Hourly land-use regression modeling for NO2 and PM2.5 in the Netherlands.

Annual average land-use regression (LUR) models have been widely used to assess spatial patterns of air pollution exposures. However, they fail to capture diurnal variability in air pollution and consequently might result in biased dynamic exposure assessments. In this study we aimed to model average hourly concentrations for two major pollutants, NO2 and PM2.5, for the Netherlands using the LUR algorithm. We modelled the spatial variation of average hourly concentrations for the years 2016-2019 combined, for two seasons, and for two weekday types. Two modelling approaches were used, supervised linear regression (SLR) and random forest (RF). The potential predictors included population, road, land use, satellite retrievals, and chemical transport model pollution estimates variables with different buffer sizes. We also temporally adjusted hourly concentrations from a 2019 annual model using the hourly monitoring data, to compare its performance with the hourly modelling approach. The results showed that hourly NO2 models performed overall well (5-fold cross validation R2 = 0.50-0.78), while the PM2.5 performed moderately (5-fold cross validation R2 = 0.24-0.62). Both for NO2 and PM2.5 the warm season models performed worse than the cold season ones, and the weekends' worse than weekdays'. The performance of the RF and SLR models was similar for both pollutants. For both SLR and RF, variables with larger buffer sizes representing variation in background concentrations, were selected more often in the weekend models compared to the weekdays, and in the warm season compared to the cold one. Temporal adjustment of annual average models performed overall worse than both modelling approaches (NO2 hourly R2 = 0.35-0.70; PM2.5 hourly R2 = 0.01-0.15). The difference in model performance and selection of variables across hours, seasons, and weekday types documents the benefit to develop independent hourly models when matching it to hourly time activity data.

Utilization of bis-MPA Dendrimers for the Calibration of Ion Mobility Collision Cross Section Calculations.

Ion mobility-mass spectrometry (IM-MS) has become increasingly popular with the rapid expansion of available techniques and instrumentation. To enable accuracy, standardization, and repeatability of IM-MS measurements, the community requires reliable and well-defined reference materials for calibration and tuning of the equipment. To address this need, synthetic dendrimers of high chemical and structural purity were tested on three ion mobility platforms as potential calibrants. First, synthesized dendrimers were characterized by drift tube ion mobility (DTIMS), using an Agilent 6560 IM-qTOF-MS to assess their drift tube collision cross section (DTCCS) values. Then, assessment of obtained CCS values on trapped ion mobility (TIMS) and traveling wave ion mobility (TWIMS) ion mobility platforms were compared to those found by DTIMS. Across all three systems, dendrimers were found to have high potential for m/z and ion mobility calibration in the CCS range of 160-1700 Å2. To further validate their use as calibrants, drift tube calculated CCS values for dendrimers were utilized to calibrate calculations of CCS for known standards including Agilent Tuning mix, the CCS Major mix from Waters, and SPLASH LIPIDOMIX. Additionally, structures of sodiated dendrimers were computated along with theoretical CCS values which showed good agreement with the experimental CCS values. On the basis of the results presented, we recommend the use of dendrimers as alternatives and/or complementary compounds to commonly used calibrants for ion mobility platforms.

The virtual pivot point concept improves predictions of ground reaction forces.

Ground reaction forces (GRFs) are essential for the analysis of human movement. To measure GRFs, 3D force plates that are fixed to the floor are used with large measuring ranges, excellent accuracy and high sample frequency. For less dynamic movements, like walking or squatting, portable 3D force plates are used, while if just the vertical component of the GRFs is of interest, pressure plates or in-shoe pressure measurements are often preferred. In many cases, however, it is impossible to measure 3D GRFs, e.g., during athletic competitions, at work or everyday life. It is still challenging to predict the horizontal components of the GRFs from kinematics using biomechanical models. The virtual pivot point (VPP) concept states that measured GRFs during walking intercept in a point located above the center of mass, while during running, the GRFs cross each other at a point below the center of mass. In the present study, this concept is used to compare predicted GRFs from measured kinematics with measured 3D-GRFs, not only during walking but also during more static movements like squatting and inline lunge. To predict the GRFs a full-body biomechanical model was used while gradually changing the positions of the VPP. It is shown that an optimal VPP improves the prediction of GRFs not only for walking but also for inline lunge and squats.

