Sample Processing Research Articles

Gut-brain axis mediated by intestinal content microbiota was associated with Zhishi Daozhi decoction on constipation

BackgroundConstipation is a common digestive system disorder, which is closely related to the intestinal flora. Zhishi Daozhi decoction (ZDD) is a traditional Chinese medicine prescription used to treat constipation caused by indigestion. This study is to evaluate the efficacy of ZDD in treating constipation and to elucidate the underlying mechanism.MethodsIn this study, Kunming mice were administered a high-protein diet (HFHPD) and loperamide hydrochloride injections to induce constipation. The mice then received varying doses (2.4, 4.7, and 9.4 mg/kg) of ZDD for seven days. Following the sampling process, we measured fecal microbial activity. The levels of 5-hydroxytryptamine (5-HT), vasoactive intestinal peptide (VIP), and aquaporin-3 (AQP3) were quantified using enzyme-linked immunosorbent assay. Changes in the gut microbiota were evaluated through 16S rRNA gene sequencing. Additionally, we investigated the correlation between specific microbiota features and the levels of 5-HT, VIP, and AQP3.ResultsThe fecal surface of the mice in the model group (CMM) was rough and dry. The stool of mice in the low-dose ZDD group (CLD), medium-dose ZDD group (CMD), and high-dose ZDD group (CHD) exhibited a smoother texture, closely resembling that of the normal group (CNM). 5-HT levels in the CMM group were significantly lower than in the CNM, CLD, and CHD. VIP levels in the CMD were lower than in the other four groups, and AQP3 levels in CMM showed a decreasing trend. The fecal microbial activity of the CMM group was significantly higher than that of the other groups. Diversity analysis indicated that CMD and CHD treatments were more effective in restoring the intestinal microbiota structure. Potential pathogenic bacteria, including Clostridium, Aerococcus, Jeotgalicoccus, and Staphylococcus were enriched in CMM. In contrast, beneficial bacteria such as Faecalibacterium, Bacillaceae, and Bacillus were more prevalent in the CLD, CMD, and CHD. Correlation analysis revealed that Streptococcus and Enterococcus were positively correlated with VIP, while Succinivibrio showed a negative correlation with 5-HT.ConclusionsConstipation induced by HFHPD and loperamide hydrochloride disrupts the structure of the intestinal microbiota. ZDD appears to alleviate constipation, potentially through mechanisms linked to the brain-gut axis and its interaction with the intestinal microbiota. Among the treatment groups, the medium dose of ZDD demonstrated the most effective results.

Interacting urns on directed networks with node-dependent sampling and reinforcement

Abstract We consider interacting urns on a finite directed network, where both sampling and reinforcement processes depend on the nodes of the network. This extends previous research by incorporating node-dependent sampling and reinforcement. We classify the sampling and reinforcement schemes, as well as the networks on which the proportion of balls of either colour in each urn converges almost surely to a deterministic limit. We also investigate conditions for achieving synchronisation of the colour proportions across the urns and analyse fluctuations under specific conditions on the reinforcement scheme and network structure.

Time‐Multiplexed Reservoir Computing with Quantum‐Dot Lasers: Impact of Charge‐Carrier Scattering Timescale

Reservoir computing with optical devices offers an energy‐efficient approach for time‐series forecasting. Quantum dot lasers with feedback are modeled in this article to explore the extent to which increased complexity in the charge‐carrier dynamics within the nanostructured semiconductor can enhance the prediction performance. By tuning the scattering interactions, the laser's dynamics and response time can be finely adjusted, allowing for a systematic investigation. It is found that both system response time and task requirements need to be considered to find optimal operation conditions. Further, lasers with pronounced relaxation oscillations outperform those with strongly damped dynamics, even if the underlying charge‐carrier dynamics is more complex. This demonstrates that optimal reservoir computing performance relies not only on a high internal phase space dimension but also on the effective utilization of these dynamics through the output sampling process, quantum dot laser, reservoir computing, feedback delay, effective scattering rate, relaxation oscillation.

Formaldehyde Fixation Helps Preserve the Proteome State during Single-Cell Proteomics Sample Processing and Analysis.

