Rapid Characterization Research Articles

A Cell-Based Screening Assay for rRNA-Targeted Drug Discovery.

Worldwide, bacterial antibiotic resistance continues to outpace the level of drug development. One way to counteract this threat to society is to identify novel ways to rapidly screen and identify drug candidates in living cells. Developing fluorescent antibiotics that can enter microorganisms and be displaced by potential antimicrobial compounds is an important but challenging endeavor due to the difficulty in entering bacterial cells. We developed a cell-based assay using a fluorescent aminoglycoside molecule that allows for the rapid and direct characterization of aminoglycoside binding in a population of bacterial cells. The assay involves the accumulation and competitive displacement of a fluorescent aminoglycoside binding probe in Escherichia coli as a Gram-negative bacterial model. The assay was optimized for high signal-to-background ratios, ease of performance for reliable outcomes, and amenability to high-throughput screening. We demonstrate that the fluorescent binding probe shows a decrease in fluorescence with cellular uptake, consistent with RNA binding, and also shows a subsequent increase upon the addition of the positive control neomycin. Fluorescence intensity increase with aminoglycosides was indicative of their relative binding affinities for A-site rRNA, with neomycin having the highest affinity, followed by paromomycin, tobramycin, sisomicin, and netilmicin. Intermediate fluorescence was found with plazomicin, neamine, apramycin, ribostamicin, gentamicin, and amikacin. Weak fluorescence was observed with kanamycin, hygromycin, streptomycin, and spectinomycin. A high degree of sensitivity was observed with aminoglycosides known to be strong binders for the 16S rRNA A-site compared with antibiotics that target other biosynthetic pathways. The quality of the optimized assay was excellent for planktonic cells, with an average Z' factor value of 0.80. In contrast to planktonic cells, established biofilms yielded an average Z' factor of 0.61. The high sensitivity of this cell-based assay in a physiological context demonstrates significant potential for identifying potent new ribosomal binding antibiotics.

Rapid Characterization and Identification of the Chemical Constituents in San-Huang-Xie-Xin-Tang, a Traditional Chinese Medicine Formula, by High Performance Liquid Chromatography Coupled to Electrospray Ionization and Quadrupole Time-of-Flight Mass Spectrometry.

San-Huang-Xie-Xin-Tang (SHXXT), a traditional Chinese medicine formula composed of Coptidis rhizome (CR), Scutellariae radix (SR) and Rhei rhizome (RR), is widely used to treat hypertension, gastritis and peptic ulcer clinically. However, the chemical constituent of SHXXT is still unclear due to its complexity, which hindered the discovery of effective compounds and quality control. Thus, an in-depth understanding of its chemical constituents is very essential. To address this problem, comprehensive analysis of chemical constituents of SHXXT was performed by high performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry (HPLC-ESI-QTOF-MS/MS). As a result, 45 compounds were identified, including 8 phenolic acids, 15 flavonoids, 13 alkaloids, 8 anthraquinones and 1 lignan. Among them, 17 compounds were from CR, 17 compounds were from SR and 11 compounds were from RR. This established method can systematically and rapidly analyze the chemical constituents in SHXXT, which provides chemical foundation for further research on effective substances and action mechanism of SHXXT.

Rapid Characterization of the Constituents in Classic Chinese Medicine Formula Guyinjian Using Ultra-High-Performance Liquid Chromatography With Quadrupole Time-of-Flight Mass Spectrometry.

Guyinjian (GYJ) is a classic traditional Chinese medicine formula for the treatment of polycystic ovary syndrome, ovulation disorders, immuno-sterility, oligomenorrhea with kidney deficiency, and so forth. Due to the unclear chemical components of GYJ, the elucidation of the pharmacological mechanism, and the comprehensive development and utilization of GYJ in clinical is being restricted. In this study, ultra-high-performance liquid chromatography with quadrupole time-of-flight-tandem mass spectrometry combined with the Progenesis QI platform and using reference standards, online and self-built databases matching, fragmentation rules analysis of mass spectrometry peaks, a total of 235 compounds were preliminarily characterized, including 69 flavonoids, 65 terpenoids, 34 phenylpropanoids, 22 saccharides, sugar esters, and glycosides, 15 organic acids, and 30 others. These compounds may reflect the chemical properties of GYJ. The method established in this study can systematically, rapidly, and accurately resolve the chemical components in GYJ, which lays the foundation for further establishment of the pharmacodynamic substance basis and quality control.

