Determination of pesticide residues in urine by chromatography-mass spectrometry: methods and applications.

Introduction: Pollution has emerged as a significant threat to humanity, necessitating a thorough evaluation of its impacts. As a result, various methods for human biomonitoring have been proposed as vital tools for assessing, managing, and mitigating exposure risks. Among these methods, urine stands out as the most commonly analyzed biological sample and the primary matrix for biomonitoring studies. Objectives: This review concentrates on exploring the literature concerning residual pesticide determination in urine, utilizing liquid and gas chromatography coupled with mass spectrometry, and its practical applications. Method: The examination focused on methods developed since 2010. Additionally, applications reported between 2015 and 2022 were thoroughly reviewed, utilizing Web of Science as a primary resource. Synthesis: Recent advancements in chromatography-mass spectrometry technology have significantly enhanced the development of multi-residue methods. These determinations are now capable of simultaneously detecting numerous pesticide residues from various chemical and use classes. Furthermore, these methods encompass analytes from a variety of environmental contaminants, offering a comprehensive approach to biomonitoring. These methodologies have been employed across diverse perspectives, including toxicological studies, assessing pesticide exposure in the general population, occupational exposure among farmers, pest control workers, horticulturists, and florists, as well as investigating consequences during pregnancy and childhood, neurodevelopmental impacts, and reproductive disorders. Future directions: Such strategies were essential in examining the health risks associated with exposure to complex mixtures, including pesticides and other relevant compounds, thereby painting a broader and more accurate picture of human exposure. Moreover, the implementation of integrated strategies, involving international research initiatives and biomonitoring programs, is crucial to optimize resource utilization, enhancing efficiency in health risk assessment.

Anaerobic co-metabolic biodegradation of pharmaceuticals and personal care products driven by glycerol fermentation.

Anaerobic digestion in two sequential phases, acidogenesis and methanogenesis, has been shown to be beneficial for enhancing the biomethane generation from wastewater. In this work, the application of glycerol (GOH) as a fermentation co-substrate during the wastewater treatment was evaluated on the biodegradation of different pharmaceuticals and personal care products (PPCPs). GOH co-digestion during acidogenesis led to a significant increase in the biodegradation of acetaminophen (from 78 to 89%), ciprofloxacin (from 25 to 46%), naproxen (from 73 to 86%), diclofenac (from 36 to 48%), ibuprofen (from 65 to 88%), metoprolol (from 45 to 59%), methylparaben (from 64 to 78%) and propylparaben (from 68 to 74%). The heterotrophic co-metabolism of PPCPs driven by glycerol was confirmed by the biodegradation kinetics, in which kbio (biodegradation kinetics constant) values increased from 0.18 to 2.11 to 0.27-3.60 L g-1-VSS d-1, for the operational phases without and with GOH, respectively. The assessment of metabolic pathways in each phase revealed that the prevalence of aromatic compounds degradation, metabolism of xenobiotics by cytochrome P450, and benzoate degradation routes during acidogenesis are key factors for the enzymatic mechanisms linked to the PPCPs co-metabolism. The phase separation of anaerobic digestion was effective in the PPCPs biodegradation, and the co-fermentation of glycerol provided an increase in the generation potential of biomethane in the system (energetic potential of 5.0 and 6.3 kJ g-1-CODremoved, without and with GOH, respectively). This study showed evidence that glycerol co-fermentation can exert a synergistic effect on the PPCPs removal during anaerobic digestion mediated by heterotrophic co-metabolism.

Residual determination and acute toxicity of the neonicotinoid clothianidin in the neotropical stingless bee Tetragonisca angustula Latreille, 1811 (Apidae: Meliponini).

