Oral Mucositis Management in Children under Cancer Treatment: A Systematic Review.

Children undergoing antineoplastic treatment often present severe side effects due to the dosage and duration of treatments, with oral mucositis emerging as one of the most prevalent and painful inflammatory conditions. There is a growing body of evidence on therapeutic interventions such as cryotherapy, low-level laser therapy, and natural compounds for this condition. The aim of this systematic review was to identify and compare therapies for the management of cancer treatment-induced oral mucositis in pediatric patients. From 2655 articles obtained in initial searches, 39 articles were considered in this systematic review, after applying inclusion/exclusion criteria. Low-level laser therapy, palifermin, honey, and zinc demonstrated reductions in oral mucositis incidence, duration, severity, and pain reported by the patient. Although there are several therapies in place for the prevention and treatment of oral mucositis in children, evidence of their efficacy is still inconclusive to establish accurate clinical protocols.

Molecular mechanisms of ischemia and glutamate excitotoxicity.

Excitotoxicity is classically defined as the neuronal damage caused by the excessive release of glutamate, and subsequent activation of excitatory plasma membrane receptors. In the mammalian brain, this phenomenon is mainly driven by excessive activation of glutamate receptors (GRs). Excitotoxicity is common to several chronic disorders of the Central Nervous System (CNS) and is considered the primary mechanism of neuronal loss of function and cell death in acute CNS diseases (e.g. ischemic stroke). Multiple mechanisms and pathways lead to excitotoxic cell damage including pro-death signaling cascade events downstream of glutamate receptors, calcium (Ca2+) overload, oxidative stress, mitochondrial impairment, excessive glutamate in the synaptic cleft as well as altered energy metabolism. Here, we review the current knowledge on the molecular mechanisms that underlie excitotoxicity, emphasizing the role of Nicotinamide Adenine Dinucleotide (NAD) metabolism. We also discuss novel and promising therapeutic strategies to treat excitotoxicity, highlighting recent clinical trials. Finally, we will shed light on the ongoing search for stroke biomarkers, an exciting and promising field of research, which may improve stroke diagnosis, prognosis and allow better treatment options.

Proteostasis networks in aging: novel insights from text-mining approaches.

Aging is a topic of paramount importance in an increasingly elderly society and has been the focus of extensive research. Protein homeostasis (proteostasis) decline is a hallmark in aging and several age-related diseases, but which specific proteins and mechanisms are involved in proteostasis (de)regulation during the aging process remain largely unknown. Here, we used different text-mining tools complemented with protein-protein interaction data to address this complex topic. Analysis of the integrated protein interaction networks identified novel proteins and pathways associated to proteostasis mechanisms and aging or age-related disorders, indicating that this approach is useful to identify previously unknown links and for retrieving information of potential novel biomarkers or therapeutic targets.

Methodology to identify a gene expression signature by merging microarray datasets.

A vast number of microarray datasets have been produced as a way to identify differentially expressed genes and gene expression signatures. A better understanding of these biological processes can help in the diagnosis and prognosis of diseases, as well as in the therapeutic response to drugs. However, most of the available datasets are composed of a reduced number of samples, leading to low statistical, predictive and generalization power. One way to overcome this problem is by merging several microarray datasets into a single dataset, which is typically a challenging task. Statistical methods or supervised machine learning algorithms are usually used to determine gene expression signatures. Nevertheless, statistical methods require an arbitrary threshold to be defined, and supervised machine learning methods can be ineffective when applied to high-dimensional datasets like microarrays. We propose a methodology to identify gene expression signatures by merging microarray datasets. This methodology uses statistical methods to obtain several sets of differentially expressed genes and uses supervised machine learning algorithms to select the gene expression signature. This methodology was validated using two distinct research applications: one using heart failure and the other using autism spectrum disorder microarray datasets. For the first, we obtained a gene expression signature composed of 117 genes, with a classification accuracy of approximately 98%. For the second use case, we obtained a gene expression signature composed of 79 genes, with a classification accuracy of approximately 82%. This methodology was implemented in R language and is available, under the MIT licence, at https://github.com/bioinformatics-ua/MicroGES.

