1,720,966 research outputs found
Drug Discovery and preclinical Development for Human and Animal African Trypanosomiasis: Profiling of a collection of Natural Compounds with ADME-(Eco)Toxicity properties
No full textHuman African trypanosomiasis (HAT), also known as sleeping sickness, and Animal African
trypanosomiasis (AAT) are life-threatening neglected tropical diseases generally caused by the
Trypanosoma brucei subspecies. HAT represents a critical public health issue in 36 African
countries, with approximately 65 million people at risk, predominantly affecting impoverished
communities in sub-Saharan Africa, where it poses a significant health and economic burden 1 .
AAT, similarly, affects livestock, leading to severe economic losses due to decreased
productivity and increased mortality in affected animals. Despite advances in reducing HAT
cases and improving treatments, AAT remains a reservoir of infection, making its control
crucial as part of the One Health approach. Current treatments, including suramin,
pentamidine, melarsoprol, eflornithine, and the recent nifurtimox-eflornithine combination
therapy, are associated with several drawbacks, like toxicity, high cost, and emerging drug
resistance 2 . Given these limitations, there is an urgent need for new, effective and safe
trypanocidal drugs.
Natural products, with their unique chemical structures and bioactivity, represent a promising
resource for drug discovery 3 . However, information on natural compounds with trypanocidal
activity is often fragmented, with existing reviews typically focusing on a single class of
molecules and often outdated. Establishing a comprehensive database of natural candidates
with proven trypanocidal activity is crucial to identify promising scaffolds and accelerate the
discovery of new hits/leads. The database built in this work includes relevant data on natural
compounds active against T. brucei, incorporating literature data from 2019 to 2024, with their
chemical structure, biological activity, cytotoxicity and, when described in the literature,
molecular target/s. By systematically classifying natural products with anti-trypanosomal
properties, this database, properly integrated with ADME and ECOTOX parameters, represents
a first crucial step to disclose new effective treatments for both HAT and AAT, thus significantly
contributing to the global effort to control and eradicate trypanosomiasis
Lipidomic profiling of MASLD: identifying lipid biomarkers for detection and stratification of disease severity
No full textMetabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease globally, particularly in Western countries, and is strongly linked to obesity, hyperlipidaemia, type 2 diabetes mellitus (T2DM), and metabolic syndrome[1]. MASLD includes a wide spectrum of conditions, from simple steatosis, often asymptomatic and benign, to metabolic dysfunction-associated steatohepatitis (MASH), a more aggressive phenotype characterized by hepatic fat accumulation, inflammation, and hepatocellular injury. MASH significantly increases the risk of fibrosis, cirrhosis, and hepatocellular carcinoma, and has become a leading indication for liver transplantation in many Western populations[2]. Despite its increasing clinical burden, early detection and accurate staging, particularly identifying those at risk of progression to MASH, remains challenging. Current non-invasive tests (NITs), such as blood-based scores and imaging techniques, are recommended as first-line diagnostic and risk stratification tools[3]. However, sensitive and specific biomarkers for reliably assessing disease severity and progression are still lacking. Against this backdrop, lipidomics offer promising avenues for improving disease characterization. In this study, high-risk metabolic patients with detailed clinical, biochemical, and imaging assessments, provided a well-characterized cohort (14 cases), covering the full MASLD spectrum, including advanced MASH. Lipids were extracted from serum and plasma collected from the patients in this cohort using a dual in-vial extraction with methyl-tert-butyl ether (MTBE)[4], then analyzed via UHPLC-HRMS using an Orbitrap Q Exactive system. Lipid annotation and identification were performed using Compound Discoverer (Thermo Fisher Scientific), supported by MS/MS-based structural validation. The analysis focused on lipid classes implicated in MASH pathogenesis, including ceramides, triglycerides, phospholipids, and sphingolipids. These findings revealed distinct lipid profiles and metabolic pathways associated with steatosis severity suggesting their potential in non-invasive disease stratification. While further validation in larger cohorts is needed, these findings, though preliminary, underscore the potential of lipidomic profiling to complement existing tools and advance precision medicine in MASLD
Identifying lipid patterns through lipidomic profiling for MASLD detection and severity stratification
No full textThe increasing global burden of metabolic dysfunction-associated steatotic liver disease (MASLD) has placed this condition at the forefront of chronic liver diseases, especially in Western populations. Strongly associated with metabolic comorbidities such as obesity, dyslipidemia, insulin resistance, and type 2 diabetes [1], MASLD follows a continuum that ranges from asymptomatic hepatic steatosis to the more advanced metabolic dysfunction-associated steatohepatitis (MASH). This progression, characterized by hepatocellular injury and inflammation, significantly increases the risk of fibrosis, cirrhosis, and hepatocellular carcinoma [2]. Although current non-invasive tools including imaging and serum-based biomarkers are helpful in initial evaluations, their limited sensitivity and specificity reduce their effectiveness in accurately staging the disease or predicting its progression [3]. To address this gap, we applied lipidomic profiling to investigate the molecular features associated with MASLD severity.
In this pilot study, we conducted untargeted lipidomic analyses on serum and plasma samples from a metabolically defined patient cohort spanning the full MASLD spectrum, including cases with advanced MASH. Lipids were extracted using a biphasic methyl-tert-butyl ether (MTBE) protocol [4] and analyzed by UHPLC coupled with high-resolution Orbitrap mass spectrometry. Lipid species were annotated using Compound Discoverer software and structurally validated through MS/MS fragmentation.
