A conceptual model for optimizing vaccine coverage to reduce vector-borne infections in the presence of antibody-dependent enhancement

Background

Many vector-borne diseases co-circulate, as the viruses from the same family are also transmitted by the same vector species. For example, Zika and dengue viruses belong to the same Flavivirus family and are primarily transmitted by a common mosquito species Aedes aegypti. Zika outbreaks have also commonly occurred in dengue-endemic areas, and co-circulation and co-infection of both viruses have been reported. As recent immunological cross-reactivity studies have confirmed that convalescent plasma following dengue infection can enhance Zika infection, and as global efforts of developing dengue and Zika vaccines are intensified, it is important to examine whether and how vaccination against one disease in a large population may affect infection dynamics of another disease due to antibody-dependent enhancement.

Methods

Through a conceptual co-infection dynamics model parametrized by reported dengue and Zika epidemic and immunological cross-reactivity characteristics, we evaluate impact of a hypothetical dengue vaccination program on Zika infection dynamics in a single season when only one particular dengue serotype is involved.

Results

We show that an appropriately designed and optimized dengue vaccination program can not only help control the dengue spread but also, counter-intuitively, reduce Zika infections. We identify optimal dengue vaccination coverages for controlling dengue and simultaneously reducing Zika infections, as well as the critical coverages exceeding which dengue vaccination will increase Zika infections.

Conclusion

This study based on a conceptual model shows the promise of an integrative vector-borne disease control strategy involving optimal vaccination programs, in regions where different viruses or different serotypes of the same virus co-circulate, and convalescent plasma following infection from one virus (serotype) can enhance infection against another virus (serotype). The conceptual model provides a first step towards well-designed regional and global vector-borne disease immunization programs.

     

A group matrix representation relevant to scales of measurement of clinical disease states via stratified vectors

Background

Previously, we applied basic group theory and related concepts to scales of measurement of clinical disease states and clinical findings (including laboratory data). To gain a more concrete comprehension, we here apply the concept of matrix representation, which was not explicitly exploited in our previous work.

Methods

Starting with a set of orthonormal vectors, called the basis, an operator R_j (an N-tuple patient disease state at the j-th session) was expressed as a set of stratified vectors representing plural operations on individual components, so as to satisfy the group matrix representation.

Results

The stratified vectors containing individual unit operations were combined into one-dimensional square matrices [R_j]s. The [R_j]s meet the matrix representation of a group (ring) as a K-algebra. Using the same-sized matrix of stratified vectors, we can also express changes in the plural set of [R_j]s. The method is demonstrated on simple examples.

Conclusions

Despite the incompleteness of our model, the group matrix representation of stratified vectors offers a formal mathematical approach to clinical medicine, aligning it with other branches of natural science.

     

PLA nanovectors with encapsulated betulin: plant leaf extract-synthesized nanovectors are more efficacious than PVA-synthesized nanovectors

Objectives

Betulin (BT) is an abundant triterpene found predominantly in the bark of Himalayan birch. It is difficult to deliver it in vivo because of its low aqueous solubility. We have therefore developed novel formulations of BT for improving its solubility, bioavailability and therapeutic efficacy.

Results

Poly-d,l-lactide nanovectors (PLA NVs) were synthesized using poly(vinyl alcohol) and Lonicera japonica leaf extract (LE) as a stabiliser and named as PLA-1 NVs and PLA-2 NVs. PLA-1 NVs and PLA-2 NVs were used for the encapsulation of betulin (BT) and named as BT-En-1 and BT-En-2 NVs. The encapsulation efficiency of BT-En-1 and BT-En-2 NVs were 99.3 and 100 % respectively. Prepared nanoformulations were physically stable. An in vitro study revealed 45 % BT was released over 24 h. BT had a prolonged release from BT-En-2 NVs as compared to BT-En-1 NVs. BT-En-2 NVs had better anticancerous activity against SiHa cells than BT-En-1 NVs.

Conclusions

Developed BT-EN-2 NVs had better biocompatibility, excellent stability and enhanced release characteristics than BT-En-1 NVs.

     

Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design.

Results

We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features.

Conclusions

In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics

Introduction

Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

Objectives

We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

Methods

Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA^® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

Results

A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

Conclusion

Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Classification of ADHD patients on the basis of independent ERP components using a machine learning system

Background

In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects.

