Metabolomics and proteomics in occupational medicine: a comprehensive systematic review.

Background: Occupational biomonitoring is essential for assessing health risks linked to workplace exposures. The use of 'omics' technologies, such as metabolomics and proteomics, has become crucial in detecting subtle biological alterations induced by occupational hazards, thereby opening novel avenues for biomarker discovery.

Aims: This systematic review aims to evaluate the application of metabolomics and proteomics in occupational health.

Data-driven, explainable machine learning model for predicting volatile organic compounds' standard vaporization enthalpy.

The accurate prediction of standard vaporization enthalpy (ΔH°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental methods for predicting ΔH° of VOCs, machine learning (ML) models enable a high-throughput, cost-effective property estimation. But despite a rising momentum, existing ML algorithms still present limitations in prediction accuracy and broad chemical applications.

Trends in ultra-processed food availability and its association with diet-related non-communicable disease health indicators in the Portuguese population.

Broad variations in dietary and physical activity patterns are part of nutritional transition concept. An additional nutritional transition has as main characteristic the change of consumption of processed foods for ultra-processed foods (UPF). This study aims to evaluate trends of UPF availability in Portuguese population and its association with diet-related non-communicable diseases (NCD) health indicators.

Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy.

Many challenges persist in developing accurate computational models for predicting solvation free energy (Δ). Despite recent developments in Machine Learning (ML) methodologies that outperformed traditional quantum mechanical models, several issues remain concerning explanatory insights for broad chemical predictions with an acceptable speed-accuracy trade-off. To overcome this, we present a novel supervised ML model to predict the Δ for an array of solvent-solute pairs.

How genomics can help biodiversity conservation.

The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species.

Structure and Biosynthesis of Desmamides A-C, Lipoglycopeptides from the Endophytic Cyanobacterium LEGE 12446.

Certain cyanobacteria of the secondary metabolite-rich order Nostocales can establish permanent symbioses with a large number of cycads, by accumulating in their coralloid roots and shifting their metabolism to dinitrogen fixation. Here, we report the discovery of two new lipoglycopeptides, desmamides A () and B (), together with their aglycone desmamide C (), from the nostocalean cyanobacterium LEGE 12446 isolated from a cycad () coralloid root. The chemical structures of the compounds were elucidated using a combination of 1D and 2D NMR spectroscopy and mass spectrometry.

New insights into ethionamide metabolism: influence of oxidized methionine on its degradation path.

Ethionamide (ETH) is a commercial drug, used as a second-line resource to neutralize infections. It is proven that its metabolization in the organism leads to the formation of the active form of the drug, but some metabolic pathways may lead to the loss of its activity. Our work proved that the presence of oxidized methionine in cells could influence ETH's degradation, leading to the appearance of an inactive metabolite that is detectable by HPLC and mass spectrometry.

MicroMundo@UPorto: an experimental microbiology project fostering student's antimicrobial resistance awareness and personal and social development.

Antimicrobial resistance (AMR) is a global societal challenge requiring the contribution of professionals along with general community citizens for their containment. Portugal is one of the European countries where a lack of knowledge on the correct use of antimicrobials and AMR problematic is preeminent. Moreover, youth demotivation to pursue science careers is emerging.

Synthesis and Characterization of Surface-Active Ionic Liquids Used in the Disruption of Escherichia Coli Cells.

Twelve surface-active ionic liquids (SAILs) and surface-active derivatives, based on imidazolium, ammonium, and phosphonium cations and containing one, or more, long alkyl chains in the cation and/or the anion, were synthetized and characterized. The aggregation behavior of these SAILs in water, as well as their adsorption at solution/air interface, were studied by assessing surface tension and conductivity. The CMC values obtained (0.

Biodegradation of mono-, di- and trifluoroacetate by microbial cultures with different origins.

This work focused on the biodegradation of three structurally related fluoroacetates (FAs), mono- (MFA), di- (DFA) and trifluoroacetate (TFA), using as microbial inocula samples collected from a site with a long history of industrial contamination and activated sludge obtained from a municipal wastewater treatment plant. Biodegradation experiments were carried out under different modes of substrate supplementation, which included (i) FAs fed as sole carbon sources; (ii) FAs (only for DFA and TFA) fed in co-metabolism with sodium acetate; and (iii) mixtures of MFA with DFA or TFA. Biodegradation of the target compounds was assessed through fluoride ion release.

The conifer biomarkers dehydroabietic and abietic acids are widespread in Cyanobacteria.

Terpenes, a large family of natural products with important applications, are commonly associated with plants and fungi. The diterpenoids dehydroabietic and abietic acids are defense metabolites abundant in resin, and are used as biomarkers for conifer plants. We report here for the first time that the two diterpenoid acids are produced by members of several genera of cyanobacteria.

Quantum Semiempirical Energy Based (SEEB) Descriptors Performance with Benzamidine Inhibitors of Trypsin.

MLR is a classical approach to regression problems in QSARs. In this study, the behaviour of SEEB descriptors was analysed with a MLR model. For this purpose a SEEB/MLR 3D-QSAR model was developed to evaluate the efficiency of benzamide trypsin inhibitors.