A Mechanism for the Treatment of Cardiovascular and Renal Disease: TRPV1 and TRPA1.

ABSTRACT: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. CVD and kidney disease are closely related, with kidney injury increasing CVD mortality. The pathogenesis of cardiovascular and renal diseases involves complex and diverse interactions between multiple extracellular and intracellular signaling molecules, among which transient receptor potential vanilloid 1 (TRPV1)/transient receptor potential ankyrin 1 (TRPA1) channels have received increasing attention. TRPV1 belongs to the vanilloid receptor subtype family of transient receptor potential ion channels, and TRPA1 belongs to the transient receptor potential channel superfamily. TRPV1/TRPA1 are jointly involved in the management of cardiovascular and renal diseases and play important roles in regulating vascular tension, promoting angiogenesis, antifibrosis, anti-inflammation, and antioxidation. The mechanism of TRPV1/TRPA1 is mainly related to regulation of intracellular calcium influx and release of nitric oxide and calcitonin gene-related peptide. Therefore, this study takes the TRPV1/TRPA1 channel as the research object, analyzes and summarizes the process and mechanism of TRPV1/TRPA1 affecting cardiovascular and renal diseases, and lays a foundation for the treatment of cardiorenal diseases.

The protective effect of vitexin on hypertensive nephropathy rats.

INTRODUCTION: Vitexin is a natural flavonoid compound extracted from Vitex leaves or seeds, exhibiting various pharmacological activities including anticancer, antihypertensive, anti-inflammatory, and spasmolytic effects. However, its protective effects on hypertensive nephropathy (HN) and the underlying mechanisms remain unclear. METHODS: Spontaneous hypertension rats were fed a high-sugar and high-fat diet for 8 weeks to induce the disease HN model. From the 5th week, the rats were administered vitexin via gavage. Blood pressure was measured bi-weekly using the tail-cuff method. Histopathological changes were assessed using HE staining, and biochemical analyses were performed to evaluate the effects of vitexin on HN rats. The underlying mechanisms of vitexin treatment were investigated through western blotting. RESULTS: The data demonstrated that vitexin significantly lowered systolic, diastolic, and mean arterial pressures, and ameliorated histopathological changes in HN rats. Biochemical analyses revealed that vitexin reduced the levels of creatinine (Cr), blood urea nitrogen (BUN), total cholesterol (TC), triglycerides (TG), total protein (TP), low-density lipoprotein cholesterol (LDL-C), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), malondialdehyde (MDA), and advanced glycation end products (AGEs), while increasing the levels of albumin (ALB) and superoxide dismutase (SOD). Western blotting results indicated that vitexin treatment decreased the expression of TNF-α, IL-6, and nuclear factor kappa-B (NF-κB), while increasing the expression of SOD. CONCLUSION: The findings of this study suggest that vitexin exerts protective effects against HN, providing pharmacological evidence for its potential use in HN treatment.

Non-Targeted Metabolomics Analysis of Mother and Infant in Gestational Diabetes Mellitus and Neonatal Clinical Characterization.

BACKGROUND: The goal was to analyze serums of GDM patients and healthy pregnant women using HPLC-MS and preliminarily screen differential metabolites by metabolomics. METHOD: Sixty pregnant women who underwent elective cesarean section at term in Dongguan Dalang Hospital from January 2023 to April 2023 were selected and divided into the GDM group and healthy pregnancy group. Pre-pregnancy and pregnancy examination information, such as age, BMI, OGTT results, triglyceride, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and other clinical data were col-lected for statistical analysis. Non-targeted metabolomics of serum from 30 GDM patients and 30 healthy pregnant women were studied by HPLC-MS, and different ions were searched. The structures of differential metabolites were identified by HMDB database. The metabolic pathways of differential metabolites were analyzed by KEGG database. RESULTS: The OGTT result, pCO2, pO2, HCO3, BE, Apgar score, and bilirubin levels in the GDM group were higher than those in the healthy pregnancy group (p < 0.05). However, there were no significant differences in age, triglyceride, total cholesterol, newborn birth weight, newborn birth blood glucose, and blood gas pH between the two groups (all p > 0.05). Using p < 0.05 as the screening standard, 55 differential metabolites were identified in serum, mainly including fatty acyl, carboxylic acids and their derivatives, steroids and their derivatives, ketoacids and their derivatives, and pyrimidine nucleosides, etc., all of which were up-regulated or down-regulated to varying degrees. The 55 metabolites were mainly involved in the metabolism of pyrimidine, pyruvate, alanine, aspartic acid, glutamic acid, and arachidonic acid, glycolysis, and biosynthesis of unsaturated fatty acids. CONCLUSIONS: The discovery of these metabolites provides a theoretical basis for an indepth understanding of GDM pathogenesis. Non-targeted metabonomics analysis of blood metabonomics research technology has shown great potential value in the early diagnosis of obstetric diseases and the study of disease mechanisms.

