Synergistic SERS enhancement of NiCo-LDHs microurchins and silver nanoparticles for ultra-sensitive and reusable detection of thiabendazole.

Two-dimensional layered semiconductor materials as a distinctive class of materials are comprehensively explored for widespread applications due to narrow bandgap, controllable morphology, and tunable metal cation composition. Herein, we constructed a sensing platform of surface enhanced Raman spectroscopy (SERS) by combination of nickel­cobalt layered double hydroxide (NiCo-LDH) microurchins and plasmonic silver nanoparticles (Ag NPs) for fungicide detection of thiabendazole (TBZ). The NiCo-LDHs/Ag-NPs microcomposites consist of NiCo-LDHs microurchins having a large number of nanoneedles deposited with photoreduced Ag NPs. The SERS platform with NiCo-LDHs/Ag-NPs shows an excellent SERS performance for TBZ detection, including an ultra-low detection limit of 1.49 × 10-11 M, a sublime enhancement factor of 1.71 × 109, high uniformity, good reproducibility, and long-term storage stability. The ultrahigh SERS activity of NiCo-LDH/Ag-NPs can be attributed to strong electromagnetic enhancement in the nanoscale gaps between Ag NPs, massive charge transfer through large-area NiCo-LDH/Ag-NPs interfaces, and the synergistic action of electromagnetic and charge transfer mechanisms. Besides, the unique morphology of NiCo-LDHs/Ag-NPs microcomposite provides a broad surface area for adsorption of TBZ molecules for further Raman signal enhancement. The practicability of the proposed SERS platform is confirmed by detecting TBZ in the real samples of apple juice and river water. The exceptional self-cleaning capability of the NiCo-LDHs/Ag-NPs microcomposite with an retention rate of 81.97 % even after the fifth degradation cycle underscores its impressive sustainable reusability and cost-effectiveness. The findings in this work lay the foundation for the development of high-performance SERS platforms to ensure food safety and environmental protection.

A multi-glycomic platform for the analysis of food carbohydrates.

Carbohydrates comprise the largest fraction of most diets and exert a profound impact on health. Components such as simple sugars and starch supply energy, while indigestible components, deemed dietary fiber, reach the colon to provide food for the tens of trillions of microbes that make up the gut microbiota. The interactions between dietary carbohydrates, our gastrointestinal tracts, the gut microbiome and host health are dictated by their structures. However, current methods for analysis of food glycans lack the sensitivity, specificity and throughput needed to quantify and elucidate these myriad structures. This protocol describes a multi-glycomic approach to food carbohydrate analysis in which the analyte might be any food item or biological material such as fecal and cecal samples. The carbohydrates are extracted by ethanol precipitation, and the resulting samples are subjected to rapid-throughput liquid chromatography (LC)-tandem mass spectrometry (LC-MS/MS) methods. Quantitative analyses of monosaccharides, glycosidic linkages, polysaccharides and alcohol-soluble carbohydrates are performed in 96-well plates at the milligram scale to reduce the biomass of sample required and enhance throughput. Detailed stepwise processes for sample preparation, LC-MS/MS and data analysis are provided. We illustrate the application of the protocol to a diverse set of foods as well as different apple cultivars and various fermented foods. Furthermore, we show the utility of these methods in elucidating glycan-microbe interactions in germ-free and colonized mice. These methods provide a framework for elucidating relationships between dietary fiber, the gut microbiome and human physiology. These structures will further guide nutritional and clinical feeding studies that enhance our understanding of the role of diet in nutrition and health.

Dietary fiber monosaccharide content alters gut microbiome composition and fermentation.

Members of the mammalian gut microbiota metabolize diverse complex carbohydrates that are not digested by the host, which are collectively labeled "dietary fiber." While the enzymes and transporters that each strain uses to establish a nutrient niche in the gut are often exquisitely specific, the relationship between carbohydrate structure and microbial ecology is imperfectly understood. The present study takes advantage of recent advances in complex carbohydrate structure determination to test the effects of fiber monosaccharide composition on microbial fermentation. Fifty-five fibers with varied monosaccharide composition were fermented by a pooled feline fecal inoculum in a modified MiniBioReactor array system over a period of 72 hours. The content of the monosaccharides glucose and xylose was significantly associated with the reduction of pH during fermentation, which was also predictable from the concentrations of the short-chain fatty acids lactic acid, propionic acid, and the signaling molecule indole-3-acetic acid. Microbiome diversity and composition were also predictable from monosaccharide content and SCFA concentration. In particular, the concentrations of lactic acid and propionic acid correlated with final alpha diversity and were significantly associated with the relative abundance of several of the genera, including Lactobacillus and Dubosiella. Our results suggest that monosaccharide composition offers a generalizable method to compare any dietary fiber of interest and uncover links between diet, gut microbiota, and metabolite production. IMPORTANCE: The survival of a microbial species in the gut depends on the availability of the nutrients necessary for that species to survive. Carbohydrates in the form of non-host digestible fiber are of particular importance, and the set of genes possessed by each species for carbohydrate consumption can vary considerably. Here, differences in the monosaccharides that are the building blocks of fiber are considered for their impact on both the survival of different species of microbes and on the levels of microbial fermentation products produced. This work demonstrates that foods with similar monosaccharide content will have consistent effects on the survival of microbial species and on the production of microbial fermentation products.

