Multiple Mass Research Articles

Multimass Analysis of Adeno-Associated Virus Vectors by Orbitrap-Based Charge Detection Mass Spectrometry.

Adeno-associated virus (AAV) vectors have attracted significant attention as the main platform for gene therapy. To ensure the safety and efficacy of AAV vectors when used as gene therapy drugs, it is essential to assess their critical quality attributes (CQAs). These CQAs include the genome packaging status, the size of the genome encapsidated within the AAV capsid, and the stoichiometry of viral proteins (VPs) that constitute the AAV capsids. Analytical methods have been established for evaluating CQAs, such as analytical ultracentrifugation, capillary gel electrophoresis with laser-induced fluorescence detection, and capillary gel electrophoresis using sodium dodecyl sulfate with UV detection. Here, we present a multimass analysis of AAV vectors using orbitrap-based charge detection mass spectrometry (CDMS), a single-ion mass spectrometry. Orbitrap-based CDMS facilitates the quantitative evaluation of the genome packaging status based on the mass distribution of empty and full particles. Additionally, we established a novel method to analyze the encapsidated genome directly without pretreatment, such as protein digestion or heat treatment, and to estimate the stoichiometric variation of VP for the capsid based on the mass distribution constituted by the single peak corresponding to AAV particles. Orbitrap-based CDMS is a distinctive method that allows multiple mass characterizations of AAV vectors with a small sample volume of 20 μL for 1013 cp/mL in a short time (30 min), and it holds the potential to become a new standard method in the assessment of CQAs for AAV vectors.

Absolute Quantitative Targeted Monitoring of Potential Plasma Protein Biomarkers: A Pilot Study on Healthy Individuals.

The development of blood tests for the early detection of individual predisposition to socially significant diseases remains a pressing issue. In this pilot study, multiple reaction monitoring mass spectrometry (MRM-MS) with a BAK-270 assay was applied for protein concentrations analysis in blood plasma from 21 healthy volunteers of the European cohort. The levels of 138 plasma proteins were reliably and precisely quantified in no less than 50% of samples. The quantified proteins included 66 FDA-approved markers of cardiovascular diseases (CVD), and other potential biomarkers of pathologies such as cancer, diabetes mellitus, and Alzheimer's disease. The analysis of individual variations of the plasma proteins revealed significant differences between the male (11) and female (10) groups. In total, fifteen proteins had a significantly different concentration in plasma; this included four proteins that exhibited changes greater than ±1.5-fold, three proteins (RBP4, APCS, and TTR) with higher levels in males, and one (SHBG) elevated in females. The obtained results demonstrated considerable agreement with the data collected from 20 samples of a North American cohort, which were analyzed with the similar MRM assay. The most significant differences between the cohorts of the two continents were observed in the level of 42 plasma proteins (including 24 FDA markers), of which 17 proteins showed a ≥1.5-fold change, and included proteins increased in North Americans (APOB, CRTAC1, C1QB, C1QC, C9, CRP, HP, IGHG1, IGKV4-1, SERPING1, RBP4, and AZGP1), as well as those elevated in Europeans (APOF, CD5L, HBG2, SELPLG, and TNA). The results suggest a different contribution of specific (patho)physiological pathways (e.g., immune system and blood coagulation) to the development of socially significant diseases in Europeans and North Americans, and they should be taken into account when refining diagnostic panels.

Long Chain Base Profiling with Multiple Reaction Monitoring Mass Spectrometry.

Sphingolipids (SLs) are essential lipids with important functions in membrane formation and cell signaling. The presence of a long chain base (LCB) structure is common to all SLs. De novo SL synthesis is initiated by the enzyme serine-palmitoyltransferase (SPT), which forms an LCB by the conjugation from serine and fatty acyl-CoAs. SPT can metabolize a variety of acyl-CoA substrates, which form diverse LCB structures within and across species. The LCB then undergoes further metabolic modifications resulting in an extraordinarily diverse spectrum of sphingolipids formed. SL analysis, using liquid chromatography-mass spectrometry (LC-MS)-based methods, poses challenges due to the diverse range of frequently isobaric species. This complexity complicates the identification of underlying LCB structures using standard lipidomics approaches. Here, we describe a simplified method to analyze the LCB profile in cells, tissue, and blood. The procedure involves chemical hydrolysis to remove the conjugated headgroups and N-acyl chains, allowing to specifically resolve the underlying LCB structures by LC-MS. This method can also be combined with an isotope labeling approach to determine in vivo SPT activity and total SL de novo synthesis over time.