Mass spectrometry-based single-cell proteomics (SCP) is gaining momentum but remains limited to a few laboratories due to the high costs and specialized expertise required. The ability to send samples to specialized core facilities would benefit nonspecialist laboratories and popularize SCP for biological applications. However, no methods have been tested in SCP to "freeze" the proteome state while maintaining cell integrity for transfer between laboratories or prolonged sorting using fluorescence-activated cell sorting (FACS). This study evaluates whether short-term formaldehyde (FA) fixation can maintain the cell states. We demonstrate that short-term FA fixation does not substantially affect protein recovery, even without heating and strong detergents, and maintains analytical depth compared with classical workflows. Fixation also preserves drug-induced specific perturbations of the protein abundance during cell sorting and sample preparation for SCP analysis. Our findings suggest that FA fixation can facilitate SCP by enabling sample shipping and prolonged sorting, potentially democratizing access to SCP technology and expanding its application in biological research, thereby accelerating discoveries in cell biology and personalized medicine.

Designing efficient Bayesian sampling plans for two-component exponential distributions model

This article studies a method about how to design efficient Bayesian sampling plans based on samples collected from two-component exponential distributions. First, based on a complete sampling, for a general loss function, a Bayes decision function δ A is derived, and then a Bayesian sampling plan (BSP) is constructed. The monotonicity of δ A is studied. By applying this monotonicity, a curtailment procedure to the preceding Bayes decision function is constructed. By applying this curtailment procedure, an on-line new Bayes decision function δ C , and then an efficient Bayesian sampling plan (EBSP) are constructed. It is shown that for each fixed sample size n, δ C and δ A are equivalent in the sense that for every sampling process, the decisions made by δ C and δ A are the same. It is also proved that the Bayes risk of EBSP is less than or equal to that of BSP. This indicates that EBSP is more efficient than the BSP. Comparisons among some BSPs and the proposed EBSP are given. The numerical results indicate that, in terms of Bayes risks, the EBSP significantly outperforms the BSP.

IMPACT OF ACADEMIC STRESS AND RESILIENCE ON LIFE SATISFACTION AMONG UNDERGRADUATES OF NASARAWA STATE UNIVERSITY, KEFFI

This study examined “Impact of Academic Stress and Resilience on Life Satisfaction among undergraduates of Nasarawa State University, Keffi.” The researcher employed a survey descriptive research design. A total of One hundred and one (101) respondents were randomly selected across 4 levels in Psychology department. Participants were selected through a simple random sampling process. Undergraduate stress questionnaire (USQ), Connor-Davidson Resilience Scale (CD-RISC), and Satisfaction with Life Scale (SWLS) were used to collect data. The responses of the respondents were analyzed using the statistical package for social sciences (SPSS). The main hypotheses of this research were tested at 0.05 level of significance. Hypothesis one indicates a negative correlation between Academic Stress and Satisfaction With life: r (99) = -.768, p >.05. Hypothesis two indicates a significant positive correlation between resilience and Life Satisfaction: r (99) = .534, p < .05.Finally, there is a significant gender difference in Life Satisfaction among Students of Nasarawa State University Keffi. The study concludes that Academic stress does not affect student’s satisfaction with life but resilience does. It was recommended that school authority should Conduct and Implement interventions aimed at reducing academic stress and fostering resilience among students. Evaluate the effectiveness of these interventions in promoting life satisfaction.

IMPACT OF ACADEMIC STRESS AND RESILIENCE ON LIFE SATISFACTION AMONG UNDERGRADUATES OF NASARAWA STATE UNIVERSITY, KEFFI

This study examined “Impact of Academic Stress and Resilience on Life Satisfaction among undergraduates of Nasarawa State University, Keffi.” The researcher employed a survey descriptive research design. A total of One hundred and one (101) respondents were randomly selected across 4 levels in Psychology department. Participants were selected through a simple random sampling process. Undergraduate stress questionnaire (USQ), Connor-Davidson Resilience Scale (CD-RISC), and Satisfaction with Life Scale (SWLS) were used to collect data. The responses of the respondents were analyzed using the statistical package for social sciences (SPSS). The main hypotheses of this research were tested at 0.05 level of significance. Hypothesis one indicates a negative correlation between Academic Stress and Satisfaction With life: r (99) = -.768, p >.05. Hypothesis two indicates a significant positive correlation between resilience and Life Satisfaction: r (99) = .534, p < .05.Finally, there is a significant gender difference in Life Satisfaction among Students of Nasarawa State University Keffi. The study concludes that Academic stress does not affect student’s satisfaction with life but resilience does. It was recommended that school authority should Conduct and Implement interventions aimed at reducing academic stress and fostering resilience among students. Evaluate the effectiveness of these interventions in promoting life satisfaction.

