Liquid Chromatography Research Articles

An isotope dilution-liquid chromatography-tandem mass spectrometry-based candidate reference measurement procedure for the quantification of cortisol in human serum and plasma.

Accurate measurement of serum cortisol is crucial for the diagnosis and management of adrenal disorders. Thus, we have developed a novel isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC MS/MS)-based candidate reference measurement procedure (RMP) to quantify cortisol in human serum/plasma, offering higher sensitivity and reliability compared to existing RMPs. Quantitative Nuclear Magnetic Resonance spectroscopic (qNMR) methodology has been utilized to assign the absolute content (g/g) and SI-traceability to the reference materials. A novel two-dimensional heart-cut liquid chromatography (LC) approach was implemented for the LC-MS/MS, combined with a supported liquid extraction (SLE) sample preparation protocol. A multi-day validation experiment assessed precision and accuracy. Reproducibility was assessed by comparing procedure results between two independent laboratories, and measurement uncertainty (MU) was evaluated in compliance with current guidelines. The established RMP exhibited high sensitivity, with a quantification range of 0.800-600 ng/mL (2.21-1,655 nmol/L), exceeding the ranges of existing JCTLM-listed RMPs. Intermediate precision was≤2.6 %, and repeatability ranged from 0.9 to 1.9 % across all concentration levels. The relative mean bias ranged from-1.3 to 1.4 % for all matrices and concentration levels. Measurement uncertainties (MU) for cortisol in single measurements were≤2.8 % regardless of the concentration level and sample type. Using the certified International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) reference panel, the equivalence between the candidate RMP and the Joint Committee on Traceability in Laboratory Medicine (JCTLM) listed RMPs (NRMeth 57 and NRMeth 8) was assessed, revealing excellent agreement. This RMP allows for highly sensitive and reproducible determination of cortisol. The performance of the RMP facilitates the standardization of routine assays and ensures traceability in the measurement of individual patient samples.

Pollution characteristics, source analysis, and health risk assessment of polycyclic aromatic hydrocarbons in atmospheric PM2.5: a case study in Xi’an, China

ABSTRACT Air samples were collected at the Lianhu (urban) and Yanta (semi-urban) regions between January 2020 and December 2023 to determine the concentrations of polycyclic aromatic hydrocarbons (PAHs) in Xi’an, which is an important tourist city in China. The concentration of PAHs was ascertained using liquid chromatography. The concentration of Σ16PAHs in Xi’an was 0.13–105.02 ng/m3, while the concentration of Σ16PAHs for the sampling regions at Lianhu and Yanta were 0.13–105.02 ng/m3 and 0.34–82.64 ng/m3, respectively. PAHs with 4–5 rings were the predominant PAHs pollutants in Xi’an, mainly from coal combustion and automobile exhaust. Risks through inhalation to three groups, adult males, adult females, and children, were estimated. The incremental lifetime cancer risk (ILCR) value for local adults and children were less than 10−6, considered to be at a safe level. However, the ILCR is relatively close to the minimum risk threshold (10−6), and it still needs to be highly valued.

Improvement and Application HPLC-UV Method for detecting of N-drugs in Pharmaceutical Formulations

The ultraviolet-visible high-performance liquid chromatography (HPLC–UV) coupled method was developed to detect five pharmaceutical compounds: indapamide (INDP), clomipramine (CMI), promethazine HCl (PMH), lisinopril (LSP) and trifluoperazine HCl (TFPH). The mobile phase consisted of 70% acetonitrile and 30% water, ensuring specific retention times (tR) for each compound. Analytical validation parameters were calculated from a calibration curve, including sensitivity, limit of detection (LOD) and linearity of the method. The LOD values of N-drugs were calculated as 6.24 μM for INDP, 2.19 for CMI, 10.57 for PMH, 6.68 for LSP and 1.25 for TFPH. Peak deconvolution or spectral deconvolution of standard solutions of drug mixtures was used to separate overlapping peaks in a dataset and extract information about individuals. Chromatographic separation of the standard mixture of pure compounds achieved a good resolution (R_s), ensuring the effective separation of the mixture components. However, other mixtures did not achieve satisfactory resolution due to retention time interference. Overall, the HPLC–UV method demonstrated good sensitivity and selectivity for the detection of the chosen pharmaceutical compounds. KEYWORDS Chromatogram, deconvolution, limit of detection, pharmaceutical analysis, retention time, sensitivity