B-146 Unlocking the potential of large-cohort proteomics studies with the Orbitrap Astral mass platform

Abstract Background Large-cohort proteomics analysis using mass spectrometry is a powerful approach to discover and validate new biomarkers. In combination with clinical data and computational analysis, large-cohort proteomics study brings opportunities in improving early diagnosis, refining patient stratification, and predicting/monitoring treatment response. Yet, to achieve meaningful biological insights in large-cohort studies, robust, reproducible, and comprehensive proteome profiling in a high-throughput manner still remains challenging. Here, we use a high-resolution accurate mass (HRAM) Oribtrap Astral platform to enable high-quality and robust protein quantification across thousands of LC-MS/MS analyses. With a throughput of 100 samples/day, we can reproducibly profile ∼9000 proteins from human cell line and ∼800 proteins from undepleted plasma across multiple instruments and more than 10 consecutive days in a 24/7 operation mode. Methods Experiments were performed on multiple Orbitrap Astral mass spectrometers with and without FAIMS Pro interface. Chromatographic separations were performed using a trap/elute method on Vanquish Neo system at a 11-minute gradient and a flow rate of 1ul/min, resulting in a throughput of 100 samples/day. Undepleted plasma digest was analyzed in a 24/7 mode for > 1000 injections on each LC-MS/MS setup. In addition, HeLa digest as quality control (QC) was analyzed every 12hours. The Oribtrap Astral platform was operated in data-independent acquisition (DIA) mode using a full scan with m/z 380-980, and DIA MS/MS scans with an isolation window of 2Th. Resulting DIA raw files were automatically transferred and processed using Chimerys in a beta version of Proteome Discoverer software. Results Multiple LC-MS/MS systems were operated in DIA mode either with or without FAIMS Pro device in a 24/7 operation mode at a throughput of 100SPD. Undepleted plasma digest was analyzed with >1000 injections on each LC-MS/MS setup. To monitor the baseline performance, HeLa digest served as QC were analyzed periodically every 12 hours with 3 technical replicates each time. To effectively manage and analyze these thousands of data files generated, we developed an automated data transfer and analysis pipeline. Automatically, the resulting DIA raw data files were immediately transferred to a server, then processed by state-of-the-art intelligent search algorithm Chimerys. Benefiting from the ultra-high scan speed of up to 200Hz on the Orbitrap Astral mass spectrometer, a much narrower isolation window width of 2Th was applied in the DIA method, comparing to 10-20Th on the classic DIA method. As a result, ∼9000 proteins from HeLa digest and ∼800 proteins from undepleted plasma digest were identified within only a 11-minutes gradient, respectively. More than 80% of the plasma proteins were reproducibly identified and quantified from all the runs on each LC-MS/MS setup, indicating a great reproducibility from run-to-run longitudinally. Stable and robust peptide quantitation was observed by extracting peptides with high, medium, and low abundant across the runs. Importantly, QC showed no performance degradation throughout the entire study, indicating high robustness of the entire LC-MS/MS setup. Conclusions Orbitrap Astral mass platform can comprehensively analyze the proteome of >1000s of sample robustly and reproducibly in a high-throughput manner, addressing the needs in large-cohort studies.

Mass-Tagged Self-Assembled Nanoprobe Reveals the Transport of PD-L1 from Cancer Cells to Tumor-Educated Platelets