Online digital health and informatics education for undergraduate nursing students in China: impacts and recommendations.

BACKGROUND: Digital health plays a vital role in healthcare services. Governments in many countries, including China, are increasingly advocating for the appropriate use of digital technologies to address significant health system challenges. It is crucial to incorporate digital health education into the curriculum for future nurses to adapt to the changes in the digital medical system. This study aimed to evaluate the impact of an online Digital Health and Informatics Course in China on the knowledge and comprehension of key digital health and informatics topics, self-assessment of nursing informatics competencies, and satisfaction among undergraduate nursing students. The findings of this study provide recommendations for the design and implementation of future digital health education. METHODS: This study employed a one-group, quasi-experimental mixed-methods design with pre- and post-assessments. The participants received digital health and informatics education through six three-hour online sessions in six interactive days, with online self-learning materials in between. An online quiz and focus group discussions pre- and post the course were designed to evaluate the knowledge and comprehension of key digital health and informatics topics. Also, a validated Chinese version of the Self-assessment of Nursing Informatics Competencies Scale was conducted pre- and post-course to assess self-assessment of nursing informatics competencies. Additionally, all students were invited to participate in an online survey with a performance-focused course evaluation form as well as focus group discussions to gather their feedback on the learning experience and their evaluations of the course. RESULTS: A total of 24 undergraduate nursing students were enrolled in the course. All students completed all sessions of this course, resulting in an attendance rate of 100%. Additionally, all students completed both pre- and post-assessments. In terms of the knowledge and comprehension of key digital health and informatics topics, scores of the quiz on knowledge assessment improved from the pre-test [mean pretest score: 78.33 (SD 6.005)] to the post-test [mean post-test score: 83.17 (SD 4.86)] upon completion of the course (P < 0.001). Also, students acknowledged that the course enhanced their knowledge and comprehension of informatics and digital health, the benefits of (nursing) informatics in clinical practice, and the role of health care professionals in informatics and digital health. In terms of self-assessment of nursing informatics competencies, scores on nursing informatics attitudes demonstrated significant improvement (P < 0.001). Furthermore, students reported high satisfaction with various aspects of this course, including the opportunity to explore broad horizons in informatics for future careers, engaging in group discussions, and analyzing case studies on the use of informatics and digital health in clinical practice. CONCLUSIONS: This Online Digital Health and Informatics education effectively improved undergraduate nursing students' knowledge and comprehension of the key digital health and informatics topics, nursing informatics attitudes in the self-assessment of nursing informatics competency with high levels of satisfaction. In order to ensure that future education in digital health and informatics for nursing students is in line with the technological advancements in clinical settings, it is necessary to foster collaboration between medical school training and clinical practice. This collaboration should involve the use of clinical examples to illustrate advanced digital health applications and the inclusion of practical exercises on the use of digital health technology in clinical settings.

A chimeric hairpin DNA aptamer-based biosensor for monitoring the therapeutic drug bevacizumab.