Large-scale prospective serum metabolomic profiling reveals candidate predictive biomarkers for suspected preeclampsia patients

Preeclampsia (PE) is a serious pregnancy complication that contributes to maternal and perinatal morbidity and mortality. Understanding its pathogenesis and revealing predictive biomarkers are essential for guiding treatment decisions. In order to explore the global changes of serum metabolites in PE patients and identify potential predictive biomarkers for suspected PE patients (pregnant women who had already shown PE-related symptoms in the middle to late stages of pregnancy, but were not yet confirmatively diagnosed as PE.), a large-scale serum metabolomic analysis was conducted in this study with a prospective cohort of 328 suspected PE patients in the middle or late pregnancy stages, as well as a retrospective cohort of 30 healthy pregnant women and 30 PE patients. Using liquid chromatography mass spectrometry (LC − MS), serum metabolomic profiling revealed that the development of PE was closely associated with disturbed amino acid metabolism. Moreover, a panel of seven predictive biomarkers including 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, gamma-glutamyl-leucine, 2-hydroxyvaleric acid, LysoPC(16:1(9Z)/0:0), PC(DiMe(13,5)/MonoMe(13,5)), ADP-D-glycero-beta-D-manno-heptose and phenylalanyl-tryptophan were identified for PE development by performing multiple statistical analysis and LASSO regression analysis. The combination of these biomarkers showed promise in the prediction of PE development for suspected PE patients, with an AUC of 0.753 and 0.885 for the discovery and validation cohorts, respectively. These findings highlight the potential of large-scale prospective metabolomic studies combined with machine learning algorithms in identifying key biomarkers for predicting PE development, while retrospective metabolomics studies provide insights into the pathogenesis of PE.

Effect of encapsulation of bioactive compounds from germinated black rice for rice cracker

The encapsulation technique was applied to improve the stability of bioactive compounds in germinated black rice. The objective of this study was to investigate the encapsulation of bioactive compounds from germinated black rice in black rice cracker products. Germinated black rice was prepared by soaking brown rice in 37°C water for 24 hrs and watering every 4 hrs (5 times). The encapsulation was done by a coacervation technique using gelatin and maltodextrin (DE20) as coating materials. The effect of the encapsulation on bioactive compounds and the antioxidant activity degradation was evaluated. High pressure liquid chromatography (HPLC), ultra-performance liquid chromatography (UPLC) and Fourier transform infrared spectra (FTIR) analyses revealed that the bioactive compounds were successfully preserved due to the encapsulation process. Encapsulation efficiency was characterized in terms of the bioactive compounds such as α-tocopherol, γ-oryzanol, GABA, and phenolic acids. The rice cracker with encapsulation using maltodextrin and gelatin (SD2:10) showed slight decreases of αtocopherol ( 3 8 . 1 7 % % ) , γ-oryzanol (33.61%), and GABA (1.01%) compared to the original black rice cracker (CR). It was found that encapsulation could prevent a decrease in phenolic compounds, flavonoids, and antioxidant capacity. While the total antioxidant activities of SD2:10 decreased from CR by 2.93%, the values of ABTS and FRAP decreased by 11.33% and 11.95%, respectively. Major phenolic acids such as gallic acid, protocatechuic acid, p-hydroxybenzoic acid, and vanillic acid were slightly decreased in SD2:10. Fourier Transform Infrared spectra (FTIR) analyses suggested that encapsulation with maltodextrin and gelatin could be protected bioactive compounds from heat, light, and oxygen, and could be used to encapsulate bioactive compounds from black rice in the food industry.