BackgroundThe expression level of immune checkpoint proteins detected by tissue biopsy is currently used as a predictive biomarker for immune checkpoint blockade (ICB) therapy. However, tissue biopsy is susceptible to invasive sample collection procedures, significant sampling heterogeneity, and the difficulty of repeated sampling. Therefore, liquid biopsy of blood samples is becoming an alternative choice for immune checkpoint protein detection. Among various vesicles in blood, platelets can obtain cancer information to form a specific group called tumor-educated platelets (TEPs). The platelet-derived proteins in TEPs may have a predictive potential in ICB therapy. ResultsIn this study, a photo-cleavable mass-tagged self-assembled (SAMT) nanoprobe with signal amplification was developed for the quantitative detection of PD-L1. The SAMT probe was assembled by photo-cleavable mass tags, PD-L1 aptamer, and amphiphilic polymer. After binding with PD-L1 on the platelet, the probe can release mass tags with UV light exposure. The amount of the mass tag, representing that of PD-L1, was subsequently determined by mass spectrometry. The assay sensitivity can be greatly improved by up to four orders of magnitude, achieving a detection limit of 10 fM. This assay was subsequently applied to cancer cells and platelet samples from non-small cell lung cancer (NSCLC) patients. The patients with higher tumor stages, higher degrees of lymph node invasion, and better ICB response had higher PD-L1 levels on platelets. Further investigation revealed that PD-L1 on the platelets was transported from cancer cells, providing evidence for the existence of TEPs. SignificanceThe SAMT probe can amplify the signal of the target molecule into that of multiple mass tags, achieving ultrasensitive ICB protein quantitative detection in platelets. Moreover, the employed SAMT assay not only revealed PD-L1 transport from cancer cells to platelets but also confirmed the presence of TEPs.

Trypsin Partially Cleaves Apolipoprotein A-I (ApoA-I) Precursor into Mature ApoA-I Hindering the Quantification of Naturally Occurring ApoA-I Proteoforms by Liquid Chromatography in Multiple Reaction Monitoring Mode Mass Spectrometry (LC-MRM-MS).

Apolipoprotein A-I (ApoA-I), one of the most abundant proteins in plasma and the major protein component of high-density lipoprotein (HDL), is naturally found in several proteoforms; two of them are ProApoA-I and mature ApoA-I. These two proteoforms of ApoA-I coexist in biological samples and differ only in their N-terminal end. Virtually, the only way to differentiate them is by detecting the proteoform-specific N-terminal proteolytic peptides (RHFWQQDEPPQSPWDR and DEPPQSPWDR, respectively) using liquid chromatography in multiple reaction monitoring mode mass spectrometry (LC-MRM-MS). We have developed a bottom-up LC-MRM-MS method to simultaneously detect proApoA-I and mature ApoA-I. To test the specificity of the method, we digested with trypsin purified mature ApoA-I and recombinant proApoA-I. As expected, only the N-term peptide corresponding to the mature ApoA-I proteoform (DEPPQSPWDR) was detected when digesting mature ApoA-I. However, the digestion of the proApoA-I produced not only the N-terminal peptide corresponding to proApoA-I (RHFWQQDEPPQSPWDR) but also the N-terminal tryptic peptide corresponding to mature ApoA-I (DEPPQSPWDR). This effect was produced by standard and high-specificity trypsin as well as by the Arg-C enzyme in a self-limited manner (approximately 10% of the total). The synthetic proApo-I peptide is not cleaved by trypsin, suggesting that the here reported effect is dependent on protein conformation. The effect is not negligible, as it can be detected by LC-MRM-MS, and correction calculations should be applied to accurately quantify proApoA-I and mature ApoA-I in biological samples where these two proteoforms may coexist.

In-depth characterization of a cysteine-linked ADC disitamab vedotin by multiple LC-MS analysis methods and cutting-edge imaged capillary isoelectric focusing coupled with native mass spectrometry

The characterization of cysteine-linked antibody‒drug conjugates (ADCs) can be more challenging than that of monoclonal antibodies (mAbs) and lysine-linked ADCs because the interchain disulfide bonds are reduced for payload conjugation, and the chains are noncovalently bonded to each other. Furthermore, payload conjugation and disulfide bond reduction/scrambling may introduce additional charge heterogeneity to biomolecules. This study illustrates an innovative workflow employing multiple separation techniques and tandem high-resolution mass spectrometry for comprehensive and in-depth characterization of disitamab vedotin, a recent-generation cysteine-linked ADC, including reversed-phase liquid chromatography (RPLC), ion exchange chromatography (IEX) and image capillary isoelectric focusing (icIEF). RPLC was employed for reduced chains analysis, subunit analysis and peptide mapping. IEX and icIEF were used for charge heterogeneity analysis. The innovation of the integrated methodology emphasizes the importance of cutting-edge icIEF-MS online coupling under near-native conditions to reveal the heterogeneity of disitamab vedotin.