A High-Throughput Integrated Nontargeted Metabolomics and Lipidomics Workflow Using Microelution Enhanced Matrix Removal-Lipid for Comparative Analysis of Human Maternal and Umbilical Cord Blood Metabolomes.

Sample pretreatment for mass spectrometry (MS)-based metabolomics and lipidomics is normally conducted independently with two sample aliquots and separate matrix cleanup procedures, making the two-step process sample-intensive and time-consuming. Herein, we introduce a high-throughput pretreatment workflow for integrated nontargeted metabolomics and lipidomics leveraging the enhanced matrix removal (EMR)-lipid microelution 96-well plates. The EMR-lipid technique was innovatively employed to effectively separate and isolate non-lipid small metabolites and lipids in sequence using significantly reduced sample amounts and organic solvents. Our proposed methodology enables parallel profiling of metabolome and lipidome within a single sample aliquot using ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Following method development and optimization with representative metabolites at levels comparable to those detected in human blood, the optimized workflow was applied to prepare metabolome-lipidome from maternal and umbilical cord-blood sera prior to comprehensive profiling using three different UHPLC columns. Results indicate that, compared with conventional two-step metabolomics-lipidomics sample pretreatment workflow, this new approach substantially reduces sample amount and processing time, while still preserving metabolite profiles and revealing additional MS features. Over 2500 metabolites were annotated in human sera with >1000 shared across maternal and cord blood. The shared metabolites are closely linked to various physiological functions, including nutrient transfer, hormonal regulation, waste product clearance, and metabolic programming, underscoring the significant impact of maternal metabolic activities on neonatal metabolic health. In summary, the proposed workflow enables efficient sample pretreatment for nontargeted metabolomics-lipidomics using one single sample while achieving broad metabolite coverage, highlighting its remarkable applicability in clinical and preclinical research.

Fully Automated Extraction of High-Quality total Nucleic Acids from FFPE specimens for Comprehensive Genomic Profiling of solid Tumors.

Comprehensive Genomic Profiling (CGP) has emerged as a progressive standard of care for the understanding clinical oncology and treatment of solid tumors (Conroy, Pabla et al. 2021). By identifying actionable mutations through next-generation sequencing of solid tumors CGP enables targeted therapy decisions. Formalin-fixed paraffin-embedded tissues are notoriously difficult samples in respect to reliably extracting high-quality nucleic acids and sufficient genetic material to meet sequencing input requirements. In this work we present an automated solution for upstream sample processing of solid tumors to enable high throughput and scalable CGP workflows by eliminating bottlenecks and enhancing results. The Sonication STAR automated DNA and RNA methods from FFPE Tissues was created as a collaboration between Hamilton Company, Covaris, and Labcorp and it offers the potential reduction in quantity not sufficient (QNS) samples and sequencing performance improvements resulting in a 16% increase in fully reported tumor profiles for patients. This automated approach offers potential saving in workflow costs, improved efficiency, and a reduction in re-extraction and re-sequencing of tumors.

Prediction of slab surface longitudinal crack based on resampling and the Bayesian optimisation of LightGBM