Monthly average air pollution models using geographically weighted regression in Europe from 2000 to 2019.

Detailed spatial models of monthly air pollution levels at a very fine spatial resolution (25 m) can help facilitate studies to explore critical time-windows of exposure at intermediate term. Seasonal changes in air pollution may affect both levels and spatial patterns of air pollution across Europe. We built Europe-wide land-use regression (LUR) models to estimate monthly concentrations of regulated air pollutants (NO2, O3, PM10 and PM2.5) between 2000 and 2019. Monthly average concentrations were collected from routine monitoring stations. Including both monthly-fixed and -varying spatial variables, we used supervised linear regression (SLR) to select predictors and geographically weighted regression (GWR) to estimate spatially-varying regression coefficients for each month. Model performance was assessed with 5-fold cross-validation (CV). We also compared the performance of the monthly LUR models with monthly adjusted concentrations. Results revealed significant monthly variations in both estimates and model structure, particularly for O3, PM10, and PM2.5. The 5-fold CV showed generally good performance of the monthly GWR models across months and years (5-fold CV R2: 0.31-0.66 for NO2, 0.4-0.79 for O3, 0.4-0.78 for PM10, 0.46-0.87 for PM2.5). Monthly GWR models slightly outperformed monthly-adjusted models. Correlations between monthly GWR model were generally moderate to high (Pearson correlation >0.6). In conclusion, we are the first to develop robust monthly LUR models for air pollution in Europe. These monthly LUR models, at a 25 m spatial resolution, enhance epidemiologists to better characterize Europe-wide intermediate-term health effects related to air pollution, facilitating investigations into critical exposure time windows in birth cohort studies.

Quo vadis, smallholder forest landscape? An introduction to the LPB-RAP model.

The impacts of the Anthropocene on climate and biodiversity pose societal and ecological problems that may only be solved by ecosystem restoration. Local to regional actions are required, which need to consider the prevailing present and future conditions of a certain landscape extent. Modeling approaches can be of help to support management efforts and to provide advice to policy making. We present stage one of the LaForeT-PLUC-BE model (Landscape Forestry in the Tropics-PCRaster Land Use Change-Biogeographic & Economic model; in short: LPB) and its thematic expansion module RAP (Restoration Areas Potentials). LPB-RAP is a high-resolution pixel-based scenario tool that relies on a range of explicit land use types (LUTs) to describe various forest types and the environment. It simulates and analyzes future landscape configurations under consideration of climate, population and land use change long-term. Simulated Land Use Land Cover Change (LULCC) builds on dynamic, probabilistic modeling incorporating climatic and anthropogenic determinants as well as restriction parameters to depict a sub-national regional smallholder-dominated forest landscape. The model delivers results for contrasting scenario settings by simulating without and with potential Forest and Landscape Restoration (FLR) measures. FLR potentials are depicted by up to five RAP-LUTs. The model builds on user-defined scenario inputs, such as the Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). Model application is here exemplified for the SSP2-RCP4.5 scenario in the time frame 2018-2100 on the hectare scale in annual resolution using Esmeraldas province, Ecuador, as a case study area. The LPB-RAP model is a novel, heuristic Spatial Decision Support System (SDSS) tool for smallholder-dominated forest landscapes, supporting near-time top-down planning measures with long-term bottom-up modeling. Its application should be followed up by FLR on-site investigations and stakeholder participation across all involved scales.

Facile preparation of embedded polar group-containing pentafluorophenyl stationary phases for highly selective separations of diverse analytes.

Pentafluorophenyl (PFP) stationary phase is one of the most important phases after the C18 phase in terms of its applications. Three embedded polar groups (EPG)-containing stationary phases were newly synthesized to act the EPGs as additional interaction sites. The silica surface was initially modified with (3-aminopropyl)trimethoxysilane (APS). The APS-modified silicas were coupled with 2,3,4,5,6-pentafluorobenzoic acid, 2,3,4,5,6-pentafluorophenylacetic acid, and 2,3,4,5,6-pentafluoro-anilino(oxo)acetic acid to obtain Sil-PFP-BA, Sil-PFP-AA, and Sil-PFP-AN phases, respectively. The new phases were characterized by elemental analysis, ATR-FTIR, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The phases were evaluated with the Tanaka and Neue tests in reversed-phase liquid chromatography (RPLC). In addition, they were characterized as hydrophilic phases by the Tanaka test protocol used in hydrophilic interaction chromatography (HILIC) separation mode. The Sil-PFP-AA phase showed the highest molecular shape selectivity in RPLC, while Sil-PFP-AN achieved the highest separability in HILIC compared to the commercial PFP reference column. The Sil-PFP-AA phase was successfully applied for the analysis of capsaicinoids from real samples of fresh chili peppers (Capsicum spp.) in RPLC and the Sil-PFP-AN phase for vitamin C (ascorbic acid) in HILIC.