Bees play a crucial role as natural pollinators, ensuring the maintenance and stability of the world's biodiversity and agricultural crops. Native bees in neotropical regions belong to the Meliponini tribe, a larger group that differs significantly in behavior and biology from honeybees (e.g., Apis mellifera) and solitary bees (e.g., Osmia spp.). Hence, the exposure and effects of pesticides is also likely to vary among these different species. The aim of this study was to develop an analytical method to determine the presence of the neonicotinoid clothianidin in the Brazilian native stingless bee Tetragonisca angustula (local common name: Jataí). The method used for the chemical analysis involved a QuEChERS technique combined with UHPLC-MS/MS analysis. The developed method was subsequently used to analyze collected field samples. In addition, the acute toxicity of the pesticide to T. angustula was evaluated in a laboratory bioassay evaluating both lethal and sublethal endpoints. The analytical method was successfully developed with detection and quantification limits of 1.55 and 5 µg L-1, respectively, along with a linear range of 1-5 ng mL-1. Clothianidin was detected in environmental samples (9.2-32.9 ng g-1), and the exposure experiments demonstrated acute oral toxicity to adults of T. angustula, (24 h-LD50 of 0.16 ng a.i./bee), as well as no significative interference in acetylcholinesterase activity. Considering the obtained toxicity endpoints for T. angustula and those reported in the literature for other bee species, this study revealed that T. angustula is more (lethally) sensitive to clothianidin than other bee species, including those commonly used in environmental risk assessment studies. This thus also supports the call for using native test species in (regional) risk assessment evaluations.

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Automated microextraction by packed sorbent of endocrine disruptors in wastewater using a high-throughput robotic platform followed by liquid chromatography-tandem mass spectrometry.

An automated microextraction by packed sorbent followed by liquid chromatography-tandem mass spectrometry (MEPS-LC-MS/MS) method was developed for the determination of four endocrine disruptors-parabens, benzophenones, and synthetic phenolic antioxidants-in wastewater samples. The method utilizes a lab-made repackable MEPS device and a multi-syringe robotic platform that provides flexibility to test small quantities (2 mg) of multiple extraction phases and enables high-throughput capabilities for efficient method development. The overall performance of the MEPS procedure, including the investigation of influencing variables and the optimization of operational parameters for the robotic platform, was comprehensively studied through univariate and multivariate experiments. Under optimized conditions, the target analytes were effectively extracted from a small sample volume of 1.5 mL, with competitive detectability and analytical confidence. The limits of detection ranged from 0.15 to 0.30 ng L-1, and the intra-day and inter-day relative standard deviations were between 3 and 21%. The method's applicability was successfully demonstrated by determining methylparaben, propylparaben, butylated hydroxyanisole, and oxybenzone in wastewater samples collected from the São Carlos (SP, Brazil) river. Overall, the developed method proved to be a fast, sensitive, reliable, and environmentally friendly analytical tool for water quality monitoring.

An open-source smart fraction collector for isocratic preparative liquid chromatography.

Preparative liquid chromatography is a technique for separating complex samples or isolating pure compounds from complex extracts. It involves eluting samples through a packed column and selectively collecting or isolating the separated bands in a sequence of fractions. Depending on the column length and the sample complexity, a large number of fractions may be obtained, making fraction collection a laborious and time-consuming process. Manual fraction collection is also tedious, error-prone, less reproducible, and susceptible to contamination. Several commercial and lab-made solutions are available for automated fraction collection, but most systems do not synchronize with the instrument detector and collect fractions at fixed volumes or time intervals. We have assembled a low-cost Arduino-based smart fraction collector that can record the signal from the UV-vis detector of the chromatography instrument and enable the automated selective collection of the targeted bands. The system consists of a robot equipped with position sensors and a 3-way solenoid valve that switches the column effluent between the waste or collection positions. By proper programming, an Arduino board records the detector response and actuates the solenoid valve, the position sensors, and the stepper motors to collect the target chromatographic bands.

Modern automated microextraction procedures for bioanalytical, environmental, and food analyses.

Sample preparation frequently is considered the most critical stage of the analytical workflow. It affects the analytical throughput and costs; moreover, it is the primary source of error and possible sample contamination. To increase efficiency, productivity, and reliability, while minimizing costs and environmental impacts, miniaturization and automation of sample preparation are necessary. Nowadays, several types of liquid-phase and solid-phase microextractions are available, as well as different automatization strategies. Thus, this review summarizes recent developments in automated microextractions coupled with liquid chromatography, from 2016 to 2022. Therefore, outstanding technologies and their main outcomes, as well as miniaturization and automation of sample preparation, are critically analyzed. Focus is given to main microextraction automation strategies, such as flow techniques, robotic systems, and column-switching approaches, reviewing their applications to the determination of small organic molecules in biological, environmental, and food/beverage samples.

