Chemical Noise Research Articles

Critical Assessment of Clean-up Procedures Used for Gas Chromatography-Mass Spectrometry Analysis of Pesticide Residues in Cannabis Inflorescence.

Accurate analysis of pesticide residues in such a complex matrix as cannabis is a challenging task. The aim of this study was to find an optimal way of removing abundant matrix co-extracts from Quick, Easy, Cheap, Effective, Rugged, and Safe extract prior to its analysis by gas chromatography-tandem mass spectrometry (GC-MS/MS). Out of the seven procedures tested, clean-up with SupelQuE Verde sorbent provided the most satisfactory performance characteristics for 277 targeted pesticides, which is the highest number of these analytes ever investigated within a GC-MS-based study focused on cannabis. The criteria set in the SANTE/11312/2021 V2 document were considered to assess the results obtained within the method validation. Recoveries in the range of 70%-120% with repeatability ≤20% were obtained for 219 and 114 pesticides at spiking levels of 0.1 and 0.01mg/kg, respectively. For a deeper insight into the function of tested sorbents and to understand the effects of interfering matrix co-extracts, the two-dimensional GC coupled with the time-of-flight MS method was employed for the analysis of all purified extracts. Co-eluting major phytocannabinoids and free fatty acids were shown to be responsible for high "chemical noise", increasing limits of quantification of pesticides at respective retention times. Since cannabis chemotypes fairly differ in phytocannabinoid content, the matrix effects, thus performance characteristics, may vary. Under such conditions, validation is recommended for different cannabis chemotypes.

Selective Gas-Phase Depletion of Chemical Contaminants in Dissolved Organic Matter Increases Compositional Coverage by FT-ICR Mass Spectrometry.

Fourier transform ion cyclotron resonance mass spectrometry of dissolved organic matter (DOM) extracted from environmental samples provides molecular speciation that enables visualization of compositional trends in the fate and cycling of biogenic and anthropogenic organics. Often, chemical contamination is introduced during field sampling (i.e., remote locations, cannot use glass). Further, preconcentration of DOM by solid-phase extraction often results in chemical contamination. When chemical noise is a dominant fraction of the ion signal, mass spectral performance is degraded by reduction of the ion trap analyte accumulation capacity and enhanced ion cloud dephasing during ICR detection. We have developed gas-phase ion depletion of unwanted chemical contaminants during ion injection into the linear RF ion trap of the hybrid linear ion trap 21 T FT-ICR mass spectrometer that improves detection of analytes by removing unwanted chemical noise. We demonstrate improvements in signal-to-noise ratio, dynamic range, and the number of observed analytes in dissolved organic matter samples that results in a 40-100% increase in the number of identified analytes. In many cases, the number of peaks observed per nominal mass more than doubles over select m/z regions. This gas-phase "clean-up" can salvage precious samples challenged by sampling location, sample volume, or collection protocols that cannot be avoided and maximizes the compositional information obtained. Further, this approach is generalizable and extendable to any hybrid linear ion trap instrument platform (e.g., LTQ-Orbitrap or linear ion trap-TOF). We highlight the power of gas-phase depletion with electrospray ionization, but this method is also applicable to other ionization modes.

Bottom-up Histone Post-translational Modification Analysis using Liquid Chromatography, Trapped Ion Mobility Spectrometry, and Tandem Mass Spectrometry.

The amino acid position within a histone sequence and the chemical nature of post-translational modifications (PTMs) are essential for elucidating the "Histone Code". Previous work has shown that PTMs induce specific biological responses and are good candidates as biomarkers for diagnostics. Here, we evaluate the analytical advantages of trapped ion mobility (TIMS) with parallel accumulation-serial fragmentation (PASEF) and tandem mass spectrometry (MS/MS) for bottom-up proteomics of model cancer cells. The study also considered the use of nanoliquid chromatography (LC) and traditional methods: LC-TIMS-PASEF-ToF MS/MS vs nLC-TIMS-PASEF-ToF MS/MS vs nLC-MS/MS. The addition of TIMS and PASEF-MS/MS increased the number of detected peptides due to the added separation dimension. All three methods showed high reproducibility and low RSD in the MS domain (<5 ppm). While the LC, nLC and TIMS separations showed small RSD across samples, the accurate mobility (1/K0) measurements (<0.6% RSD) increased the confidence of peptide assignments. Trends were observed in the retention time and mobility concerning the number and type of PTMs (e.g., ac, me1-3) and their corresponding unmodified, propionylated peptide that aided in peptide assignment. Mobility separation permitted the annotation of coeluting structural and positional isomers and compared with nLC-MS/MS showed several advantages due to reduced chemical noise.