An active derivatization detection method for inline monitoring the isolation of carbohydrates by preparative liquid chromatography.

Polysaccharides have unique physio-chemical properties and various biological functions and have rapidly expanded interest over the last two decades. The purification of polysaccharides and their degraded oligosaccharides is challenging because carbohydrates have no chromophore and need a proper detector to monitor the chromatographic elution process. This study proposed an active derivatization detection (ADD) method based on active splitting from post-column flow, a microchannel reactor for efficient derivatization of polysaccharide reducing sugars with p-hydroxybenzoic acid hydrazide, and in-line detection by the UV detector of liquid chromatography system. The method and device were validated by the use of 11 monosaccharides, sulfated oligosaccharides (from degraded carrageenan), and polysaccharides (from Zizania latifolia). It has shown much better performance than the traditional phenol-sulfuric acid method (gold standard). Moreover, the ADD module presumes an add-in to the original preparative LC system, independent of the scale of the purification process and type of system. The developed method is versatile for chromatographic separation of carbohydrates and lays the foundation for their subsequent studies.

Loss of Pip4k2c confers liver-metastatic organotropism through insulin-dependent PI3K-AKT pathway activation.

Liver metastasis (LM) confers poor survival and therapy resistance across cancer types, but the mechanisms of liver-metastatic organotropism remain unknown. Here, through in vivo CRISPR-Cas9 screens, we found that Pip4k2c loss conferred LM but had no impact on lung metastasis or primary tumor growth. Pip4k2c-deficient cells were hypersensitized to insulin-mediated PI3K/AKT signaling and exploited the insulin-rich liver milieu for organ-specific metastasis. We observed concordant changes in PIP4K2C expression and distinct metabolic changes in 3,511 patient melanomas, including primary tumors, LMs and lung metastases. We found that systemic PI3K inhibition exacerbated LM burden in mice injected with Pip4k2c-deficient cancer cells through host-mediated increase in hepatic insulin levels; however, this circuit could be broken by concurrent administration of an SGLT2 inhibitor or feeding of a ketogenic diet. Thus, this work demonstrates a rare example of metastatic organotropism through co-optation of physiological metabolic cues and proposes therapeutic avenues to counteract these mechanisms.

Surface Modification of Silica with ß-Alanine Derivatives for Unique Applications in Liquid Chromatography.

Column purchasing cost is an important issue for an analyst to analyze complex sample matrices. Here, we report the development of an amino acid (ß-alanine)-derived stationary phase (Sil-Ala-C12) with strategic and effective interaction sites (amide and urea as embedded polar groups with C12 alkyl chain) able to separate various kinds of analytes. Owing to the balanced hydrophobicity and hydrophilicity of the phase, it showed exceptional separation abilities in both reversed-phase high-performance liquid chromatography (RP-HPLC) as a hydrophobic phase and hydrophilic interaction chromatography (HILIC) as a hydrophilic phase. Remarkably, the baseline separation was achieved for the challenging ß- and γ-isomers of tocopherol. Usually, three columns such as pentafluorophenyl or C30, C18, and sulfobetaine HILIC are required for the analysis of vitamin E, capsaicinoids, and vitamin C in chili peppers (Capsicum spp.), respectively. However, only Sil-Ala-C12 was able to separate these analytes. A single column can serve 3-4 purposes, which suggests that Sil-Ala-C12 had the potential to reduce column purchasing costs.

Design of ß-Alanine-Derived Novel C18 Stationary Phase Containing Embedded Urea and Amide Groups for the Separation of Versatile Analytes.

