Identification and validation of oxidative stress-related genes in sepsis-induced myopathy.

BACKGROUND: Sepsis-induced myopathy (SIM) a complication of sepsis that results in prolonged mechanical ventilation, long-term functional disability, and increased patient mortality. This study was performed to identify potential key oxidative stress-related genes (OS-genes) as biomarkers for the diagnosis of SIM using bioinformatics. METHODS: The GSE13205 was obtained from the Gene Expression Omnibus (GEO) database, including 13 SIM samples and 8 healthy samples, and the differentially expressed genes (DEGs) were identified by limma package in R language. Simultaneously, we searched for the genes related to oxidative stress in the Gene Ontology (GO) database. The intersection of the genes selected from the GO database and the genes from the GSE13205 was considered as OS-genes of SIM, where the differential genes were regarded as OS-DEGs. OS-DEGs were analyzed using GO enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in OS-DEGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed. RESULTS: A total of 1089 DEGs were screened from the GSE13205, and 453 OS-genes were identified from the GO database. The overlapping DEGs and OS-genes constituted 25 OS-DEGs, including 15 significantly upregulated and 10 significantly downregulated genes. The top 10 hub genes, including CD36, GPX3, NQO1, GSR, TP53, IDH1, BCL2, HMOX1, JAK2, and FOXO1, were screened. Furthermore, 5 diagnostic genes were identified: CD36, GPX3, NQO1, GSR, and TP53. The ROC analysis showed that the respective area under the curves (AUCs) of CD36, GPX3, NQO1, GSR, and TP53 were 0.990, 0.981, 0.971, 0.971, and 0.971, which meant these genes had very high diagnostic values of SIM. Finally, based on these 5 diagnostic genes, we found that miR-124-3p and miR-16-5p may be potential targets for the treatment of SIM. CONCLUSIONS: The results of this study suggest that OS-genes might play an important role in SIM. CD36, GPX3, NQO1, GSR, and TP53 have potential as specific biomarkers for the diagnosis of SIM.

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing.

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcriptome sequencing and bulk RNA-seq. Using single-cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage-related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH-associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment.

Ultraviolet Protection From a Patented Amino Acid Complex Technology.

OBJECTIVE:   This study aimed to investigate the ultraviolet (UV) protection/repair benefits of a patented Amino Acid Complex (AAComplex). METHODS: I) AAComplex was incubated with dermal fibroblasts, with/without UVA, and collagen I was measured with a GlasBoxPlus device. II) A lotion, with/without AAComplex (1%) was applied topically to skin explants, following UVA irradiation, and quantified for health-related biomarkers (TNFalpha, histamine, and MMP-1). III) A broad spectrum sunscreen with SPF 46 and a skincare serum containing AAComplex (2%) were assessed using epidermal equivalents, in the presence of UV irradiation, for effects on IL-1alpha, thymine dimers, Ki-67, filaggrin and Nrf2. RESULTS: I) Collagen I synthesis in dermal fibroblasts was significantly decreased after UVA compared to without UV. The presence of AAComplex prevented this decrease. II) UVA irradiation of skin explants increased histamine, TNFα, and MMP-1. Hydrocortisone aceponate cream significantly decreases all 3 biomarkers. AAComplex contained lotion also significantly decreased all 3 biomarkers, the no AAComplex control lotion only reduced histamine. III) With the regimen of sunscreen + AAComplex contained skincare serum, the significant reduction in IL-1alpha was observed along with a complete recovery of Ki-67 and stimulation of filaggrin and Nrf2T. No thymine dimer positive cell was observed indicating the most positive skin impact from the regiment.  Conclusion: This research using different human skin models demonstrated that AAComplex can provide protection and damage repair caused by UV, at the ingredient level also when formulated in a serum or lotion formula. Skin may be best protected from UV damage when the regimen is used.   J Drugs Dermatol. 2024;23(5):366-375. doi:10.36849/JDD.7916.

Evaluating lumbar disc degeneration by MRI quantitative metabolic indicators: the perspective of factor analysis.