Two-phase (acidogenic-methanogenic) anaerobic fixed bed biofilm reactor enhances the biological domestic sewage treatment: Perspectives for recovering bioenergy and value-added by-products.

The organic matter bioconversion into methane during anaerobic digestion (AD) comprises different steps, the acidogenic and methanogenic phases being clearly distinct in terms of metabolic activities. In this work, new configurations of anaerobic fixed bed biofilm reactors (AFBBR) were operated under conventional methanogenic conditions (single phase - SP-AFBBR, M1R), and in a sequential two-phase system, acidogenic reactor followed by methanogenic reactor (TP-AFBBR, AcR + M2R), in order to verify the impact of the AD phase separation on the overall system performance in operational, kinetics and microbiological aspects. The results indicated that feeding the methanogenic reactor with the acidogenic effluent stream provided a shorter operating start-up period (11 and 32 days for SP and TP-AFBBR, respectively), a greater alkalinity generation (0.14 and 0.41 g-CaCO3·g-CODremoved-1 for M1R and M2R, respectively), and the optimization of biomethane production (methane yield of 95 and 154 N-mLCH4·g-CODremoved-1 for M1R and M2R, respectively). The COD removal kinetics was also favored in the TP-AFBBR (k1-COD = 1.4 and 2.9 h-1 for M1R and M2R, respectively), since the soluble fermentation products were readily bioavailable to the biomass in the reactor. Hydrogenotrophic methanogenesis was the predominant pathway in the M2R, while the Methanosaeta-driven acetoclastic pathway predominated in the M1R. The greater diversity of Bacteria and Archaea in M2R denotes a better balance between the species that degrade volatile organic acids from AcR (i.e. Syntrophorhabdus, Syntrophus and Syntrophobacter) and the hydrogenotrophic methanogens (Methanoregula, Methanolinea and Methanospirillum) that consume the biodegradation products. The estimated bioenergy generation potential (range of 0.39-0.64 kWh·m-3-sewage considering the COD removed) for full-scale TP-sewage treatment plants evidences the feasibility of energetic recovery in the domestic sewage anaerobic treatment.

Determination of parabens in wastewater samples via robot-assisted dynamic single-drop microextraction and liquid chromatography-tandem mass spectrometry.

Dynamic single-drop microextraction (SDME) was automatized employing an Arduino-based lab-made Cartesian robot and implemented to determine parabens in wastewater samples in combination with liquid chromatography-tandem mass spectrometry. A dedicated Arduino sketch controls the auto-performance of all the stages of the SDME process, including syringe filling, drop exposition, solvent recycling, and extract collection. Univariate and multivariate experiments investigated the main variables affecting the SDME performance, including robot-dependent and additional operational parameters. Under selected conditions, limit of detections were established at 0.3 µg/L for all the analytes, and the method provided linear responses in the range between 0.6 and 10 µg/L, with adequate reproducibility, measured as intraday relative standard deviations (RSDs) between 5.54% and 17.94%, (n = 6), and inter-days RSDs between 8.97% and 16.49% (n = 9). The robot-assisted technique eased the control of dynamic SDME, making the process more feasible, robust, and reliable so that the developed setup demonstrated to be a competitive strategy for the automated extraction of organic pollutants from water samples.

Packed in-tube SPME-LC-MS/MS for fast and straightforward analysis of cannabinoids and metabolites in human urine.