Methods

Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine.

Results

The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%.

Conclusions

This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

High level soluble expression and one-step purification of IBDV VP2 protein in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Objectives

To improve the expression of soluble IBDV VP2 protein by using different tagged vectors in Escherichia coli.

Results

Fusion tags, Grifin, MBP, SUMO, thioredoxin, γ-crystallin, ArsC and PpiB, enhanced the expression and solubility of VP2 protein. The fusion proteins were purified by Ni–NTA chromatography, MBP-VP2 showed the highest purity about 90 %. After removing the MBP tag, VP2 self-assembled into virus-like particles, ~25 nm diam. Results from AGP suggested the recombinant IBDV VP2 protein identified by reference serum like IBDV.

Conclusion

All the seven tags enhanced the expression and solubility of IBDV VP2 protein. The recombinant protein self-assembly into virus like particles and possess antigenicity as reference IBDV.

     

Corneal Collagen Cross-Linking for the Management of Mycotic Keratitis

Purpose

To evaluate the efficiency of corneal collagen cross-linking (CXL) in addition to topical voriconazole in cases with mycotic keratitis.

Design

Retrospective case series in a tertiary university hospital.

Participants

CXL was performed on 13 patients with mycotic keratitis who presented poor or no response to topical voriconazole treatment.

Methods

The clinical features, symptoms, treatment results and complications were recorded retrospectively. The corneal infection was graded according to the depth of infection into the stroma (from grade 1 to grade 3). The visual analogue scale was used to calculate the pain score before and 2 days after surgery.

Main Outcome Measures

Grade of the corneal infection.

Results

Mean age of 13 patients (6 female and 7 male) was 42.4 ± 17.7 years (20–74 years). Fungus was demonstrated in culture (eight patients) or cytological examination (five patients). Seven of the 13 patients (54%) were healed with topical voriconazole and CXL adjuvant treatment in 26 ± 10 days (15–40 days). The remaining six patients did not respond to CXL treatment; they initially presented with higher grade ulcers. Pre- and post-operative pain score values were 8 ± 0.8 and 3.5 ± 1, respectively (p < 0.05).

Conclusions

The current study suggests that adjunctive CXL treatment is effective in patients with small and superficial mycotic ulcers. These observations require further research by large randomized clinical trials.

     

Resazurin-based 96-well plate microdilution method for the determination of minimum inhibitory concentration of biosurfactants

Objectives

To develop and validate a microdilution method for measuring the minimum inhibitory concentration (MIC) of biosurfactants.

Results

A standardized microdilution method including resazurin dye has been developed for measuring the MIC of biosurfactants and its validity was established through the replication of tetracycline and gentamicin MIC determination with standard bacterial strains.

Conclusion

This new method allows the generation of accurate MIC measurements, whilst overcoming critical issues related to colour and solubility which may interfere with growth measurements for many types of biosurfactant extracts.

     

Metabolomics analysis of liver reveals profile disruption in bovines upon steroid treatment

Introduction

The surveillance of illegal anabolic practices in bovine meat production is necessary to guarantee consumers’ health. Screening strategies based on the recognition of indirect biological effects are considered by the community as promising tools to overcome some limitations of classical analytical methods and might therefore concur to ensure safer food for the consumer.

Objectives

The present work aims at characterizing the metabolic profile induced in liver by administration of anabolic steroids, and at identifying potential disturbances in the hepatic metabolism.

Methods

A total of 32 liver samples, 16 from untreated bulls and 16 from bulls treated with an ear implant (Revalor-XS^®) containing trenbolone acetate (200 mg) and β-estradiol (40 mg), were analyzed following a LC–MS-based metabolomic analysis combining RP and HILIC chromatographic separations. Different multivariate statistical tools were applied to the datasets to select common metabolites that may be considered as potential markers based on their significant changes in concentrations after administration of sexual steroids.

Results

Eight candidate markers were identified. Moreover, a subset of four markers was also validated by a different laboratory that performed the same analysis using an independent instrumental and elaboration platform, confirming the robustness of the results achieved.