Prodrug-conjugated tumor-seeking commensals for targeted cancer therapy.

Prodrugs have been explored as an alternative to conventional chemotherapy; however, their target specificity remains limited. The tumor microenvironment harbors a range of microorganisms that potentially serve as tumor-targeting vectors for delivering prodrugs. In this study, we harness bacteria-cancer interactions native to the tumor microbiome to achieve high target specificity for prodrug delivery. We identify an oral commensal strain of Lactobacillus plantarum with an intrinsic cancer-binding mechanism and engineer the strain to enable the surface loading of anticancer prodrugs, with nasopharyngeal carcinoma (NPC) as a model cancer. The engineered commensals show specific binding to NPC via OppA-mediated recognition of surface heparan sulfate, and the loaded prodrugs are activated by tumor-associated biosignals to release SN-38, a chemotherapy compound, near NPC. In vitro experiments demonstrate that the prodrug-loaded microbes significantly increase the potency of SN-38 against NPC cell lines, up to 10-fold. In a mouse xenograft model, intravenous injection of the engineered L. plantarum leads to bacterial colonization in NPC tumors and a 67% inhibition in tumor growth, enhancing the efficacy of SN-38 by 54%.

Plasma ddPCR for the detection of MET amplification in advanced NSCLC patients: a comparative real-world study.

Background: Mesenchymal-epithelial transition (MET) amplification is a crucial oncogenic driver and a resistance mechanism to epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) of non-small-cell lung cancer (NSCLC). Fluorescence in situ hybridization (FISH) is the gold standard for MET amplification detection. However, it is inapplicable when tissue samples are unavailable. Objective: This study assessed the performance of plasma droplet digital polymerase chain reaction (ddPCR) in MET amplification detection in NSCLC patients. Design and methods: A total of 87 NSCLC patients were enrolled, and 94 paired tissue and plasma samples were analyzed for the concordance between FISH and plasma ddPCR/tissue next-generation sequencing (NGS) in detecting MET amplification. In addition, the efficacy of patients with MET amplification using different detection methods who were treated with MET-TKIs was evaluated. Results: Plasma ddPCR showed substantial concordance with FISH (74.1% sensitivity, 92.5% specificity, and 87.2% accuracy with a kappa value of 0.68) and outperformed tissue NGS (kappa value of 0.64) in MET amplification detection. Combined plasma ddPCR and tissue NGS showed substantial concordance with FISH (92.3% sensitivity, 89.2% specificity, and an accuracy of 90.1% with a kappa value of 0.77). The efficacy is comparable in these NSCLC patients with MET amplification detected by FISH and plasma ddPCR who were treated with MET-TKIs. Conclusion: Plasma ddPCR is a potentially reliable method for detecting MET amplification in advanced NSCLC patients. Combined plasma ddPCR and tissue NGS might be an alternative or complementary method to MET amplification detection.

Presentation of glomerulocystic disease in a young onset diabetes: A case report.

RATIONALE: This case report presents a challenging medical scenario involving a young adult male who exhibited an unusual combination of symptoms, including abrupt weight loss, declining renal function, proteinuria, and concurrent onset of diabetes mellitus. Remarkably, the patient had no previous medical history or family history of similar conditions, necessitating a comprehensive investigation. PATIENT CONCERNS: On March 10, 2021, a 25-year-old male sought medical attention due to the aforementioned symptoms. Initial assessments revealed stage 5 chronic kidney disease, with elevated blood urea nitrogen (BUN) and serum creatinine (Cr) levels, as well as significant proteinuria. The only notable physical finding was obesity, and renal ultrasound showed normal-sized kidneys without cysts. DIAGNOSIS: A treatment plan was initiated to stabilize creatinine levels, including medications such as Glimepiride, Glyxambi, Bisoprolol, Amlodipine, and Valsartan. However, despite diligent medication management, proteinuria persisted, prompting further evaluation. A renal biopsy was performed on April 12th, 2023, leading to the diagnosis of glomerulocystic kidney disease with early-stage changes indicative of diabetic nephropathy. INTERVENTIONS: The patient continues to receive ongoing care and follow-up at our outpatient clinic to optimize therapeutic interventions and elucidate the underlying etiology of this complex clinical scenario. OUTCOMES: Ongoing investigations and therapeutic interventions are crucial to understand the underlying cause and optimize patient care in this intricate clinical scenario. LESSONS: This case underscores the complexity of diagnosing and managing a young adult presenting with concurrent renal dysfunction, proteinuria, and diabetes mellitus in the absence of prior underlying conditions. It highlights the importance of comprehensive evaluation and ongoing care in such challenging cases.