Crown ether dopant to reduce ion suppression and improve detection in the liquid microjunction surface sampling probe.

Sodium and potassium are required in agar media for the growth of some microorganisms (e.g., marine bacteria). However, alkali cations are a significant source of contamination for mass spectrometry causing ion suppression and adduct formation. Conventionally, salts can be removed before mass spectrometric analysis with appropriate and often lengthy sample preparation. The direct mass spectrometric sampling of bacterial colonies grown on agar media seeks to minimize or eliminate sample preparation to improve workflow. However, this may exacerbate ion suppression and contamination since these metal cations will degrade spectral quality and limit the rapid profiling of microbial metabolites. Different approaches are needed to sequester sodium and potassium ions to minimize unwanted background interferences. Herein, we use crown ethers (CEs) in combination with a liquid microjunction surface sampling probe (LMJ-SSP) to directly sample the surface of the bacterial colonies from two marine bacteria species (Pseudoalteromonas rubra DSM6842 and Pseudoalteromonas tunicata DSM 14096). CEs (e.g., 18-crown-6 or 15-crown-5) are added to the carrier solvent of the LMJ-SSP, the chemical noise is reduced, and spectra are easier to interpret. The liquid microjunction formed at the tip of LMJ-SSP was used to directly touch bacterial colonies on agar. The carrier solvent was either methanol (100%) or methanol: H2O (50:49.9%) with or without 0.01% CEs. Information-theoretic measures are employed to investigate qualitative changes between spectra before and after adding CEs. Our work demonstrates the capability of CEs to reduce background interferences within the direct profiling of bacterial colonies from agar plates. The data obtained from both P. rubra DSM6842 and P. tunicata DSM 14096 show that CEs can be used to mitigate the salty background and improve compound detection. Our approach can be implemented in natural product discovery using LMJ-SSP to allow fast and accurate detection of interesting/novel compounds.

Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer.

Chemical exposures may impact human metabolism and contribute to the etiology of neurodegenerative disorders like Alzheimer's Disease (AD). Identifying these small metabolites involves matching experimental spectra to reference spectra in databases. However, environmental chemicals or physiologically active metabolites are usually present at low concentrations in human specimens. The presence of noise ions can significantly degrade spectral quality, leading to false negatives and reduced identification rates. In response to this challenge, the Spectral Denoising algorithm removes both chemical and electronic noise. Spectral Denoising outperformed alternative methods in benchmarking studies on 240 tested metabolites. It improved high confident compound identifications at an average 35-fold lower concentrations than previously achievable. Spectral Denoising proved highly robust against varying levels of both chemical and electronic noise even with >150-fold higher intensity of noise ions than true fragment ions. For human plasma samples of AD patients that were analyzed on the Orbitrap Astral mass spectrometer, Denoising Search detected 2.3-fold more annotated compounds compared to the Exploris 240 Orbitrap instrument, including drug metabolites, household and industrial chemicals, and pesticides. This combination of advanced instrumentation with a superior denoising algorithm opens the door for precision medicine in exposome research.