Our analysis revealed distinct lipidomic profiles corresponding to different stages of MASLD. Key changes were observed in ceramides, sphingolipids and phospholipids, with specific patterns reflecting the extent of steatosis and inflammatory activity. These results point to a gradual reprogramming of lipid metabolism as the disease progresses, highlighting lipidomic alterations as potential indicators of disease status.
Overall, our findings underscore the value of lipidomics as a high-resolution molecular tool for improving early detection, patient stratification, and personalized monitoring in MASLD. While larger validation studies are needed, this approach may enrich current diagnostic frameworks and support the transition toward a more personalized model of care
Targeted metabolomics for the analysis of p-cresol in mouse brain by HPLC-ESI-MS/MS
No full textp-Cresol, an environmental contaminant and endogenous metabolite primarily derived from
tyrosine conversion by intestinal microflora, is gaining increasing attention for its potential health
impact. Once produced, the compound is converted into p-cresyl-glucuronide and p-cresyl-sulfate
and excreted via organic anion transporters (OAT), which are also expressed in the brain, mediating
efflux across the blood-brain barrier (BBB). While the impact of p-cresol and its metabolites as
uremic toxins in chronic kidney disease (CKD) is well-known, affecting the central nervous,
immune, and cardiovascular systems, their role in neurodegenerative and neurodevelopmental
disorders is still under investigation. Elevated urinary levels of p-cresol and p-cresyl-sulfate have
been found in autistic children with altered intestinal microbiota, suggesting a link to increased
autism severity and gut dysfunction [1,2]. Moreover, p-cresol’s effects on dopamine metabolism
suggest possible roles in post-traumatic stress disorder (PTSD) and Parkinson’s disease (PD) [3].
However, the evidence on the presence and concentration of p-cresol in the central nervous system
(CNS) is virtually unknown, highlighting the need to develop an analytical method capable of
quantifying this compound at very low concentrations.
To address this gap, we optimized and validated a new HPLC-ESI-MS/MS method for targeted
metabolomics of p-cresol in brain areas. Using reversed-phase HPLC with gradient elution coupled
with electrospray ionization-mass spectrometry (ESI-MS/MS) detection in multiple reaction
monitoring (MRM) mode, we analyzed brain tissue from male and female C57BL/6 mice, revealing
p-cresol distribution across seven brain regions. Additional measurements in the cortex of three
mouse strains - CD1, C57BL/6 and the model of idiopathic autism BTBR +tf/J - showed that p-
cresol levels were influenced by both sex and genotype. This effect was also observed in
experiments on wild-type (WT) and CX3CR1 knockout (KO) mice: while sex and genotype
affected p-cresol distribution in the prefrontal cortex, treatment with lipopolysaccharide (LPS) did
not produce any significant changes in p-cresol levels. Additional targeted metabolomic analyses
were performed to further explore potential correlations between this compound, neurotransmitters
and their metabolites, particularly in dopaminergic and noradrenergic pathways. Preliminary
analyses on human cortex samples also confirmed the presence of p-cresol, underscoring its
potential relevance to brain health. Finally, molecular docking studies on OAT provided insights
into potential BBB transport mechanisms for p-cresol and its derivatives. The determination of
basal p-cresol levels in the brain lays the groundwork for studying its role in neurodevelopmental
and neurodegenerative diseases. Future research will explore whether targeting transporters may
interfere with its accumulation, offering new therapeutic strategies for autism, PTSD and PD
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A new HPLC method with multiple detection systems for impurity analysis and discrimination of natural versus synthetic cannabidiol
No full textCannabidiol (CBD) is the main non-psychoactive phytocannabinoid derived from Cannabis sativa L. It is now an active pharmaceutical ingredient (API), given its usage in treating some types of pediatric epilepsy. For this reason, this compound requires a deep characterization in terms of purity and origin. Previous research work has shown two impurities in CBD samples from hemp inflorescences, namely, cannabidivarin (CBDV) and cannabidibutol (CBDB), while abnormal-cannabidiol (abn-CBD) has been described as the primary by-product that is generated from CBD synthesis. Both natural and synthetic CBD samples exhibit the presence of Delta 9-tetrahydrocannabinol (Delta 9-THC) and Delta 8-THC. This study aimed to develop a new analytical method based on high-performance liquid chromatography (HPLC) with different detection systems to study the purity of CBD and to define its origin based on the impurity profile. In addition to the above-mentioned cannabinoids, other compounds, such as cannabigerovarin (CBGV), cannabigerol (CBG), cannabichromevarin (CBCV), and cannabichromene (CBC), were examined as potential discriminating impurities. Qualitative and quantitative analyses were carried out by UHPLC-HRMS and HPLC-UV/Vis, respectively. Principal component analysis was applied for statistical exploration. Natural CBD samples exhibited purities ranging between 97.5 and 99.7%, while synthetic samples were generally pure, except for three initially labeled as synthetic, revealing natural-derived impurities. To further confirm the origin of CBD samples, the presence of other two minor impurities, namely cannabidihexol (CBDH) and cannabidiphorol (CBDP), was assessed as unequivocal for a natural origin. Finally, an enantioselective HPLC analysis was carried out and the results confirmed the presence of the (-)-trans enantiomer in all CBD samples. In conclusion, the HPLC method developed represents a reliable tool for detecting CBD impurities, thus providing a clear discrimination of the compound origin
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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