Identification Of Markers Research Articles

Role of liver sinusoidal endothelial cell damage in the developmental process of hepatic sinusoidal obstruction syndrome: a focus on the research progress of immune inflammatory mechanisms

Hepatic sinusoidal obstruction syndrome (HSOS) is a type of secondary vascular disease of the liver that is mainly associated with the ingestion of pyrrole alkaloids (PAs) and hematopoietic stem cell transplantation (HSCT) treatment, resulting in severe liver dysfunction, multiple organ failure, and even death. Hepatic sinusoidal dilatation and obstruction, hepatocyte coagulative necrosis, and hepatic lobular inflammation are the main pathological manifestations of HSOS. The key initiating process for the pathogenesis of HSOS is damage to liver sinusoidal endothelial cells (LSECs). Currently, it is believed that LSECs are damaged by the involvement of multiple etiologies and mechanisms, and secondary coagulation and fibrinolysis disorders, oxidative stress, and inflammatory responses are the occurrence contributors to HSOS; however, the mechanism has not been fully elucidated. Therefore, the role of immune-inflammatory mechanisms has received increasing attention in LSEC damage. This article provides an overview of the epidemiology, etiology, and pathological changes of HSOS and reviews the physiological functions, common etiological damage mechanisms, and the key role of LSEC damage in the pathogenesis of HSOS, with a special focus on the role and research progress of immune-inflammatory mechanisms for LSEC damage in recent years. Furthermore, we believe that in-depth study and elucidation of the role of immune-inflammatory mechanisms in LSEC damage and the pathogenesis of HSOS and diagnosis will provide feasible research and development ideas for the screening and identification of new markers and drug treatment targets for HSOS.

Roles of pyroptosis and immune infiltration in aortic dissection.

Introduction: Aortic dissection (AD) is often fatal, and its pathogenesis involves immune infiltration and pyroptosis, though the molecular pathways connecting these processes remain unclear. This study aimed to investigate the role of immune infiltration and pyroptosis in AD pathogenesis using bioinformatics analysis. Methods: Two Gene Expression Omnibus datasets and a Gene Cards dataset of pyroptosis-related genes (PRGs) were utilized. Immunological infiltration was assessed using CIBERSORT, and AD diagnostic markers were identified through univariate logistic regression and least absolute shrinkage and selection operator regression. Interaction networks were constructed using STRING, and weighted gene correlation network analysis (WGCNA) was employed to identify important modules and essential genes. Single-sample gene set enrichment analysis determined immune infiltration, and Pearson correlation analysis assessed the association of key genes with infiltrating immune cells. Results: Thirty-one PRGs associated with inflammatory response, vascular epidermal growth factor receptor, and Rap1 signaling pathways were identified. WGCNA revealed seven important genes within a critical module. CIBERSORT detected immune cell infiltration, indicating significant changes in immune cell infiltration and pyroptosis genes in AD and their connections. Discussion: Our findings suggest that key PRGs may serve as indicators for AD or high-risk individuals. Understanding the role of pyroptosis and immune cell infiltration in AD pathogenesis may lead to the development of novel molecular-targeted therapies for AD. Conclusion: This study provides insights into the molecular mechanisms underlying AD pathogenesis, highlighting the importance of immune infiltration and pyroptosis. Identification of diagnostic markers and potential therapeutic targets may improve the management of AD and reduce associated morbidity and mortality.

Identification of polymorphic markers for germplasm conservation of three precious Chinese palace goldfish using whole-genome sequencing.

China was the first country in the world to breed goldfish and has generated many unique goldfish varieties, including the most aristocratic Chinese palace goldfish. Due to the lack of scientific research on Chinese palace goldfish, their selection and breeding are mainly carried out through traditional hybridization, leading to serious inbreeding and the degradation of germplasm resources. To this end, whole-genome resequencing was performed to understand the genetic variation among three different varieties (eggpompons, goosehead, and tigerhead) from nine core conserved populations in China. A total of 15 polymorphic SSRs were developed for population genetics, and all tested populations were considered moderately polymorphic with an average polymorphism information content value of 0.4943. Genetic diversity in different varieties showed that all conserved populations were well protected with the potential for continued exploitation. This study provides reliable molecular tools and a basis for designing conservation and management programs in Chinese palace goldfish.