Online LC-Orbitrap MS method for the rapid molecular characterization of dissolved organic matter.

High-resolution mass spectrometry (HRMS) combined with electrospray ionization (ESI) has been the most useful technique for molecular characterization of dissolved organic matter (DOM) derived from diverse sources. However, the comprehensive detection of DOM composition was hindered by ionization suppression observed in ESI sources. HRMS coupled with liquid chromatography (LC) is a potential tool for comprehensive molecular characterization of DOM. The Suwannee River fulvic acids (SRFAs) and two DOM samples from seawater and refinery wastewater extracted by solid phase extraction (SPE) were analyzed by LC-Orbitrap MS coupled with ESI. The mobile phases, solvent composition, and gradient in the LC-Orbitrap MS analysis were optimized. The number of detected molecular formulae of SRFAs by online LC-Orbitrap MS was significantly increased by approximately 40% compared to direct injection. These additional detected compounds are mainly protein and lignin-like compounds, with a low O/C ratio and high H/C ratio. For the SRFAs, the relative standard deviations (%) of reproducibility are 5.51, 2.33, 7.97, and 1.80 for average O/C, H/C, double bond equivalent, and modified aromaticity index, respectively. This study proposed a simple and rapid method based on LC-Orbitrap MS for an in-depth analysis of the molecular composition of DOM, achieving a remarkable analysis time of only 5 min per sample. The rapid method provides a dependable and efficient approach for the molecular characterization of DOM, thereby advancing our comprehension and investigation of DOM across diverse ecosystems.

Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications

The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.

Morphology Determination of Luminescent Carbon Nanotubes by Analytical Super-Resolution Microscopy Approaches.

The ability to determine the precise structure of nano-objects is essential for a multitude of applications. This is particularly true of single-walled carbon nanotubes (SWCNTs), which are produced as heterogeneous samples. Current techniques used for their characterization require sophisticated instrumentation, such as atomic force microscopy (AFM), or compromise on accuracy. In this paper, we propose to use super-resolution microscopy (SRM) to accurately determine the morphology (orientation, length, and shape) of individual luminescent SWCNTs. We generate super-resolved images using three recently published SRM analytical software packages (DPR, eSRRF, and MSSR) and metrologically compare their performances to determine the morphological properties of SWCNTs. For this, ground-truth information on nanotube morphologies was obtained using polarization measurements and AFM to directly correlate the results from SRM at the single particle level. We show a more than 4-fold improvement in resolution over standard photoluminescence imaging, revealing hidden morphologies as efficiently as AFM. We finally demonstrate that DPR, and eventually eSRRF, can effectively assess SWCNT length distribution in a much faster and more accessible way than AFM. We believe that this approach can be generalized to other types of luminescent nanostructures and thus become a standard for rapid and accurate characterization of samples.

Advancing the Understanding of Microplastic Weathering: Insights from a Novel Polarized Light Scattering Approach.

Weathering is a significant process that alters the properties of microplastics (MPs) and consequently affects their environmental behaviors. In this study, we introduced a novel approach based on polarized light scattering technique, which offers advantages in terms of rapid, high-throughput, and submicron-sized detection. This technique was successfully applied to characterize the weathered MPs after a 180-day laboratory simulation of coastal environments. By employing polarization measurements, we obtained a 46-dimensional matrix data set for the weathered MP fragments and subsequently processed them using a backpropagation neural network. The successful extraction of effective polarization pulses confirmed the presence of MP fragments within the size range of 0.2-60 μm, yielding total accuracies for size classification ranging from 78.9 to 86.9%. Furthermore, this technique achieved an overall accuracy of 93.8% in classifying MPs with different weathering degrees and polymer types, revealing polarization parameters associated with size and morphological changes play a dominant role in characterizing the weathering process of MPs. Compared with conventional approaches, the novel polarized light scattering approach holds great promise for rapid, high-throughput, and accurate characterization of MPs with small sizes. The findings of this study provided new insights into how MPs change after long-term weathering in aquatic environments.