PURPOSE: This study aimed to investigate an early diagnostic method for lumbar disc degeneration (LDD) and improve its diagnostic accuracy. METHODS: Quantitative biomarkers of the lumbar body (LB) and lumbar discs (LDs) were obtained using nuclear magnetic resonance (NMR) detection technology. The diagnostic weights of each biological metabolism indicator were screened using the factor analysis method. RESULTS: Through factor analysis, common factors such as the LB fat fraction, fat content, and T2* value of LDs were identified as covariates for the diagnostic model for the evaluation of LDD. This model can optimize the accuracy and reliability of LDD diagnosis. CONCLUSION: The application of biomarker quantification methods based on NMR detection technology combined with factor analysis provides an effective means for the early diagnosis of LDD, thereby improving diagnostic accuracy and reliability.

Metabolomic pathways in food allergy.

Food allergy (FA) is a widespread issue, affecting as many as 10% of the population. Over the past two to three decades, the prevalence of FA has been on the rise, particularly in industrialized and westernized countries. FA is a complex, multifactorial disease mediated by type 2 immune responses and involving environmental and genetic factors. However, the precise mechanisms remain inadequately understood. Metabolomics has the potential to identify disease endotypes, which could beneficially promote personalized prevention and treatment. A metabolome approach would facilitate the identification of surrogate metabolite markers reflecting the disease activity and prognosis. Here, we present a literature overview of recent metabolomic studies conducted on children with FA.

A study on assessing the toxic effects of ethyl paraben on rohu (Labeo rohita) using different biomarkers; hemato-biochemical assays, histology, oxidant and antioxidant activity and genotoxicity.

Parabens are being used as preservatives due to their antifungal and antimicrobial effects. They are emerging as aquatic pollutants due to their excessive use in many products. The purpose of this study was to determine the toxic effect of ethyl paraben (C9H10O3) on the hematobiochemical, histological, oxidative, and anti-oxidant enzymatic and non-enzymatic activity; the study also evaluates the potential of ethyl paraben to cause genotoxicity in Rohu Labeo rohita. A number of 15 fish with an average weight of 35.45±1.34g were placed in each group and exposed to ethyl paraben for 21 days. Three different concentrations of ethyl paraben, i.e., T1 (2000µg/L), T2 (4000 µg/L), andT3 (6000 µg/L) on which fish were exposed as compared to the control T0 (0.00 µg/L). Blood was used for hematobiochemical and comet assay. Gills, kidneys, and liver were removed for histological alterations. The results showed a significant rise in all hemato-biochemical parameters such as RBCs, WBCs, PLT count, blood sugar, albumin, globulin, and cholesterol. An increase in aspartate aminotransferase (AST) and alanine transaminase (ALT) levels directed the hepatocytic damage. Histological alterations in the liver, gills and kidneys of fish were found. Ethylparaben induces oxidative stress by suppressing antioxidant enzyme activity such as SOD, GSH, CAT and POD. Based on the comet assay, DNA damage was also observed in blood cells, resulting in genotoxicity. Findings from the present study indicate that ethyl paraben induces hemato-biochemical alterations, tissue damage, oxidative stress, and genotoxicity.

[Clinical study of the cytokine panel in the diagnosis of ocular chronic graft-versus-host disease].

Objective: To investigate the association between cytokines and ocular chronic graft-versus-host disease (cGVHD) and identify specific biomarkers for ocular cGVHD to enhance clinical diagnosis, treatment, and evaluation. Methods: A mouse model of cGVHD was established to explore the correlation between cGVHD and serum cytokines. Based on the findings from the animal experiments and literature review, a panel of 16 cytokine combinations was identified. Enzyme-linked immunosorbent assay (ELISA) was used to compare the cytokine concentrations in the serum and tear samples from patients who underwent allogeneic hematopoietic stem cell transplantation from June 2017 to March 2022 at the Medical Center of Hematology, Xinqiao Hospital, Army Medical University. Results: ① Compared with the control group, mice with cGVHD exhibited elevated serum IL-1ß, IL-6, IL-8, IL-17, IFN-γ, CX3CL1, CXCL11, CXCL13, CCL11, and CCL19 concentrations (all P<0.05). ② Analysis of the cytokine profiles of the serum and tear samples revealed that compared with patients without ocular cGVHD, those with ocular cGVHD exhibited increased serum IL-8 [P=0.032, area under the curve (AUC) =0.678]; decreased serum IL-10 (P=0.030, AUC=0.701) ; elevated IL-8, IFN-γ, CXCL9, and CCL17 in tear samples; and lower IL-10 and CCL19 in tear samples (all P<0.05, all AUC>0.7). Moreover, cytokines in tear samples showed correlations with ocular surface parameters related to ocular cGVHD. Conclusions: Tear fluid demonstrates greater specificity and sensitivity as a biomarker for diagnosing ocular cGVHD than serum biomarkers. Among the identified cytokines in tear samples, IL-8, IL-10, IFN-γ, CXCL9, CCL17, and CCL19 serve as diagnostic biomarkers for ocular cGVHD post-transplantation, offering practical reference value for diagnosis.

