A non-targeted high-resolution mass spectrometry data analysis of dissolved organic matter in wastewater treatment

The dissolved organic matter (DOM) in wastewater is typically described by a limited number of concentration measurements of select DOM fractions or micro-contaminants, which determine the removal efficiency in a wastewater treatment. Current methods do not necessarily reflect the true performance of the treatment with regard to environmental and public health risk. Herein we describe the development and application of a non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) data analysis for the evaluation of wastewater treatment processes. Our data analysis approach was applied to a real wastewater system with secondary biological treatment and tertiary treatment consisting of sand filtration, UV-treatment, and chlorination. We identified significant changes in DOM during wastewater treatment. The secondary treatment removed 1617 of 2409 (67%) detected molecular features (grouped isotopologues belonging to the same molecule) from the influent while 255 of 1047 (24%) new molecular features appeared in the secondary effluent. A reduction in the number of large molecules (>450 Da) and an increase in unsaturated molecular features of the effluent organic matter was observed. Van Krevelen plots revealed the distribution of unsaturation and heteroatoms and Kendrick mass defect plots uncovered single bondCH2- homologous series implying a removal of heavy constituents in that fraction. The demonstrated approach is a step towards a more comprehensive monitoring of DOM in wastewater and contributes to the understanding of current treatment technologies

Extraction and cleansing of data for a non-targeted analysis of high-resolution mass spectrometry data of wastewater

We provide a workflow to extract unidentified signals from chromatography-high resolution mass spectrometry (LC-HRMS) data of wastewater samples as a pre-step of a non-targeted analysis of dissolved organic matter (DOM). We provide detailed methodology on data processing and cleanup using MS processing software MZmine 2 and an own set of functions in R developed for wastewater analysis. The processing involves signal extraction, linear mass correction, reduction of noise, grouping of isotopologues, molecular formula assignment and merging of replicates. The article contains software settings and reasoning behind the choice of data extraction options. The supplementary information contains a script for the correction of signal masses using internal standards and templates of internal standard lists. We included a reproducible example as an R notebook with data cleansing workflow and data exported from MZmine. The data were used according to the described methodology in the article “A non-targeted high-resolution mass spectrometry data analysis of dissolved organic matter in wastewater treatment” by Verkh et al., 2018

Synthesis of Chiral Scaffolds Based on Polyfunctional Cyclobutane β-Amino Acids

Altres ajuts: Acord transformatiu CRUE-CSICChiral scaffolds have been synthesized through selective transformations from conveniently protected cyclobutane β-amino acids. The obtained derivatives present additional functional groups, such as hydroxyl, carboxyl, or carbon-carbon triple bond, linked to the amino acid core through a flexible C or C alkyl fragment. The resultant molecules are highly versatile to be used as chiral precursors for the production of polyfunctional chemical platforms. These can be suitable for the synthesis of complex molecules, through condensation reactions, such as peptide coupling, dehydration between a carboxylic acid and an alcohol, or click chemistry. To illustrate some of these possibilities, two hybrid tripeptides have been prepared as examples of their synthetic potential

Sunitinib in combination with docetaxel in patients with advanced solid tumors: a phase I dose-escalation study

PURPOSE: Sunitinib in combination with docetaxel enhances antitumor activity in xenograft models of human breast and non-small cell lung cancer. We assessed the maximum tolerated doses (MTDs), safety, pharmacokinetic profiles, and preliminary efficacy of sunitinib plus docetaxel in patients with advanced solid tumors. METHODS: In this phase I study, successive patient cohorts received sunitinib 25, 37.5, or 50 mg/day for 4 weeks of a 6-week cycle (Schedule 4/2, 4 weeks on, 2 weeks off) or for 2 weeks of a 3-week cycle (Schedule 2/1, 2 weeks on, 1 week off) with docetaxel 60 or 75 mg/m(2) IV q21d to determine the MTDs of this treatment combination. RESULTS: Fifty patients enrolled: 10 on Schedule 4/2 and 40 on Schedule 2/1. MTDs were established as sunitinib 25 mg on Schedule 4/2 with docetaxel 60 mg/m(2) q21d, and as sunitinib 37.5 mg on Schedule 2/1 with docetaxel 75 mg/m(2) q21d. On Schedule 2/1, the most frequent dose-limiting toxicity was neutropenia (±fever; grade [G]3/4, n = 5) and the most common G3/4 non-hematologic adverse event (AE) was fatigue (G3, n = 8). Hematologic AEs were managed with growth factor support in 11 of 23 (48%) patients treated at Schedule 2/1 MTD. Three patients achieved a partial response at the Schedule 2/1 MTD. There were no pharmacokinetic drug–drug interactions with either schedule. CONCLUSIONS: Oral sunitinib 37.5 mg/day on Schedule 2/1 with docetaxel 75 mg/m(2) IV q21d is a clinically feasible regimen with a manageable safety profile, no pharmacokinetic drug–drug interactions, and shows antitumor activity in patients with advanced solid tumors

Characterization of dissolved organic matter in wastewater using liquid chromatography-high resolution mass spectrometry