Preserving condensate structure and composition by lowering sequence complexity

Biomolecular condensates play a vital role in organizing cellular chemistry. They selectively partition biomolecules, preventing unwanted cross talk and buffering against chemical noise. Intrinsically disordered proteins (IDPs) serve as primary components of these condensates due to their flexibility and ability to engage in multivalent interactions, leading to spontaneous aggregation. Theoretical advancements are critical at connecting IDP sequences with condensate emergent properties to establish the so-called molecular grammar. We proposed an extension to the stickers and spacers model, incorporating heterogeneous, nonspecific pairwise interactions between spacers alongside specific interactions among stickers. Our investigation revealed that although spacer interactions contribute to phase separation and co-condensation, their nonspecific nature leads to disorganized condensates. Specific sticker-sticker interactions drive the formation of condensates with well-defined networked structures and molecular composition. We discussed how evolutionary pressures might emerge to affect these interactions, leading to the prevalence of low-complexity domains in IDP sequences. These domains suppress spurious interactions and facilitate the formation of biologically meaningful condensates.

Improving throughput in Orbitrap using the ion funnel with orthogonal injection and observation of chemical noise in high-resolution MS instruments

Overall, the nanoflow chromatographic separation, nano-electrospray source, and Orbitrap Elite mass spectrometer with the dual-stage ion funnel that replaced the standard heated-cone inlet were used in the MS analysis of low-abundance peptide samples. The analytical advantage of the ion funnel was demonstrated in the LC-MS analysis of the HeLa protein digest mixture. Chemical noise patterns in Orbitrap, linear ion traps, and quadrupole time-of-flight mass spectrometers were compared. The chemical noise patterns in Orbitrap were found to be generally similar to those observed in linear ion traps and time-of-flight instruments, yet it was observed only under the condition of selecting a few Da mass range for the mass analysis. The Orbitrap's ultrahigh mass resolution enabled the intricate internal structure of the chemical noise to be uncovered. In addition to singly charged ions representing a bulk of chemical noise, doubly charged ions were also observed, though the intensity of the latter was found to be significantly lower, suggesting that chemical noise-limited detection levels in the MS analysis of low-abundance peptides could be significantly lower for 2+ or 3+ peptide ions compared to singly charged ones.

Mathematical Modeling of the Normal Fuel Consumption of Certain Vehicles

The scientific paper introduces original research and unique perspectives on the technical and economic aspects of fuel consumption in motor vehicles. Numerous experts argue that conducting practical experiments, specifically through active determinations, can yield noteworthy outcomes in this domain. To substantiate this viewpoint, the paper includes practical examples of experiments and considerations related to the mathematical model used for validating objective functions. These functions encompass the average fuel consumption in liters per 100 kilometers and the quantity of CO2 emitted per kilometer by the thermal engine of motor vehicles. The research also articulates the authors’ stance, citing the World Health Organization’s recommendation to decrease urban traffic speed from 50 km/h to 30 km/h. This reduction aims to mitigate traffic accidents and curb chemical noise and vibration pollution. The study amalgamates results from tests conducted on both urban and extra-urban routes, incorporating eco-friendly driving practices for comparative purposes. The primary focus of the mathematical model is to validate fuel consumption under real driving conditions. The paper concludes with insights and future research directions in modeling.

Multiple ion isolation and accumulation events for selective chemical noise reduction and dynamic range enhancement in MALDI imaging mass spectrometry.

Abundant chemical noise in MALDI imaging mass spectrometry experiments can impede the detection of less abundant compounds of interest. This chemical noise commonly originates from the MALDI matrix as well as other endogenous compounds present in high concentrations and/or with high ionization efficiencies. MALDI imaging mass spectrometry of biological tissues measures numerous biomolecular compounds that exist in a wide range of concentrations in vivo. When ion trapping instruments are used, highly abundant ions can dominate the charge capacity and lead to space charge effects that hinder the dynamic range and detection of lowly abundant compounds of interest. Gas-phase fractionation has been previously utilized in mass spectrometry to isolate and enrich target analytes. Herein, we have characterized the use of multiple continuous accumulations of selected ions (Multi CASI) to reduce the abundance of chemical noise and diminish the effects of space charge in MALDI imaging mass spectrometry experiments. Multi CASI utilizes the mass-resolving capability of a quadrupole mass filter to perform multiple sequential ion isolation events prior to a single mass analysis of the combined ion population. Multi CASI was used to improve metabolite and lipid detection in the MALDI imaging mass spectrometry analysis of rat brain tissue.

