Search Results (14)

Background: Aging is associated with the development of various disorders, including postural imbalance, which increases the risk of falls and related health complications. This study examines changes in static postural balance after a 4-week intervention involving appropriate exercise and an optimized daily regimen. Additionally, it explores the relationship between these changes and the steroidome. Methods: The study was conducted on a clinically homogeneous group of 41 females around their sixth decade, diagnosed with anxiety-depressive syndrome and treated with selective serotonin reuptake inhibitors (SSRIs). Postural balance was assessed using the dual-scales method (DLLL-DSM), which estimates postural imbalance by evaluating differences in the lower limb load in the standing position. Correlations between initial DLLL-DSM values, age, BMI, and the baseline levels of nine serum steroids, as well as post-intervention changes in five steroids, were analyzed using multivariate regression (OPLS model). Results: A significant reduction in lower limb load differences (-ΔDLLL-DSM), indicating improved postural balance, was observed. The -ΔDLLL-DSM strongly correlated with initial DLLL-DSM values, age, BMI, initial levels of nine serum steroids, and post-intervention changes in five steroids (R = 0.892, p < 0.001). Furthermore, initial DLLL-DSM values negatively correlated with adrenal androgen androstenediol sulfate and various sulfated 5α/β-reduced androgen metabolites (R = 0.323, p < 0.05), suggesting that the activity of steroid sulfotransferase (SULT2A1) and C17-hydroxylase-C17,20-lyase (CYP17A1) at the lyase step is negatively associated with postural imbalance in elderly females. Conclusions: The findings suggest that even severe postural imbalance can be effectively and relatively rapidly improved through an appropriate exercise-based intervention and an optimized daily regimen, provided that initial adrenal activity is not significantly impaired. Additionally, the identified associations between steroid levels and postural balance provide new insights into the hormonal mechanisms regulating balance control in older individuals. Full article

Sulfation plays a critical role in the biosynthesis of small molecules, regulatory mechanisms such as hormone signaling, and detoxification processes (phase II enzymes). The sulfation reaction is catalyzed by a broad family of enzymes known as sulfotransferases (SULTs), which have been extensively studied in animals due to their medical importance, but also in plant key processes. Despite the identification of some sulfated metabolites in fungi, the mechanisms underlying fungal sulfation remain largely unknown. To address this knowledge gap, we conducted a comprehensive search of available genomes, resulting in the identification of 174 putative SULT genes in the Ascomycota phylum. Phylogenetic analysis and structural modeling revealed that these SULTs belong to the aryl sulfotransferase family, and they are divided into two potential distinct clusters of PAPS-dependent SULTs within the fungal kingdom. SULT genes from two marine fungi isolated from deep-sea hydrothermal vents, Hortaea werneckii UBOCC-A-208029 (HwSULT) and Aspergillus sydowii UBOCC-A-108050 SULT (AsSULT), were selected as representatives of each cluster. Recombinant proteins were expressed in Escherichia coli and biochemically characterized. HwSULT demonstrated high and versatile activity, while AsSULT appeared more substrate-specific. Here, HwSULT was used to sulfate the mycotoxin zearalenone, enhancing its cytotoxicity toward healthy feline intestinal cells. Full article

