Cryptococcosis in Patients with Hematologic Diseases

Purpose of Review

In this paper, we reviewed the epidemiology, diagnosis, and treatment of cryptococcosis in patients with hematologic malignancies. We reviewed all case series of cryptococcosis in different hematologic conditions, and looked at epidemiologic trends considering the new antineoplastic drugs introduced in the treatment of hematologic malignancies.

Recent Findings

Case series of cryptococcosis in patients with hematologic malignancies are scarce. We identified an increase in the proportion of cases of cryptococcosis occurring in patients with hematologic malignancies, and many case reports of cryptococcosis in patients receiving ibrutinib, a Bruton kinase inhibitor used in the treatment of chronic lymphoproliferative diseases.

Summary

Cryptococcosis is uncommon in patients with hematologic malignancies, but its occurrence may be associated with poor outcome. Hematologists should be aware of this complication if patients develop neurologic symptoms or present with pulmonary infiltrates that do not improve with antibiotics.

     

Three-dimensional perfused tumour spheroid model for anti-cancer drug screening

Objective

To build an in vitro-perfused, three-dimensional (3D) spheroid model based on the TissueFlex system for anti-cancer drug efficacy testing in order to mimic avascular micro-tissues with inherent O₂, nutrient and metabolite gradients, and to provide a more accurate prediction of drug toxicity and efficacy than traditional in vitro tumour models in conventional static culture well plates.

Results

The perfused cancer spheroid model showed higher cell viability and increased diameter of spheroids over a relatively long culture period (17 days). Three anti-cancer drugs with different cytotoxic mechanisms were tested. In perfusion, lower cytotoxicity was observed for traditional cytotoxic drug 5-fluorouracil and microtubule-interfering, paclitaxel, showed greater interruption of spheroid integrity. For the hypoxic-dependent drug, tirapazamine, there was no significant difference observed between static and perfusion cultures.

Conclusion

The perfusion culture provides a better homeostasis for cancer cell growth in a more controllable working platform for long-term drug testing.

     

Urinary antihypertensive drug metabolite screening using molecular networking coupled to high-resolution mass spectrometry fragmentation

Introduction

Mass spectrometry is the current technique of choice in studying drug metabolism. High-resolution mass spectrometry in combination with MS/MS gas-phase experiments has the potential to contribute to rapid advances in this field. However, the data emerging from such fragmentation spectral files pose challenges to downstream analysis, given their complexity and size.

Objectives

This study aims to detect and visualize antihypertensive drug metabolites in untargeted metabolomics experiments based on the spectral similarity of their fragmentation spectra. Furthermore, spectral clusters of endogenous metabolites were also examined.

Methods

Here we apply a molecular networking approach to seek drugs and their metabolites, in fragmentation spectra from urine derived from a cohort of 26 patients on antihypertensive therapy. The mass spectrometry data was collected on a Thermo Q-Exactive coupled to pHILIC chromatography using data dependent analysis (DDA) MS/MS gas-phase experiments.

Results

In total, 165 separate drug metabolites were found and structurally annotated (17 by spectral matching and 122 by classification based on a clustered fragmentation pattern). The clusters could be traced to 13 drugs including the known antihypertensives verapamil, losartan and amlodipine. The molecular networking approach also generated clusters of endogenous metabolites, including carnitine derivatives, and conjugates containing glutamine, glutamate and trigonelline.

Conclusions

The approach offers unprecedented capability in the untargeted identification of drugs and their metabolites at the population level and has great potential to contribute to understanding stratified responses to drugs where differences in drug metabolism may determine treatment outcome.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

<Emphasis Type="Italic">massPix</Emphasis>: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Introduction

Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.

Objectives

We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.

Methods

massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.

Results

Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.

Conclusion

massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.

     

Funding innovation for treatment for rare diseases: adopting a cost-based yardstick approach

Background

Manufacturers justify the high prices for orphan drugs on the basis that the associated R&D costs must be spread over few patients. The proliferation of these drugs in the last three decades, combined with high prices commonly in excess of $100,000 per patient per year are placing a substantial strain on the budgets of drug plans in many countries. Do insurers spend a growing portion of their budgets on small patient populations, or leave vulnerable patients without coverage for valuable treatments? We suggest that a third option is present in the form of a cost-based regulatory mechanism.

Methods

This article explores the use of a cost-based price control mechanism for orphan drugs, adapted from the standard models applied in utilities regulation.

Results and conclusions

A rate-of-return style model, employing yardsticked cost allocations and a modified two-stage rate of return calculation could be effective in setting a new standard for orphan drugs pricing. This type of cost-based pricing would limit the costs faced by insurers while continuing to provide an efficient incentive for new drug development.