Statistical studies of the characteristics and key influencing factors of sediment changes in the upper Yangtze River over the past 60 years

Sediments in the upper Yangtze River have significantly changed over the past 60 years. The characteristics and causes of these sediment changes must be determined in the upcoming phases of the comprehensive management of the Yangtze River Basin. Based on sediment observation data from 1960 to 2020, this study examined the trends and sudden changes in the sediments in the mainstream and its significant tributaries in the upper Yangtze River. The relative contributions of precipitation change and various human activities to sediment load changes are quantified. The relationships between sediment variations and the construction and large dam projects, soil and water conservation measures, and earthquake disasters are established. The results indicate that there was a significant decline in sediment load with main changes occurring around the 1985s and 2010s. Multiple double mass curves are used to quantify the relative contributions of precipitation change and human activities to sediment load changes. The relative contribution of dams to the decrease in sediment load ranges from 53 % to 74 %. Precipitation change serves a significant role in the observed changes, accounting for a range of 10 % to 27 %. Soil conservation measures take some time to show their impact on sediment reduction. These measures work by stabilizing the soil and improving hydrological conditions. On average, they contribute between 7 % and 20 % towards reducing sediment. In recent times, there has been a noticeable rise in sediment load in rivers like the Jialing and Min Rivers. This unexpected increase could potentially be linked to a combination of factors including earthquakes, heavy precipitation, and localized sediment scouring. The results of this study offer valuable insights into the variations in river sediment load, aiding in the improved management of water resources and sediment in large dams. These findings provide helpful insights for dam management.

Extraction and Quantification of Phenolic Compounds in Maize.

Plants accumulate hundreds of thousands of specialized metabolites that participate in their interactions with the environment. Among these compounds, phenolics represent a large class, and they play important physiological roles, such as providing a first barrier against pathogens, cues to pollinators, and radiation protection. Maize is one of the most important crops worldwide for food, animal feed, and biofuels, and it has the potential to accumulate different phenolics in vegetative tissues as well as in seeds. Recent studies have identified a large number of phenolic compounds-with a diversity of chemical decorations-in different maize tissues, but these likely represent just a fraction of the metabolic diversity of maize. In this protocol, we describe a specific method for the extraction and quantification of maize phenolic compounds by ultra-high-pressure liquid chromatography-tandem multiple reaction monitoring mass spectrometry (UHPLC-MRM-MS/MS) analysis. We provide detailed instructions for the extraction of phenolics using acidic methanol, and for the quantification of 33 different compounds in maize stems, including flavonoids, phenolic acids, and lignin precursors.

Cosmological dynamics of string theory axion strings

The quantum chromodynamics (QCD) axion may solve the strong CP problem and explain the dark matter (DM) abundance of our Universe. The axion was originally proposed to arise as the pseudo-Nambu-Goldstone boson of global U(1)PQ Peccei-Quinn (PQ) symmetry breaking, but axions also arise generically in string theory as zero modes of higher-dimensional gauge fields. In this work we show that string theory axions behave fundamentally differently from field theory axions in the early Universe. Field theory axions may form axion strings if the PQ phase transition takes place after inflation. In contrast, we show that string theory axions do not generically form axion strings. In special inflationary paradigms, such as D-brane inflation, string theory axion strings may form; however, their tension is parametrically larger than that of field theory axion strings. We then show that such QCD axion strings overproduce the DM abundance for all allowed QCD axion masses and are thus ruled out, except in scenarios with large warping. A loop-hole to this conclusion arises in the axiverse, where an axion string could be composed of multiple different axion mass eigenstates; a heavier eigenstate could collapse the network earlier, allowing for the QCD axion to produce the correct DM abundance and also generating observable gravitational wave signals. Published by the American Physical Society 2024

Sequencing Sialic Acid Positioning in Gangliosides by High-Resolution Cyclic Ion Mobility Separations Coupled with Multiple Collision-Induced Dissociation-Based Tandem Mass Spectrometry Strategies.

Gangliosides, a diverse class of glycosphingolipids, are highly abundant in neural tissue and have been implicated in numerous aging-related diseases. Their characterization with methods such as liquid chromatography-tandem mass spectrometry is often precluded by their structural complexity, isomeric heterogeneity, and lack of commercially available authentic standards. In this work, we coupled high-resolution cyclic ion mobility spectrometry with multiple collision-induced dissociation-based tandem mass spectrometry strategies to sequence the sialic acid positions in various ganglioside isomers. Initially, as a proof-of-concept demonstration, we were able to characterize the sialic acid positions in several GD1 and GT1 species. From there, we extended our approach to identify the location of N-glycolylneuraminic acid (NeuGc) residues in previously uncharacterized GD1 and GQ1 isomers. Our results highlight the potential of this presented methodology for the de novo characterization of gangliosides within complex biological matrices without the need for authentic standards.