Annotation-free prediction of microbial dioxygen utilization.

Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes-aerobes, anaerobes, and facultative organisms alike-express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content-e.g., triplets of amino acids-perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or "sense," pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology-an organism's capacity to engage metabolically with its environment-may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.

Chromatography and Spectroscopic Technique-Based Rapid Characterization of Nano-Carrier Pharmaceuticals.

A nanocarrier is a novel colloidal system whose particle size ranges between 1-100 nm. It is extensively utilized in drug delivery and various other sectors, such as the pharmaceutical, food, and dairy industries. The nanocarrier systems, including solid lipid nanoparticles, micelles, liposomes, and other encapsulated compounds, have improved stability, solubility, bioavailability, and quality. Nanocarriers offer therapeutic effectiveness with low toxicity because of their biocompatibility and ability to cross body barriers. Various analytical techniques, such as chromatography and spectroscopy, are crucial in qualitative and quantitative analysis of nanocarrier-based formulations. Molecular identification and drug content determination require chromatographic techniques, particularly HPLC. Spectroscopic techniques such as LC-MS, NMR, GC-MS, CE-MS, Raman, and IR are used to analyze the interaction and molecular structure of the sample. Nanocarriers have several benefits but face various challenges like stability, drug loading, regulatory standards, and biocompatibility. Future surface engineering and nanocarrier design advancements could improve targeted drug delivery and sustained diagnostic applications, significantly impacting healthcare.

Ultrasonic fatigue of superelastic Nitinol and in situ synchrotron observation of strain and damage

Superelastic Nitinol was tested at ultrasonic frequency in the high and very high cycle fatigue regime. Thin sheet specimens were initially preloaded to mimic crimping and deployment of Nitinol implants, which lead to a sample in a multi-phase state with martensitic phase in the middle and adjacent zones with austenitic phase. In situ synchrotron X-ray diffraction (XRD) was used to monitor cyclic strains over an entire ultrasonic cycle, and to compare the results with low frequency loading. Both austenitic and martensitic regimes showed similar sinusoidal elastic deformation at cycling frequencies 0.1 Hz and 18.3 kHz, and strains were comparable over the entire gauge section of the specimen. XRD data showed progressive growth of austenitic bands in formerly martensitic areas with increasing numbers of ultrasonic cycles. This increased specimen stiffness and cyclic stresses promoting crack initiation, which nearly exclusively occurred at cracked surface inclusions. The strain versus fatigue lifetime diagram shows a pronounced change in slope below 106 cycles. The overlapping properties measured at low and ultrasonic frequency demonstrate that ultrasonic fatigue testing is in principle appropriate for rapid characterization of the cyclic properties of Nitinol.

A rapid method for measuring the rock brittleness index: Rapid characterization of rock brittleness based on LIBS technology

The brittle index is a crucial indicator in the assessment of rockbursts. The mineral brittle index (MBI) is widely utilized due to its simplicity and accessibility. However, the lengthy and inefficient mineral composition testing cycle presents a significant challenge. A novel approach using laser-induced breakdown spectroscopy (LIBS) to rapidly convert spectral elements into minerals and measure the rock brittleness index was introduced in this paper. The laser spectra of metamorphic sandstone and granite were measured by LIBS, and some rock elements were tested by X-ray fluorescence (XRF) to construct a spectral-elemental model. Furthermore, the mineral composition of the rocks was determined by X-ray diffraction (XRD). Eight major elements, Si, Al, K, Ca, Na, Fe, Mg, and Ti, were selected as independent variables. Element-mineral correlation analysis was performed using centered log-ratio transformation (CLR) processing. A random forest regression (RF-R) element-mineral transformation model was established for rapid conversion of spectral-element-mineral brittle index. Finally, mechanical testing of rock embrittlement in the DJ Tunnel was conducted to verify the efficacy of MBI in characterizing rock embrittlement in the DJ Tunnel. The results demonstrate that predicted values of mineral compositions are in good agreement with experimental values and that predicted values of brittleness indices are also in good agreement with experimental values. The rapid and effective application of LIBS in determining rock mineral composition and rock brittleness index has been realised, which is of great significance for further realising the rapid assessment of rock brittleness and rockburst prediction at engineering sites.