     

BicNET: Flexible module discovery in large-scale biological networks using biclustering

Background

Despite the recognized importance of module discovery in biological networks to enhance our understanding of complex biological systems, existing methods generally suffer from two major drawbacks. First, there is a focus on modules where biological entities are strongly connected, leading to the discovery of trivial/well-known modules and to the inaccurate exclusion of biological entities with subtler yet relevant roles. Second, there is a generalized intolerance towards different forms of noise, including uncertainty associated with less-studied biological entities (in the context of literature-driven networks) and experimental noise (in the context of data-driven networks). Although state-of-the-art biclustering algorithms are able to discover modules with varying coherency and robustness to noise, their application for the discovery of non-dense modules in biological networks has been poorly explored and it is further challenged by efficiency bottlenecks.

Methods

This work proposes Biclustering NETworks (BicNET), a biclustering algorithm to discover non-trivial yet coherent modules in weighted biological networks with heightened efficiency. Three major contributions are provided. First, we motivate the relevance of discovering network modules given by constant, symmetric, plaid and order-preserving biclustering models. Second, we propose an algorithm to discover these modules and to robustly handle noisy and missing interactions. Finally, we provide new searches to tackle time and memory bottlenecks by effectively exploring the inherent structural sparsity of network data.

Results

Results in synthetic network data confirm the soundness, efficiency and superiority of BicNET. The application of BicNET on protein interaction and gene interaction networks from yeast, E. coli and Human reveals new modules with heightened biological significance.

Conclusions

BicNET is, to our knowledge, the first method enabling the efficient unsupervised analysis of large-scale network data for the discovery of coherent modules with parameterizable homogeneity.

     

TarMet: a reactive GUI tool for efficient and confident quantification of MS based targeted metabolic and stable isotope tracer analysis

Introduction

Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately.

Objectives

TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface.

Methods

TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically.

Results

TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well.

Conclusion

TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.

     

Optimizationof neural network architecture using genetic programming improvesdetection and modeling of gene-gene interactions in studies of humandiseases

Background

Appropriate definitionof neural network architecture prior to data analysis is crucialfor successful data mining. This can be challenging when the underlyingmodel of the data is unknown. The goal of this study was to determinewhether optimizing neural network architecture using genetic programmingas a machine learning strategy would improve the ability of neural networksto model and detect nonlinear interactions among genes in studiesof common human diseases.

Results

Using simulateddata, we show that a genetic programming optimized neural network approachis able to model gene-gene interactions as well as a traditionalback propagation neural network. Furthermore, the genetic programmingoptimized neural network is better than the traditional back propagationneural network approach in terms of predictive ability and powerto detect gene-gene interactions when non-functional polymorphismsare present.

Conclusion

This study suggeststhat a machine learning strategy for optimizing neural network architecturemay be preferable to traditional trial-and-error approaches forthe identification and characterization of gene-gene interactionsin common, complex human diseases.

     

Interactive processing and visualization of image data for biomedical and life science applications

Background

Applications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations. It is becoming increasingly difficult for scientists to explore and analyze these data using traditional tools. Interactive data processing and visualization tools can support scientists to overcome these limitations.

Results

We show that new data processing tools and visualization systems can be used successfully in biomedical and life science applications. We present an adaptive high-resolution display system suitable for biomedical image data, algorithms for analyzing and visualization protein surfaces and retinal optical coherence tomography data, and visualization tools for 3D gene expression data.

Conclusion

We demonstrated that interactive processing and visualization methods and systems can support scientists in a variety of biomedical and life science application areas concerned with massive data analysis.

     

How the chemical features of molecules may have addressed the settlement of metabolic steps

Introduction

While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.

Objectives

Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.

Methods

The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.

Results

Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.

Conclusions

Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.

     

Automatic detection and resolution of measurement-unit conflicts in aggregated data

Background

Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase.

Methods

We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study.

Results

We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units.

Conclusions

We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.

     

Hypocapnia is a biological marker for orthostatic intolerance in some patients with chronic fatigue syndrome

Context

Patients with chronic fatigue syndrome and those with orthostatic intolerance share many symptoms, yet questions exist as to whether CFS patients have physiological evidence of orthostatic intolerance.

Objective

To determine if some CFS patients have increased rates of orthostatic hypotension, hypertension, tachycardia, or hypocapnia relative to age-matched controls.

Design

Assess blood pressure, heart rate, respiratory rate, end tidal CO2 and visual analog scales for orthostatic symptoms when supine and when standing for 8 minutes without moving legs.