Soil organic matter composition affects ecosystem multifunctionality by mediating the composition of microbial communities in long-term restored meadows

BackgroundSoil organic matter composition and microbial communities are key factors affecting ecosystem multifunctionality (EMF) during ecosystem restoration. However, there is little information on their interacting mechanisms in degraded and restored meadows. To fill this knowledge gap, plant, root and soil samples from alpine swamp meadows, alpine Kobresia meadows, severely degraded alpine meadows, short-term restored meadows (< 5 years) and long-term restored meadows (6–14 years) were collected. We leveraged high-throughput sequencing, liquid chromatography and mass spectrometry to characterize soil microbial communities and soil organic matter composition, measured microbial carbon metabolism and determined EMF.ResultsIt emerged that the similarity of soil microorganisms in meadows decreased with increasing heterogeneity of soil properties. Dispersal limitation and ecological drift led to the homogenization of the bacterial community. Based on co-occurrence network analysis, an increase in microbial network complexity promoted EMF. Root total phosphorus and soil organic matter components were the key predictors of EMF, while organic acids and phenolic acids increased the stability of the microbial network in long-term restored meadows. Carbon metabolism did not increase in restored meadows, but the niche breadth of soil microorganisms and the utilization efficiency of small molecular carbon sources such as amino acids did increase.ConclusionsThese findings emphasize the importance of soil organic matter composition in ecological restoration and that the composition should be considered in management strategies aimed at enhancing EMF.

Unraveling relationship between the genetic polymorphism CYP2A13 and nicotine metabolism of male smokers in Medan, Indonesia

BackgroundNicotine metabolism significantly influences the levels of harmful nicotine metabolites in smokers. CYP2A13, a key enzyme in nicotine and xenobiotic metabolism, is implicated in tobacco smoke-related lung cancer.AimThis study investigated the association between CYP2A13 genetic polymorphism and nicotine metabolism in male smokers in Medan, Indonesia.Materials and methodsThis cross-sectional study included 66 male smokers (aged 20–65 years) who met pre-defined inclusion and exclusion criteria. Nicotine metabolite levels were quantified in urine samples using high-performance liquid chromatography (HPLC). CYP2A13 polymorphism was determined using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) analysis of venous blood samples. Logistic regression analysis (Epi Info-7) assessed the association between CYP2A13 genotype and nicotine metabolism.ResultsNo significant association (p > 0.05) was found between CYP2A13 genotype and nicotine metabolism. The CC genotype was most prevalent. The majority of participants exhibited rapid nicotine metabolism.ConclusionFurther research with larger sample sizes and diverse populations is needed to elucidate the relationship between CYP2A13 genetic polymorphism and nicotine metabolism.

Multiplatform Lipid Analysis of the Brain of Aging Mice by Mass Spectrometry.

Lipids are critical to brain structure and function, accounting for approximately 50% of its dry weight. However, the impact of aging on brain lipids remains poorly characterized. To address this, here we applied three complementary mass spectrometry techniques: multiple reaction monitoring (MRM) profiling, untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS), and desorption electrospray ionization-MS imaging (DESI-MSI). We used brains from mice of three age groups: adult (3-4 months), middle-aged (10 months), and old (19-21 months). Phospholipids such as phosphatidylcholine, phosphatidylethanolamine, and phosphatidylglycerol were more abundant, while phosphatidylinositol and phosphatidylserine were reduced in old mice compared to adults or middle-aged mice. Key lipids such as polyunsaturated fatty acids, including DHA, AA, HexCer, SHexCer, and SM, were among the most abundant lipids in aged brains. DESI-MSI revealed spatial lipid distribution patterns consistent with findings from MRM profiling and LC-MS/MS. Integration of lipidomic data with the recently published proteomics data from the same tissues highlighted changes in proteins and phosphorylation levels of several proteins associated with Cer, HexCer, FA, PI, SM, and SHexCer metabolism, aligning with the multiplatform lipid surveillance. These findings shed insight into age-dependent brain lipid changes and their potential contribution to age-related cognitive decline.