Longitudinal crack is a typical surface defect for slab of steel. Accurate prediction of longitudinal crack is of great significance to improve slab quality. However, in actual production, the quantity distribution of normal and longitudinally cracked slabs is extremely unbalanced, which brings great challenges to the subsequent modeling and prediction. To solve the above problems, this paper proposes a prediction method for the longitudinal crack under the condition of data imbalance. Firstly, multiple sampling methods (SMOTE, BorderlineSMOTE, SMOTE-ENN and SMOTE-Tomk) were used to construct feature data sets respectively to alleviate the problem of data imbalance. Then, based on the data sets after sampling processing, the prediction models of the longitudinal crack were constructed by using Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), XGBoost and LightGBM as classification algorithms. The models’ hyperparameters were determined by Bayesian optimisation and the optimal classification algorithm was selected according to the evaluation metrics. Meantime, SHapley Additive exPlanations (SHAP) was used to analyse the model and verify the influence of input parameters on the model output. The results show that, compared with other models, the combined model of SMOTE sampling and LightGBM classification algorithm can better deal with the problem of imbalanced data for prediction of the longitudinal crack. The Recall of normal and longitudinally cracked slabs are 90.57% and 84.62%, respectively, false alarm rate is 9.44% and AUC is 0.93. At the same time, the training time of this model is about 0.15 s, and prediction time is less than 0.01 s. The time consumed in each stage is significantly shorter than other models. It shows obvious advantages and provides a reliable method for predicting the longitudinal crack.

P-2120. Clinical significance of 16S rRNA sequencing identification of Legionella species

Abstract Background Incorporation of 16S rRNA sequencing into clinical diagnostics has improved the ability of clinicians to diagnose fastidious bacteria and facilitates the identification of causative organisms in culture-negative infections. However, its clinical utility is unclear, with estimates of antimicrobial management changes from 16S identification ranging from only 4-15%. Legionella species are fastidious bacteria that can be difficult to identify without prior clinical suspicion, and thus can cause culture-negative infections that lead to 16S sequencing. However, Legionella are found ubiquitously in aquatic environments and its identification on 16S could represent a clinically significant infection, a nonpathogenic sample isolate, or a contaminant from sample processing or analysis. In this study, we reviewed 16S Legionella species results from our institution and determined whether they represented a clinical infection. Methods 16S results from our institution were queried for Legionella species and a retrospective analysis of the resulting 10 cases was conducted. Multiple factors from the cases were assessed including demographics, comorbidities, type of 16S specimen, and antibiotic regimen change in response to 16S results. Additionally, we identified whether the 16S results represented clinically significant infections or contaminants. Results 70% of the Legionella identifications were indicative of a clinically relevant infection. Specimens from a pulmonary source were much more likely to represent a true infection, while identifications from extrapulmonary sources were more likely to be a contaminant. The species of Legionella identified on 16S did not impact the likelihood of a true causative agent. The 16S results affected antimicrobial regiments in 60% of the cases and were often the only diagnostic test to point towards Legionella as a causative agent. Conclusion Legionella species identification on 16S can be an important diagnostic clue to the etiology of a patient's infection, but various clinical factors should be taken into account when assessing whether the result represents a true infection or contaminant. Disclosures All Authors: No reported disclosures

P-115. Lessons from Establishing a Vaccine Trial Clinic: Insights from the University of Louisville's Center of Excellence for Research in Infectious Diseases

Abstract Background The COVID-19 pandemic spurred an urgent need for swift vaccine development to combat the disease. This study focuses on outlining the implementation approach for the Phase 3 clinical trial of the Ad26.COV2.S vaccine. The University of Louisville's Division of Infectious Diseases, known as the Center of Excellence for Research in Infectious Diseases (CERID), was contacted by Janssen representatives in July 2020 to conduct the trial.Figure 1.The structure of the Center of Excellence for Research in Infectious Diseases (CERID). Methods The CERID site was fully activated in November 2020, and the enrollment period spanned 16 working days, from November 21 to December 11, 2020. The study employed a randomized, double-blind, placebo-controlled design. Various organizational units within CERID, including community outreach, implementation, quality assurance, and laboratory, collaborated to develop standard operating protocols for communication and execution. These steps included community outreach, trainings, and the development of case report forms.Figure 2.Data collected at Screening and Day 1 participant visits. Results During the enrollment period, 64 participants were seen, with 62 enrolled in the trial. The self-sufficient organizational infrastructure of CERID was pivotal in facilitating the successful implementation of the Phase 3 clinical trial. Quality metrics were developed to minimize systematic errors and ensure accurate reporting of results. The Division of Infectious Diseases Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory provided essential support for COVID-19 diagnosis, sample processing, and shipping.Figure 3.Workflow in laboratory. Gold top humoral blood collection tube, PAXgene RNA blood sequencing tube, NP specimen tube, and saliva samples were delivered to the laboratory. Specimens processed per laboratory manual and stored in the -80°C freezer until shipping to the central laboratory. Conclusion The seamless execution of the Phase 3 clinical trial at CERID highlights the effectiveness of a multidisciplinary research coordinating center. The collaborative efforts of various units within CERID, along with proactive measures such as pre-labeling specimen tubes and addressing participant concerns directly, contributed to the trial's success. The described methods and approach can be adapted for use in diverse clinical and laboratory research settings, showcasing resilience and adaptability in the face of pandemic challenges Disclosures All Authors: No reported disclosures