Predicting the entire pyrolysis process of representative charring material infiltrated with kerosene using an improved artificial neural network

It is crucial to predict the entire pyrolysis process of charring materials infiltrated with flammable liquids to provide guidance for reducing the fire hazards and implementing numerical simulations of fire accidents caused by the leakage of flammable liquids. In the present study, pyrolysis data obtained from the thermogravimetric experiments were preprocessed using linear interpolation and data normalization methods. The processed data set was then used to train the artificial neural network (ANN) framework to predict the pyrolysis behaviors of typical charring material (Mongolian Scots pine) infiltrated with typical flammable liquid (kerosene) under three different conditions: (1) pyrolysis at a constant mass fraction of kerosene with multiple heating rates; (2) pyrolysis at multiple mass fractions of kerosene with a constant heating rate; and (3) pyrolysis at multiple mass fractions of kerosene and multiple heating rates. The ANN, with the double hidden layer structure (6−3), was capable to well predict the entire pyrolysis behaviors of Mongolian Scots pine under all the three scenarios. Besides, five data transformation function (multiplication, exponential function with base e, logarithmic function with base e, square root, and exponentiation function) were applied to the present three input variables (temperature, mass fraction of kerosene, and heating rate) to generate new input variables in order to extract more characteristics among the pyrolysis data. Therein, the ANN utilizing the data transformation functions of multiplication and exponential function with base e exhibited the best predictive ability. Among the three input variables in the ANN (temperature, mass fraction of kerosene, and heating rate), temperature was identified as the most sensitive one to the prediction performance, followed by mass fraction of kerosene, with heating rate being the least sensitive.

CompNET: Boosting image recognition and writer identification via complementary neural network post-processing

In current classification tasks, an important method to improve accuracy is to pre-train the model using a large-scale domain-specific dataset. However, many tasks such as writer identification (writerID) lack suitable large-scale datasets in practical scenarios. To address this issue, this paper proposes a method that can improve prediction accuracy without relying on significant pre-training but leveraging the diversity of probability distributions predicted by multiple networks, and enhancing the top-1 accuracy through complementary post-processing. Specifically, top-k distributions are sampled from the multiple probability mass functions separately. When the distribution differences of top-k are maximized, the intersection other than the correct category can be narrowed down. Finally, the correct target with suboptimal probability can be rectified by the only intersection. Furthermore, our method has exhibited an intriguing trait during experimentation. Its prediction accuracy enhances concurrently with the incorporation of novel SOTA methods, ultimately surpassing the performance of these new methods.

A Comparison of Statistical Validity of In-Situ Hydraulic Conductivity Prediction Models of Rock Mass Inferred from Borehole Logs and Lugeon Test Data

In-situ hydraulic conductivity is a vital property in rock engineering for jointed rock mass. Understanding its correlation with rock mass parameters is crucial for water circulation. Therefore, a study was carried out to develop statistically significant empirical relationships between hydraulic conductivity and various rock mass parameters to estimate in-situ hydraulic conductivity from Lugeon test and various rock mass parameters obtained from borehole logs.The study initially aimed to establish a correlation between hydraulic conductivity and Rock Quality Designation (RQD). However, the outcomes were unsatisfactory, prompting further research. Later, two more robust models were developed, namely the HC-model and modified HC-model. The HC-model incorporated four rock mass parameters, including Rock Quality Designation Index, Depth Index, Gouge Content Designation Index, and Lithology Permeability Index, achieving a maximum coefficient of determination (R2) of 0.46. The modified HC-model included six parameters, encompassing fracture frequency and theoretical aperture, resulting in an improved R2 of 0.69. Both models significantly outperformed RQD-alone predictions (R2 < 0.10), highlighting the need for incorporating multiple rock mass parameters in predicting hydraulic conductivity due to a complex interplay of various factors. However, the effects of joint persistence and roughness are limiting in the present analysis.

An Efficient Integrated Strategy for Comprehensive Metabolite Profiling of Sakurasosaponin from Aegiceras corniculatum in Rats.