Stable Isotope Labeling-Based Nontargeted Strategy for Characterization of the In Vitro Metabolic Profile of a Novel Doping BPC-157 in Doping Control by UHPLC-HRMS

Traditional strategies for the metabolic profiling of doping are limited by the unpredictable metabolic pathways and the numerous proportions of background and chemical noise that lead to inadequate metabolism knowledge, thereby affecting the selection of optimal detection targets. Thus, a stable isotope labeling-based nontargeted strategy combined with ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) was first proposed for the effective and rapid metabolism analysis of small-molecule doping agents and demonstrated via its application to a novel doping BPC-157. Using 13C/15N-labeled BPC-157, a complete workflow including automatic 13C0,15N0-13C6,15N2 m/z pair picking based on the characteristic behaviors of isotope pairs was constructed, and one metabolite produced by a novel metabolic pathway plus eight metabolites produced by the conventional amide-bond breaking metabolic pathway were successfully discovered from two incubation models. Furthermore, a specific method for the detection of BPC-157 and the five main metabolites in human urine was developed and validated with satisfactory detection limits (0.01~0.11 ng/mL) and excellent quantitative ability (linearity: 0.02~50 ng/mL with R2 &gt; 0.999; relative error (RE)% &lt; 10% and relative standard deviation (RSD)% &lt; 5%; recovery &gt; 90%). The novel metabolic pathway and the in vitro metabolic profile could provide new insights into the biotransformation of BPC-157 and improved targets for doping control.

NECTAR: A New Algorithm for Characterizing and Correcting Noise in QToF-Mass Spectrometry Imaging Data.

A typical mass spectrometry imaging experiment yields a very high number of detected peaks, many of which are noise and thus unwanted. To select only peaks of interest, data preprocessing tasks are applied to raw data. A statistical study to characterize three types of noise in MSI QToF data (random, chemical, and background noise) is presented through NECTAR, a new NoisE CorrecTion AlgoRithm. Random noise is confirmed to be dominant at lower m/z values (∼50-400 Da) while systematic chemical noise dominates at higher m/z values (>400 Da). A statistical approach is presented to demonstrate that chemical noise can be corrected to reduce its presence by a factor of ∼3. Reducing this effect helps to determine a more reliable baseline in the spectrum and therefore a more reliable noise level. Peaks are classified according to their spatial S/N on the single ion images, and background noise is thus removed from the list of peaks of interest. This new algorithm was applied to MALDI and DESI QToF data generated from the analysis of a mouse pancreatic tissue section to demonstrate its applicability and ability to filter out these types of noise in a relevant data set. PCA and t-SNE multivariate analysis reviews of the top 4000 peaks and the final 744 and 299 denoised peak list for MALDI and DESI, respectively, suggests an effective removal of uninformative peaks and proper selection of relevant peaks.

Imaging and Structural Characterization of Phosphatidylcholine Isomers from Rat Brain Tissue Using Sequential Collision-Induced Dissociation/Electron-Induced Dissociation.

The chemical complexity of biological tissues creates challenges in the analysis of lipids via imaging mass spectrometry. The presence of isobaric and isomeric compounds introduces chemical noise that makes it difficult to unambiguously identify and accurately map the spatial distributions of these compounds. Electron-induced dissociation (EID) has previously been shown to profile phosphatidylcholine (PCs) sn-isomers directly from rat brain tissue in matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry. However, the acquisition of true pixel-by-pixel images, as opposed to regional profiling measurements, using EID is difficult due to low fragmentation efficiency and precursor ion signal dilution into multiple fragment ion channels, resulting in low sensitivity. In this work, we have developed a sequential collision-induced dissociation (CID)/EID method to visualize the distribution of sn-isomers in MALDI imaging mass spectrometry experiments. Briefly, CID is performed on sodium-adducted PCs, which results in facile loss of the phosphocholine headgroup. This ion is then subjected to an EID analysis. Since the lipid headgroup is removed prior to EID, a major fragmentation pathway common to EID ion activation is eliminated, resulting in a more sensitive analysis. This sequential CID/EID workflow generates sn-specific fragment ions allowing for the assignment of the sn-positions. Carbon-carbon double-bond (C═C) positions are also localized along the fatty acyl tails by the presence of a 2 Da shift pattern in the fragment ions arising from carbon-carbon bond cleavages. Moreover, the integration of the CID/EID method into MALDI imaging mass spectrometry enables the mapping of the absolute and relative distribution of sn-isomers at every pixel. The localized relative abundances of sn-isomers vary throughout brain substructures and likely reflect different biological functions and metabolism.