A multiscale symbolic approach to decoding delta and ripple oscillation bands as biomarkers for epileptiform discharges.

We use a multiscale symbolic approach to study the complex dynamics of temporal lobe refractory epilepsy employing high-resolution intracranial electroencephalogram (iEEG). We consider the basal and preictal phases and meticulously analyze the dynamics across frequency bands, focusing on high-frequency oscillations up to 240 Hz. Our results reveal significant periodicities and critical time scales within neural dynamics across frequency bands. By bandpass filtering neural signals into delta, theta, alpha, beta, gamma, and ripple high-frequency bands (HFO), each associated with specific neural processes, we examine the distinct nonlinear dynamics. Our method introduces a reliable approach to pinpoint intrinsic time lag scales τ within frequency bands of the basal and preictal signals, which are crucial for the study of refractory epilepsy. Using metrics such as permutation entropy (H), Fisher information (F), and complexity (C), we explore nonlinear patterns within iEEG signals. We reveal the intrinsic τmax that maximize complexity within each frequency band, unveiling the nonlinear subtle patterns of the temporal structures within the basal and preictal signal. Examining the H×F and C×F values allows us to identify differences in the delta band and a band between 200 and 220 Hz (HFO 6) when comparing basal and preictal signals. Differences in Fisher information in the delta and HFO 6 bands before seizures highlight their role in capturing important system dynamics. This offers new perspectives on the intricate relationship between delta oscillations and HFO waves in patients with focal epilepsy, highlighting the importance of these patterns and their potential as biomarkers.

Integrating machine learning algorithms and single-cell analysis to identify gut microbiota-related macrophage biomarkers in atherosclerotic plaques.

Objective: The relationship between macrophages and the gut microbiota in patients with atherosclerosis remains poorly defined, and effective biological markers are lacking. This study aims to elucidate the interplay between gut microbial communities and macrophages, and to identify biomarkers associated with the destabilization of atherosclerotic plaques. The goal is to enhance our understanding of the underlying molecular pathways and to pave new avenues for diagnostic approaches and therapeutic strategies in the disease. Methods: This study employed Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis on atherosclerosis datasets to identify macrophage-associated genes and quantify the correlation between these genes and gut microbiota gene sets. The Random Forest algorithm was utilized to pinpoint PLEK, IRF8, BTK, CCR1, and CD68 as gut microbiota-related macrophage genes, and a nomogram was constructed. Based on the top five genes, a Non-negative Matrix Factorization (NMF) algorithm was applied to construct gut microbiota-related macrophage clusters and analyze their potential biological alterations. Subsequent single-cell analyses were conducted to observe the expression patterns of the top five genes and the interactions between immune cells. Finally, the expression profiles of key molecules were validated using clinical samples from atherosclerosis patients. Results: Utilizing the Random Forest algorithm, we ultimately identified PLEK, IRF8, CD68, CCR1, and BTK as gut microbiota-associated macrophage genes that are upregulated in atherosclerotic plaques. A nomogram based on the expression of these five genes was constructed for use as an auxiliary tool in clinical diagnosis. Single-cell analysis confirmed the specific expression of gut microbiota-associated macrophage genes in macrophages. Clinical samples substantiated the high expression of PLEK in unstable atherosclerotic plaques. Conclusion: Gut microbiota-associated macrophage genes (PLEK, IRF8, CD68, CCR1, and BTK) may be implicated in the pathogenesis of atherosclerotic plaques and could serve as diagnostic markers to aid patients with atherosclerosis.