Novel stationary phases have been emerging recently. A ß-alanine-derived embedded urea and amide group-containing C18 phase (Sil-Ala-C18) was prepared for the first time. The media were packed into a 150 × 2.1 mm HPLC column, and the newly designed column was evaluated with the Tanaka and Neue test protocols in reversed-phase liquid chromatography (RPLC) separation mode. Moreover, it was characterized by the Tanaka test protocol in hydrophilic interaction chromatography (HILIC) separation mode. The new phase was characterized by elemental analysis, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and solid-state 13C cross-polarization magic angle spinning (CP/MAS) NMR spectroscopy at variable temperatures. The chromatographic evaluation involved very good separation of nonpolar shape-constrained isomers, polar and basic compounds in RPLC, and highly polar compounds in HILIC compared to the commercial reference columns. The Sil-Ala-C18 phase was able to separate the challenging ß- and γ-isomers of tocopherol. The phase was also successfully applied for the separation of the isomers of tocopherol (vitamin E) and capsaicinoids from real samples of chili peppers (Capsicum spp.) in RPLC and ascorbic acid (vitamin C) in HILIC.

Comprehensive two-dimensional gas chromatography with flow modulator coupled via tube plasma ionization to an atmospheric pressure high-resolution mass spectrometer for the analysis of vermouth volatile profile.

The analysis of complex samples is a big analytical challenge due to the vast number of compounds present in these samples as well as the influence matrix components could cause in the methodology. In this way, comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS) is a very powerful tool to achieve the characterization of complex samples. Nevertheless, due to possible coelutions occurring in these matrices, mixed spectra are generally obtained with electron ionization (EI) which could extremely complicate the identification of the analytes. Thereby, new methodology setups are required to improve the confidence on the identification in non-targeted determinations. Here, we present a high-throughput methodology consisting of GC × GC with flow modulation coupled to high-resolution atmospheric pressure mass spectrometry (HRMS) via a novel tube plasma ion source (TPI). The flow modulator allows to easily automate the GC × GC method compared to traditional cryo-modulators, while the soft ionization provided by TPI helps to preserve the [M]+• or [M+H]+ ions, thus increasing the confidence in the identification. Additionally, the combination of a flow modulation with an atmospheric pressure mass spectrometer significantly improves the sensitivity over flow modulated GC × GC-EI-MS methods because no split is required. This methodology was applied to the analysis of a complex sample such as vermouth where the volatile profile is usually considered by consumers as a product quality indicator since it raises the first sensations produced during its consumption. Using this approach, different classes of compounds were tentatively identified in the sample, including monoterpenes, terpenoids, sesquiterpenoids and carboxylic acid, and carboxylate esters among others, showing the great potential of a GC × GC-TPI-qTOF-MS platform for improving the confidence of the identifications in non-targeted applications.

Enhancing the compatibility of normal-phase chromatography x reversed-phase chromatography by combination of low-temperature sensitive aqueous-phase compatible normal- phase chromatography and at-column dilution modulation.

The nearly opposite retention mechanism in the two-dimensional liquid chromatography (2D-LC), which combines normal phase liquid chromatography (NPLC) and reversed phase liquid chromatography (RPLC), shows extremely high orthogonality and theoretical peak capacity. However, peak breakthrough and peak distortion caused by the highly incompatible 2D mobile phases counteracts the advantages offered by high orthogonality. To address this difficulty, this study proposes a comprehensive two-dimensional NPLC × RPLC integrating temperature-sensitive aqueous-phase compatible normal-phase chromatography (TSACNPLC) and at-column dilution modulation (ACDM). The proposed 2D-LC system uses an aqueous-miscible acetonitrile/methanol eluent in the 1st D NPLC, instead of an aqueous-phase immiscible eluent, such as n-hexane/methanol, to increase the miscibility with the RP mobile phase system. Additionally, the system exploits temperature-sensitive retention behavior to enhance the retention ability of aqueous-phase compatible NPLC. To verify the feasibility of the proposed 2D-LC, this study selected three multi-component samples with mid-to-low polarity, including ethoxylated (n ≈ 6) bisphenol A (BPA-6EO), ethoxylated (n ≈ 6) tristearylphenol (TSP-6EO), and safflower methanol extract. Next, the effectiveness of the constructed 2D-LC was systematically investigated, including low temperature-induced retention enhancement of NPLC, overcoming solvent incompatibility by ACDM, and optimization of 2 D separation conditions, was systematically investigated.