Individual hazardous chemicals and substance mixtures with synergistic toxicity ef-fects occur in the dissolved organic matter (DOM) of wastewater and negatively im-pact human health. Yet a large number of chemicals and their treatment by-products in wastewater makes the tracking of individual compounds nearly impossible and de-mands new analytical strategies. The thesis describes the development and evaluation of non-targeted and suspect anal-ysis methods aimed at the transformation of DOM and micro-contaminants of interest during wastewater treatment using liquid chromatography-high-resolution mass spec-trometry (LC-HRMS) data. On one hand, a non-targeted method to track transformations of DOM in a multiphase wastewater treatment using LC-HRMS data was developed. LC-MS signals were ex-tracted, aligned, and had their isotopologues clustered and elemental composition pre-dicted using open license software MZmine 2 in a way that conceptually prioritized the detection of anthropogenic compoundsEl destino de los microcontaminantes en el tratamiento de aguas residuales ha ido ga-nando atención debido al impacto ecológico y toxicológico de estas sustancias en la salud humana. Adicionalmente a los productos químicos peligrosos individuales, las mezclas de sustancias como las que ocurren en la materia orgánica disuelta (MOD) en las aguas residuales, pueden producir efectos de toxicidad sinérgicos. Sin embargo, el gran número de compuestos naturales y antropogénicos, así como sus productos de transformación de tratamiento (PTs) provocan que el seguimiento de los compuestos individuales sea casi imposible, exigiendo nuevas estrategias para realizar un segui-miento eficaz de transformaciones MOD. Esta tesis describe un método desarrollado y probado para rastrear transformaciones de MOD en aguas residuales, utilizando un análisis no dirigido de cromatografía de líquidos y espectrometría de masas de alta resolución (LC-MS). Potencialmente, el análisis prioriza la detección de compuestos antropogénico

Characterization of dissolved organic matter in wastewater using liquid chromatography-high resolution mass spectrometry

Individual hazardous chemicals and substance mixtures with synergistic toxicity ef-fects occur in the dissolved organic matter (DOM) of wastewater and negatively im-pact human health. Yet a large number of chemicals and their treatment by-products in wastewater makes the tracking of individual compounds nearly impossible and de-mands new analytical strategies. The thesis describes the development and evaluation of non-targeted and suspect anal-ysis methods aimed at the transformation of DOM and micro-contaminants of interest during wastewater treatment using liquid chromatography-high-resolution mass spec-trometry (LC-HRMS) data. On one hand, a non-targeted method to track transformations of DOM in a multiphase wastewater treatment using LC-HRMS data was developed. LC-MS signals were ex-tracted, aligned, and had their isotopologues clustered and elemental composition pre-dicted using open license software MZmine 2 in a way that conceptually prioritized the detection of anthropogenic compoundsEl destino de los microcontaminantes en el tratamiento de aguas residuales ha ido ga-nando atención debido al impacto ecológico y toxicológico de estas sustancias en la salud humana. Adicionalmente a los productos químicos peligrosos individuales, las mezclas de sustancias como las que ocurren en la materia orgánica disuelta (MOD) en las aguas residuales, pueden producir efectos de toxicidad sinérgicos. Sin embargo, el gran número de compuestos naturales y antropogénicos, así como sus productos de transformación de tratamiento (PTs) provocan que el seguimiento de los compuestos individuales sea casi imposible, exigiendo nuevas estrategias para realizar un segui-miento eficaz de transformaciones MOD. Esta tesis describe un método desarrollado y probado para rastrear transformaciones de MOD en aguas residuales, utilizando un análisis no dirigido de cromatografía de líquidos y espectrometría de masas de alta resolución (LC-MS). Potencialmente, el análisis prioriza la detección de compuestos antropogénico

Phase I/II Study of Safety and Preliminary Efficacy of Intravenous Allogeneic Mesenchymal Stem Cells in Chronic Stroke.

Background and Purpose- Stroke is a leading cause of long-term disability. Limited treatment options exist for patients with chronic stroke and substantial functional deficits. The current study examined safety and preliminary efficacy estimates of intravenous allogeneic mesenchymal stem cells in this population. Methods- Entry criteria included ischemic stroke >6 months prior and substantial impairment (National Institutes of Health Stroke Scale score ≥6) and disability. Enrollees received a single intravenous dose of allogeneic ischemia-tolerant mesenchymal stem cells. Phase 1 used a dose-escalation design (3 tiers, n=5 each). Phase 2 was an expanded safety cohort. The primary end point was safety over 1-year. Secondary end points examined behavioral change. Results- In phase 1 (n=15), each dose (0.5, 1.0, and 1.5 million cells/kg body weight) was found safe, so phase 2 subjects (n=21) received 1.5 million cells/kg. At baseline, subjects (n=36) averaged 4.2±4.6 years poststroke, age 61.1±10.8 years, National Institutes of Health Stroke Scale score 8 (6.5-10), and Barthel Index 65±29. Two were lost to follow-up, one was withdrawn and 2 died (unrelated to study treatment). Of 15 serious adverse events, none was possibly or probably related to study treatment. Two mild adverse events were possibly related to study treatment, a urinary tract infection and intravenous site irritation. Treatment was safe based on serial exams, electrocardiograms, laboratory tests, and computed tomography scans of chest/abdomen/pelvis. All behavioral end points showed significant gains over the 12-months of follow-up. For example, Barthel Index scores increased by 6.8±11.4 points (mean±SD) at 6-months (P=0.002) and by 10.8±15.5 points at 12-months (P<0.001) post-infusion; the proportion of patients achieving excellent functional outcome (Barthel score ≥95) increased from 11.4% at baseline to 27.3% at 6-months and to 35.5% at 12-months. Conclusions- Intravenous transfusion of allogeneic ischemia-tolerant mesenchymal stem cell in patients with chronic stroke and substantial functional deficits was safe and suggested behavioral gains. These data support proceeding to a randomized, placebo-controlled study of this therapy in this population. Clinical Trial Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT01297413