295. Methods for Cost-efficient Real-time Whole Genome Sequencing Surveillance for Enhanced Detection of Outbreaks in a Hospital Setting

Abstract Background Healthcare associated infections (HAI) are common hospital complications associated with increased length of stay, economic burden, morbidity, and mortality. Traditionally, HAI outbreaks were detected using reactive whole genome sequencing (WGS); however, with costs decreasing over time, WGS has become a practical tool for the real time detection of nosocomial outbreaks. This study describes such methods, provides a cost analysis, and reviews notable outbreaks observed while performing real time WGS surveillance of HAIs. EDS-HAT real-time genomic surveillance methodsFigure 1:EDS-HAT real-time genomic surveillance methods A) collect list generation, B) sample collection C) sample processing, D) DNA extraction, E) Library preparation, F) WGS, and G-I) Data analysis, including determining SNPs between samples and infection clusters Methods The Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT) was devised to identify potential transmitted HAIs in real time among patients admitted to the hospital for ≥ 3 days or with a previous exposure in the prior 30-days (Fig 1). We performed a cost analysis for real time genomic HAI surveillance, based on an average cutoff of 35× coverage per genome, considering personnel, reagents, supplies, and WGS platform. We also considered maximum sample counts that could be sequenced on two platforms (MiSeq or NextSeq), based on genome size (Fig 2). Bioinformatic analyses were completed following WGS, and epidemiological links were investigated for isolates that clustered with ≤ 15 pair-wise SNP differences (C. diff ≤ 2 SNPs). Maximum Sample CountsFigure 2:Maximum number of genomes that can be run on a MiSeq v3 600 cycle flow cell and NextSeq500 v2.5 300 cycle flow cell based on size (Mb). Sample counts were calculated using Illumina coverage calculator based on 80× coverage criteria. Genome size of an average run by the MiGEL lab is shown in comparison Results From November 1, 2021 to October 31, 2023, we sequenced 4,723 isolates (weekly mean N=49). The per sample cost depended on platform used and sample count, totaling $49 or $19 for MiSeq (N=32) and NextSeq (N=96), respectively (Table 1). With the inclusion of personnel costs for 1 lab technician and 1 biostatistician (salary only, based on percent effort) the average weekly cost to run EDS-HAT was $4,293 (range $3,626-$4,758). We highlight multiple outbreaks involving a common hospital unit, equipment, or location (Table 2). Following Infection Prevention (IP) intervention, no additional cases were detected for these clusters on the associated routes. Cost per sample BreakdownTable 1.Cost per sample across MiSeq, NextSeq, and commercial WGS Conclusion We describe time- and cost-efficient methods for real time outbreak surveillance and detection using WGS. These genomic methods, as described in EDS-HAT, can be utilized with traditional epidemiological methods to guide hospital IP teams to mitigate and stop the spread of deadly transmitted HAIs. Notable OutbreaksTable 2.Description of notable outbreaks detected by real-time EDS-HAT HAI surveillance Disclosures Alexander Sundermann, DrPH, CIC, FAPIC, OpGen: Honoraria Lee Harrison, MD, GSK: Advisor/Consultant|Merck: Advisor/Consultant|Pfizer: Advisor/Consultant|Sanofi: Advisor/Consultant

P-2219. Demonstrating a Novel Immune Cell Isolation Strategy for Scalable Single-Cell RNA Sequencing Studies in Patients with Sepsis