The accurate and rapid detection of specific antibodies in blood is very important for efficient diagnosis and precise treatment. Conventional methods often suffer from time-consuming operations and/or a narrow detection range. In this work, for the rapid determination of bevacizumab in plasma, a series of chimeric hairpin DNA aptamer-based probes were designed by the modification, labeling and theoretical computation of an original aptamer. Then, the dissociation constant of the modified hairpin DNA to bevacizumab was measured and screened using microscale thermophoresis. The best chimeric hairpin DNA aptamer-based probe was then selected, and a one-step platform for the rapid determination of bevacizumab was constructed. This strategy has the advantages of being simple, fast and label-free. Because of the design and screening of the hairpin DNA, as well as the optimization of the concentration and electrochemical parameters, a low detection limit of 0.37 pM (0.054 ng mL-1) with a wide linear range (1 pM-1 µM) was obtained. Finally, the rationally constructed biosensor was successfully applied to the determination of bevacizumab in spiked samples, and it showed good accuracy and precision. This method is expected to truly realize accurate and rapid detection of bevacizumab and provides a new idea for the precise treatment of diseases.

Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review.

Medical time series are sequential data collected over time that measures health-related signals, such as electroencephalography (EEG), electrocardiography (ECG), and intensive care unit (ICU) readings. Analyzing medical time series and identifying the latent patterns and trends that lead to uncovering highly valuable insights for enhancing diagnosis, treatment, risk assessment, and disease progression. However, data mining in medical time series is heavily limited by the sample annotation which is time-consuming and labor-intensive, and expert-depending. To mitigate this challenge, the emerging self-supervised contrastive learning, which has shown great success since 2020, is a promising solution. Contrastive learning aims to learn representative embeddings by contrasting positive and negative samples without the requirement for explicit labels. Here, we conducted a systematic review of how contrastive learning alleviates the label scarcity in medical time series based on PRISMA standards. We searched the studies in five scientific databases (IEEE, ACM, Scopus, Google Scholar, and PubMed) and retrieved 1908 papers based on the inclusion criteria. After applying excluding criteria, and screening at title, abstract, and full text levels, we carefully reviewed 43 papers in this area. Specifically, this paper outlines the pipeline of contrastive learning, including pre-training, fine-tuning, and testing. We provide a comprehensive summary of the various augmentations applied to medical time series data, the architectures of pre-training encoders, the types of fine-tuning classifiers and clusters, and the popular contrastive loss functions. Moreover, we present an overview of the different data types used in medical time series, highlight the medical applications of interest, and provide a comprehensive table of 51 public datasets that have been utilized in this field. In addition, this paper will provide a discussion on the promising future scopes such as providing guidance for effective augmentation design, developing a unified framework for analyzing hierarchical time series, and investigating methods for processing multimodal data. Despite being in its early stages, self-supervised contrastive learning has shown great potential in overcoming the need for expert-created annotations in the research of medical time series.

Inhibition of tumor necrosis factor improves conventional steroid therapy for Stevens-Johnson syndrome/toxic epidermal necrolysis in a cohort of patients.

BACKGROUND: Systemic steroid therapies for Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN) have been challenged because of their limited benefits. Whether additional tumor necrosis factor (TNF) α inhibition provides an optimized approach remains unexplored. OBJECTIVE: To investigate the efficacy of TNF-α inhibition combined with a steroid to treat SJS/TEN and to identify potential biomarkers. METHODS: Twenty-five patients with SJS/TEN were recruited and divided into 2 groups: 10 patients received methylprednisolone and 15 patients received etanercept plus methylprednisolone. Serum levels of granzyme B, perforin, interferon-γ, interleukin (IL) 6, IL-15, IL-18, macrophage inflammatory protein 1α, macrophage inflammatory protein 1ß, and TNF-α were measured by multiplex cytokine analysis kits during the acute and resolution phases. RESULTS: Compared with the steroid monotherapy, the combination therapy significantly shortened the course of the initial steroid treatment and the duration of the acute stage, hospitalization stay, and skin re-epithelialization. Although both therapies significantly reduced IL-15 levels; the combination therapy also decreased IL-6 and IL-18 levels. While the level of IL-15 was positively correlated with skin re-epithelialization time in both groups, the level of IL-6 served as an additional marker for the course of the disease in the combination therapy group. LIMITATIONS: The cohort size is relatively small. CONCLUSION: Additional TNF-α inhibition to steroid treatment appeared to improve outcomes for SJS/TEN.