Study of NAD-interacting proteins highlights the extent of NAD regulatory roles in the cell and its potential as a therapeutic target.

Nicotinamide adenine dinucleotide (NAD) levels are essential for the normal physiology of the cell and are strictly regulated to prevent pathological conditions. NAD functions as a coenzyme in redox reactions, as a substrate of regulatory proteins, and as a mediator of protein-protein interactions. The main objectives of this study were to identify the NAD-binding and NAD-interacting proteins, and to uncover novel proteins and functions that could be regulated by this metabolite. It was considered if cancer-associated proteins were potential therapeutic targets. Using multiple experimental databases, we defined datasets of proteins that directly interact with NAD - the NAD-binding proteins (NADBPs) dataset - and of proteins that interact with NADBPs - the NAD-protein-protein interactions (NAD-PPIs) dataset. Pathway enrichment analysis revealed that NADBPs participate in several metabolic pathways, while NAD-PPIs are mostly involved in signalling pathways. These include disease-related pathways, namely, three major neurodegenerative disorders: Alzheimer's disease, Huntington's disease, and Parkinson's disease. Then, the complete human proteome was further analysed to select potential NADBPs. TRPC3 and isoforms of diacylglycerol (DAG) kinases, which are involved in calcium signalling, were identified as new NADBPs. Potential therapeutic targets that interact with NAD were identified, that have regulatory and signalling functions in cancer and neurodegenerative diseases.

The role of NAD metabolism in neuronal differentiation.

BACKGROUND: Nicotinamide adenine dinucleotide (NAD) metabolism is involved in redox and non-redox reactions that regulate several processes including differentiation of cells of different origins. Here, the role of NAD metabolism in neuronal differentiation, which remains elusive so far, was investigated. MATERIAL AND METHODS: A protein-protein interaction network between neurotrophin signaling and NAD metabolic pathways was built. Expression of NAD biosynthetic enzymes in SH-SY5Y cells during retinoic acid (RA)/brain derived neurotrophic factor (BDNF) differentiation, was evaluated. The effects of NAD biosynthetic enzymes QPRT and NAPRT inhibition in neurite outgrowth, cell viability, NAD availability and histone deacetylase (HDAC) activity, were analyzed in RA- and BDNF-differentiated cells. RESULTS: Bioinformatics analysis revealed the interaction between NAD biosynthetic enzyme NMNAT1 and NTRK2, a receptor activated by RA/BDNF sequential treatment. Differences were found in the expression of NAD biosynthetic enzymes during neuronal differentiation, namely, increased QPRT gene expression along the course of RA/BDNF treatment and NAPRT protein expression after a 5-day treatment with RA. QPRT inhibition in BDNF-differentiated SH-SY5Y cells resulted in less neuritic length per cell, decreased expression of the neuronal marker ß-III Tubulin and also decreased NAD+ levels and HDAC activity. NAPRT inhibition had no effect in neuritic length per cell, NAD+ levels and HDAC activity. Of note, NAD supplementation along with RA, but not with BDNF, resulted in considerable cell death. CONCLUSIONS: Taken together, our results show the involvement of NAD metabolism in neuronal differentiation, specifically, the importance of QPRT-mediated NAD biosynthesis in BDNF-associated SH-SY5Y differentiation and suggest additional roles for NAPRT beyond NAD production in RA-differentiated cells.

Population wide testing pooling strategy for SARS-CoV-2 detection using saliva.