Abstract Background Though immune dysregulation often plays a key role in disease, characterizing circulating immune cells in critical illnesses is challenging. Studies using single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) reveals the type and function of patients' immune cells (cell substates) that could advance diagnostics and therapeutics, particularly in diseases defined by immune response heterogeneity such as sepsis. However, PBMC isolation from blood is required for scRNA-seq, and the gold-standard method (density gradient separation, or ‘Ficoll’) requires two hours of onsite processing, precluding large-scale sample collection at most clinical sites. Simplifying sample collection could enable participation of more health care centers, as well as the over-enrollment of patients for later retrospective adjudication, better reflecting the true patient heterogeneity in diseases.Figure 1.Workflow depicting the process from patient presentation in a health care center to sequencing results. The WB cryo method expedites sample collection in clinical settings by eliminating the need for Ficoll PBMC separation, a time-intensive process requiring laboratory equipment and trained operators. Differences in methods are highlighted in yellow. Methods We developed an alternative PBMC isolation method from cryopreserved whole blood (WB-cryo) using magnetic- and fluorescence- activated cell sorting (Fig. 1). We isolated PBMCs using the WB-cryo and Ficoll methods from patients with sepsis (n = 5) who sought evaluation at an Emergency Department and one healthy control. We performed scRNA-seq to identify and compare cell substate proportions and marker genes for key substates.Figure 2.Results of scRNA-seq on PBMCs isolated using Ficoll and WB cryo methods (n = 5 patients with sepsis, 1 healthy control). a) Uniform Manifold Approximation and Projection (UMAP) of separately clustered and annotated scRNA-seq data from each method; Bm denotes memory B cells, Bn: naive B cells, NK: natural killer cells, Mono: monocytes, MS1: monocyte substate 1, DC: dendritic cells, Tn: naive T cells, Tm: memory T cells, gdT: gamma delta T cells, Treg: regulatory T cells. b) correlation plot of resulting cell substate proportions (R = 0.87, p < 0.0001). Results Analysis included 9,996 cells isolated by Ficoll and 15,482 cells from WB-cryo. Sequencing quality was comparable between methods, as were cell substate fractions (Pearson correlation 0.87, p < 0.0001) (Fig. 2), and marker genes for a key monocyte substate enriched in patients with sepsis (19 of top 20 marker genes shared). WB-cryo reduced onsite sample processing time from 2 hours to < 10 minutes. Conclusion PBMCs isolated by WB-cryo retained similar transcriptional states when compared to PBMCs isolated using Ficoll, with > 10-fold less onsite hands-on time. With further validation, WB-cryo may expand scRNA-seq study enrollment in sepsis and other diseases. Ongoing work in a larger cohort (n = 23 patients with sepsis) processed across two clinical sites is underway to validate our isolation method as a way to extend the utility of scRNA-seq in multisite studies of complex and heterogeneous conditions like sepsis. Disclosures Michael R. Filbin, MD, Day Zero Diagnostics: Grant/Research Support|Quidel: Grant/Research Support

Optimal processing of tongue swab samples for Mycobacterium tuberculosis detection by the Xpert MTB/RIF Ultra assay.