A-216 Measuring Inflammation and Cardiovascular Markers at Benchtop NMR using Diffusion and Relaxation Edited Experiments

Abstract Background Metabolic phenotyping is an established tool in systems medicine that captures a profile of one’s individual health status and reflects the interaction between genes and external stressors. It uses analytical platforms such as NMR or MS to acquire molecular profiles, and modelling to extract actionable knowledge. Applying these techniques to a cohort of Australians infected by SARS-CoV-2 revealed a strong alteration in regions of 1D NMR spectra associated with lipoproteins and glycoproteins, and referred as Supramolecular Phospholipid Composite SPC (δ = 3.2 ppm) and Glyc (δ = 2.07 ppm). The latter is an established marker of inflammation. These results were later confirmed using larger cohorts from Spain (n = 525) and the UK (n = 1022). The urgent need for very rapid testing, at the early stage of the pandemic, prompted the development of bespoke NMR experiments able to measure this lipoproteins/glycoproteins signature without requiring complex modelling. Methods Physico-chemical properties of lipoprotein particles, such as diffusion, transverse and longitudinal relaxation rates, differ from low molecular weight metabolites. Therefore, an edited experiment JEDI (PGPE) was designed that combines diffusion, relaxation and scalar coupling editing blocks to produce a lipoprotein profile devoid of chemical noise (overlapping peaks) and where peaks give quantitative results. Results The SPC peak was further broken down into 3 sub-regions that are related to the main subfraction HDL and LDL (choline headgroups of phospholipids). Interestingly the ratio of SPC3/SPC2 highly correlates with the Apo-B100/Apo-A1 ratio, an established cardiovascular risk marker that is increased in patients with COVID19. Longitudinal data suggest this latter remains elevated even 30 days after onset in some patients. Furthermore, the edited experiment performs equally well at low field using a benchtop NMR. Conclusion Translation of a spectral signature relevant for monitoring COVID patients from high to low field NMR is possible using sophisticated editing techniques.

Quantification of pharmaceutical compounds in tissue and plasma samples using selective ion accumulation with multiple mass isolation windows.

Quantification of pharmaceutical compounds using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is an alternative to traditional liquid chromatography (LC)-MS techniques. Benefits of MALDI-based approaches include rapid analysis times for liquid samples and imaging mass spectrometry capabilities for tissue samples. As in most quantification experiments, the use of internal standards can compensate for spot-to-spot and shot-to-shot variability associated with MALDI sampling. However, the lack of chromatographic separation in traditional MALDI analyses results in diminished peak capacity due to the chemical noise background, which can be detrimental to the dynamic range and limit of detection of these approaches. These issues can be mitigated by using a hybrid mass spectrometer equipped with a quadrupole mass filter (QMF) that can be used to fractionate ions based on their mass-to-charge ratios. When the masses of the analytes and internal standards are sufficiently disparate in mass, it can be beneficial to effect multiple narrow mass isolation windows using the QMF, as opposed to a single wide mass isolation window, to minimize chemical noise while allowing for internal standard normalization. Herein, we demonstrate a MALDI MS quantification workflow incorporating multiple sequential mass isolation windows enabled on a QMF, which divides the total number of MALDI laser shots into multiple segments (i.e., one segment for each mass isolation window). This approach is illustrated through the quantitative analysis of the pharmaceutical compound enalapril in human plasma samples as well as the simultaneous quantification of three pharmaceutical compounds (enalapril, ramipril, and verapamil). Results show a decrease in the limit of detection, relative standard deviations below 10%, and accuracy above 85% for drug quantification using multiple mass isolation windows. This approach has also been applied to the quantification of enalapril in brain tissue from a rat dosed in vitro. The average concentration of enalapril determined by imaging mass spectrometry is in agreement with the concentration determined by LC-MS, giving an accuracy of 104%.