Cyto-swapping in maize by haploid induction with a cenh3 mutant.

Maize mutants of the centromeric histone H3 (CENP-A/CENH3) gene can form haploids that inherit only chromosomes of the pollinating parent but the cytoplasm from the female parent. We developed CENH3 haploid inducers carrying a dominant anthocyanin colour marker for efficient haploid identification and harbouring cytoplasmic male sterile cytoplasm, a type of cytoplasm that results in male sterility useful for efficient hybrid seed production. The resulting cytoplasmic male sterility cyto-swapping method provides a faster and cheaper way to convert commercial lines to cytoplasmic male sterile compared to conventional trait introgression.

From Code to Crop: How Bioinformatics is Transforming Crop Genomics in Modern Agriculture and Bettering Environment

Advancements in bioinformatics have ushered in a new era in modern agriculture by seamlessly integrating computational methodologies with crop genomics. This paper explores the transformative impact of bioinformatics on crop genomics and its consequential benefits for both agriculture and the environment. Bioinformatics tools and techniques are instrumental in decoding the intricate genetic information of crops, leading to the development of tailored solutions for improved crop yield, resistance to diseases, and environmental sustainability. The first aspect of this transformation involves the utilization of high-throughput sequencing technologies, which generate vast amounts of genomic data. Bioinformatics algorithms play a crucial role in processing and analysing these data sets, enabling researchers to unravel the complex genetic codes of crops efficiently. This genomic information serves as a foundation for precision breeding programs, allowing scientists to identify desirable traits and accelerate the development of crops with enhanced resilience and productivity. Furthermore, bioinformatics facilitates the identification of molecular markers associated with key agronomic traits. This information enables the implementation of marker-assisted breeding, a technique that expedites the selection of desired traits in crops, reducing the time and resources required for traditional breeding methods. The result is the development of crop varieties that are not only more productive but also more resistant to pests and diseases, contributing to global food security. Beyond enhancing crop performance, bioinformatics-driven crop genomics also addresses environmental concerns. By deciphering the genetic basis of stress tolerance and resource- use efficiency, researchers can develop crops that require fewer inputs such as water, fertilizers, and pesticides. This not only benefits farmers economically but also reduces the ecological footprint of agriculture, promoting sustainable practices and minimizing environmental impact.

Diagnosis of oral cancer using biomarkers, a non invasive proposal

The present study aimed to identify, through scientific literature, the use of biomarkers that help in the diagnosis of cancer in the oral cavity. This is a narrative review study with a qualitative and descriptive approach. To investigate the data, the databases of Periódicos Capes, PubMed and Sciencedirect were used, on the use of scientific articles, published during the time frame from 2019 to 2023, in Portuguese, English and Spanish, available online and free of charge, with expanded summary and in full text format. After applying filters, selecting descriptors and including review studies, meta-analysis, controlled and randomized tests, 52 articles were identified, among which 27 were from PubMed, 14 from Periódicos Capes and 11 from Science direct, in addition considering suitability, only 17 articles were registered for review. In this important study, it became evident that despite advances in the identification of tumor markers, they still do not have sufficient capacity to diagnose cancer in the oral cavity. However, it highlights its influence as an important tool for the prognosis of clinical conditions. Furthermore, it appears as a less invasive alternative, with more accessible samples such as saliva and promising results.

Integrated diagnosis of grade 3-4 gliomas using targeted next-generation sequencing and traditional diagnostic data, and its overall implications on patient management