Impaired cognitive function and decreased monoamine neurotransmitters in the DNAJC12 gene knockout mouse model

BackgroundHyperphenylalaninemia, a prevalent amino acid metabolism disorder, often results in cognitive impairment. Recent studies have identified a rare variant of this disorder caused by mutations in the DNAJC12 gene. The specific mechanisms by which DNAJC12 mutations lead to hyperphenylalaninemia and the lack of an animal model for study remain significant gaps in understanding.PurposeThis study aims to elucidate the role of DNAJC12 in intellectual disability and explore the mechanisms by which DNAJC12 deficiency leads to hyperphenylalaninemia through developing a DNAJC12 gene knockout mouse model.MethodsWe thoroughly examined the clinical features and genetic mutations evident in two patients with biallelic mutations in the DNAJC12 gene. Based on the patient’s mutation locations, we determined the target site for the knockout utilizing CRISPR/Cas9 technology. To assess the impact of these mutations on DNAJC12 expression, we used quantitative real-time PCR and Western blotting techniques to measure mRNA and protein levels, respectively. The Morris water maze test was administered to evaluate the cognitive functions of the mice. Additionally, we utilized High-Performance Liquid Chromatography (HPLC) to measure serum aromatic amino acids and brain monoamines, facilitating an investigation into the metabolism of phenylalanine and tyrosine.ResultsWe reported two patients with mutations in the DNAJC12 gene. Case 1 carried the mutations c.158-1G > A and c.262 C > T in the DNAJC12 gene. He presented with nocturnal eye closure, crying, and arching back in reverse tension before treatment, suggesting a neurotransmitter metabolism disorder. Case 2 carried the mutations c.473 C > G, and c.102 deletion in the DNAJC12 gene. He showed elevated blood phenylalanine levels, although further clinical details were not available. Based on the patients’ mutation locations, exons 2–4 of the DNAJC12 gene were targeted and eliminated. In our animal model experiments, DNAJC12 gene knockout mice exhibited a complete absence of DNAJC12 expression at both mRNA and protein levels. These knockout mice showed significant deficits in learning and memory performance as assessed by the Morris water maze test. Quantitative real-time PCR analysis indicated no significant differences in the levels of aromatic amino hydroxylases between knockout and wild-type mice. However, Western blot analysis revealed a substantial reduction in phenylalanine hydroxylase (PAH) protein levels in the liver of knockout mice, while tyrosine hydroxylase (TH) and tryptophan hydroxylase 2 (TPH2) expression remained unchanged. HPLC analysis demonstrated increased serum Phe concentrations and decreased levels of brain neurotransmitters in the knockout group.ConclusionsWe report two patients with four novel DNAJC12 mutations (c.158-1G > A, c.262 C > T, c.473 C > G, c.102delT), expanding the mutation spectrum. Based on the patients’ mutation location, we established the first DNAJC12 gene knockout mouse model. The knockout mice exhibit hyperphenylalaninemia, impaired cognitive function, and decreased monoamine neurotransmitters. DNAJC12 deficiency may contribute to the clinical phenotype via the PAH pathway, potentially at the post-transcriptional level.

Identification of potential biomarkers for coronary slow flow using untargeted metabolomics.

Coronary slow flow (CSF) is associated with poor cardiovascular prognosis. However, its pathogenesis is unclear. This study aimed to identify potential characteristic biomarkers in patients with CSF using untargeted metabolomics. We prospectively enrolled 30 patients with CSF, 30 with coronary artery disease (CAD), and 30 with normal coronary arteries (NCA), all of whom were age-matched, according to the results of coronary angiography. Serum metabolomics were analyzed using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Differentially expressed metabolites were identified through orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with univariate fold-change and VIP value analysis. Pathway enrichment of these metabolites was performed using the KEGG database, and ROC curves were plotted to assess the diagnostic value of the metabolites in CSF patients. Compared to the CAD and NCA groups, 256 metabolites showed specific expression in CSF, with 18 meeting stringent screening criteria (VIP > 1, FC ≥ 2, or FC ≤ 0.5, and P < 0.05). Seven metabolites demonstrated high diagnostic value for CSF: inositol 1,3,4-trisphosphate (AUC: 1.0), Cer (d24:1/18:0 (2OH)) (AUC: 0.984), Creosol (AUC: 0.976), Chaps (AUC: 0.904), Arg-Thr-Lys-Arg (AUC: 0.929), Ser-Tyr-Arg (AUC: 0.912), and Methyl Indole-3-Acetate (AUC: 0.909). Pathway analysis highlighted the HIF-1 signaling pathway as the most significant metabolic pathway. We identified seven metabolites that may serve as serum biomarkers for predicting and diagnosing CSF through untargeted metabolomics. The HIF-1 signaling pathway appears to be crucial in the development of CSF.