Sakurasosaponin, a primary bioactive saponin from Aegiceras corniculatum, shows potential as an anti-cancer agent. However, there is a lack of information on its in vivo metabolism. This study aims to profile the in vivo metabolites of sakurasosaponin in rat feces, urine, and plasma after oral administration. An efficient strategy using ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry was developed, which combined metabolic prediction, multiple mass defects filtering, and highresolution extracted ion chromatograms for rapid and systematic analysis. Firstly, a theoretical list of metabolites for sakurasosaponin was developed. This was done by considering the metabolic pathways of saponins. Next, the multiple mass defects filtering method was employed to identify potential metabolites in feces and urine, using the unique metabolites of sakurasosaponin as multiple mass defects filtering templates. Subsequently, a high-resolution extracted ion chromatogram was used to quickly determine the metabolites in rat plasma post-identification in feces and urine. Lastly, the analysis of accurate mass, typical neutral loss, and diagnostic ion of the candidate metabolites was carried out to confirm their structural elucidation, and metabolic pathways of sakurasosaponin in vivo were also proposed. In total, 30 metabolites were provisionally identified in feces, urine, and plasma. Analysis of metabolic pathways revealed isomerization, deglycosylation, oxidation, hydroxylation, sulfate conjugation, glucuronide conjugation, and other related reactions as the primary biotransformation reactions of sakurasosaponin in vivo. The findings demonstrate that the designed research strategy effectively minimizes matrix interference, prevents the omission of low-concentration metabolites, and serves as a foundation for the discovery of active metabolites of sakurasosaponin.

Mass media competition and alternative ordering in social dynamics.

We investigate the collective behavior of a system of social agents subject to the competition between two mass media influences considered as external fields. We study under what conditions either of two mass media with different intensities can impose its message to the majority. In addition to a collective state dominated by the stronger mass media and a disordered phase, we characterize two nontrivial effects as the parameters of the system are varied: (i) the appearance of a majority sharing the state of the weaker mass media, and (ii) the emergence of an alternative ordering in a state different from those of either media. We explore the dependence of both phenomena on the topology of the network of interactions. We show that the presence of long-range interactions rather than random connections is essential for the occurrence of both effects. The model can be extended to include multiple mass media and we illustrate it by considering three mass media fields acting on the system. Nontrivial collective behaviors persist for some ranges of parameters: the weakest mass media can convince the majority, and the system can spontaneously order against all applied fields.

Bioactivation of cinnamic alcohol in a reconstructed human epidermis model and evaluation of sensitizing potency of the identified metabolites.

Cinnamic alcohol is a natural compound, widely used in fragrances, which can cause allergic contact dermatitis. Cinnamic alcohol lacks intrinsic reactivity and autoxidation or metabolic activation is necessary for it to act as a sensitizer. Bioactivation of cinnamic alcohol was explored using human liver microsomes, human liver S9 and SkinEthic™ Reconstructed Human Epidermis. A targeted multiple reaction monitoring mass spectrometry method was employed to study and quantify cinnamic alcohol along with eight potential phase I or phase II metabolites. The reconstructed human epidermis model, treated with cinnamic alcohol, was also analyzed with a non-targeted high-resolution mass spectrometry method to identify metabolites not included in the targeted method. Two metabolites identified with the targeted method, namely, pOH-cinnamic alcohol and pOH-cinnamic aldehyde, have not previously been identified in a metabolic in vitro system. Their reactivity toward biologically relevant nucleophiles was investigated and compared to their sensitizing potency in vivo in the murine local lymph node assay (LLNA). According to the LLNA, the pOH-cinnamic alcohol is non-sensitizing and pOH-cinnamic aldehyde is a moderate sensitizer. This makes pOH-cinnamic aldehyde less sensitizing than cinnamic aldehyde, which has been found to be a strong sensitizer in the LLNA. This difference in sensitizing potency was supported by the reactivity experiments. Cinnamic sulfate, previously proposed as a potential reactive metabolite of cinnamic alcohol, was not detected in any of the incubations. In addition, experiments examining the reactivity of cinnamic sulfate toward a model peptide revealed no evidence of adduct formation. The only additional metabolite that could be identified with the non-targeted method was a dioxolan derivative. Whether or not this metabolite, or one of its precursors, could contribute to the sensitizing potency of cinnamic alcohol would need further investigation. Cinnamic alcohol is one of the most common fragrance allergens and as it is more effective to patch test with the actual sensitizer than with the prohapten itself, it is important to identify metabolites with sensitizing potency. Further, improved knowledge of metabolic transformations occurring in the skin can improve prediction models for safety assessment of skin products.