Copy number variation (CNV) serves as a crucial source of genomic variation and significantly aids in the mining of genomic information in cattle. This study aims to analyze re–sequencing data from Chinese Hainan yellow cattle, to uncover breed CNV information, and to elucidate the resources of population genetic variation. We conducted whole–genome sequencing on 30 Chinese Hainan yellow cattle, thus generating 814.50 Gb of raw data. CNVs were called using CNVnator software, and subsequent filtering with Plink and HandyCNV yielded 197,434 high–quality CNVs and 5852 CNV regions (CNVRs). Notably, the proportion of deleted sequences (81.98%) exceeded that of duplicated sequences (18.02%), with the lengths of CNVs predominantly ranging between 20 and 500 Kb This distribution demonstrated a decrease in CNVR count with increasing fragment length. Furthermore, an analysis of the population genetic structure using CNVR databases from Chinese, Indian, and European commercial cattle breeds revealed differences between Chinese Bos indicus and Indian Bos indicus. Significant differences were also observed between Hainan yellow cattle and European commercial breeds. We conducted gene annotation for both Hainan yellow cattle and European commercial cattle, as well as for Chinese Bos indicus and Indian Bos indicus, identifying 206 genes that are expressed in both Chinese and Indian Bos indicus. These findings may provide valuable references for future research on Bos indicus. Additionally, selection signatures analysis based on Hainan yellow cattle and three European commercial cattle breeds identified putative pathways related to heat tolerance, disease resistance, fat metabolism, environmental adaptation, candidate genes associated with reproduction and the development of sperm and oocytes (CABS1, DLD, FSHR, HSD17B2, KDM2A), environmental adaptation (CNGB3, FAM161A, DIAPH3, EYA4, AAK1, ERBB4, ERC2), oxidative stress anti–inflammatory response (COMMD1, OXR1), disease resistance (CNTN5, HRH4, NAALADL2), and meat quality (EHHADH, RHOD, GFPT1, SULT1B1). This study provides a comprehensive exploration of CNVs at the molecular level in Chinese Hainan yellow cattle, offering theoretical support for future breeding and selection programs aimed at enhancing qualities of this breed. Full article

The challenges resulting from rapid economic growth, urbanization, and increased motorization in developing nations necessitate a comprehensive and sustainable approach to urban public transport planning. While sustainable urban public transport (SUPT) planning offers a solution, the complexity of choosing suitable policy measure options remains a challenge. This study first introduces a decision support framework (DSF) that integrates the sustainable urban public transport manual (SUPTM) adopted for generating the potential SUPT policy measure options, the KonSULT knowledge base applied for providing the performance scores of each measure option for all determined criteria, and the HMADM (including FAHP, FSM, and TOPSIS) technique to create, rank, and select SUPT policy measure options tailored to medium-sized urban areas in developing nations. A case study of Khon Kaen City, Thailand, illustrates the practical application of the framework, resulting in a set of 31 (91.2%) out of the total of 34 ranked policy measure options. Comparing these prioritizations with the city’s existing plan reveals a substantial agreement, which suggests the potential applicability of the DSF. Overall, the DSF marks a significant advancement in SUPT planning, which is crucial for shaping efficient, equitable, and environmentally conscious urban mobility in developing countries, which are undergoing transformative change. Full article

Sulfotransferases (SULTs) are phase II metabolizing enzymes catalyzing the sulfoconjugation from the co-factor 3′-Phosphoadenosine 5′-Phosphosulfate (PAPS) to a wide variety of endogenous compounds, drugs and natural products. Although SULT1A1 and SULT1A3 share 93% identity, SULT1A1, the most abundant SULT isoform in humans, exhibits a broad substrate range with specificity for small phenolic compounds, while SULT1A3 displays a high affinity toward monoamine neurotransmitters like dopamine. To elucidate the factors determining the substrate specificity of the SULT1 isoenzymes, we studied the dynamic behavior and structural specificities of SULT1A1 and SULT1A3 by using molecular dynamics (MD) simulations and ensemble docking of common and specific substrates of the two isoforms. Our results demonstrated that while SULT1A1 exhibits a relatively rigid structure by showing lower conformational flexibility except for the lip (loop L1), the loop L2 and the cap (L3) of SULT1A3 are extremely flexible. We identified protein residues strongly involved in the recognition of different substrates for the two isoforms. Our analyses indicated that being more specific and highly flexible, the structure of SULT1A3 has particularities in the binding site, which are crucial for its substrate selectivity. Full article