Conclusion

This study was performed mimicking experimental conditions that may be used during a potential misuse practice. It is promising in the objective of setting up an analytical strategy to highlight sexual steroids abuse in livestock animals.

     

A constitutive expression system for <Emphasis Type="Italic">Pichia pastoris</Emphasis> based on the <Emphasis Type="Italic">PGK1</Emphasis> promoter

Objectives

To develop a new vector for constitutive expression in Pichia pastoris based on the endogenous glycolytic PGK1 promoter.

Results

P. pastoris plasmids bearing at least 415 bp of PGK1 promoter sequences can be used to drive plasmid integration by addition at this locus without affecting cell growth. Based on this result, a new P. pastoris integrative vector, pPICK2, was constructed bearing some features that facilitate protein production in this yeast: a ~620 bp PGK1 promoter fragment with three options of restriction sites for plasmid linearization prior to yeast transformation: a codon-optimized α-factor secretion signal, a new polylinker, and the kan marker for vector propagation in bacteria and selection of yeast transformants.

Conclusions

A new constitutive vector for P. pastoris represents an alternative platform for recombinant protein production and metabolic engineering purposes.

     

Reliable RT-qPCR-based titration of retroviral and lentiviral vectors via quantification of residual vector plasmid DNA in samples

Objectives

To develop a method for reliable quantification of viral vectors, which is necessary for determining the optimal dose of vector particles in clinical trials to obtain the desired effects without severe unwanted immune responses.

Results

A significant level of vector plasmid remained in retroviral and lentiviral vector samples, which led to overestimation of viral titers when using the conventional RT-qPCR-based genomic titration method. To address this problem, we developed a new method in which the residual plasmid was quantified by an additional RT-qPCR step, and standard molecules and primer sets were optimized. The obtained counts were then used to correct the conventionally measured genomic titers of viral samples. While the conventional method produced significantly higher genomic titers for mutant retroviral vectors than for wild-type vectors, our method produced slightly higher or equivalent titers, corresponding with the general idea that mutation of viral components mostly results in reduced or, at best, retained titers.

Conclusion

Subtraction of the number of residual vector plasmid molecules from the conventionally measured genomic titer can yield reliable quantification of retroviral and lentiviral vector samples, a prerequisite to advancing the safety of gene therapy applications.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Iridoid and phenylethanoid/phenylpropanoid metabolite profiles of <Emphasis Type="Italic">Scrophularia</Emphasis> and <Emphasis Type="Italic">Verbascum</Emphasis> species used medicinally in North America

Introduction

Botanicals containing iridoid and phenylethanoid/phenylpropanoid glycosides are used worldwide for the treatment of inflammatory musculoskeletal conditions that are primary causes of human years lived with disability, such as arthritis and lower back pain.

Objectives

We report the analysis of candidate anti-inflammatory metabolites of several endemic Scrophularia species and Verbascum thapsus used medicinally by peoples of North America.

Methods

Leaves, stems, and roots were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and partial least squares-discriminant analysis (PLS-DA) was performed in MetaboAnalyst 3.0 after processing the datasets in Progenesis QI.

Results

Comparison of the datasets revealed significant and differential accumulation of iridoid and phenylethanoid/phenylpropanoid glycosides in the tissues of the endemic Scrophularia species and Verbascum thapsus.

Conclusions

Our investigation identified several species of pharmacological interest as good sources for harpagoside and other important anti-inflammatory metabolites.

     

<Emphasis Type="Italic">Candida auris</Emphasis>: Antifungal Multi-Resistant Emerging Yeast

Purpose of Review

The purpose of this review is to contribute to the knowledge about the existence of Candida auris as an emerging pathogenic fungus, multi-resistant to antifungal, and causing health care-associated infections (HCAI).

Recent Findings

C. auris emerges as yeast with clonal transmission resistance to three families of commonly used antifungals, mainly azoles (fluconazole and voriconazole), diminishing therapeutic options for the treatment of fungal infections. In 2009, C. auris was isolated for the first time in Japan and by the time of this review, it has been reported in different countries in Africa, America, Asia, and Europe.

Summary

It is important to identify yeasts of the Candida genus up to species, to perform susceptibility tests and to implement surveillance, prevention, and control measures, to minimize the global spread of this fungus, due to its impact on public health.