SARS-CoV-2 pandemic has forced frequent testing of populations. It is necessary to identify the most cost-effective strategies for the detection of COVID-19 outbreaks. Nasopharyngeal samples have been used for SARS-CoV-2 detection but require a healthcare professional to collect the sample and cause discomfort and pain to the individual. Saliva has been suggested as an appropriate fluid for the diagnosis of COVID-19. We have investigated the possibility of using pools of saliva samples to detect SARS-CoV-2 in symptomatic and asymptomatic patients. Two hundred and seventy-nine saliva samples were analyzed through RT-PCR of Envelope, Nucleocapsid and Open Reading Frame 1ab genes. Reproducibility assays showed an almost perfect agreement as well as high sensitivity (96.6%), specificity (96.8%), positive predicted value (96.6%), and negative predicted value (96.8%). The average Cycle Threshold of the genes detected was 29.7. No significant differences (p > 0.05) were detected when comparing the cycle threshold average of two consecutive reactions on the same positive saliva samples. Saliva samples have a higher median viral load (32.6) than in nasopharyngeal samples (28.9), although no significant differences were detected (p > 0.05). Saliva-pool samples allowed effective SARS-CoV-2 screening, with a higher sensibility (96.9%) on 10-sample pools than in 20-sample pools (87.5%). Regardless of pools size specificity was high (99.9%) and an almost perfect agreement was observed. Our strategy was successfully applied in population wide testing of more than 2000 individuals, showing that it is possible to use pooled saliva as diagnostic fluid for SARS-CoV-2 infection.

Influence of saliva interaction on surface properties manufactured for rapid osseointegration in dental implants.

Surface treatments are designed to promote modified implant surfaces with positive interactions with the surrounding living tissues. However, the inadvertent early contact of these surfaces with oral fluids during surgery may lead to undesired conditions affecting osseointegration. This study aimed to investigate the possible alterations in the physico-chemical properties of modified-surfaces caused by early saliva exposure. Titanium (Ti) surfaces were exposed to three different samples of human saliva and later analyzed for protein adhesion, physico-chemical surface alterations, and osteogenic cell-viability. The results indicated that surface roughness was the most significant factor influencing saliva protein adsorption; moreover, hydrophilic surfaces had critically lost their characteristics after contact with saliva. Decreased cell viability was observed in cultures after contact with saliva. Early contact with saliva might negatively influence modified surface properties and local cell viability. Careful surgical insertion of implants with hydrophilic surfaces is recommended, particularly in sites where saliva interaction is prone to occur.

Exosomal Aß-Binding Proteins Identified by "In Silico" Analysis Represent Putative Blood-Derived Biomarker Candidates for Alzheimer´s Disease.

The potential of exosomes as biomarker resources for diagnostics and even for therapeutics has intensified research in the field, including in the context of Alzheimer´s disease (AD). The search for disease biomarkers in peripheral biofluids is advancing mainly due to the easy access it offers. In the study presented here, emphasis was given to the bioinformatic identification of putative exosomal candidates for AD. The exosomal proteomes of cerebrospinal fluid (CSF), serum and plasma, were obtained from three databases (ExoCarta, EVpedia and Vesiclepedia), and complemented with additional exosomal proteins already associated with AD but not found in the databases. The final biofluids' proteomes were submitted to gene ontology (GO) enrichment analysis and the exosomal Aß-binding proteins that can constitute putative candidates were identified. Among these candidates, gelsolin, a protein known to be involved in inhibiting Abeta fibril formation, was identified, and it was tested in human samples. The levels of this Aß-binding protein, with anti-amyloidogenic properties, were assessed in serum-derived exosomes isolated from controls and individuals with dementia, including AD cases, and revealed altered expression patterns. Identification of potential peripheral biomarker candidates for AD may be useful, not only for early disease diagnosis but also in drug trials and to monitor disease progression, allowing for a timely therapeutic intervention, which will positively impact the patient's quality of life.

The transcription factor Ndt80 is a repressor of Candida parapsilosis virulence attributes.