Background: Androgenetic alopecia (AGA) and alopecia areata (AA) are the most common types of non-cicatricial alopecia. Both diseases have limited effective therapeutic options and affect patient quality of life. Pharmacogenetic tests can help predict the most appropriate treatment option by evaluating the single nucleotide polymorphisms (SNPs) corresponding to genes related to alopecia. The objective of the study was to evaluate and compare selected SNPs and genes in AA and AGA patients from Romania and Brazil. Materials and Methods: We performed a retrospective study regarding the associations between AA and AGA and 45 tag SNPs of 15 genes in 287 Romanian and 882 Brazilian patients. The DNA samples were collected from oral mucosa using a swab. The SNPs were determined by the qPCR technique. Each genetic test displays the subject’s genotype of the selected gene and the prediction of a successful treatment (e.g., genotype AA of the GR-alpha gene is related to a predisposition to normal sensibility to topical glucocorticoid, and, therefore, glucocorticoids should be effective). Results: The GR-alpha, GPR44-2, SULT1A1, and CRABP2 genes were statistically significantly different in Brazil compared to Romania. The SULT1A1 activity that predicts the response to minoxidil treatment showed in our analysis that minoxidil is recommended in half of the cases of AGA and AA. Patients with AGA and a high expression of SRD5A1 or PTGFR-2 may benefit from Dutasteride or Latanoprost treatment, respectively. Most of the studied genes showed no differences between the two populations. Conclusions: The DNA analysis of the patients with alopecia may contribute to a successful treatment. Full article

Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients. Full article

In this study, we have evaluated whether 57 genome-wide association studies (GWAS)-identified common variants for type 2 diabetes (T2D) influence the risk of developing prostate cancer (PCa) in a population of 304 Caucasian PCa patients and 686 controls. The association of selected single nucleotide polymorphisms (SNPs) with the risk of PCa was validated through meta-analysis of our data with those from the UKBiobank and FinnGen cohorts, but also previously published genetic studies. We also evaluated whether T2D SNPs associated with PCa risk could influence host immune responses by analysing their correlation with absolute numbers of 91 blood-derived cell populations and circulating levels of 103 immunological proteins and 7 steroid hormones. We also investigated the correlation of the most interesting SNPs with cytokine levels after in vitro stimulation of whole blood, peripheral mononuclear cells (PBMCs), and monocyte-derived macrophages with LPS, PHA, Pam3Cys, and Staphylococcus Aureus. The meta-analysis of our data with those from six large cohorts confirmed that each copy of the FTO_rs9939609A, HNF1B_rs7501939T, HNF1B_rs757210T, HNF1B_rs4430796G, and JAZF1_rs10486567A alleles significantly decreased risk of developing PCa (p = 3.70 × 10⁻⁵, p = 9.39 × 10⁻⁵⁴, p = 5.04 × 10⁻⁵⁴, p = 1.19 × 10⁻⁷¹, and p = 1.66 × 10⁻¹⁸, respectively). Although it was not statistically significant after correction for multiple testing, we also found that the NOTCH2_rs10923931T and RBMS1_rs7593730 SNPs associated with the risk of developing PCa (p = 8.49 × 10⁻⁴ and 0.004). Interestingly, we found that the protective effect attributed to the HFN1B locus could be mediated by the SULT1A1 protein (p = 0.00030), an arylsulfotransferase that catalyzes the sulfate conjugation of many hormones, neurotransmitters, drugs, and xenobiotic compounds. In addition to these results, eQTL analysis revealed that the HNF1B_rs7501939, HNF1B_rs757210, HNF1B_rs4430796, NOTCH2_rs10923931, and RBMS1_rs7593730 SNPs influence the risk of PCa through the modulation of mRNA levels of their respective genes in whole blood and/or liver. These results confirm that functional TD2-related variants influence the risk of developing PCa, but also highlight the need of additional experiments to validate our functional results in a tumoral tissue context. Full article

The importance of anti-androgen therapy for prostate cancer (PC) has been well recognized. However, the mechanisms underlying prostate cancer resistance to anti-androgens are not completely understood. Therefore, identifying pharmacological targets in driving the development of castration-resistant PC is necessary. In the present study, we sought to identify core genes in regulating steroid hormone pathways and associating them with the disease progression of PC. The selection of steroid hormone-associated genes was identified from functional databases, including gene ontology, KEGG, and Reactome. The gene expression profiles and relevant clinical information of patients with PC were obtained from TCGA and used to examine the genes associated with steroid hormone. The machine-learning algorithm was performed for key feature selection and signature construction. With the integrative bioinformatics analysis, an eight-gene signature, including CA2, CYP2E1, HSD17B, SSTR3, SULT1E1, TUBB3, UCN, and UGT2B7 was established. Patients with higher expression of this gene signature had worse progression-free interval in both univariate and multivariate cox models adjusted for clinical variables. The expression of the gene signatures also showed the aggressiveness consistently in two external cohorts, PCS and PAM50. Our findings demonstrated a validated eight-gene signature could successfully predict PC prognosis and regulate the steroid hormone pathway. Full article