Adult gliomas vary significantly in terms of their genetics, epigenetics, phenotypes as well as clinical outcomes [1]. Optimal tumor classification that leads to more precise diagnoses, and which influences therapy selection is hence critically important. Targeted next-generation sequencing (NGS) is a highly reliable and efficient novel tool for the identification of biomarkers for the diagnosis of CNS tumors [2]. In this study, we aimed to determine the implications of integrating NGS findings with the traditional diagnostic data on clinical diagnostics and patient management. All patients who were diagnosed with glioma at our institution between 2019 and 2020 and whose tumor biopsy materials were analyzed by both traditional histomorphological and immunohistochemical diagnostic techniques as well as NGS were included in our study. Patients’ information was retrieved from the electronic medical record. Data analyzed included the histopathologic diagnosis, tumor grade, ki67, and the mutation status of TP53 and /or IDH, as well as other genes such as BRAF and HER2 for some patients. The overall concordance between NGS and the traditional diagnostic tools for IDH and TP53 mutations was also evaluated. Further, we derived the overall survival of patients using the Kaplan–Meier estimate. We identified 9 patients with grade 3-4 gliomas whose biopsy materials were analyzed by NGS as well as traditional diagnostic tools. Our patients were 33.3 % females and had a median age of 43 years old at diagnosis. In terms of the identification of gene mutations by NGS in comparison to immunohistochemistry (IHC), it was found that the concordance for mutant identification was 77.8 % (7/9) for IDH mutations and 55.6 % (5/9) for TP53 mutations. NGS further led to a change in patient management in which evidence-based targeted therapy (dabrafenib plus trametinib) was used for one patient (11.1 %) with BRAF V600E mutated astroblastoma. Integrating NGS with traditional diagnostic tools for the diagnosis of gliomas can have significant implications on patients. Such integrated diagnosis can lead to more precise diagnosis, enhanced identification of molecular markers, and offers the potential of using targeted therapies for patients.

Stylometry and Deep Learning: A case study on Milan Kundera's Le Livre du rire et de l'oubli

This study aims to uncover the prototypical linguistic elements and patterns of Kundera's prose in his
 novel Le Livre du rire et de l'oubli (1979, Gallimard). The exploration employs statistical and machine
 learning techniques, including the application of Hyperbase in both its web and standard versions.
 Hyperbase provides deep learning features for text classification tasks (Savoy 2015; Tuzzi & Cortelazzo
 2018), based on convolutional neural networks (Kalchbrenner et al. 2014; Kim 2014) which go beyond
 the process of convolution and incorporate an innovative deconvolution mechanism that extracts key
 linguistic markers essential for classification purposes (Vanni et al. 2018; Mayaffre & Vanni 2021). The
 training of the Hyperbase deep learning model involves an extensive corpus containing novels by 36
 authors, including Kundera, thus encompassing the French literature landscape from 1960-2014. The
 study leads to the identification of linguistic markers related to vocabulary, morphosyntax, lexical and
 grammatical patterns, and lexico-grammatical structures. These markers are then examined to reveal
 the underlying aesthetic intentions of the author. The conclusion focuses on the contribution of deep
 learning and statistics in the context of this qualitative linguistic study of a literary text.

Identification of New Markers of Angiogenic Sprouting Using Transcriptomics: New Role for RND3.

New blood vessel formation requires endothelial cells to transition from a quiescent to an invasive phenotype. Transcriptional changes are vital for this switch, but a comprehensive genome-wide approach focused exclusively on endothelial cell sprout initiation has not been reported. Using a model of human endothelial cell sprout initiation, we developed a protocol to physically separate cells that initiate the process of new blood vessel formation (invading cells) from noninvading cells. We used this model to perform multiple transcriptomics analyses from independent donors to monitor endothelial gene expression changes. Single-cell population analyses, single-cell cluster analyses, and bulk RNA sequencing revealed common transcriptomic changes associated with invading cells. We also found that collagenase digestion used to isolate single cells upregulated the Fos proto-oncogene transcription factor. Exclusion of Fos proto-oncogene expressing cells revealed a gene signature consistent with activation of signal transduction, morphogenesis, and immune responses. Many of the genes were previously shown to regulate angiogenesis and included multiple tip cell markers. Upregulation of SNAI1 (snail family transcriptional repressor 1), PTGS2 (prostaglandin synthase 2), and JUNB (JunB proto-oncogene) protein expression was confirmed in invading cells, and silencing JunB and SNAI1 significantly reduced invasion responses. Separate studies investigated rounding 3, also known as RhoE, which has not yet been implicated in angiogenesis. Silencing rounding 3 reduced endothelial invasion distance as well as filopodia length, fitting with a pathfinding role for rounding 3 via regulation of filopodial extensions. Analysis of in vivo retinal angiogenesis in Rnd3 heterozygous mice confirmed a decrease in filopodial length compared with wild-type littermates. Validation of multiple genes, including rounding 3, revealed a functional role for this gene signature early in the angiogenic process. This study expands the list of genes associated with the acquisition of a tip cell phenotype during endothelial cell sprout initiation.