Tongue swabs represent a potential alternative to sputum as a sample type for detecting pulmonary tuberculosis (TB) with molecular diagnostic tests. The methods used to process tongue swabs for testing in the World Health Organization-recommended Xpert MTB/RIF Ultra (Xpert Ultra) assay vary greatly. Here, we aimed to identify the optimal tongue swab processing for Xpert Ultra testing. We compared four methods for treating dry tongue swabs with the Xpert Sample Reagent (SR) mixed with various concentrations of Tris-EDTA-Tween to treatment with SR alone or to a commonly used heat inactivation protocol. In each condition, swabs obtained from volunteers without TB were placed into test buffer spiked with known amounts of Mycobacterium tuberculosis (Mtb) H37Rv-mc26230. Swabs processed with 1:1 diluted SR buffer had the lowest Mtb limit of detection (LOD) at 22.7 CFU/700 µL (95% confidence interval (CI) 14.2-31.2), followed by 2:1 diluted SR buffer at 30.3 CFU/700 µL (95% CI 19.9-40.7), neat SR at 30.9 CFU/700 µL (95% CI 21.5-40.3), and SR prefilled in the Xpert Ultra at 57.1 CFU/700 µL (95% CI 42.4-71.7). Swabs processed using the heat-based protocol had the highest LOD (77.6 CFU/700 µL; 95% CI 51.2-104.0). Similar findings were observed for the LOD of RIF susceptibility. The 2:1 diluted SR buffer condition produced similar LODs when swabs were tested in the presence of sputum matrix or phosphate buffer saline. Further studies are needed to assess the performance of this processing protocol in a clinical setting.IMPORTANCEXpert MTB/RIF Ultra (Xpert Ultra) is approved by the World Health Organization for the diagnosis of tuberculosis (TB). This test is typically performed using sputum specimens obtained from people with presumptive TB. In order to inactivate Mycobacterium tuberculosis (Mtb) and aid liquefaction, sputum must be mixed with Xpert SR prior to transfer into the Xpert Ultra. However, some people under evaluation for TB are unable to produce sputum. Alternative sample types for TB diagnosis would, therefore, be of value. Oral swabs, including tongue swabs, have shown promise, but there are technical challenges associated with sample processing. In this study, several new tongue swab processing conditions were evaluated by utilizing SR, either neat or diluted in buffer. The ability of Xpert Ultra to detect TB was improved under these conditions compared with the previously published heat-processing method; processing steps were simplified; and technical challenges were overcome.

Design and Validation of an Open-Close Device for Integrated Environmental DNA Sampling Detects A Depth Gradient in Indian Ocean Deep-Sea Fish Assemblages.

Advances in methods for collecting environmental DNA (eDNA) are revolutionizing biomonitoring capabilities. The goal of this study was to leverage existing survey technology to design and test an eDNA sampler that captures an integrated eDNA sample over the length of a deep-water transect. We manufactured a 300 × 100 × 100 mm mountable, open-ended box made of high-density polyethylene that could be attached to the frame of a preexisting deep tow camera system. The box (OCD; open-close device) was equipped with an actuator that attached to hinged doors at both ends, enabling it to be opened and closed remotely at depths up to 6000 m through preexisting communications, thereby exposing the internal chamber to the surrounding water upon activation. A sterile active carbon sponge was inserted into the internal chamber for eDNA capture during each deployment. The OCD sampler was field tested during a voyage to the Gascoyne Marine Park region off northwest Australia. We compared three different methods for processing the captured eDNA from the sampler: filtering OCD water, extracting eDNA from sponge pieces, and filtering sponge rinse water. Using fish as our example organism, we also compared the identities of fishes from eDNA detections with bottom trawl survey data collected during the same survey, and the known regional species pool, to confirm the eDNA identifications were plausible. A large number of fishes (193 taxa, from 87 families) were detected, and the majority were found within their expected depth ranges (> 75%), and in the trawl catches (60%). We discuss design and manufacturing lessons, ideas for increased eDNA capture efficiency for improved methodologies in sample processing, and how to establish appropriate field controls. We also discuss how this technology could advance our scientific understanding in ocean studies in terms of ecological metrics provided and the trade-offs compared to other sampling tools.

A Semi-Automated Machine-Learning Tool for Assessing Building Phases: Discriminant Analysis of Mortars from the 2022 Excavation at the Sarno Bath Complex in Pompeii

This study presents the results of the analyses of 15 structural mortars from the building at civ. 21, level +0 of the Sarno Bath complex in Pompeii. These samples were collected during recent stratigraphic excavations (year 2022) for detailed in-laboratory compositional characterization, aiming to trace the construction phases of the originating walls. The 2022 samples were firstly analyzed via quantitative phase analysis–X-ray powder diffraction. The resulting quantitative mineralogical profiles were then processed alongside those analyzed in previous studies from level +0 structures of the Sarno Baths using multivariate statistical methods, including principal component analysis (PCA) and discriminant analysis, applied to quantitative phase analysis (QPA)–X-ray powder diffraction data (XRPD), to identify and map the construction phases. This approach enabled the correlation of the 2022 samples with previously established construction phases. Polarized-light optical microscopy and scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS) were then primarily used for validation purposes. These methods highlighted the compositional differences between samples and revealed significant features related to the use of specific raw materials. These results confirm the reliability of the semi-automated sample processing proposed in this research, adopting discriminant analysis as a machine-learning-based tool for defining construction phases in Pompeian contexts.