Introduction: To facilitate rapid and effective diagnosis of COVID-19, effective screening can alleviate the challenges facing healthcare systems. We aimed to develop a machine learning-based prediction of COVID-19 diagnosis and design a graphical user interface (GUI) to diagnose COVID-19 cases by recording their symptoms and demographic features. Methods: We imple-mented different classification models including support vector machine (SVM), Decision tree (DT), Naïve Bayes (NB) and K-nearest neighbor (KNN) to predict the result of COVID-19 test for individ-uals. We trained these models by data of 16973 individuals (90% of all individuals included in data gathering) and tested by 1885 individuals (10% of all individuals). Maximum relevance minimum redundancy (MRMR) algorithms used to score features for prediction of result of COVID-19 test. A user-friendly GUI was designed to predict COVID-19 test results in individuals. Results: Study re-sults revealed that coughing had the highest positive correlation with the positive results of COVID-19 test followed by the duration of having COVID-19 signs and symptoms, exposure to infected individuals, age, muscle pain, recent infection by COVID-19 virus, fever, respiratory distress, loss of smell or taste, nausea, anorexia, headache, vertigo, CT symptoms in lung scans, diabetes and hyper-tension. The values of accuracy, precision, recall, F1-score, specificity and area under receiver oper-ating curve (AUROC) of different classification models computed in different setting of features scored by MRMR algorithm. Finally, our designed GUI by receiving each of the 42 features and symptoms from the users and through selecting one of the SVM, KNN, Naïve Bayes and decision tree models, predict the result of COVID-19 test. The accuracy, AUROC and F1-score of SVM model as the best model for diagnosis of COVID-19 test were 0.7048 (95% CI: 0.6998, 0.7094), 0.7045 (95% CI: 0.7003, 0.7104) and 0.7157 (95% CI: 0.7043, 0.7194), respectively. Conclusion: In this study we implemented a machine learning approach to facilitate early clinical decision making during COVID-19 outbreak and provide a predictive model of COVID-19 diagnosis capable of categorizing populations in to infected and non-infected individuals the same as an efficient screening tool. Full article

The separation, concentration and transport of the amino acids through membranes have been continuously developed due to the multitude of interest amino acids of interest and the sources from which they must be recovered. At the same time, the types of membranes used in the sepa-ration of the amino acids are the most diverse: liquids, ion exchangers, inorganic, polymeric or composites. This paper addresses the recuperative separation of three amino acids (alanine, phe-nylalanine, and methionine) using membranes from cellulosic derivatives in polypropylene ma-trix. The microfiltration membranes (polypropylene hollow fibers) were impregnated with solu-tions of some cellulosic derivatives: cellulose acetate, 2-hydroxyethyl-cellulose, methyl 2-hydroxyethyl-celluloseand sodium carboxymethyl-cellulose. The obtained membranes were characterized in terms of the separation performance of the amino acids considered (retention, flux, and selectivity) and from a morphological and structural point of view: scanning electron microscopy (SEM), high resolution SEM (HR-SEM), Fourier transform infrared spectroscopy (FT-IR), energy dispersive spectroscopy (EDS) and thermal gravimetric analyzer (TGA). The re-sults obtained show that phenylalanine has the highest fluxes through all four types of mem-branes, followed by methionine and alanine. Of the four kinds of membrane, the most suitable for recuperative separation of the considered amino acids are those based on cellulose acetate and methyl 2-hydroxyethyl-cellulose. Full article