Investigation of Natural Dyes and Taxonomic Identification of Fibers Used in Chancay Textiles by Vibrational Spectroscopy and Mass Spectrometry.

Textiles provide a valuable source of information regarding past cultures and their artistic practices. Understanding ancient textiles requires identifying the raw materials used, since the origin of dyes and fibers may be from plants or animals, with the specific species used varying based on geography, trade routes and cultural significance. A selection of nine Chancay textile fragments attributed to 800-1200 CE were studied with liquid chromatography mass spectrometry (LC-MS) and direct analysis in real time mass spectrometry (DART-MS) to identify the chemical compounds in extracts of natural dyes used to create green, blue, red, yellow and black colors. From the identified molecular markers, the green colors involved the overdyeing of indigo and flavonoid dyes, the blue colors were achieved using an indigo dye, the yellows came from a flavonoid dye, the reds from anthraquinone dyes of both plant and animal origin, and the black from a mixture of flavonoid, anthraquinone and indigo dyes. A subset of the textiles was identified as containing proteinaceous fibers based on ATR-FTIR. These textiles were further studied using a mass spectrometry-based proteomics approach to identify the species used, with the peptide sequences measured confirming the presence of South American camelids, most likely llama or alpaca.

Protection of stainless steel surfaces in desalination units against corrosion during acid cleaning under dynamic conditions by using lavender angustifolia extract as a green inhibitor

This study investigates the thermodynamics, kinetics, and adsorption mechanisms of Lavender angustifolia extract (LAE) as a corrosion inhibitor for stainless steel (316SS) in desalination units. The primary aim is to evaluate the efficacy of LAE in mitigating corrosion in a 5.0 M HCl solution under dynamic conditions. High-Performance Liquid Chromatography (HPLC) analysis identified key components of the LAE extract that contribute to corrosion inhibition, including linalyl acetate (41.7%), linalool (13.6%), 1,8-cineole (8.3%), β-ocimene (6.2%), terpinen-4-ol (5.7%), lavandulyl acetate (7.5%), and camphor (4.7%). Results indicate that the inhibitory efficiency of LAE increases with concentration, peaking at 94.3% at 300 mg L⁻¹. The Freundlich adsorption isotherm model best describes the experimental adsorption data. Notably, the activation energy for corrosion increases from 7.17 kJ mol⁻¹ in the 5.0 M HCl solution to 21.65 kJ mol⁻¹ with the addition of LAE, reflecting enhanced protection. The enthalpy change (∆H*) in the presence of LAE (19.04 kJ mol⁻¹) is significantly greater than that of the extract-free solution (4.55 kJ mol⁻¹), indicating improved corrosion resistance of 316SS. Electrochemical techniques confirmed the mixed-type inhibition behavior of LAE, while UV and SEM-EDAX analyses demonstrated effective adsorption of the extract on the stainless steel surface.

Determination of 14 Benzodiazepine Multiresidues in Aquaculture Environment by Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry

Determination of 14 Benzodiazepine Multiresidues in Aquaculture Environment by Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry

Gut Microbiota-Mediated Degradation of Food-Grade Lambda-Carrageenan by Bacteroides xylanisolvens and Its Role in Inflammation.

Concerns about the safety of food additives have intensified among consumers, scientists, and policymakers. Ensuring the safety of these additives is crucial to public health. Carrageenan (CGN), a common additive in the food industry, has become the subject of controversy, particularly regarding whether it can be degraded in the gastrointestinal tract, forming degraded carrageenans (dCGNs) that may pose health risks. This study is among the first to identify Bacteroides xylanisolvens C3 as a key gut bacterium involved in the degradation of food-grade lambda-CGN (L-CGN). Using high-performance liquid chromatography (HPLC), thin-layer chromatography (TLC), and metabolic analysis, we confirmed the ability of this bacterium to degrade L-CGN. Importantly, we found that the microbiota-generated dCGNs significantly increased nitric oxide (NO) and COX-2 production and upregulated pro-inflammatory genes, including IL-1β, TNF-α, and IL-6, in macrophages. This study also highlights how microbial degradation of L-CGN can drive inflammation, particularly through the activation of the Nrf2 and NLRP3 pathways. These results suggest that microbial degradation of L-CGN in the gut may contribute to inflammation, underscoring the need to better understand microbial interactions with food-grade L-CGN, particularly in the context of colon health and inflammation-related diseases such as inflammatory bowel disease.