In-situ profiling of glycosylation on single cells with surface plasmon resonance imaging

Cellular glycosylation is crucial for cell recognition, signal transduction, and the development of various diseases, especially in tumor initiation, progression, and metastasis. Current glycosylation profiling methods normally involve laborious sample processing and labeling and lack in-situ quantitative analysis. Here, we present a direct optical method to investigate and quantify the glycan expression on single cells based on lectin-glycan kinetic quantification with plasmonic imaging. Three unlabeled lectins (WGA, SBA, ConA) are employed as probes to bind with specific glycans, and binding kinetics are assessed to determine glycosylation profiles. The result reveals cell-to-cell heterogeneity in glycosylation patterns. To demonstrate the capability of our method, the glycosylation profiling of four distinct cell lines is explored, showing obvious alterations in glycan expression related to tumor initiation, progression, and metastasis. This approach enables direct quantification of glycosylation and binding kinetics, providing insights into tumor cell glycosylation mechanisms and potential applications in disease diagnosis and treatment.

Characterizing the heterogeneous contamination of commercial paper and board food packaging at different scales

Assessing the contamination of paper and board (P&B) food packaging materials poses significant challenges due to the sensitivity limits of analytical methods and the low precision of sampling processes. This study aims to enhance the understanding of P&B food packaging contamination by investigating the distribution of contaminants at different scales using a combination of chromatographic and spectroscopic techniques. A total of 36 substances were targeted, including phthalates, photoinitiators, and bisphenol A. Key findings reveal that intra-packaging variability can lead to concentration variations by a factor of 2–7. Recycled materials generally exhibit higher contamination levels, with concentrations of certain contaminants reaching up to 700 mg/kg. Microscopy, including confocal laser scanning microscopy (CLSM) and Raman micro-spectroscopy, enabled the identification and differentiation of contaminants, highlighting specific marker molecules and characteristic Raman bands. The study underscores the necessity of comprehensive sampling strategies, advocating for the grinding of entire packaging to obtain representative samples. The introduction of contamination "fingerprints," based on occurrences and correlations between concentrations, offers a promising approach for hazard identification and risk assessment. Overall, the findings contribute to the development of safer and more sustainable food packaging solutions, emphasizing the need for improved analytical techniques and standardized sampling methods in the context of increasing use of recycled materials.

Technical note: A fast and reproducible autosampler for direct vapor equilibration isotope measurements

Abstract. To investigate water movement in environmental systems, stable isotope (2H and 18O) ratios of water are commonly used tracers. Analyzing the isotopic ratios of water in or adsorbed to substances like soil or plant tissue necessitates the extraction or equilibration of water prior to analysis. One such method, direct vapor equilibration, is popular due to its cost-effectiveness and straightforward sample processing. However, sample analysis requires significant manual labor, thereby limiting the number of samples that can be analyzed. This limitation is compounded by the fact that stored samples undergo evaporative isotopic changes over time. Moreover, manual measurements require many laborious procedural steps that can easily compromise reproducibility. The operator has to subjectively decide if the measurements are stable and then record the analyzer readings. To address these challenges, we have developed a system that automates the analysis process. Our autosampler for vapor samples, named VapAuSa, features a modular design that allows for up to 350 ports for direct vapor equilibration samples. These ports sequentially connect the prepared samples to a laser isotope analyzer, enabling continuous automated measurements. Within the accompanying software, measurement criteria can be specified, facilitating reproducible analysis. The developed system was tested by co-measuring 90 soil samples and 21 liquid water samples with known δ values. VapAuSa measurements have a negligible measurement bias (<1×10-13 ‰ for both δ2H and δ18O) and similar measurement repeatability compared to manual analysis of identical samples (δ2H=±4.5 ‰ and δ18O=±0.58 ‰ for VapAuSa measurements vs. δ2H=±5.7 ‰ and δ18O=±0.37 ‰ for manual analysis). However, the increased sample throughput minimizes storage-induced isotopic changes. Moreover, VapAuSa triples sample throughput per week while also reducing the direct labor time to just 10 % of that required for manual processing.