Risk factors and related miRNA phenotypes of chronic pain after thoracoscopic surgery in lung adenocarcinoma patients.

Chronic postsurgical pain may have a substantial impact on patient's quality of life, and has highly heterogenous presentation amongst sufferers. We aimed to explore the risk factors relating to chronic pain and the related miRNA phenotypes in patients with lung adenocarcinoma after video-assisted thoracoscopic lobectomy to identify potential biomarkers. Our prospective study involved a total of 289 patients with early invasive adenocarcinoma undergoing thoracoscopic lobotomy and a follow-up period of 3 months after surgery. Blood was collected the day before surgery for miRNA detection and patient information including operation duration, duration of continuous drainage of the chest, leukocyte count before and after operation, and postoperative pain scores were recorded. Using clinical and biochemical information for each patient, the risk factors for chronic postsurgical pain and related miRNA phenotypes were screened. We found that chronic postsurgical pain was associated with higher body mass index; greater preoperative history of chronic pain; longer postoperative drainage tube retention duration; higher numerical rating scale scores one, two, and three days after surgery; and changes in miRNA expression, namely lower expression of miRNA 146a-3p and higher expression of miRNA 550a-3p and miRNA 3613-3p in peripheral blood (p < 0.05). Of these factors, patient body mass index, preoperative history of chronic pain, average numerical rating scale score after operation, and preoperative peripheral blood miRNA 550a-3P expression were independent risk factors for the development of chronic postsurgical pain. Identification of individual risk markers may aid the development and selection of appropriate preventive and control measures.

DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination.

Aim: To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the currentlimited understanding. Materials & methods: Genetically predicted DNA methylation models wereestablished(n=2478). These models were applied to genome-wide association study data on HST. Then, a poly-methylationrisk score (PMRS) was established in 241,008 individuals from theUK Biobank. Results: Of the 63,046 CpGs from the prediction models, 13 novel CpGs wereassociated with HST. Furthermore, people with high PMRSs showed higher HST risk (hazard ratio: 1.18; 95% CI: 1.13-1.25). Conclusion: The study indicates that DNA methylationmay influence HST by regulating the expression of genes (e.g., PRMT6, CTSK). PMRSs have apromising application in discriminating subpopulations to facilitate early prevention.

Alzheimer's Disease Diagnosis in the Preclinical Stage: Normal Aging or Dementia.

Alzheimer's disease (AD) progressively impairs the memory and thinking skills of patients, resulting in a significant global economic and social burden each year. However, diagnosis of this neurodegenerative disorder can be challenging, particularly in the early stages of developing cognitive decline. Current clinical techniques are expensive, laborious, and invasive, which hinders comprehensive studies on Alzheimer's biomarkers and the development of efficient devices for Point-of-Care testing (POCT) applications. To address these limitations, researchers have been investigating various biosensing techniques. Unfortunately, these methods have not been commercialized due to several drawbacks, such as low efficiency, reproducibility, and the lack of accurate identification of AD markers. In this review, we present diverse promising hallmarks of Alzheimer's disease identified in various biofluids and body behaviors. Additionally, we thoroughly discuss different biosensing mechanisms and the associated challenges in disease diagnosis. In each context, we highlight the potential of realizing new biosensors to study various features of the disease, facilitating its early diagnosis in POCT. This comprehensive study, focusing on recent efforts for different aspects of the disease and representing promising opportunities, aims to conduct the future trend toward developing a new generation of compact multipurpose devices that can address the challenges in the early detection of AD.