A Systematic Study of Liquid Chromatography in Search of the Best Separation of Cannabinoids for Potency Testing of Hemp-Based Products

A Systematic Study of Liquid Chromatography in Search of the Best Separation of Cannabinoids for Potency Testing of Hemp-Based Products

Phytochemical Profile and Anticancer Activity of Achillea conferta Leaf Extracts: Insights into Antioxidant Properties.

This study explores the phytochemical composition and biological potential of extracts from Achillea conferta leaves, specifically Hydroethanolic Extract (HE), Total Flavonoid Extract (TFE), and Glycoside Flavonoid Extract (GFE). Phytochemical screening of HE revealed significant concentrations of phenolic compounds, flavonoids, and tannins, quantified as 48.36 µg GAE/mL extract, 32.40 µg QE/mL extract, and 4.85 µg TAE/mL extract, respectively. High-Performance Liquid Chromatography (HPLC) identified key flavonoids in TFE and GFE, including catechin, epigallocatechin, hesperidin, myricetin, rutin, isorhamnetin, and luteolin. Antioxidant activities were assessed using assays for reactive oxygen species (ROS), total peroxides, and free radical scavenging (DPPH). GFE demonstrated the highest ROS concentration at 269 µM/g extract. The antiproliferative effects on breast, esophageal, and large intestine cancer cell lines were evaluated, with GFE showing greater efficacy than TFE in all tested cell lines, highlighting the therapeutic potential of A. conferta extracts. These findings highlight the medicinal potential of A. conferta as a natural source of antioxidants and anticancer agents. However, further research is necessary to explore detailed mechanistic pathways and the in vivo efficacy of these extracts.

Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.

The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. This study introduces a novel machine learning framework that can effectively characterize the bioactivity of natural products by leveraging liquid chromatography tandem mass spectrometry and untargeted metabolomics analysis. This accelerates natural product drug discovery by addressing the challenge of dereplicating previously discovered bioactive compounds. Utilizing the SIRIUS 5 metabolomics software suite and in-silico-generated fragmentation spectra, we have trained a ML model capable of predicting a compound's drug class. This approach enables the rapid identification of bioactive scaffolds from LC-MS/MS data, even without reference experimental spectra. The model was trained on a diverse set of molecular fingerprints generated by SIRIUS 5 to effectively classify compounds based on their core pharmacophores. Our model robustly classified 21 diverse bioactive drug classes, achieving accuracies greater than 93% on experimental spectra. This study underscores the potential of ML combined with MFPs to dereplicate bioactive natural products based on pharmacophore, streamlining the discovery process and expediting improved methods of isolating novel antibacterial and antifungal agents.

Emergence of MDR Enterobacter hormaechei RSM5 in Pharma Effluent and its Implications in β-lactam Antibiotic Removal from Effluent.

Antibiotic resistance poses the biggest threats to global health and development and also to food security. β-lactam antibiotics (BLAs) responsible for the transpeptidation/cross-linking process during cell wall biosynthesis contribute to the maximum resistance. The production of β-lactamase enzyme is a significant contributing factor to the development of antibiotic resistance to β-lactam antibiotics. Unintentional disposal of antibiotics from the manufacturing units of pharma industries to the water bodies enhances the exposure of antibiotics, contributing to resistance. This study describes the presence of > 50 antibiotic-resistant bacterial strains in pharma effluent of Himachal Pradesh, India. Among 54 isolates, 40% showed ampicillin resistance above 100µg/mL, 13% showed resistance above 5000µg/mL, and 3 strains showed resistance at 15,000µg/mL of ampicillin. Enterobacter hormaechei RSM5 showed the highest minimum inhibitory concentration (MIC) and cell viability and was selected for further studies. It produces lactamase (0.24 U/mL) to resist the higher concentration of antibiotics present in the media/effluent and demonstrated resistance against 3 different classes of antibiotics, confirming its status as a multidrug resistance (MDR) strain. The high-performance liquid chromatography (HPLC) analysis of the isolate demonstrated that Enterobacter hormaechei RSM5 can degrade ampicillin within 24h of incubation in medium/effluent. The emergence of Enterobacter as a pathogen with antibiotic resistance poses a significant health concern that could also be explored for the removal of antibiotics from the effluent at the source. The future of research in this area needs to be open and mindful of new approaches.