Cannabinoids are pharmacologically active compounds present in cannabis plants, which have become important research topics in the modern toxicological and medical research fields. Not only is cannabis the most used drug globally, but also cannabinoids have a growing use to treat a series of diseases. Therefore, new, fast, and efficient analytical methods for analyzing these substances in different matrices are demanded. This study developed a new packed-in-tube solid-phase microextraction (IT-SPME) method coupled to liquid chromatography with tandem mass spectrometry (LC-MS/MS), for the automated microextraction of seven cannabinoids from human urine. Packed IT-SPME microcolumns were prepared in (508 µm i.d. × 50 mm) stainless-steel hardware; each one required only 12 mg of sorbent phase. Different sorbents were evaluated; fractional factorial design 24-1 and a central composite design were employed for microextraction optimization. Under optimized conditions, the developed method was a fast and straightforward approach. Only 250 µl of urine sample was needed, and no hydrolysis was required. The sample pretreatment included only dilution and centrifugation steps (8 min), whereas the complete IT-SPME-LC-MS/MS method took another 12 min, with a sample throughput of 3 samples h-1 . The developed method presented adequate precision, accuracy and linearity; R2 values ranged from 0.990 to 0.997, in the range of 10-1000 ng ml-1 . The lower limits of quantification varied from 10 to 25 ng ml-1 . Finally, the method was successfully applied to analyze 20 actual urine samples, and the IT-SPME microcolumn was reused over 150 times.

On-line solid-phase extraction of pharmaceutical compounds from wastewater treatment plant samples using restricted access media in column-switching liquid chromatography-tandem mass spectrometry.

An on-line solid phase extraction using a lab-made restricted access media (RAM) was developed as sample preparation procedure for determination of the pharmaceutical compounds caffeine (CAF), carbamazepine (CBZ), norfloxacin (NOR), ciprofloxacin (CIP), fluoxetine (FLX) and venlafaxine in wastewater treatment plant samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This method is suitable for use in routine of analysis, avoiding cross-contamination and requiring only a small sample volume (50 µL), with minimal handling. The method was validated according to international guidelines. The chromatographic efficiency was evaluated using peak resolution and asymmetry parameters. Carryover was also evaluated, in order to ensure reliability of the analysis and the ability to reuse the cartridge. Satisfactory linearity (r2 > 0.99) was obtained for all the compounds. The intra- and inter-day precision values were lower than 5.79 and 14.1%, respectively. The limits of detection ranged from 0.01 to 3 µg L-1 and the limits of quantification were from 0.1 to 5 µg L-1. The method was applied to 20 environmental wastewater samples, with caffeine being the most widely detected compound, at the highest concentration of 392 µg L-1, while other compounds were detected in fewer samples at lower concentrations (up to 9.60 µg L-1). The lab-made modification is a cheaper option for on-line sample preparation, compared to commercially available on-line SPE cartridges and RAM columns. Moreover, a high-throughput procedure was achieved, with an analysis time of 16 min including sample preparation and chromatographic separation. The same RAM column was applied over 200 injections including method optimization, validation and application in wastewater samples without loss of analytical response.

Identification of Dose-Dependent DNA Damage and Repair Responses From Subchronic Exposure to 1,4-Dioxane in Mice Using a Systems Analysis Approach.

1,4-Dioxane (1,4-DX) is an environmental contaminant found in drinking water throughout the United States. Although it is a suspected liver carcinogen, there is no federal or state maximum contaminant level for 1,4-DX in drinking water. Very little is known about the mechanisms by which this chemical elicits liver carcinogenicity. In the present study, female BDF-1 mice were exposed to 1,4-DX (0, 50, 500, and 5,000mg/L) in their drinking water for 1 or 4 weeks, to explore the toxic effects. Histopathological studies and a multi-omics approach (transcriptomics and metabolomics) were performed to investigate potential mechanisms of toxicity. Immunohistochemical analysis of the liver revealed increased H2AXγ-positive hepatocytes (a marker of DNA double-strand breaks), and an expansion of precholangiocytes (reflecting both DNA damage and repair mechanisms) after exposure. Liver transcriptomics revealed 1,4-DX-induced perturbations in signaling pathways predicted to impact the oxidative stress response, detoxification, and DNA damage. Liver, kidney, feces, and urine metabolomic profiling revealed no effect of 1,4-DX exposure, and bile acid quantification in liver and feces similarly showed no effect of exposure. We speculate that the results may be reflective of DNA damage being counterbalanced by the repair response, with the net result being a null overall effect on the systemic biochemistry of the exposed mice. Our results show a novel approach for the investigation of environmental chemicals that do not elicit cell death but have activated the repair systems in response to 1,4-DX exposure.