Assembly and characterization of the complete mitochondrial genome of Descurainia sophia: a medical plant producing glucosinolate

As a commonly used traditional Chinese medicine, Descurainia sophia has various reported pharmacological activities such as prevention of chronic diseases, cardiovascular protection, neuroprotection, anticancer, antioxidant, and has high nutritional values, but its mitochondrial genome (mitogenome) has not been reported. In this study, the D. sophia mitogenome was sequenced, assembled and annotated using next generation sequencing technologies on the Illumina HiSeq and PacBio Sequel platform. The results showed that the D. sophia mitogenome was a circular DNA molecule with the length of 265,457 bp and the GC content of 44.78%, encoding unique 56 genes, including 35 protein coding genes, 18 tRNA genes and 3 rRNA genes. We analyzed codon preference, repeated sequences, DNA sequence transformation, phylogenetic relationship, RNA editing and synteny in the D. sophia mitogenome. Based on the DNA sequences of mitogenomes, the phylogenetic and synteny analysis indicated that D. sophia was more closely related to Boechera stricta, and the mitogenome of D. sophia underwent frequent genome recombination. In this study, we obtained the complete mitogenome of D. sophia, which can provide valuable data support for future studies on genetic characteristics, phylogenetic relationships, species identification and development of new molecular markers in D. sophia.

Identification of Volatile Markers in Sweat for COVID‐19 Screening by Gas Chromatography‐Mass Spectrometry

AbstractDue to an outbreak of coronavirus spreading in recent years, there is an urgent need for effective, rapid, and non‐invasive diagnostics to detect and differentiate among patients who are infected and uninfected with SARS‐CoV‐2 for controlling the virus propagation. This study developed an alternative method for COVID‐19 screening from volatile analysis of metabolites mainly studied in sweat samples obtained from the populations in Bangkok, Thailand, during December 2020 to April 2022. A total of 140 collected samples; 70 positive confirmed COVID‐19 cases and another 70 negatives confirmed COVID‐19 cases were applied to be separated, detected, and identified as volatile organic compounds (VOCs)/odor occurring from SARS‐CoV‐2 infection body by the technique of Headspace solid‐phase microextraction gas chromatography‐mass spectrometry (HS‐SPME‐GC‐MS) together with principle component analysis (PCA), which allowed potential volatile markers of COVID‐19 such as pentadecane, nonanal, styrene, xylene, ethylbenzene, and 2‐ethylhexyl acrylate (up to 94 % accuracy, 93 % sensitivity, 96 % selectivity, and 94 % specificity), respectively, along with limit of detection in a range of 0.26–125 μg. The result was validated by comparison with the RT‐PCR results.

Ultrasensitive Electrochemical Immunosensor for Multiplex Sandwich Bioassaying Based on the Functional Antibodies.

In vitro diagnostics (IVDs) based on electrochemical immunosensors are crucial for disease screening, diagnosis, prognosis, and treatment monitoring. However, label-free electrochemical immunosensors commonly suffer from poor specificity, leading to false positives. To address this issue, we propose a highly sensitive and precise electrochemical immunosensor for protein marker detection. This approach involves directly labeling the detection antibodies (Ab2) with thionine (Thi). The Ab2 labeled by Thi exhibits a distinct redox peak upon targeted voltage stimulation, enabling accurate quantification of protein biomarkers. Thi-modified antibodies provide significant advantages over traditional antibody modification methods, such as enhanced detection sensitivity, improved accuracy, and specificity in protein marker identification. The method is straightforward and efficient, ensuring specific analyte detection while minimizing interference from other substances in the sample. Additionally, a multielectrode detection method was employed, achieving remarkably low limits of detection (LoDs) for tumor necrosis factor-alpha (TNF-alpha), cardiac troponin I (cTnI), and interleukin-6 (IL-6), with LoDs of 9.38 fg/mL, 1.70 fg/mL, and 8.14 fg/mL, respectively. The proposed electrochemical immunosensor also exhibited high selectivity and repeatability, with relative standard deviations (RSD) of 6.39% for TNF-alpha, 2.42% for cTnI, and 2.72% for IL-6 (n = 5). Moreover, it demonstrated high sensitivity and was evaluated for serum detection using the standard addition method. The results highlight the great potential of the proposed electrochemical immunosensor for clinical applications, offering a novel approach for future utilization in clinical settings.