Refining the adriamycin-induced focal segmental glomerulosclerosis mouse model to improve reproducibility and animal welfare.

Reliable animal models are crucial to drug development for focal segmental glomerulosclerosis (FSGS), a rare kidney disease. Variability in success rates in literature and significant ethical concerns with animal welfare necessitate further optimization of adriamycin (ADR)-induced FSGS model developed on BALB/c mice. High-performance liquid chromatography (HPLC) was used to assess ADR stability in water and upon light exposure. To identify the optimal ADR level, single intravenous ADR injections with dosing levels from 10 to 17 mg/kg body weight were administered to BALB/c mice to induce FSGS-like pathology. Body weight and proteinuria of FSGS mice were monitored and analyzed for FSGS model-associated morbidity. Animals were euthanized for hematological and kidney histological assessments 8 weeks post induction. To identify the suitable experiment time frame of the ADR-induced FSGS mouse model, a longitudinal study was performed, with an 11-week continuous monitoring of the symptoms. ADR was found to be unstable in aqueous media and light sensitive. A dosing level of 10.5 mg/kg of ADR was optimal for consistent FSGS mouse model induction on BALB/c strain, characterized by minimal mortality and sustained FSGS-like symptoms. Findings from the longitudinal study suggest that 6 weeks post ADR induction may represent the peak of FSGS pathology severity in this mouse model. This time frame may be used for FSGS drug development projects. Based on the outcome from this study, we identified the optimal ADR dosing level and model testing duration. A standard operating procedure (SOP) for the ADR-induced FSGS mouse model was established to facilitate FSGS basic research and drug development.

Metabolites induced by citrus tristeza virus and ‘Candidatus Liberibacter asiaticus’ influence the feeding behavior of Diaphorina citri: an electrical penetration graph and LC–MS/MS study

Citrus Huanglongbing and Citrus tristeza are two diseases that affect the citrus industry worldwide. The pathogens causing these diseases are the phloem-limited bacteria ‘Candidatus Liberibacter spp.’ (mainly Ca. L. asiaticus, CLas) and citrus tristeza virus (CTV). We recently found that both CLas and CTV could be acquired and retained by the Asian citrus psyllid Diaphorina citri. However, the mechanism through which CLas and CTV interact with the insect vectors and plant hosts has not been defined. In this study, an electrical penetration graph was used to study the feeding behavior of D. citri adults on four groups of Citrus reticulata Blanco cv. Hongjü plants: healthy, CLas-infected, CTV-infected, and CTV-CLas coinfected plants. Liquid chromatography with tandem mass spectrometry (LC–MS/MS) was applied to analyze the metabolites of the four groups of plants. The combined results are as follows: (1) The lowest number of metabolites were enriched in CTV-infected plants, which hardly influenced the feeding behavior of D. citri, suggesting that mild CTV strain (CT31) infection caused limited disorders in citrus plants compared with CLas infection; (2) Increased levels of L-arabinose and kaempferol in CTV-infected and CLas-CTV coinfected plants were suggested to contribute to increased penetration time during feeding of D. citri. CLas-infection increases the difficulty of finding appropriate feeding sites by the vector and results in xylem feeding for certain duration; (3) A significant reduction in α-linolenic acid metabolism in CLas-infected plants was found to be related to methyl jasmonate signaling, which induced resistance to D. citri and increased the duration of salivation. This effect was reversed by coinfection with CTV and was consistent with the phloem structure and carbohydrate accumulation alteration; (4) Stress response-associated 2'-hydroxygenistein and sakuranetin were highly upregulated flavonoid in CTV-CLas coinfected plants. This combinged with the anatomical alterations might interfere with D. citri feeding in the citrus phloem, as reflected by the time reduction of sap-sucking there. These findings will provide new insights into the interactions between CTV and CLas in citrus and the insect vector D. citri that transmiting these pathogens.