Hyaluronidase inhibits TGF-ß-mediated rat periodontal ligament fibroblast expression of collagen and myofibroblast markers: An in vitro exploration of periodontal tissue remodeling.

OBJECTIVE: To determine the effect of hyaluronic acid (HA) degradation by hyaluronidase (HYAL) in inhibiting collagen fiber production by rat periodontal ligament cells (rPDLCs). DESIGN: Primary rPDLCs were isolated from the euthanized rats and used for in vitro experiments. The appropriate HYAL concentration was determined through CCK-8 testing for cytotoxicity detection and Alizarin red staining for mineralization detection. RT-qPCR and western blot assays were conducted to assess the effect of HYAL, with or without TGF-ß, on generation of collagen fiber constituents and expression of actin alpha 2, smooth muscle (ACTA2) of rPDLCs. RESULTS: Neither cell proliferation nor mineralization were significantly affected by treatment with 4 U/mL HYAL. HYAL (4 U/mL) alone downregulated type I collagen fiber (Col1a1 and Col1a2) and Acta2 mRNA expression; however, ACTA2 and COL1 protein levels were only downregulated by HYAL treatment after TGF-ß induction. CONCLUSIONS: Treatment of rPDLCs with HYAL can inhibit TGF-ß-induced collagen matrix formation and myofibroblast transformation.

Tear Proteomics in Infants at Risk of Retinopathy of Prematurity: A Feasibility Study.

Purpose: This feasibility study investigated the practicability of collecting and analyzing tear proteins from preterm infants at risk of retinopathy of prematurity (ROP). We sought to identify any tear proteins which might be implicated in the pathophysiology of ROP as well as prognostic markers. Methods: Schirmer's test was used to obtain tear samples from premature babies, scheduled for ROP screening, after parental informed consent. Mass spectrometry was used for proteomic analysis. Results: Samples were collected from 12 infants, which were all adequate for protein analysis. Gestational age ranged from 25 + 6 to 31 + 1 weeks. Postnatal age at sampling ranged from 19 to 66 days. One infant developed self-limiting ROP. Seven hundred one proteins were identified; 261 proteins identified in the majority of tear samples, including several common tear proteins, were used for analyses. Increased risk of ROP as determined by the postnatal growth ROP (G-ROP) criteria was associated with an increase in lactate dehydrogenase B chain in tears. Older infants demonstrated increased concentration of immunoglobulin complexes within their tear samples and two sets of twins in the cohort showed exceptionally similar proteomes, supporting validity of the analysis. Conclusions: Tear sampling by Schirmer test strips and subsequent proteomic analysis by mass spectrometry in preterm infants is feasible. A larger study is required to investigate the potential use of tear proteomics in identification of ROP. Translational Relevance: Tear sampling and subsequent mass spectrometry in preterm infants is feasible. Investigation of the premature tear proteome may increase our understanding of retinal development and provide noninvasive biomarkers for identification of treatment-warranted ROP.

MicroRNAs regulate the vicious cycle of vascular calcification-osteoporosis in postmenopausal women.

Menopause is a normal physiological process accompanied by changes in various physiological states. The incidence of vascular calcification (VC) increases each year after menopause and is closely related to osteoporosis (OP). Although many studies have investigated the links between VC and OP, the interaction mechanism of the two under conditions of estrogen loss remains unclear. MicroRNAs (miRNAs), which are involved in epigenetic modification, play a critical role in estrogen-mediated mineralization. In the past several decades, miRNAs have been identified as biomarkers or therapeutic targets in diseases. Thus, we hypothesize that these small molecules can provide new diagnostic and therapeutic approaches. In this review, we summarize the close interactions between VC and OP and the role of miRNAs in their interplay.

Dynamic molecular signatures of acute myocardial infarction based on transcriptomics and metabolomics.