Oxidative stress as markers in identification of aluminum-tolerant peach tree rootstock cultivars and clonal selections

ABSTRACT Peach rootstock and scion cultivars are selected in breeding programs considering resistance to pests and diseases, salt tolerance, drought tolerance, and vigor. However, rootstock tolerance to aluminum (Al), which is markedly present in tropical and subtropical soils of the world, is not considered. Thus, it is essential to define potential markers that can contribute to the selection of Al-resistant or Al-tolerant peach rootstocks. The objective of this study was to identify Al-tolerant peach tree rootstock cultivars and clonal selections using physiological and oxidative stress variables. A completely randomized experimental design was used in a 13 (rootstock cultivars and clonal selections) × 2 (with and without Al) factorial arrangement, with three replications. Nursery peach trees of own-rooted ‘BRS Mandinho’ (without rootstock) and nursery trees of ‘BRS Mandinho’ grafted on different rootstock cultivars and clonal selections were grown in a hydroponic system, consisting of two treatments, with and without 100 mg L -1 of Al. Dry biomass, photosynthetic variables, pigment concentration, hydrogen peroxide content, membrane lipid peroxidation, and activity of the antioxidant enzymes were evaluated. The total dry matter production of the own-rooted ‘BRS Mandinho’ trees and the SS-CHI-09-39 and SS-CHI-09-40 selections is affected by the Al presence, representing a decline of 35.4, 37.2, and 24.4 %, respectively, compared to the treatment with Al. The highest total dry matter production in Al presence was observed for the ‘Sharpe’ rootstock. ‘Capdeboscq’, DB-SEN-09-23, FB-ESM-09-43, JB-ESM-09-13, JAH-MAC-09-77, SAS-SAU-09-71, and VEH-GRA-09-55 rootstock selections are tolerant to Al. The use of physiological and biochemical variables shows potential for the selection of clonal rootstocks tolerant or resistant to Al.

Identification of diagnostic markers for moyamoya disease by combining bulk RNA-sequencing analysis and machine learning

Moyamoya disease (MMD) remains a chronic progressive cerebrovascular disease with unknown etiology. A growing number of reports describe the development of MMD relevant to infection or autoimmune diseases. Identifying biomarkers of MMD is to understand the pathogenesis and development of novel targeted therapy and may be the key to improving the patient’s outcome. Here, we analyzed gene expression from two GEO databases. To identify the MMD biomarkers, the weighted gene co-expression network analysis (WGCNA) and the differential expression analyses were conducted to identify 266 key genes. The KEGG and GO analyses were then performed to construct the protein interaction (PPI) network. The three machine-learning algorithms of support vector machine-recursive feature elimination (SVM-RFE), random forest and least absolute shrinkage and selection operator (LASSO) were used to analyze the key genes and take intersection to construct MMD diagnosis based on the four core genes found (ACAN, FREM1, TOP2A and UCHL1), with highly accurate AUCs of 0.805, 0.903, 0.815, 0.826. Gene enrichment analysis illustrated that the MMD samples revealed quite a few differences in pathways like one carbon pool by folate, aminoacyl-tRNA biosynthesis, fat digestion and absorption and fructose and mannose metabolism. In addition, the immune infiltration profile demonstrated that ACAN expression was associated with mast cells resting, FREM1 expression was associated with T cells CD4 naive, TOP2A expression was associated with B cells memory, UCHL1 expression was associated with mast cells activated. Ultimately, the four key genes were verified by qPCR. Taken together, our study analyzed the diagnostic biomarkers and immune infiltration characteristics of MMD, which may shed light on the potential intervention targets of moyamoya disease patients

DNA Identifications for Wheat Improvement: Targeting Disease Resistance, Quality Traits, and Yield Potential