Detection of anti-cancer drugs and metabolites in the effluents from a large Brazilian cancer hospital and an evaluation of ecotoxicology.

The use of chemotherapy agents has been growing worldwide, due to the increase number of cancer cases. In several countries, mainly in Europe countries, these drugs have been detected in hospitals and municipal wastewaters. In Brazil this issue is poorly explored. The main goal of this study was to assess the presence of three anti-cancer drugs, 5-fluorouracil (5-FU), gemcitabine (GEM) and cyclophosphamide (CP), and two metabolites, alpha-fluoro-beta-alanine (3-NH2-F) and 2'-deoxy-2',2'-difluorouridine (2-DOH-DiF), in effluents from a large cancer hospital, in the municipal wastewater treatment plant (WWTP) influent and effluent, and also to evaluate toxicity of the mixtures of these compounds by ecotoxicological testing in zebrafish. The sample collections were performed in Barretos Cancer Hospital of the large cancer center in Brazil. After each collection, the samples were filtered for subsequent Liquid Chromatography Mass Spectrometry analysis. The presence of CP, GEM, and both metabolites (3-NH2-F and 2-DOH-DiF) were detected in the hospital wastewater and the WWTP influent. Three drugs, GEM, 2-DOH-DiF and CP, were detected in the WWTP effluent. Two drugs were detected below the limit of quantification, 2-DOH-DiF:

Hybrid constructed wetlands as post-treatment of blackwater: An assessment of the removal of antibiotics.

New sanitation systems have been developed to treat, recover energy and nutrients, and permit reuse processes at the source of generation, minimizing water use and flow segregation. Thus, this study was carried out with the objective of evaluating the potential of hybrid constructed wetlands in the removal of organic matter, nutrients, pathogenic microorganisms, and 12 antibiotics from blackwater previously treated by an upflow anaerobic sludge blanket reactor. A hybrid system of constructed wetlands was used, comprised of a horizontal subsurface flow constructed wetland with a total volume of 0.60 m3 followed by a vertical subsurface flow constructed wetland with a total volume of 0.20 m3. Three different hydraulic retention times were comparatively tested (1.0, 2.0, and 3.0 days for the horizontal subsurface flow constructed wetland, and 1.1, 0.9, and 0.4 days for the vertical subsurface flow constructed wetland) in four distinct stages. The plant species used was Canna x generalis. The results from this study demonstrate the potential of constructed wetlands as a suitable technology for post-treatment of segregated domestic wastewater (anaerobically-digested blackwater). Efficient reduction of COD, BOD5, total nitrogen, and total phosphorus (74, 93, 50, and 61%, respectively) was achieved, with a hydraulic retention time of 3.0 and 1.1 days for horizontal and vertical subsurface flow constructed wetland, respectively (stage IV). The presence of ciprofloxacin was confirmed by chromatographic and mass spectrometric analysis in an average concentration of 442.6 ng.L-1 at the inflow of the horizontal subsurface flow constructed wetland, but was not observed at the outflow.

Automated microextraction by packed sorbent of cannabinoids from human urine using a lab-made device packed with molecularly imprinted polymer.

An original, selective and automated method, for the microextraction by packed sorbent (MEPS) of Δ9-tetrahydrocannabinol (THC), 11-hydroxy-Δ9-tetrahydrocannabinol (THC-OH), and 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH) from human urine, was developed by using (i) a catechin-molded molecularly imprinted polymer (MIP), (ii) a new lab-made MEPS device easily repackable with any commercial or lab-made sorbent, and (iii) a lab-made multi syringe autosampler. Analyses were performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and the developed method proved to be precise, accurate and showed good linearity. Determination coefficients ranged from 0.96 to 0.99, in the range of 5-250 ng mL-1. Limits of detection and quantification ranged between 1.0 and 5.0 ng mL-1 and 5.0 and 20.0 ng mL-1. The method was successfully applied in the analysis of real urine samples. The same packed syringe was effectively used over 90 consecutive extractions without carry-over effects.