Modern health worries and annoyance from environmental factors are largely unrelated to smoking, alcohol consumption, and physical activity

ObjectiveModern health worries, as well as environmental annoyance from chemical agents, noise, and electromagnetic exposure are associated with symptom reporting and marked affective-behavioural changes. As promotion and protection of health is a primary characteristic of these conditions, it can be expected that they will be related to less risk behaviour (smoking and alcohol consumption) and more health behaviour (physical activity), both cross-sectionally and longitudinally. MethodsHypotheses were tested in a sample of 2336 individuals participating in T1 and T2 data collection (3 years apart) of the Västerbotten Environmental Health Study, Sweden. Health-related behaviours were assessed using single self-report questions. Smoking was measured on a binary (yes-or-no) scale; frequency of alcohol consumption and physical activity was measured on a 5-point and a 4-point scale, respectively. ResultsModern health worries showed no cross-sectional association with the three behaviours, whereas annoyance was typically inversely, very weakly, related to smoking and alcohol consumption. Physical activity was significantly positively associated only with chemical annoyance. None of the variables significantly predicted change of behaviours at T2 after controlling for the respective T1 value and demographic variables. Conclusions: Individuals with high levels of modern health worries and annoyance from various environmental agents are not clearly characterized by a healthier lifestyle. Perhaps they focus on the alleviation of their existing symptoms; alternatively, somatic symptom distress decreases their cognitive-affective resources necessary for a long-term life style change.

Proteomics Methodologies: The Search of Protein Biomarkers Using Microfluidic Systems Coupled to Mass Spectrometry.

Protein biomarkers have been the subject of intensive studies as a target for disease diagnostics and monitoring. Indeed, biomarkers have been extensively used for personalized medicine. In biological samples, these biomarkers are most often present in low concentrations masked by a biologically complex proteome (e.g., blood) making their detection difficult. This complexity is further increased by the needs to detect proteoforms and proteome complexity such as the dynamic range of compound concentrations. The development of techniques that simultaneously pre-concentrate and identify low-abundance biomarkers in these proteomes constitutes an avant-garde approach to the early detection of pathologies. Chromatographic-based methods are widely used for protein separation, but these methods are not adapted for biomarker discovery, as they require complex sample handling due to the low biomarker concentration. Therefore, microfluidics devices have emerged as a technology to overcome these shortcomings. In terms of detection, mass spectrometry (MS) is the standard analytical tool given its high sensitivity and specificity. However, for MS, the biomarker must be introduced as pure as possible in order to avoid chemical noise and improve sensitivity. As a result, microfluidics coupled with MS has become increasingly popular in the field of biomarker discovery. This review will show the different approaches to protein enrichment using miniaturized devices and the importance of their coupling with MS.

Separation and Simultaneous Trapping of Multiply Charged and Singly Charged Ions for Mass Spectrometry: Application to Lipid Mixtures.

Conventional electrospray ionization (ESI) of mixtures can give rise to singly and multiply charged analyte species that overlap in mass-to-charge (m/z) ratios, which can complicate the analysis of individual components. The overlap in m/z for ions of different mass and charge is particularly problematic when ions of low relative abundance are of interest. For example, cardiolipins (CLs) are structurally complex phospholipids present in low relative abundance in the lipidome but play crucial roles in mitochondrial metabolism and various regulatory processes. ESI of CLs in negative ion mode shows abundant doubly deprotonated ions and minor singly deprotonated ions. In the ESI of lipid extracts, highly abundant singly charged phospholipids extensively overlap in m/z space with CL dianions of much lesser abundance, thereby complicating the study of the CLs. To address this challenge, we employed a gas-phase approach to separate singly charged ions from a population of ions of mixed charge states while allowing for the storage of one or both of the separated ion populations. Herein, we describe the considerations for applying enhanced singly charged (ESC) and enhanced multiply charged (EMC) scans to perform a gas-phase separation of singly charged lipids from doubly charged lipids in an Escherichia coli extract. This method allows for improved signal-to-noise (S/N) ratio of low abundance ions with minimal overall signal loss, removal of "chemical noise" arising from singly charged ions, and allows for retention of spatially separated ions within a mass spectrometer.