Acute pancreatic injuries: A complication of Stevens-Johnson syndrome/toxic epidermal necrolysis associated with cytotoxic immunocell activation.

BACKGROUND: Complications involving internal organs are usually present in Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). However, pancreatic complications are rarely reported and studied. OBJECTIVE: To summarize clinical characteristics of SJS/TEN-associated acute pancreatic injuries and to investigate underlying inflammatory mechanisms. METHODS: Clinical records of 124 inpatients with SJS/TEN were reviewed. Serum levels of tumor necrosis factor α, interleukin (IL) 6, IL-18, IL-15, IL-12p70, and soluble CD56 were determined in 18 healthy donors and 17 patients with SJS/TEN, including 3 with acute pancreatic injuries. RESULTS: Acute pancreatic injury was diagnosed in 7.3% of patients (9/124) in the SJS/TEN cohort. Elevation of serum transaminase level and hypoalbuminemia occurred more frequently in patients with acute pancreatic injuries compared with those without pancreatic symptoms (P = .004 and <.001, respectively). Although acute pancreatic injury did not alter mortality rate of SJS/TEN, it was associated with longer hospitalization stays (P = .008). Within the serum cytokines whose levels were elevated in SJS/TEN, only IL-18 was found to be selectively increased in patients with acute pancreatic injuries compared with those without them (P = .03). LIMITATIONS: Cohort was small. CONCLUSION: Acute pancreatic injury is a gastrointestinal complication of SJS/TEN in which hepatotoxicity is more likely to occur. Overexpression of IL-18 might be involved in this unique entity.

Pyruvate cycle increases aminoglycoside efficacy and provides respiratory energy in bacteria.

The emergence and ongoing spread of multidrug-resistant bacteria puts humans and other species at risk for potentially lethal infections. Thus, novel antibiotics or alternative approaches are needed to target drug-resistant bacteria, and metabolic modulation has been documented to improve antibiotic efficacy, but the relevant metabolic mechanisms require more studies. Here, we show that glutamate potentiates aminoglycoside antibiotics, resulting in improved elimination of antibiotic-resistant pathogens. When exploring the metabolic flux of glutamate, it was found that the enzymes that link the phosphoenolpyruvate (PEP)-pyruvate-AcCoA pathway to the TCA cycle were key players in this increased efficacy. Together, the PEP-pyruvate-AcCoA pathway and TCA cycle can be considered the pyruvate cycle (P cycle). Our results show that inhibition or gene depletion of the enzymes in the P cycle shut down the TCA cycle even in the presence of excess carbon sources, and that the P cycle operates routinely as a general mechanism for energy production and regulation in Escherichia coli and Edwardsiella tarda These findings address metabolic mechanisms of metabolite-induced potentiation and fundamental questions about bacterial biochemistry and energy metabolism.

Two New Dolabrane Diterpenes from the Chinese Mangrove Ceriops tagal.

Two new dolabrane diterpenes, tagalenes J and K (1 and 2), together with eleven known analogues (3 - 13), were isolated from the ethanolic extract of the Chinese mangrove Ceriops tagal. The structures of these compounds were determined by extensive spectroscopic analysis, including 1D-, 2D-NMR and HR-ESI-MS, as well as the comparison with data in the literatures. Cytotoxicities of isolated compounds against MCF-7, SW480, HepG2, HeLa, PANC-1, and A2058 cancer cell lines were also evaluated. Compound 4 exhibited weak cytotoxic activity against SW480, HeLa, and PANC-1 cell lines with IC50 values of 27.7, 22.2, and 17.6 µm, respectively.