Influence of organic loading rate on ciprofloxacin and sulfamethoxazole biodegradation in anaerobic fixed bed biofilm reactors.

Antibiotic compounds, notably sulfamethoxazole (SMX) and ciprofloxacin (CIP), are ubiquitous emerging contaminants (ECs), which are often found in domestic sewage. They are associated with the development of antimicrobial resistance. Operational parameters, e.g. organic loading rate (OLR), hydraulic retention time (HRT) and sludge retention time, may influence EC biodegradation in wastewater treatment plants. This study assessed the impact of the OLR variation on the biodegradation of CIP and SMX, applying two configurations of anaerobic fixed bed reactors: anaerobic packed bed biofilm reactor (APBBR) and anaerobic structured bed biofilm reactor (ASBBR). A significant reduction in the biodegradation of SMX (APBBR: 93-69%; ASBBR: 94-81%) and CIP (APBBR: 85-66%; ASBBR: 85-64%) was observed increasing OLR from 0.6 to 2.0 kgCOD m-3 d-1. The decrease in the HRT from 12 to 4 h resulted in higher liquid-phase mass transfer coefficient (APBBR: ks from 0.01 to 0.05 cm h-1; ASBBR: ks from 0.07 to 0.24 cm h-1), but this was not enough to overcome the decrease in the antibiotic-biomass contact time on biofilm, thus reducing the bioreactors' performance. The ASBBR favored biomethane production (from 7 to 17 mLCH4 g-1VSS L-1 d-1) and biodegradation kinetics (kbio from 1.7 to 4.2 and for SMX and from 2.1 to 4.8 L g-1VSS d-1 for CIP) due to the higher relative abundance of the archaea community in the biofilm and the lower liquid-phase mass transfer resistance in the structured bed. CIP and SMX cometabolic biodegradation was associated to the hydrogenotrophic methanogenesis (mainly Methanobacterium genus) in co-culture with fermentative bacteria (notably the genera Clostridium, Bacillus, Lactivibrio, Syntrophobacter and Syntrophorhabdus). The anaerobic fixed bed biofilm reactors proved to be highly efficient in biodegrading the antibiotics, preventing them from spreading to the environment.

Tumor Tissue-Specific Biomarkers of Colorectal Cancer by Anatomic Location and Stage.

The progress in the discovery and validation of metabolite biomarkers for the detection of colorectal cancer (CRC) has been hampered by the lack of reproducibility between study cohorts. The majority of discovery-phase biomarker studies have used patient blood samples to identify disease-related metabolites, but this pre-validation phase is confounded by non-specific disease influences on the metabolome. We therefore propose that metabolite biomarker discovery would have greater success and higher reproducibility for CRC if the discovery phase was conducted in tumor tissues, to find metabolites that have higher specificity to the metabolic consequences of the disease, that are then validated in blood samples. This would thereby eliminate any non-tumor and/or body response effects to the disease. In this study, we performed comprehensive untargeted metabolomics analyses on normal (adjacent) colon and tumor tissues from CRC patients, revealing tumor tissue-specific biomarkers (n = 39/group). We identified 28 highly discriminatory tumor tissue metabolite biomarkers of CRC by orthogonal partial least-squares discriminant analysis (OPLS-DA) and univariate analyses (VIP > 1.5, p < 0.05). A stepwise selection procedure was used to identify nine metabolites that were the most predictive of CRC with areas under the curve (AUCs) of >0.96, using various models. We further identified five biomarkers that were specific to the anatomic location of tumors in the colon (n = 236). The combination of these five metabolites (S-adenosyl-L-homocysteine, formylmethionine, fucose 1-phosphate, lactate, and phenylalanine) demonstrated high differentiative capability for left- and right-sided colon cancers at stage I by internal cross-validation (AUC = 0.804, 95% confidence interval, CI 0.670-0.940). This study thus revealed nine discriminatory biomarkers of CRC that are now poised for external validation in a future independent cohort of samples. We also discovered a discrete metabolic signature to determine the anatomic location of the tumor at the earliest stage, thus potentially providing clinicians a means to identify individuals that could be triaged for additional screening regimens.