Short-term impact of noise, other air pollutants and meteorological factors on emergency hospital mental health admissions in the Madrid region

BackgroundA number of environmental factors, such as air pollution, noise in urbanised settings and meteorological-type variables, may give rise to important effects on human health. In recent years, many studies have confirmed the relation between various mental disorders and these factors, with a possible impact on the increase in emergency hospital admissions due to these causes. The aim of this study was to analyse the impact of a range of environmental factors on daily emergency hospital admissions due to mental disorders in the Madrid Autonomous Region (MAR), across the period 2013–2018. MethodologyLongitudinal ecological time series study analysed by Generalised Linear Models with Poisson regression, with the dependent variable being daily Emergency Hospital Mental Health Admissions (EHMHA) in the MAR, and the independent variable being mean daily concentrations of chemical pollutants, noise levels and meteorological variables. ResultsEHMHA were related statistically significantly in the short term with diurnal noise levels. Relative risks (RRs) for total admissions due to mental disorders and self-inflicted injuries, in the case of diurnal noise was RR: 1.008 95%CI (1.003 1.013). Admissions attributable to diurnal noise account for 5.5% of total admissions across the study period. There was no association between hospital admissions and chemical air pollution. ConclusionNoise is a variable that shows a statistically significant short-term association with EHMHA across all age groups in the MAR region. The results of this study may serve as a basis for drawing up public health guidelines and plans, which regard these variables as risk factors for mental disorders, especially in the case of noise, since this fundamentally depends on anthropogenic activities in highly urbanised areas with high levels of traffic density.

Analysis of Liquid Particles in Aerosols via Charge-Induction Amperometry (ALPACA) for Rapid Electrospray Droplet Charge Analysis.

The rapid and on-line study of aerosols and their properties is technically demanding due to their small size (<10 μm diameter) and the resultant required scale of any such measurements. Most such techniques require the use of lasers (e.g., phase Doppler anemometry), condensation growth, or other complex hardware. To this end we introduce analysis of liquid particles in aerosols via charge-induction amperometry (ALPACA), an extremely simple potentiostat-based technique capable of on-line, rapid measurement of the aggregate charge of aerosol particles. This technique demonstrates high signal-to-noise responses, is not subject to chemical noise, and has the potential for significant future miniaturization. This technique is applied in this work for the detection of charges on electrosprayed droplets. The mechanism of detection of the technique is discussed using both amperometry and open circuit potential (OCP) to measure droplet charge properties. ALPACA represents a significant advancement toward simple, inexpensive aerosol charge detection.

Convolutional Codec Implemented by Genetic Circuits for Molecular Communication.

Molecular communication (MC), which transmits information through molecules, has emerged as a promising technique to enable communication links between nanomachines. To establish information transmission using molecules, synthetic biology through genetic circuits techniques can be utilized to construct biological components. Recent efforts on genetic circuits have produced many exciting MC systems and generated substantial insights. With basic gene regulatory modules and motifs, researchers are now constructing artificial networks with novel functions that will serve as building blocks in the MC system. In this paper, we investigate the design of genetic circuits to implement the convolutional codec in a diffusion-based MC channel with the concentration shift keying (CSK) transmission scheme. At the receiver, a majority-logic decoder is applied to decode the received symbols. These functions are completely realized in the field of biochemistry through the activation and inhibition of genes and biochemical reactions, rather than through classical electrical circuits. Biochemical simulations are used to verify the feasibility of the system and analyze the impairments caused by diffusion noise and chemical reaction noise of genetic circuits.