High incidence of multidrug-resistant tuberculosis in Bhutan: A cohort study based on national TB surveillance data

ObjectivesThe emergence of multidrug-resistant tuberculosis (MDR-TB) has made the elimination of TB difficult. Currently, there are limited data on MDR-TB and other drug-resistant TB in Bhutan. We aimed to estimate the incidence and explore the potential risk factors associated with MDR/pre-extensively drug-resistant (pre-XDR)-TB using comprehensive national TB data. MethodsWe used the data from the Tuberculosis Information Surveillance System of the National Tuberculosis Reference Laboratory to analyze the resistance pattern and epidemiologic data for all TB cases tested for resistance for the year 2018-2021. Multiple logistic regression was performed to identify risk factors associated with MDR/pre-XDR-TB. ResultsOf the 2,290 samples tested for drug resistance, 10.6% (n = 243) was MDR-TB, 3.5% (n = 81) was isoniazid-resistant TB, and 0.61% (n = 14) was pre-XDR-TB. A high incidence of MDR/RR-TB/pre-XDR-TB was documented among patients in Thimphu, Samtse, and Sarpang districts. MDR/pre-XDR-TB was more likely documented among patients aged 18-39 years (adjusted odds ratio [aOR] 2.79; 95% confidence interval [CI] 1.46-6.07), female sex (aOR 1.37; 95% CI 1.01-1.86), and patients previously treated for TB (aOR 2.98; 95% CI 1.99-4.42). ConclusionsGiven the high burden of MDR-TB in some districts, decentralization of diagnostic facilities for more rapid characterization could improve early recognition of drug-resistant cases and assist in management. Comprehensive follow-up and monitoring of high-risk groups should be performed.

AutoGater: a weakly supervised neural network model to gate cells in flow cytometric analyses

Flow cytometry is a useful and efficient method for the rapid characterization of a cell population based on the optical and fluorescence properties of individual cells. Ideally, the cell population would consist of only healthy viable cells as dead cells can confound the analysis. Thus, separating out healthy cells from dying and dead cells, and any potential debris, is an important first step in analysis of flow cytometry data. While gating of debris can be conducted using measured optical properties, identifying dead and dying cells often requires utilizing fluorescent stains (e.g. Sytox, a nucleic acid stain that stains cells with compromised cell membranes) to identify cells that should be excluded from downstream analyses. These stains prolong the experimental preparation process and use a flow cytometer’s fluorescence channels that could otherwise be used to measure additional fluorescent markers within the cells (e.g. reporter proteins). Here we outline a stain-free method for identifying viable cells for downstream processing by gating cells that are dying or dead. AutoGater is a weakly supervised deep learning model that can separate healthy populations from unhealthy and dead populations using only light-scatter channels. In addition, AutoGater harmonizes different measurements of dead cells such as Sytox and CFUs.

Morphological and Autofluorescence Dataset for ‘Touch’ Epidermal Cell Populations Collected with Imaging Flow Cytometry

Background New methods for processing ‘touch’ or trace biological samples is an ongoing priority for forensic caseworking laboratories. These samples often contain materials from multiple individuals in varying quantities and/or degrees of degradation. Rapid characterization of cellular material before DNA profiling can allow laboratories to screen samples for the presence of multiple contributors or the amount of biological material present. Methods This dataset contains autofluorescence and morphological profiles of epidermal cell populations analyzed using Imaging Flow Cytometry. The epidermal samples were aged for varying amounts of time prior to analysis. Multiple samples from the same individual were also collected to assess profile variations within and across the contributors. Conclusions This data set may be used to investigate variability in epidermal cell populations from different individuals and potential forensic signatures contained within the non-genetic components that comprise touch biological evidence.

Using the Herschel-Bulkley Consistency Index to Characterise Complex Biopolymer Systems-The Effect of Screening.

