. While the function of such γδ T cell clones requires further investigation, TRDV γδ T cell clones might be potential immune biomarkers for AML outcome.

     

Volumetric hand‐held optoacoustic angiography as a tool for real‐time screening of dense breast

Existing mammographic screening solutions are generally associated with several major drawbacks, such as exposure to ionizing radiation or insufficient sensitivity in younger populations with radiographically‐dense breast. Even when combined with ultrasound or magnetic resonance imaging, X‐Ray mammography may still attain unspecific or false positive results. Thus, development of new breast imaging tools represents a timely medical challenge. We report on a new approach to high‐resolution functional and anatomical breast angiography using volumetric hand‐held optoacoustic tomography, which employs light intensities safe for human use. Experiments in young healthy volunteers with fibroglandular‐dominated dense breasts revealed the feasibility of rendering three‐dimensional images representing vascular anatomy and functional blood oxygenation parameters at video rate. Sufficient contrast was achieved at depths beyond 2 cm within dense breasts without compromising the real‐time imaging performance. The suggested solution may thus find applicability as a standalone or supplemental screening tool for early detection and follow‐up of carcinomas in radiographically‐dense breasts.

Volumetric handheld optoacoustic tomography scanner uses safe pulses of near‐infrared light to render three‐dimensional images of deep vascular anatomy, blood oxygenation and breast parenchyma at video rate.     

Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients

Objective

Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the prediction performance for subsequent shocks is still uncertain.

Methods

A total of 528 defibrillation shocks from 199 patients experienced out-of-hospital cardiac arrest were analyzed in this study. VF waveform was quantified using amplitude spectrum area (AMSA) from defibrillator''s ECG recordings prior to each shock. Combinations of AMSA with previous shock index (PSI) or/and change of AMSA (ΔAMSA) between successive shocks were exercised through a training dataset including 255shocks from 99patientswith neural networks. Performance of the combination methods were compared with AMSA based single feature prediction by area under receiver operating characteristic curve(AUC), sensitivity, positive predictive value (PPV), negative predictive value (NPV) and prediction accuracy (PA) through a validation dataset that was consisted of 273 shocks from 100patients.

Results

A total of61 (61.0%) patients required subsequent shocks (N = 173) in the validation dataset. Combining AMSA with PSI and ΔAMSA obtained highest AUC (0.904 vs. 0.819, p<0.001) among different combination approaches for subsequent shocks. Sensitivity (76.5% vs. 35.3%, p<0.001), NPV (90.2% vs. 76.9%, p = 0.007) and PA (86.1% vs. 74.0%, p = 0.005)were greatly improved compared with AMSA based single feature prediction with a threshold of 90% specificity.

Conclusion

In this retrospective study, combining AMSA with previous shock information using neural networks greatly improves prediction performance of defibrillation outcome for subsequent shocks.     

Natural products from marine invertebrates against <Emphasis Type="Italic">Leishmania</Emphasis> parasites: a comprehensive review

Parasitic infections by Leishmania parasites remains a severe public health problem, especially in developing countries where it is highly endemic. Chemotherapy still remains a first option for the treatment of those diseases, despite the fact that available drugs exhibit a variety of shortcomings. Thus, innovative, less toxic more affordable and effective antileishmanial agents are urgently needed. The marine environment holds an immeasurable bio- and chemical diversity, being a valuable source of natural products with therapeutic potential. As invertebrates comprise about 60 % of all marine organisms, bioprospecting this class of organisms for antileishmanial properties may unravel unique and selective hit molecules. In this context, this review covers results on the literature of marine invertebrate extracts and pure compounds evaluated against Leishmania parasites mainly by in vitro methods. It comprises results obtained from the phyla Porifera, Cnidaria, Bryozoa (Ectoprota), Mollusca, Echinodermata, Annelida, Cetnophora, Platyhelminthes, sub phyla Crustacea (phylum Arthropoda) and Tunicata (phylum Chordata). Moreover, structure–activity relationships and possible mechanisms of action are mentioned, whenever available information is provided. About 70 species of marine invertebrates belonging to seven different phyla are included in this work. Besides a variety of crude extracts, a total of 140 pure compounds was tested against different Leishmania species. Although the research on the antileishmanial potential of marine invertebrates is in its early beginnings, promising results have been achieved that encourage further research. As more extracts and compounds are being screened, the possibility of finding active and selective antileishmanial molecules increases, rising new hope in the search for new treatments against leishmaniases.     

Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level

Genetic association analyses of rare variants in next-generation sequencing (NGS) studies are fundamentally challenging due to the presence of a very large number of candidate variants at extremely low minor allele frequencies. Recent developments often focus on pooling multiple variants to provide association analysis at the gene instead of the locus level. Nonetheless, pinpointing individual variants is a critical goal for genomic researches as such information can facilitate the precise delineation of molecular mechanisms and functions of genetic factors on diseases. Due to the extreme rarity of mutations and high-dimensionality, significances of causal variants cannot easily stand out from those of noncausal ones. Consequently, standard false-positive control procedures, such as the Bonferroni and false discovery rate (FDR), are often impractical to apply, as a majority of the causal variants can only be identified along with a few but unknown number of noncausal variants. To provide informative analysis of individual variants in large-scale sequencing studies, we propose the Adaptive False-Negative Control (AFNC) procedure that can include a large proportion of causal variants with high confidence by introducing a novel statistical inquiry to determine those variants that can be confidently dispatched as noncausal. The AFNC provides a general framework that can accommodate for a variety of models and significance tests. The procedure is computationally efficient and can adapt to the underlying proportion of causal variants and quality of significance rankings. Extensive simulation studies across a plethora of scenarios demonstrate that the AFNC is advantageous for identifying individual rare variants, whereas the Bonferroni and FDR are exceedingly over-conservative for rare variants association studies. In the analyses of the CoLaus dataset, AFNC has identified individual variants most responsible for gene-level significances. Moreover, single-variant results using the AFNC have been successfully applied to infer related genes with annotation information.