Quantifying Gut Microbial Short-Chain Fatty Acids and Their Isotopomers in Mechanistic Studies Using a Rapid, Readily Expandable LC-MS Platform.

Short-chain fatty acids (SCFAs) comprise the largest group of gut microbial fermentation products. While absorption of most nutrients occurs in the small intestine, indigestible dietary components, such as fiber, reach the colon and are processed by the gut microbiome to produce a wide array of metabolites that influence host physiology. Numerous studies have implicated SCFAs as key modulators of host health, such as in regulating irritable bowel syndrome (IBS). However, robust methods are still required for their detection and quantitation to meet the demands of biological studies probing the complex interplay of the gut-host-health paradigm. In this study, a sensitive, rapid-throughput, and readily expandible UHPLC-QqQ-MS platform using 2-PA derivatization was developed for the quantitation of gut-microbially derived SCFAs, related metabolites, and isotopically labeled homologues. The utility of this platform was then demonstrated by investigating the production of SCFAs in cecal contents from mice feeding studies, human fecal bioreactors, and fecal/bacterial fermentations of isotopically labeled dietary carbohydrates. Overall, the workflow proposed in this study serves as an invaluable tool for the rapidly expanding gut-microbiome and precision nutrition research field.

Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes.

Rising antimicrobial resistance (AMR) and lack of innovation in the antibiotic pipeline necessitate novel approaches to discovering new drugs. Metal complexes have proven to be promising antimicrobial compounds, but the number of studied compounds is still low compared to the millions of organic molecules investigated so far. Lately, machine learning (ML) has emerged as a valuable tool for guiding the design of small organic molecules, potentially even in low-data scenarios. For the first time, we extend the application of ML to the discovery of metal-based medicines. Utilising 288 modularly synthesized ruthenium arene Schiff-base complexes and their antibacterial properties, a series of ML models were trained. The models perform well and are used to predict the activity of 54 new compounds. These displayed a 5.7x higher hit-rate (53.7 %) against methicillin-resistant Staphylococcus aureus (MRSA) compared to the original library (9.4 %), demonstrating that ML can be applied to improve the success-rates in the search of new metalloantibiotics. This work paves the way for more ambitious applications of ML in the field of metal-based drug discovery.

Immune modulation of gut microbiota and its metabolites in chronic hepatitis B.

The gut microbiota is a diverse ecosystem consisting of 100 trillion microbiomes. The interaction between the host's gut and distal organs profoundly impacts various functions such as metabolism, immunity, neurology, and nutrition within the human body. The liver, as the primary immune organ, plays a crucial role in maintaining immune homeostasis by receiving a significant influx of gut-derived components and toxins. Perturbations in gut microbiota homeostasis have been linked to a range of liver diseases. The advancements in sequencing technologies, such as 16S rRNA and metagenomics, have opened up new avenues for comprehending the intricate physiological interplay between the liver and the intestine. Metabolites produced by the gut microbiota function as signaling molecules and substrates, influencing both pathological and physiological processes. Establishing a comprehensive host-bacterium-metabolism axis holds tremendous potential for investigating the mechanisms underlying liver diseases. In this review, we have provided a summary of the detrimental effects of the gut-liver axis in chronic liver diseases, primarily focusing on hepatitis B virus-related chronic liver diseases. Moreover, we have explored the potential mechanisms through which the gut microbiota and its derivatives interact with liver immunity, with implications for future clinical therapies.

Interferon-alpha and MxA inhibit BK polyomavirus replication by interaction with polyomavirus large T antigen.

INTRODUCTION: BK Polyomavirus (BKPyV) infection is a common complication in kidney transplant recipients and can result in poor outcome and graft failure. Currently, there is no known effective antiviral agent. This study investigated the possible antiviral effects of Interferon alpha (IFNα) and its induced protein, MxA, against BKPyV. METHODS: In vitro cell culture experiments were conducted using human primary renal proximal tubular epithelial cells (HRPTECs). We also did animal studies using Balb/c mice with unilateral kidney ischemic reperfusion injury. RESULTS: Our results demonstrated that IFNα effectively inhibited BKPyV in vitro and murine polyomavirus in animal models. Additionally, IFNα and MxA were found to suppress BKPyV TAg and VP1 production. Silencing MxA attenuated the antiviral efficacy of IFNα.We observed that MxA interacted with BKPyV TAg, causing it to remain in the cytosol and preventing its nuclear translocation. To determine MxA's essential domain for its antiviral activities, different mutant MxA constructs were generated. The MxA mutant K83A retained its interaction with BKPyV TAg, and its antiviral effects were intact. The MxA T103A mutant, on the other hand, abolished GTPase activity and lost its protein-protein interaction with BKPyV TAg, and lost its antiviral effect. CONCLUSION: IFNα and its downstream protein, MxA, have potent antiviral properties against BKPyV. Furthermore, our findings indicate that the interaction between MxA and BKVPyV TAg plays a crucial role in determining the anti-BKPyV effects of MxA.