The use of the consistency index, as determined from fitting rheological data to the Herschel-Bulkley model, is described such that it may yield systematic trends that allow a very convenient description of the dissipative flow properties of linear and branched (bio)polymers in general, both in molecular and weakly associated supramolecular solutions. The effects of charge-mediated interactions by the systematic variation of the ionic strength and hydrogen bonding by a systematic variation in pH, using levels that are frequently encountered in systems used in practice, is investigated. These effects are then captured using the associated changes in the intrinsic viscosity to highlight the above-mentioned trends, while it also acts as an internal standard to describe the data in a concise form. The trends are successfully captured up to 100 times the polymer coil overlap and 100,000 times the solvent viscosity (or consistency index). These results therefore enable the rapid characterization of biopolymer systems of which the morphology remains unknown and may continue to remain unknown due to the wide-ranging monomer diversity and a lack of regularity in the structure, while the macromolecular coil size may be determined readily.

Rapid aerodynamic characterization of surface heat exchangers for turbofan aeroengines through optical techniques and additive manufacturing

Surface heat exchangers that use the bypass flow as heat sink are becoming a widely used solution to alleviate the high thermal load of modern aeroengines. Experimental characterization of such heat exchangers in full-scale engine tests is extremely expensive and time-consuming, so carrying out experiments in scaled wind tunnels that can replicate their very challenging flow conditions is highly desirable. However, intrusive instrumentation can affect the actual aerodynamics of the component due to the reduced size of the section and the typical high air velocities of turbofan engines. For this reason, a methodology to characterize a surface heat exchanger designed to work in the turbofan bypass using optical techniques is presented in this work. Additionally, the possibility of replicating the experimental conditions using additively manufactured models of exchangers would allow rapid preliminary characterization of these components. In this investigation, different non-intrusive techniques such as PIV, LDA, Schlieren, or LDV have been applied to determine the heat exchanger aerodynamic performance and vibration response, and a detailed characterization of the flow field has been carried out. Data have been cross-validated using different measurement techniques. A 3D-printed model has also been built to compare with the aluminum heat exchanger, showing almost an identical behavior in terms of velocity distribution downstream of the heat exchanger and pressure drop induced by its fins, as well as corrected frequencies, confirming thus the suitability of additive manufacturing for the aerodynamic characterization of these devices in preliminary stages.

Evaluating the detection of barbiturates in dried blood spots: A comparative analysis using gas chromatography-mass spectrometry, gas chromatography-tandem mass spectrometry, and liquid chromatography-tandem mass spectrometry with different extraction methods

Rapid and accurate characterization and quantitation of blood barbiturates and their combination drugs are very important for the clinical treatment of acute barbiturate poisoning. A comparison of dried blood spot (DBS) and traditional liquid-liquid extraction (LLE) in the pre-treatment stage, as well as a comparison of gas chromatography-mass spectrometry (GC–MS), gas chromatography-tandem mass spectrometry (GC–MS/MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS) as instrumental analysis methods, revealed differences in the analysis results of barbiturates and their combination drugs under different conditions. Based on these findings, we introduce a DBS-GC–MS/MS method. The developed and validated method showed good selectivity, sensitivity (LOD: 0.1 μg mL−1, LOQ: 0.2 μg mL−1), linearity (R2>0.9992), trueness (<15 %, except for carbamazepine, at 29.4 %), and precision (<15 %). Recovery was also good for most target compounds, but significant matrix effects were evident. Compared with the LLE method, the DBS method has the benefits of easy sample collection, storage, and transport, as well as simple pre-treatment and reduced reagent and energy consumption. Compared to LC-MS/MS, GC–MS/MS requires no switching between positive and negative ion modes and uses the MRM detection mode, meaning that more information about the sample compounds can be obtained in less analysis time. Using actual sample analysis, we have demonstrated the advantages of the DBS-GC–MS/MS method for the qualitative and quantitative analysis of barbiturates and poisoning events due to combinations of these drugs. Comparison of the three instruments and the two treatment methods revealed their analysis characteristics. From the perspective of practical application, the broad practical value and advantages of DBS should be embraced in more applications, and future analytical laboratory development should continue to recognize GC–MS/MS as a useful supplement to LC-MS/MS.