Small fish are an excellent experimental model to screen endocrine-disrupting compounds, but current fish-based assays to detect endocrine disruption have not been standardized yet, meaning that there is not consensus on endpoints and biomarkers to be measured. Moreover, exposure conditions may vary depending on the species used as the experimental model and the endocrine pathway evaluated. At present, a battery of a wide range of assays is usually needed for the complete assessment of endocrine activities. With the aim of providing a simple, robust, and fast assay to assess endocrine-disrupting potencies for the three major endocrine axes, i.e., estrogens, androgens, and thyroid, we propose the use of a panel of eight gene expression biomarkers in zebrafish larvae. This includes brain aromatase (cyp19a1b) and vitellogenin 1 (vtg1) for estrogens, cytosolic sulfotransferase 2 family 2 (sult2st3) and cytochrome P450 2k22 (cyp2k22) for androgens, and thyroid peroxidase (tpo), transthyretin (ttr), thyroid receptor α (trα), and iodothyronine deiodinase 2 (dio2) for thyroid metabolism. All of them were selected according to their responses after exposure to the natural ligands 17β-estradiol, testosterone, and 3,3′,5-triiodo-L-thyronine (T3), respectively, and subsequently validated using compounds reported as endocrine disruptors in previous studies. Cross-talk effects were also evaluated for all compounds. Full article

Introduction: Additional or better markers are needed to guide the clinical monitoring of patients with non-muscle-invasive bladder cancer (NMIBC). Aim: To investigate the influence of occupational exposures and genetic polymorphisms on recurrence and progression of NMIBC. Methods: The study includes 160 NMIBC patients. We collected on questionnaire information on demographic variables, lifetime smoking history, lifetime history of occupational exposure to aromatic amines and polycyclic aromatic hydrocarbons. Genetic polymorphism (glutathione S-transferase M1; T1; P1 (GSTM1; GSTT1; GSTP1); N-acetyltransferase 1; 2 (NAT1; NAT2); cytochrome P450 1B1 (CYP1B1); sulfotransferase 1A1 (SULT1A1); myeloperoxidase (MPO); catechol-O-methyltransferase (COMT); manganese superoxide dismutase (MnSOD); NAD(P)H:quinone oxidoreductase (NQO1); X-ray repair cross-complementing group 1; 3 (XRCC1; XRCC3) and xeroderma pigmentosum complementation group (XPD)) was assessed in peripheral blood lymphocytes. DNA adducts were evaluated by 32P-postlabeling. Predictors of recurrence (histological confirmation of a newly found bladder tumor) and progression (transition of tumor from low-grade to high-grade and/or increase in TNM stage) were identified by multivariate Cox proportional hazard regression with stepwise backward selection of independent variables. Hazard ratios (HR) with 95% confidence interval (95%CI) and two-tail probability of error (p-value) were estimated. Results: The risk of BC progression decreased with the homozygous genotype “ValVal” of both COMT and MnSOD (HR = 0.195; 95%CI = 0.060 to 0.623; p = 0.006). The results on BC recurrence were of borderline significance. No occupational exposure influenced recurrence or progression. Conclusion: Our results are supported by experimental evidence of a plausible mechanism between cause (ValVal genotype of both MnSOD and COMT) and effect (decreased progression of tumor in NMIBC patients). The genetic polymorphisms associated with better prognosis may be used in clinic to guide selection of treatment for patients initially diagnosed with NMIBC. However, external validation studies are required. Full article

This review summarizes the results found in studies investigating the enzymatic activation of two genotoxic nitro-aromatics, an environmental pollutant and carcinogen 3-nitrobenzanthrone (3-NBA) and a natural plant nephrotoxin and carcinogen aristolochic acid I (AAI), to reactive species forming covalent DNA adducts. Experimental and theoretical approaches determined the reasons why human NAD(P)H:quinone oxidoreductase (NQO1) and cytochromes P450 (CYP) 1A1 and 1A2 have the potential to reductively activate both nitro-aromatics. The results also contributed to the elucidation of the molecular mechanisms of these reactions. The contribution of conjugation enzymes such as N,O-acetyltransferases (NATs) and sulfotransferases (SULTs) to the activation of 3-NBA and AAI was also examined. The results indicated differences in the abilities of 3-NBA and AAI metabolites to be further activated by these conjugation enzymes. The formation of DNA adducts generated by both carcinogens during their reductive activation by the NOQ1 and CYP1A1/2 enzymes was investigated with pure enzymes, enzymes present in subcellular cytosolic and microsomal fractions, selective inhibitors, and animal models (including knock-out and humanized animals). For the theoretical approaches, flexible in silico docking methods as well as ab initio calculations were employed. The results summarized in this review demonstrate that a combination of experimental and theoretical approaches is a useful tool to study the enzyme-mediated reaction mechanisms of 3-NBA and AAI reduction. Full article