Candida parapsilosis is an emergent opportunistic yeast among hospital settings that affects mainly neonates and immunocompromised patients. Its most remarkable virulence traits are the ability to adhere to prosthetic materials, as well as the formation of biofilm on abiotic surfaces. The Ndt80 transcription factor was identified as one of the regulators of biofilm formation by C. parapsilosis; however, its function in this process was not yet clarified. By knocking out NDT80 (CPAR2-213640) gene, or even just one single copy of the gene, we observed substantial alterations of virulence attributes, including morphogenetic changes, adhesion and biofilm growth profiles. Both ndt80Δ and ndt80ΔΔ mutants changed colony and cell morphologies from smooth, yeast-shaped to crepe and pseudohyphal elongated forms, exhibiting promoted adherence to polystyrene microspheres and notably, forming a higher amount of biofilm compared to wild-type strain. Interestingly, we identified transcription factors Ume6, Cph2, Cwh41, Ace2, Bcr1, protein kinase Mkc1 and adhesin Als7 to be under Ndt80 negative regulation, partially explaining the phenotypes displayed by the ndt80ΔΔ mutant. Furthermore, ndt80ΔΔ pseudohyphae adhered more rapidly and were more resistant to murine macrophage attack, becoming deleterious to such cells after phagocytosis. Unexpectedly, our findings provide the first evidence for a direct role of Ndt80 as a repressor of C. parapsilosis virulence attributes. This finding shows that C. parapsilosis Ndt80 functionally diverges from its homolog in the close related fungal pathogen C. albicans.

Merging microarray studies to identify a common gene expression signature to several structural heart diseases.

BACKGROUND: Heart disease is the leading cause of death worldwide. Knowing a gene expression signature in heart disease can lead to the development of more efficient diagnosis and treatments that may prevent premature deaths. A large amount of microarray data is available in public repositories and can be used to identify differentially expressed genes. However, most of the microarray datasets are composed of a reduced number of samples and to obtain more reliable results, several datasets have to be merged, which is a challenging task. The identification of differentially expressed genes is commonly done using statistical methods. Nonetheless, these methods are based on the definition of an arbitrary threshold to select the differentially expressed genes and there is no consensus on the values that should be used. RESULTS: Nine publicly available microarray datasets from studies of different heart diseases were merged to form a dataset composed of 689 samples and 8354 features. Subsequently, the adjusted p-value and fold change were determined and by combining a set of adjusted p-values cutoffs with a list of different fold change thresholds, 12 sets of differentially expressed genes were obtained. To select the set of differentially expressed genes that has the best accuracy in classifying samples from patients with heart diseases and samples from patients with no heart condition, the random forest algorithm was used. A set of 62 differentially expressed genes having a classification accuracy of approximately 95% was identified. CONCLUSIONS: We identified a gene expression signature common to different cardiac diseases and supported our findings by showing their involvement in the pathophysiology of the heart. The approach used in this study is suitable for the identification of gene expression signatures, and can be extended to different diseases.

FKS1 mutation associated with decreased echinocandin susceptibility of Aspergillus fumigatus following anidulafungin exposure.

Invasive aspergillosis (IA) is a potentially lethal infection that affects mostly immunocompromised patients caused by Aspergillus fumigatus. Echinocandins are a second-line therapy against IA, used as a salvage therapy as well as for empirical or prophylactic therapy. Although they cause lysis of growing hyphal tips, they are considered fungistatic against molds. In vivo echinocandins resistance is uncommon; however, its wide clinical use could shortly lead to the emergence of A. fumigatus resistance. The aims of the present work was to assess the development of reduced echinocandins susceptibility phenotype by a A. fumigatus strain and to unveil the molecular mechanism underlying such phenotype. We induced in vitro cross-resistance to echinocandins following exposure of A. fumigatus to anidulafungin. Stability of the resistant phenotype was confirmed after removal of anidulafungin pressure. The FKS1 gene was partially sequenced and a E671Q mutation was found. A computational approach suggests that it can play an important role in echinocandin resistance. Given the emerging importance of this mechanism for clinical resistance in pathogenic fungi, it would be prudent to be alert to the potential evolution of this resistant mechanism in Aspergillus spp infecting patients under echinocandins therapeutics.

Tracking the functional meaning of the human oral-microbiome protein-protein interactions.