Multi-2D LC × LC as a Novel and Powerful Implement for the Maximum Separation of Complex Samples.

Achieving complete information about the chemical composition of complex samples requires the use of multianalytical platforms able to maximize the acquisition of high-quality data for unequivocal identification. However, this process requires long analysis times and several instruments. Food analysis is one of the analytical fields where the analysis of very complex samples has a huge impact. One of these complex samples is vermouth, a fortified wine based on the maceration of a large number of herbs, fruits, barks, seeds, and leaves. The application of conventional or even advanced analytical techniques like comprehensive two-dimensional (2D) liquid chromatography (LC × LC) does not provide enough separation power to resolve the complete profile of this sample. In this work, a novel 2DLC strategy called multi-2D LC × LC is developed. This new setup consists of the use of two different columns with different separation properties in the second dimension (2D) that can be selected during the LC × LC analysis accordingly to the chemical nature of the compounds eluted from the first dimension (1D). The vermouth sample was analyzed using a 1D-PFP and a combination of HILIC (from 0 to 30 min) and C18 (from 30 to the end) columns in the 2D. This setup increased both the peak capacity and the orthogonality of the analysis in comparison to the use of only one of the columns in the 2D. Multi-2D LC × LC is presented as an integrated 2DLC tool that maximizes the separation capacity for very complex samples.

Post-fast refeeding enhances intestinal stem cell-mediated regeneration and tumourigenesis through mTORC1-dependent polyamine synthesis.

For more than a century, fasting regimens have improved health, lifespan, and tissue regeneration in diverse organisms, including humans. However, how fasting and post-fast refeeding impact adult stem cells and tumour formation has yet to be explored in depth. Here, we demonstrate that post-fast refeeding increases intestinal stem cell (ISC) proliferation and tumour formation: Post-fast refeeding augments the regenerative capacity of Lgr5+ intestinal stem cells (ISCs), and loss of the tumour suppressor Apc in ISCs under post-fast refeeding leads to a higher tumour incidence in the small intestine and colon than in the fasted or ad libitum (AL) fed states. This demonstrates that post-fast refeeding is a distinct state. Mechanistically, we discovered that robust induction of mTORC1 in post-fast-refed ISCs increases protein synthesis via polyamine metabolism to drive these changes, as inhibition of mTORC1, polyamine metabolite production, or protein synthesis abrogates the regenerative or tumourigenic effects of post-fast refeeding. Thus, fast-refeeding cycles must be carefully considered when planning diet-based strategies for regeneration without increasing cancer risk, as post-fast refeeding leads to a burst not only in stem cell-driven regeneration but also in tumourigenicity.

Review on atmospheric pressure ionization sources for gas chromatography-mass spectrometry. Part I: Current ion source developments and improvements in ionization strategies.

The use of atmospheric pressure ionization (API) sources has become very popular for gas chromatography-mass spectrometry (GC-MS) determinations. GC-API-MS shows important advantages over traditional vacuum ionization sources such as a lower fragmentation preserving the molecular or quasi-molecular ion, the combination of GC separations with advanced mass spectrometers typically developed for liquid chromatography (LC) systems, a significantly higher sensitivity, or the reduction of costs due to the capability to use the same MS for both LC- and GC- couplings. For these reasons, the development of new API sources and GC-API-MS platforms has exponentially increased during the last years. Thus, this review is mainly focused on the last advances in GC-API-MS instrumentation. New setups and couplings on extensively reported API techniques as well as the development of new API sources for GC-MS coupling are thoroughly discussed. Moreover, novel ionization strategies have been reviewed to overcome some of the drawbacks of GC-API-MS methodologies.

Review on atmospheric pressure ionization sources for gas chromatography-mass spectrometry. Part II: Current applications.

The application of atmospheric pressure ionization (API) sources in gas chromatography-mass spectrometry (GC-MS) determinations is becoming more popular since they have shown great capabilities to sort out the main drawbacks of vacuum ionization techniques like electron ionization (EI) and chemical ionization (CI). The development of new API techniques and set-ups have grown in the last decades, opening the field of GC-MS to new applications and facing some of the major issues in current analytical methodologies such as the requirement of a compromise between sensitivity and selectivity. Thus, this review is mainly focused on the use of GC-API-MS in different application fields such as food analysis (food safety and food metabolomics), environmental analysis, clinical analysis, drug and pharmaceutical analysis, and petroleomics, among others. The methodologies have been critically reviewed to compare the performance of different API sources and approaches, highlighting the main contributions to overcoming some of the major limitations of the current methodologies as well as the new perspectives that GC-API-MS might open in the different fields.