Acute myocardial infarction (AMI) commonly precedes ventricular remodeling, heart failure. Few dynamic molecular signatures have gained widespread acceptance in mainstream clinical testing despite the discovery of many potential candidates. These unmet needs with respect to biomarker and drug discovery of AMI necessitate a prioritization. We enrolled patients with AMI aged between 30 and 70. RNA-seq analysis was performed on the peripheral blood mononuclear cells collected from the patients at three time points: 1 day, 7 days, and 3 months after AMI. PLC/LC-MS analysis was conducted on the peripheral blood plasma collected from these patients at the same three time points. Differential genes and metabolites between groups were screened by bio-informatics methods to understand the dynamic changes of AMI in different periods. We obtained 15 transcriptional and 95 metabolite expression profiles at three time points after AMI through high-throughput sequencing. AMI-1d: enrichment analysis revealed the biological features of 1 day after AMI primarily included acute inflammatory response, elevated glycerophospholipid metabolism, and decreased protein synthesis capacity. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) might stand promising biomarkers to differentiate post-AMI stage. Anti-inflammatory therapy during the acute phase is an important direction for preventing related pathology. AMI-7d: the biological features of this stage primarily involved the initiation of cardiac fibrosis response and activation of platelet adhesion pathways. Accompanied by upregulated TGF-beta signaling pathway and ECM receptor interaction, GP5 help assess platelet activation, a potential therapeutic target to improve haemostasis. AMI-3m: the biological features of 3 months after AMI primarily showed a vascular regeneration response with VEGF signaling pathway, NOS3 and SHC2 widely activated, which holds promise for providing new therapeutic approaches for AMI. Our analysis highlights transcriptional and metabolomics signatures at different time points after MI, which deepens our understanding of the dynamic biological responses and associated molecular mechanisms that occur during cardiac repair.

Estimating Gestational Age and Prediction of Preterm Birth Using Metabolomics Biomarkers.

Preterm birth (PTB) is a leading cause of morbidity and mortality in children aged under 5 years globally, especially in low-resource settings. It remains a challenge in many low-income and middle-income countries to accurately measure the true burden of PTB due to limited availability of accurate measures of gestational age (GA), first trimester ultrasound dating being the gold standard. Metabolomics biomarkers are a promising area of research that could provide tools for both early identification of high-risk pregnancies and for the estimation of GA and preterm status of newborns postnatally.

Mitochondria: A source of potential biomarkers for non-communicable diseases.

Mitochondria, as an endosymbiont of eukaryotic cells, controls multiple cellular activities, including respiration, reactive oxygen species production, fatty acid synthesis, and death. Though the majority of functional mitochondrial proteins are translated through a nucleus-controlled process, very few of them (∼10%) are translated within mitochondria through their own machinery. Germline and somatic mutations in mitochondrial and nuclear DNA significantly impact mitochondrial homeostasis and function. Such modifications disturbing mitochondrial biogenesis, metabolism, or mitophagy eventually resulted in cellular pathophysiology. In this chapter, we discussed the impact of mitochondria and its dysfunction on several non-communicable diseases like cancer, diabetes, neurodegenerative, and cardiovascular problems. Mitochondrial dysfunction and its outcome could be screened by currently available omics-based techniques, flow cytometry, and high-resolution imaging. Such characterization could be evaluated as potential biomarkers to assess the disease burden and prognosis.

Blood-brain barrier biomarkers.

The blood-brain barrier (BBB) is a dynamic interface that regulates the exchange of molecules and cells between the brain parenchyma and the peripheral blood. The BBB is mainly composed of endothelial cells, astrocytes and pericytes. The integrity of this structure is essential for maintaining brain and spinal cord homeostasis and protection from injury or disease. However, in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, and multiple sclerosis, the BBB can become compromised thus allowing passage of molecules and cells in and out of the central nervous system parenchyma. These agents, however, can serve as biomarkers of BBB permeability and neuronal damage, and provide valuable information for diagnosis, prognosis and treatment. Herein, we provide an overview of the BBB and changes due to aging, and summarize current knowledge on biomarkers of BBB disruption and neurodegeneration, including permeability, cellular, molecular and imaging biomarkers. We also discuss the challenges and opportunities for developing a biomarker toolkit that can reliably assess the BBB in physiologic and pathophysiologic states.