The interactome - the network of protein-protein interactions (PPIs) within a cell or organism - is technically difficult to assess. Bioinformatic tools can, not only, identify potential PPIs that can be later experimentally validated, but also be used to assign functional meaning to PPIs. Saliva's potential as a non-invasive diagnostic fluid is currently being explored by several research groups. But, in order to fully attain its potential, it is necessary to achieve the full characterization of the mechanisms that take place within this ecosystem. The onset of omics technologies, and specifically of proteomics, delivered a huge set of data that is largely underexplored. Quantitative information relative to proteins within a given context (for example a given disease) can be used by computational algorithms to generate information regarding PPIs. These PPIs can be further analyzed concerning their functional meaning and used to identify potential biomarkers, therapeutic targets, defense and pathogenicity mechanisms. We describe a computational pipeline that can be used to identify and analyze PPIs between human and microbial proteins. The pipeline was tested within the scenario of human PPIs of systemic (Zika Virus infection) and of oral conditions (Periodontal disease) and also in the context of microbial interactions (Candida-Streptococcus) and showed to successfully predict functionally relevant PPIs. The pipeline can be applied to different scientific areas, such as pharmacological research, since a functional meaningful PPI network can provide insights on potential drug targets, and even new uses for existing drugs on the market.

Mechanisms of Acquired In Vivo and In Vitro Resistance to Voriconazole by Candida krusei following Exposure to Suboptimal Drug Concentration.

Five Candida krusei isolates (susceptible and resistant) recovered from the urine of a kidney transplant patient treated with voriconazole (VRC) 200 mg twice daily for 20 days were studied. Eight unrelated clinical isolates of C. krusei were exposed in vitro to VRC 0.001 µg/ml for 30 days. Development of VRC transient resistance occurred in vivo, and induction of permanent resistance occurred in vitro Mostly, ABC1 and ERG11 genes were overexpressed, and a homozygous T418C mutation in the ERG11 gene was found.

Essential genetic findings in neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) represent a growing medical challenge in modern societies. Ever-increasing sophisticated diagnostic tools have been continuously revealing a remarkably complex architecture that embraces genetic mutations of distinct types (chromosomal rearrangements, copy number variants, small indels, and nucleotide substitutions) with distinct frequencies in the population (common, rare, de novo). Such a network of interacting players creates difficulties in establishing rigorous genotype-phenotype correlations. Furthermore, individual lifestyles may also contribute to the severity of the symptoms fueling a large spectrum of gene-environment interactions that have a key role on the relationships between genotypes and phenotypes.Herein, a review of the genetic discoveries related to NDDs is presented with the aim to provide useful general information for the medical community.

Distribution of Distances Between Symmetric Words in the Human Genome: Analysis of Regular Peaks.

Finding DNA sites with high potential for the formation of hairpin/cruciform structures is an important task. Previous works studied the distances between adjacent reversed complement words (symmetric word pairs) and also for non-adjacent words. It was observed that for some words a few distances were favoured (peaks) and that in some distributions there was strong peak regularity. The present work extends previous studies, by improving the detection and characterization of peak regularities in the symmetric word pairs distance distributions of the human genome. This work also analyzes the location of the sequences that originate the observed strong peak periodicity in the distance distribution. The results obtained in this work may indicate genomic sites with potential for the formation of hairpin/cruciform structures.

A Transcriptomics Approach To Unveiling the Mechanisms of In Vitro Evolution towards Fluconazole Resistance of a Candida glabrata Clinical Isolate.

Candida glabrata is an emerging fungal pathogen. Its increased prevalence is associated with its ability to rapidly develop antifungal drug resistance, particularly to azoles. In order to unravel new molecular mechanisms behind azole resistance, a transcriptomics analysis of the evolution of a C. glabrata clinical isolate (isolate 044) from azole susceptibility to posaconazole resistance (21st day), clotrimazole resistance (31st day), and fluconazole and voriconazole resistance (45th day), induced by longstanding incubation with fluconazole, was carried out. All the evolved strains were found to accumulate lower concentrations of azole drugs than the parental strain, while the ergosterol concentration remained mostly constant. However, only the population displaying resistance to all azoles was found to have a gain-of-function mutation in the C. glabrataPDR1 gene, leading to the upregulation of genes encoding multidrug resistance transporters. Intermediate strains, exhibiting posaconazole/clotrimazole resistance and increased fluconazole/voriconazole MIC levels, were found to display alternative ways to resist azole drugs. Particularly, posaconazole/clotrimazole resistance after 31 days was correlated with increased expression of adhesin genes. This finding led us to identify the Epa3 adhesin as a new determinant of azole resistance. Besides being required for biofilm formation, Epa3 expression was found to decrease the intracellular accumulation of azole antifungal drugs. Altogether, this work provides a glimpse of the transcriptomics evolution of a C. glabrata population toward multiazole resistance, highlighting the multifactorial nature of the acquisition of azole resistance and pointing out a new player in azole resistance.