Exopolysaccharide composition and size in Sulfolobus acidocaldarius biofilms.

Extracellular polymeric substances (EPS) comprise mainly carbohydrates, proteins and extracellular DNA (eDNA) in biofilms formed by the thermoacidophilic Crenarchaeon Sulfolobus acidocaldarius. However, detailed information on the carbohydrates in the S. acidocaldarius biofilm EPS, i.e., the exopolysaccharides (PS), in terms of identity, composition and size were missing. In this study, a set of methods was developed and applied to study the PS in S. acidocaldarius biofilms. It was initially shown that addition of sugars, most significantly of glucose, to the basal N-Z-amine-based growth medium enhanced biofilm formation. For the generation of sufficient amounts of biomass suitable for chemical analyses, biofilm growth was established and optimized on the surface of membrane filters. EPS were isolated and the contents of carbohydrates, proteins and eDNA were determined. PS purification was achieved by enzymatic digestion of other EPS components (nucleic acids and proteins). After trifluoroacetic acid-mediated hydrolysis of the PS fraction, the monosaccharide composition was analyzed by reversed-phase liquid chromatography (RP-LC) coupled to mass spectrometry (MS). Main sugar constituents detected were mannose, glucose and ribose, as well as minor proportions of rhamnose, N-acetylglucosamine, glucosamine and galactosamine. Size exclusion chromatography (SEC) revealed the presence of one single PS fraction with a molecular mass of 4-9 × 104 Da. This study provides detailed information on the PS composition and size of S. acidocaldarius MW001 biofilms and methodological tools for future studies on PS biosynthesis and secretion.

Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression.

Previous European land-use regression (LUR) models assumed fixed linear relationships between air pollution concentrations and predictors such as traffic and land use. We evaluated whether including spatially-varying relationships could improve European LUR models by using geographically weighted regression (GWR) and random forest (RF). We built separate LUR models for each year from 2000 to 2019 for NO2, O3, PM2.5 and PM10 using annual average monitoring observations across Europe. Potential predictors included satellite retrievals, chemical transport model estimates and land-use variables. Supervised linear regression (SLR) was used to select predictors, and then GWR estimated the potentially spatially-varying coefficients. We developed multi-year models using geographically and temporally weighted regression (GTWR). Five-fold cross-validation per year showed that GWR and GTWR explained similar spatial variations in annual average concentrations (average R2 = NO2: 0.66; O3: 0.58; PM10: 0.62; PM2.5: 0.77), which are better than SLR (average R2 = NO2: 0.61; O3: 0.46; PM10: 0.51; PM2.5: 0.75) and RF (average R2 = NO2: 0.64; O3: 0.53; PM10: 0.56; PM2.5: 0.67). The GTWR predictions and a previously-used method of back-extrapolating 2010 model predictions using CTM were overall highly correlated (R2 > 0.8) for all pollutants. Including spatially-varying relationships using GWR modestly improved European air pollution annual LUR models, allowing time-varying exposure-health risk models.

Aliphatic Aldehydes in the Earth's Crust-Remains of Prebiotic Chemistry?

The origin of life is a mystery that has not yet been solved in the natural sciences. Some promising interpretative approaches are related to hydrothermal activities. Hydrothermal environments contain all necessary elements for the development of precursor molecules. There are surfaces with possible catalytic activity, and wide ranges of pressure and temperature conditions. The chemical composition of hydrothermal fluids together with periodically fluctuating physical conditions should open up multiple pathways towards prebiotic molecules. In 2017, we detected potentially prebiotic organic substances, including a homologous series of aldehydes in Archean quartz crystals from Western Australia, more than 3 billion years old. In order to approach the question of whether the transformation of inorganic into organic substances is an ongoing process, we investigated a drill core from the geologically young Wehr caldera in Germany at a depth of 1000 m. Here, we show the existence of a similar homologous series of aldehydes (C8 to C16) in the fluid inclusions of the drill core calcites, a finding that supports the thesis that hydrothermal environments could possibly be the material source for the origin of life.