Setting

Referral practice and research center.

Participants

60 women and 15 men with CFS and 36 women and 4 men serving as age matched controls with analyses confined to 62 patients and 35 controls showing either normal orthostatic testing or a physiological abnormal test.

Main outcome measures

Orthostatic tachycardia; orthostatic hypotension; orthostatic hypertension; orthostatic hypocapnia or combinations thereof.

Results

CFS patients had higher rates of abnormal tests than controls (53% vs 20%, p < .002), but rates of orthostatic tachycardia, orthostatic hypotension, and orthostatic hypertension did not differ significantly between patients and controls (11.3% vs 5.7%, 6.5% vs 2.9%, 19.4% vs 11.4%, respectively). In contrast, rates of orthostatic hypocapnia were significantly higher in CFS than in controls (20.6% vs 2.9%, p < .02). This CFS group reported significantly more feelings of illness and shortness of breath than either controls or CFS patients with normal physiological tests.

Conclusion

A substantial number of CFS patients have orthostatic intolerance in the form of orthostatic hypocapnia. This allows subgrouping of patients with CFS and thus reduces patient pool heterogeneity engendered by use of a clinical case definition.

     

Treatment of Advanced Non-small-Cell Lung Cancer with Qi-Nourishing Essence-Replenishing Chinese Herbal Medicine Combined with Chemotherapy

Background

To evaluate the effect of qi-nourishing essence-replenishing Chinese herbal medicine combined with chemotherapy in survival of advanced non-small-cell lung cancer(NSCLC) patients with essence and qi deficiency.

Methods

A prospective multi-centered randomized controlled study was conducted, and 266 advanced NSCLC patients were enrolled. 126 patients in control group received Vinorelbine plus cisplatin(NP) chemotherapy combined with symptom-oriented Chinese herbs medication(without qi-nourishing essence-replenishing herbs);140 patients in experimental group received NP chemotherapy combined with qi-nourishing essence-replenishing Chinese herbal medication(Kangliu Zengxiao Decoction and modified Feiyanning Decoction, during and after chemotherapy respectively).

Results

One patient in control and 2 in experimental group were excluded for failure to complete two cycles of chemotherapy. During follow-up, 17 and 7 patients in control and experimental group were excluded respectively(4 and 4 for taking Gefetinib after disease progression, 4 and 2 for receiving other chemotherapeutic regimens, 9 and 1 for lost to follow-up). 239 patients were included in the final analysis (131 in experimental group and 108 in control). Median overall survival in experimental group was significantly longer than control group (14.87vs.12.97 months,P?=?0.027). In experimental and control group, 1-year, 3-year, 5-year, 7-year, and 9-year survival rates were 57% vs. 53%, 17% vs. 8%, 10% vs. 2%, 6% vs. 0%, and 6% vs. 0%, respectively.

Conclusion

Qi-nourishing essence-replenishing Chinese herbal medicine combined with chemotherapy improves survival of advanced NSCLC patients with essence and qi deficiency.

     

Factor XIII Val34Leu polymorphism and risk of recurrent pregnancy loss in Iranian population: a case control study

BACKGROUND

Recurrent pregnancy loss (RPL) is a heterogeneous condition and thrombophilias have been considered as a probable cause.

OBJECTIVE

The aim of this study was to investigate the prevalence of the coagulation factor XIII Val34Leu polymorphism among women with unexplained RPL.

METHODS

A total of 140 women with a history of unexplained RPL and 100 age-matched healthy fertile women were recruited. The presence of FXIII Val34Leu polymorphism among the cases and controls was investigated using PCR-RFLP method.

RESULTS

Genotype analyses of the subjects revealed that the patients had a significantly higher prevalence of V/L and L/L than the controls (P<0.05): 33.5% vs. 15%, and 9.2% vs. 2%, respectively.

CONCLUSION

These results indicate a significant association between FXIII Val34Leu polymorphism and unexplained RPL in the Iranian patient.

     

Nucleotide binding domain 1 pharmacophore modeling for visualization and analysis of P-glycoprotein–flavonoid molecular interactions

Background

P-glycoprotein (P-gp) is a 170-kDa membrane protein. It provides a barrier function and help to excrete toxins from the body as a transporter. Some bioflavonoids have been shown to block P-gp activity.

Objective

To evaluate the important amino acid residues within nucleotide binding domain 1 (NBD1) of P-gp that play a key role in molecular interactions with flavonoids using structure-based pharmacophore model.