Sex Differences in Colon Cancer Metabolism Reveal A Novel Subphenotype.

Women have a lower incidence of colorectal cancer (CRC) than men, however, they have a higher incidence of right-sided colon cancer (RCC). This is of concern as patients with RCC have the poorest clinical outcomes among all CRC patients. Aberrant metabolism is a known hallmark and therapeutic target for cancer. We propose that metabolic subphenotypes exist between CRCs due to intertumoral molecular and genomic variation, and differences in environmental milieu of the colon which vary between the sexes. Metabolomics analysis of patient colon tumors (n = 197) and normal tissues (n = 39) revealed sex-specific metabolic subphenotypes dependent on anatomic location. Tumors from women with RCC were nutrient-deplete, showing enhanced energy production to fuel asparagine synthesis and amino acid uptake. The clinical importance of our findings were further investigated in an independent data set from The Cancer Genomic Atlas, and demonstrated that high asparagine synthetase (ASNS) expression correlated with poorer survival for women. This is the first study to show a unique, nutrient-deplete metabolic subphenotype in women with RCC, with implications for tumor progression and outcomes in CRC patients.

Determination of ring-substituted amphetamines through automated online hollow fiber liquid-phase microextraction-liquid chromatography.

The present paper describes an original method for the online preconcentration and analysis of ring-substituted amphetamines in urine samples, used on the integration of robot-assisted hollow fiber liquid-phase microextraction (HF-LPME), high-performance liquid chromatography (HPLC), and fluorescence detection (FLD). A lab-made autosampler, actuating a 100-µL syringe and equipped with a three-way solenoid microvalve, allowed the acceptor phase to flow through and be withdrawn from the lumen fiber, enabling the automated online transference of the enriched acceptor phase for chromatographic analysis, through a six-port switching valve. The developed online HF-LPME-LC/FLD method demonstrated high analytical throughput and confidence, facilitating the efficient extraction and determination of the target analytes, with minimal solvent consumption and sample manipulation, in a straightforward way. Sample cleanup, analyte uptake, and analysis were carried out in 14.5 min. Under optimal conditions, automated online HF-LPME showed excellent linearity, precision, and trueness, obtaining intraday RSDs between 2.9 and 9.2% (n = 6) and interday RSDs between 5.3 and 9.3% (n = 6). Enrichment factors (EFs) ranged between 14.2 and 15.7, extraction recoveries (ERs) ranged between 17.7 and 19.5%, and the limits of detection (S/N = 3) were 2.0, 3.0, and 3.0 µg L-1 for MDA, MDMA, and MDEA, respectively. The method proved to be an effortless, rapid, reliable, and environment-friendly approach for the determination of drug abuse in urine samples. Graphical abstract.

Normalizing Untargeted Periconceptional Urinary Metabolomics Data: A Comparison of Approaches.

Metabolomics studies of the early-life exposome often use maternal urine specimens to investigate critical developmental windows, including the periconceptional period and early pregnancy. During these windows changes in kidney function can impact urine concentration. This makes accounting for differential urinary dilution across samples challenging. Because there is no consensus on the ideal normalization approach for urinary metabolomics data, this study's objective was to determine the optimal post-analytical normalization approach for untargeted metabolomics analysis from a periconceptional cohort of 45 women. Urine samples consisted of 90 paired pre- and post-implantation samples. After untargeted mass spectrometry-based metabolomics analysis, we systematically compared the performance of three common approaches to adjust for urinary dilution-creatinine adjustment, specific gravity adjustment, and probabilistic quotient normalization (PQN)-using unsupervised principal components analysis, relative standard deviation (RSD) of pooled quality control samples, and orthogonal partial least-squares discriminant analysis (OPLS-DA). Results showed that creatinine adjustment is not a reliable approach to normalize urinary periconceptional metabolomics data. Either specific gravity or PQN are more reliable methods to adjust for urinary concentration, with tighter quality control sample clustering, lower RSD, and better OPLS-DA performance compared to creatinine adjustment. These findings have implications for metabolomics analyses on urine samples taken around the time of conception and in contexts where kidney function may be altered.