The pursuit of enhancing wheat cultivars to meet the challenges of evolving pathogens, quality demands, and yield optimization necessitates a profound understanding of the underlying genetic architecture. This review delves into recent advancements in DNA identification techniques and their pivotal role in elucidating key genetic markers associated with disease resistance, quality attributes, and yield potential in wheat. By integrating genomic tools with traditional breeding methods, researchers have made significant strides in pinpointing genomic regions linked to resistance against major pathogens, including rusts, powdery mildew, and Fusarium head blight. Moreover, the identification of genetic markers governing traits such as grain protein content, dough strength, and micronutrient composition has provided breeders with precise targets for improving wheat quality. Furthermore, the exploration of genomic regions associated with yield-related traits, such as biomass accumulation, flowering time, and stress tolerance, holds promise for enhancing wheat productivity under diverse environmental conditions. This synthesis underscores the importance of leveraging DNA identification strategies to expedite the development of resilient, high-quality, and high-yielding wheat varieties, thus contributing to global food security and sustainability in agriculture.

Metabolite markers for three synthetic tryptamines N-ethyl-N-propyltryptamine, 4-hydroxy-N-ethyl-N-propyltryptamine, and 5-methoxy-N-ethyl-N-propyltryptamine.

N-Ethyl-N-propyltryptamine (EPT), 4-hydroxy-N-ethyl-N-propyltryptamine (4-OH-EPT), and 5-methoxy-N-ethyl-N-propyltryptamine (5-MeO-EPT) are new psychoactive substances classified as tryptamines, sold online. Many tryptamines metabolize rapidly, and identifying the appropriate metabolites to reveal intake is essential. While the metabolism of 4-OH-EPT and 5-MeO-EPT are not previously described, EPT is known to form metabolites by indole ring hydroxylation among others. Based on general knowledge of metabolic patterns, 5-MeO-EPT is also expected to form ring hydroxylated EPT (5-OH-EPT). In the present study, the aim was to characterize the major metabolites of EPT, 4-OH-EPT, and 5-MeO-EPT, to provide markers for substance identification in forensic casework. The tryptamines were incubated with pooled human liver microsomes at 37°C for up to 4 h. The generated metabolites were separated and detected by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry analysis. The major in vitro EPT metabolites were formed by hydroxylation, N-dealkylation, and carbonylation. In comparison, 4-OH-EPT metabolism was dominated by double bond formation, N-dealkylation, hydroxylation, and carbonylation in vitro and hydroxylation or carbonylation combined with double bond loss, carbonylation, N-dealkylation, and hydroxylation in vivo. 5-MeO-EPT was metabolized by O-demethylation, hydroxylation, and N-dealkylation in vitro. The usefulness of the characterized metabolites in forensic casework was demonstrated by identification of unique metabolites for 4-OH-EPT in a human postmortem blood sample with suspected EPT or 4-OH-EPT intoxication.

Linguistic markers for major depressive disorder: a cross-sectional study using an automated procedure.

The identification of language markers, referring to both form and content, for common mental health disorders such as major depressive disorder (MDD), can facilitate the development of innovative tools for early recognition and prevention. However, studies in this direction are only at the beginning and are difficult to implement due to linguistic variability and the influence of cultural contexts. This study aims to identify language markers specific to MDD through an automated analysis process based on RO-2015 LIWC (Linguistic Inquiry and Word Count). A sample of 62 medicated patients with MDD and a sample of 43 controls were assessed. Each participant provided language samples that described something that was pleasant for them. (1) Screening tests for MDD (MADRS and DASS-21); (2) Ro-LIWC2015 - Linguistic Inquiry and Word Count - a computerized text analysis software, validated for Romanian Language, that analyzes morphology, syntax and semantics of word use. Depressive patients use different approaches in sentence structure, and communicate in short sentences. This requires multiple use of the punctuation mark period, which implicitly requires directive communication, limited in exchange of ideas. Also, participants from the sample with depression mostly use impersonal pronouns, first person pronoun in plural form - not singular, a limited number of prepositions and an increased number of conjunctions, auxiliary verbs, negations, verbs in the past tense, and much less in the present tense, increased use of words expressing negative affects, anxiety, with limited use of words indicating positive affects. The favorite topics of interest of patients with depression are leisure, time and money. Depressive patients use a significantly different language pattern than people without mood or behavioral disorders, both in form and content. These differences are sometimes associated with years of education and sex, and might also be explained by cultural differences.