Methods

In the molecular docking with NBD1 models, a putative binding site of flavonoids was proposed and compared with the site for ATP. The binding modes for ligands were achieved using LigandScout to generate the P-gp–flavonoid pharmacophore models.

Results

The binding pocket for flavonoids was investigated and found these inhibitors compete with the ATP for binding site in NBD1 including the NBD1 amino acid residues identified by the in silico techniques to be involved in the hydrogen bonding and van der Waals (hydrophobic) interactions with flavonoids.

Conclusion

These flavonoids occupy with the same binding site of ATP in NBD1 proffering that they may act as an ATP competitive inhibitor.

     

A metabolomics approach to uncover effects of different exercise modalities in type 1 diabetes

Introduction

Exercise-associated metabolism in type 1 diabetes (T1D) remains under-studied due to the complex interplay between exogenous insulin, counter-regulatory hormones and insulin-sensitivity.

Objective

To identify the metabolic differences induced by two exercise modalities in T1D using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) based metabolomics.

Methods

Twelve T1D adults performed intermittent high-intensity (IHE) and continuous-moderate-intensity (CONT) exercise. Serum samples were analysed by UHPLC–HRMS.

Results

Metabolic profiling of IHE and CONT highlighted exercise-induced changes in purine and acylcarnitine metabolism.

Conclusion

IHE may increase beta-oxidation through higher ATP-turnover. UHPLC–HRMS based metabolomics as a data-driven approach without an a priori hypothesis may help uncover distinctive metabolic effects during exercise in T1D.Clinical trial registration number is www.clinicaltrials.gov: NCT02068638.

     

A randomized,placebo-controlled clinical trial evaluating the safety and efficacy of the once-weekly DPP-4 inhibitor omarigliptin in patients with type 2 diabetes mellitus inadequately controlled by glimepiride and metformin

Background

Type 2 diabetes (T2D) is a progressive disease that often requires a patient to use multiple antihyperglycemic agents to achieve glycemic control with disease progression. Omarigliptin is a once-weekly dipeptidyl peptidase-4 inhibitor. The purpose of this trial was to assess the efficacy and safety of adding omarigliptin to the treatment regimen of patients with T2D inadequately controlled by dual therapy with metformin and glimepiride.

Methods

Patients with T2D and HbA1c ≥7.5% and ≤10.5% while on metformin (≥1500 mg/day) and glimepiride (≥4 mg/day) were randomized to omarigliptin 25 mg once-weekly (N = 154) or placebo (N = 153) for 24 weeks. The primary objective was to assess whether omarigliptin was superior to placebo in reducing HbA1c at Week 24. Secondary objectives were to assess the effects of omarigliptin vs. placebo on FPG and the proportion of subjects attaining HbA1c goals of <7% and <6.5%.

Results

From a mean baseline HbA1c of 8.5% (omarigliptin) and 8.6% (placebo), the least squares (LS) mean change from baseline in HbA1c at Week 24 was ?0.67% in the omarigliptin group and ?0.06% in the placebo group, with a between-group difference (95% CI) of ?0.61% (?0.85, ?0.38). Treatment with omarigliptin resulted in a significantly greater reduction in FPG relative to placebo (LS mean difference [95% CI] -0.9 mmol/L [?1.4, ?0.4]; p < 0.001). The proportion of patients achieving glycemic goals of <7.0% and <6.5% was higher in the omarigliptin group relative to the placebo group. The overall incidences of adverse events (AEs), serious AEs, drug-related AEs and discontinuations were generally similar between treatment groups. The incidence of symptomatic hypoglycemia was 10.5% in the omarigliptin group and 8.5% in the placebo group. Relative to baseline, omarigliptin and placebo treatments were associated with LS mean changes in body weight of ?0.1 kg and ?0.9 kg, respectively.

Conclusion

In patients with T2D and inadequate glycemic control on dual therapy with metformin and glimepiride, compared with placebo, once-weekly omarigliptin provided greater improvement in glycemic control and was generally well tolerated.

Trial registration

ClinicalTrials.gov: NCT01704261, EudraCT Number: 2012-002612-10. Trial Registration Date: October 8, 2012.

     

An oncoplastic technique to reduce the formation of lateral 'dog-ears' after mastectomy

Background

Lateral skin folds or 'dog-ears' are frequent following mastectomy, particularly in patients with large body habitus.

Methods

We describe a method of modifying the mastectomy incision and suturing to eliminate these lateral 'dog-ears'.

Conclusion

This surgical technique, as compared to others described in the literature, is simple, does not require additional incisions and is cosmetically acceptable to the patient.