Metabolomics Analysis Identifies Differential Metabolites as Biomarkers for Acute Myocardial Infarction.

Myocardial infarction (MI), including ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI), is still a leading cause of death worldwide. Metabolomics technology was used to explore differential metabolites (DMs) as potential biomarkers for early diagnosis of STEMI and NSTEMI. In the study, 2531 metabolites, including 1925 DMs, were discovered. In the selected 27 DMs, 14 were successfully verified in a new cohort, and the AUC values were all above 0.8. There were 10 in STEMI group, namely L-aspartic acid, L-acetylcarnitine, acetylglycine, decanoylcarnitine, hydroxyphenyllactic acid, ferulic acid, itaconic acid, lauroylcarnitine, myristoylcarnitine, and cis-4-hydroxy-D-proline, and 5 in NSTEMI group, namely L-aspartic acid, arachidonic acid, palmitoleic acid, D-aspartic acid, and palmitelaidic acid. These 14 DMs may be developed as biomarkers for the early diagnosis of MI with high sensitivity and specificity. These findings have particularly important clinical significance for NSTEMI patients because these patients have no typical ECG changes.

Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease.

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Multispecies and multibiomarker assessment of fish health from Iguaçu River reservoir, Southern Brazil.

This study investigated the impact of micropollutants on fish health from Segredo hydroelectric reservoir (HRS) along the Iguaçu River, Southern Brazil, contaminated by urban, industrial, and agricultural activities. This is the first comprehensive study assessment in the river after the severe drought in the 2020s in three fish species from different trophic levels Astyanax spp. (water column depth/omnivorous), Hypostomus commersoni (demersal/herbivorous), and Pimelodus maculatus (demersal/omnivorous). Animals, water, and sediment samples were collected from three distinct sites within the reservoir: Floresta (upstream), Iratim (middle), and Station (downstream). The chemical analysis revealed elevated concentrations of metals (Al, Cu, Fe) and the metalloid As in water, or Cu, Zn, and As in sediment, surpassing Brazilian regulatory limits, while the organic pollutants as DDT, PAHs, PCBs, and PBDEs were found under the Brazilian regulatory limits. The metal bioaccumulation was higher in gills with no significant differences among sites. The species Astyanax spp. and H. commersoni displayed variations in hepatosomatic index (HSI) and P. maculatus in the condition factor index (K) between sites, while adverse effects due to micropollutants bioaccumulation were observed by biochemical, genotoxic, and histopathological biomarkers. The principal component analysis and integrated biomarker response highlighted the upstream site Floresta as particularly inhospitable for biota, with distinctions based on trophic level. Consequently, this multifaceted approach, encompassing both fish biomarkers and chemical analyses, furnishes valuable insights into the potential toxic repercussions of micropollutant exposure. These findings offer crucial data for guiding management and conservation endeavors in the Iguaçu River.

Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression.

BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disease with increasing prevalence. Effective diagnostic markers and therapeutic methods are still lacking. Exploring key molecular markers and mechanisms for PD can help with early diagnosis and treatment improvement. METHODS: Three datasets GSE174052, GSE77668, and GSE168496 were obtained from the GEO database to search differentially expressed circRNA (DECs), miRNAs (DEMis), and mRNAs (DEMs). GO and KEGG enrichment analyses, and protein-protein interaction (PPI) network construction were implemented to explore possible actions of DEMs. Hub genes were selected to establish circRNA-related competing endogenous RNA (ceRNA) networks. RESULTS: There were 1005 downregulated DECs, 21 upregulated and 21 downregulated DEMis, and 266 upregulated and 234 downregulated DEMs identified. The DEMs were significantly enriched in various PD-associated functions and pathways such as extracellular matrix organization, dopamine synthesis, PI3K-Akt, and calcium signaling pathways. Twenty-one hub genes were screened out, and a PD-related ceRNA regulatory network was constructed containing 31 circRNAs, one miRNA (miR-371a-3p), and one hub gene (KCNJ6). CONCLUSION: We identified PD-related molecular markers and ceRNA regulatory networks, providing new directions for PD diagnosis and treatment.