Metagenomic Composition Analysis of an Ancient Sequenced Polar Bear Jawbone from Svalbard.

The sequencing of ancient DNA samples provides a novel way to find, characterize, and distinguish exogenous genomes of endogenous targets. After sequencing, computational composition analysis enables filtering of undesired sources in the focal organism, with the purpose of improving the quality of assemblies and subsequent data analysis. More importantly, such analysis allows extinct and extant species to be identified without requiring a specific or new sequencing run. However, the identification of exogenous organisms is a complex task, given the nature and degradation of the samples, and the evident necessity of using efficient computational tools, which rely on algorithms that are both fast and highly sensitive. In this work, we relied on a fast and highly sensitive tool, FALCON-meta, which measures similarity against whole-genome reference databases, to analyse the metagenomic composition of an ancient polar bear (Ursus maritimus) jawbone fossil. The fossil was collected in Svalbard, Norway, and has an estimated age of 110,000 to 130,000 years. The FASTQ samples contained 349 GB of nonamplified shotgun sequencing data. We identified and localized, relative to the FASTQ samples, the genomes with significant similarities to reference microbial genomes, including those of viruses, bacteria, and archaea, and to fungal, mitochondrial, and plastidial sequences. Among other striking features, we found significant similarities between modern-human, some bacterial and viral sequences (contamination) and the organelle sequences of wild carrot and tomato relative to the whole samples. For each exogenous candidate, we ran a damage pattern analysis, which in addition to revealing shallow levels of damage in the plant candidates, identified the source as contamination.

Comparison of Compression-Based Measures with Application to the Evolution of Primate Genomes.

An efficient DNA compressor furnishes an approximation to measure and compare information quantities present in, between and across DNA sequences, regardless of the characteristics of the sources. In this paper, we compare directly two information measures, the Normalized Compression Distance (NCD) and the Normalized Relative Compression (NRC). These measures answer different questions; the NCD measures how similar both strings are (in terms of information content) and the NRC (which, in general, is nonsymmetric) indicates the fraction of one of them that cannot be constructed using information from the other one. This leads to the problem of finding out which measure (or question) is more suitable for the answer we need. For computing both, we use a state of the art DNA sequence compressor that we benchmark with some top compressors in different compression modes. Then, we apply the compressor on DNA sequences with different scales and natures, first using synthetic sequences and then on real DNA sequences. The last include mitochondrial DNA (mtDNA), messenger RNA (mRNA) and genomic DNA (gDNA) of seven primates. We provide several insights into evolutionary acceleration rates at different scales, namely, the observation and confirmation across the whole genomes of a higher variation rate of the mtDNA relative to the gDNA. We also show the importance of relative compression for localizing similar information regions using mtDNA.

Comparing Reverse Complementary Genomic Words Based on Their Distance Distributions and Frequencies.

In this work, we study reverse complementary genomic word pairs in the human DNA, by comparing both the distance distribution and the frequency of a word to those of its reverse complement. Several measures of dissimilarity between distance distributions are considered, and it is found that the peak dissimilarity works best in this setting. We report the existence of reverse complementary word pairs with very dissimilar distance distributions, as well as word pairs with very similar distance distributions even when both distributions are irregular and contain strong peaks. The association between distribution dissimilarity and frequency discrepancy is also explored, and it is speculated that symmetric pairs combining low and high values of each measure may uncover features of interest. Taken together, our results suggest that some asymmetries in the human genome go far beyond Chargaff's rules. This study uses both the complete human genome and its repeat-masked version.