Development of a Two-Dimensional Supercritical Fluid Chromatography System in Multiple Heart-Cutting Modes.

In this study, we present the development of a loop-based two-dimensional supercritical fluid system in multiple heart-cutting modes (mSFC-SFC), with diode-array and mass spectrometric detection. The instrument design was developed to be as simple as possible, based on a single SFC instrument, with the sole addition of three external 2-port 6-position valves. The objective was to achieve the most complete transfer of a peak from the first to the second dimension, whatever the composition of the mobile phase, i.e., whatever the proportion of carbon dioxide and methanol cosolvent along a wide gradient elution. Thanks to fine adjustment of the valve switching times, the first-dimension peaks were parked in 50 μL or 100 μL loops and later discharged to the second dimension. The interest of this instrument was then demonstrated with a sample application on a natural product: an extract of Citrus aurantium L. bark was analyzed, with a particular focus on chiral flavonoids, neohesperidin, and naringin. In this system, the first dimension was an achiral separation of the flavonoids, based on a polar diethylamine-bonded silica stationary phase (ACQUITY Torus DEA), while the second dimension used a stereoselective polysaccharide stationary phase (CHIRALPAK IB-3) to resolve flavonoid diastereomers. Excellent repeatability was demonstrated, with relative standard deviation values on retention times and peak areas all below 2%, together with excellent peak capacity and peak shapes (no distortion observed), making it possible to quantify diastereomers in the second-dimension separation. This good repeatability was also shown for the transfer rate between the two dimensions, which reached a value of 83%. Finally, transferring a compressible sample from the first to the second dimension is demonstrated to yield excellent performance, despite the large loop volume.

Systemic Metastase in Late Management of Group D Retinoblastoma: A Case Report

Background: Retinoblastoma (RB) is a common malignancy that affects children and is fatal if left untreated. This case report aims to raise awareness the importance of starting therapy immediately in RB patients. Case presentation: A girl aged 1 year 9 months, came with complaints that her left eye (LE) appeared white for 2 weeks. Anterior segment examination was normal. On funduscopic examination, optic nerve was difficult to evaluate, covered by a mass, multiple mass scars on the retina, a size of > 6 mm at the posterior pole, and vitreous seeding. Ultrasound examination and CT scan showed an intraocular mass with calcification. The patient was diagnosed with group D intraocular LE RB and was planned for enucleation but was postponed due to cost constraints. The patient came back after 1 year and was diagnosed with extraocular LE RB stage IVB. Conclusion: Early diagnosis without adequate therapy leads to tumor spread and reduces patient survival.

Numerical simulation of continuous microwave drying of rice grains

AbstractTo comprehensively understand temperature and moisture changes in a continuous microwave rice grain drying system, this study proposes a simulation strategy that facilitates the continuous movement of rice grains. The study establishes a three‐dimensional model concerning multiple physical fields, including electromagnetism, heat, and mass transfer. It examines the effects of rice grain layer thickness and microwave intensity on the moisture and temperature of rice grains. The results indicate that the drying rate is negatively correlated with material thickness but positively correlated with temperature. The optimal thickness for the rice grain layer is 8 mm. Furthermore, both the microwave drying rate and temperature increase with microwave intensity. These findings contribute to a deeper understanding of the hydrothermal change mechanisms in rice grains during microwave drying.Practical applicationsMicrowave drying, as an emergent drying technology, has garnered widespread attention for its selective heating, efficient drying, energy savings, and environmental protection. Nevertheless, enhancing uniformity during the microwave heating process constitutes an important research topic in scientific research and technological applications. Numerical simulation methods can visually analyze electric field distribution, thereby optimizing microwave heating uniformity and improving drying effects. This article aims to accurately predict the continuous microwave drying time of paddy and maximize energy usage by optimizing drying thickness and microwave power parameters establishing a mathematical model for the process. The study not only provides a solid theoretical basis for microwave dryer design but also scientifically guides the continuous microwave drying of rice and other food crops.