Recombinant Influenza A Viruses Expressing Reporter Genes from the Viral NS Segment.

Studying influenza A viruses (IAVs) requires secondary experimental procedures to detect the presence of the virus in infected cells or animals. The ability to generate recombinant (r)IAV using reverse genetics techniques has allowed investigators to generate viruses expressing foreign genes, including fluorescent and luciferase proteins. These rIAVs expressing reporter genes have allowed for easily tracking viral infections in cultured cells and animal models of infection without the need for secondary approaches, representing an excellent option to study different aspects in the biology of IAV where expression of reporter genes can be used as a readout of viral replication and spread. Likewise, these reporter-expressing rIAVs provide an excellent opportunity for the rapid identification and characterization of prophylactic and/or therapeutic approaches. To date, rIAV expressing reporter genes from different viral segments have been described in the literature. Among those, rIAV expressing reporter genes from the viral NS segment have been shown to represent an excellent option to track IAV infection in vitro and in vivo, eliminating the need for secondary approaches to identify the presence of the virus. Here, we summarize the status on rIAV expressing traceable reporter genes from the viral NS segment and their applications for in vitro and in vivo influenza research.

Rapid Characterization of the Potential Active of Sinomenine in Rats by Ultra-High-Performance Liquid Chromatography-Quadrupole-Exactive Orbitrap Mass Spectrometry and Molecular Docking.

Sinomenium acutum (Thunb.) Rehd. et Wils is widely used in the treatment of rheumatoid arthritis, with its alkaloid compound sinomenine (SIN) being renowned for its significant anti-inflammatory properties. However, despite its widespread application, the in vivo anti-inflammatory mechanisms and metabolic pathways of SIN remain incompletely understood. This study established a rapid and reliable method based on an ultra-high-performance liquid chromatography method coupled with Quadrupole-Exactive Orbitrap mass spectrometry and molecular docking to identify and characterize SIN and 69 metabolites in rat plasma, urine, and feces, revealing primary metabolic pathways of hydroxylation, demethylation, sulfation, and glucuronidation. Molecular docking results revealed that phase I reactions, including dedimethylation, demethylation, dehydrogenation, and dihydroxylation, along with their composite reactions, were pivotal in influencing SIN's in vivo anti-inflammatory activity. M28, M36, and M59 are potentially the most anti-inflammatory active metabolites of SIN in vivo. This comprehensive analysis unveils SIN's metabolic pathways, offering insights into its biological processes and suggesting a novel approach for exploring active drug constituents. These findings pave the way for further understanding SIN's anti-inflammatory mechanisms, contributing significantly to the development of new therapeutic strategies.

Molecular characterization of Streptococcus suis isolates recovered from diseased pigs in Europe

Streptococcus suis is a major swine pathogen and zoonotic agent, causing important economic losses to the porcine industry. Here, we used genomics approaches to characterize 251 S. suis isolates recovered from diseased pigs across Belgium, France, Germany, Hungary, the Netherlands, Spain, and the United Kingdom. We identified 13 serotypes, being serotypes 9 and 2 the most prevalent, and 34 sequence types (STs), including 16 novel STs, although ST16 and ST1 dominated the strain population. Phylogenetic analysis revealed complex genetic relationships, notable geographic clustering, and potential differential capacity for capsular switching among serotype 9 isolates. We found antimicrobial resistance (AMR) genes in 85.3% of the isolates, with high frequencies of genes conferring resistance to tetracyclines and macrolides. Specifically, 49.4% of the isolates harbored the tetO gene, and 64.9% possessed the ermB gene. Additionally, we observed a diverse array of virulence-associated genes (VAGs), including the classical VAGs mrp, epf, and sly, with variable presence across different genotypes. The high genetic diversity among European S. suis isolates highlights the importance of targeted antimicrobial use and flexible vaccine strategies. Rapid strain characterization is crucial for optimizing swine health management, enabling tailored interventions like the development of autovaccines to mitigate S. suis infections.