Metabolic Mechanism for l-Leucine-Induced Metabolome To Eliminate Streptococcus iniae.

Crucial metabolites that modulate hosts' metabolome to eliminate bacterial pathogens have been documented, but the metabolic mechanisms are largely unknown. The present study explores the metabolic mechanism for l-leucine-induced metabolome to eliminate Streptococcus iniae in tilapia. GC-MS-based metabolomics was used to investigate the tilapia liver metabolic profile in the presence of exogenous l-leucine. Thirty-seven metabolites of differential abundance were determined, and 11 metabolic pathways were enriched. Pattern recognition analysis identified serine and proline as crucial metabolites, which are the two metabolites identified in survived tilapias during S. iniae infection, suggesting that the two metabolites play crucial roles in l-leucine-induced elimination of the pathogen by the host. Exogenous l-serine reduces the mortality of tilapias infected by S. iniae, providing a robust proof supporting the conclusion. Furthermore, exogenous l-serine elevates expression of genes IL-1ß and IL-8 in tilapia spleen, but not TNFα, CXCR4 and Mx, suggesting that the metabolite promotes a phagocytosis role of macrophages, which is consistent with the finding that l-leucine promotes macrophages to kill both Gram-positive and Gram-negative bacterial pathogens. Therefore, the ability of phagocytosis enhanced by exogenous l-leucine is partly attributed to elevation of l-serine. These results demonstrate a metabolic mechanism by which exogenous l-leucine modulates tilapias' metabolome to enhance innate immunity and eliminate pathogens.

Trends in culprit drugs and clinical entities in cutaneous adverse drug reactions: a retrospective study.

PURPOSE: Morbidity due to cutaneous adverse drug reactions (CADRs) is quite common. The specific culprit drugs change over time and clinicians must be kept informed with updated knowledge, thus preventing potential CADRs. This retrospective study is a survey of CADRs encountered in a hospital-based population in Southern China during three time intervals, from 1984 to 2015. MATERIALS AND METHODS: The clinical records were review of 306 patients with CADRs who were admitted to our hospital from 2011 to 2015. These data were compared with patients visiting our hospital during 1984-1994 and 2003-2010. RESULTS: From 2011 to 2015, the most common CADRs were exanthematous reactions (40.8%) and Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN; 17.0%). There were eight cases (2.6%) of CADRs related to targeted therapy in oncology. In the 205 CADR cases that were due to single medications, the most common offending drugs were allopurinol (21.5%), cephalosporins (10.7%) and carbamazepine (10.2%). The percentages of CADR cases due to allopurinol, carbamazepine, or epidermal growth factor receptor inhibitors were significantly higher from 2011 to 2015 compared with 1984-1994 or 2003-2010. The rate of SJS/TEN occurrence was significantly higher in the two recent periods compared with 1984-1994. CONCLUSIONS: Changes in drug prescriptions are a major factor that affects the CADRs seen in clinical records. Newer drugs can be culpable for CADRs, and more CADRs are now documented with increased severity at clinical presentation. Reliable screening tests for specific drugs are urgently required to eliminate possible fatalities.

GC-MS-Based Metabolome and Metabolite Regulation in Serum-Resistant Streptococcus agalactiae.

Streptococcus agalactiae causes severe systemic infections in human and fish. In the present study, we established a pathogen-plasma interaction model by which we explored how S. agalactiae evaded serum-mediated killing. We found that S. agalactiae grew faster in the presence of yellow grouper plasma than in the absence of the plasma, indicating S. agalactiae evolved a way of evading the fish immune system. To determine the events underlying this phenotype, we applied GC-MS-based metabolomics approaches to identify differential metabolomes between S. agalactiae cultured with and without yellow grouper plasma. Through bioinformatics analysis, decreased malic acid and increased adenosine were identified as the most crucial metabolites that distinguish the two groups. Meanwhile, they presented with decreased TCA cycle and elevated purine metabolism, respectively. Finally, exogenous malic acid and adenosine were used to reprogram the plasma-resistant metabolome, leading to elevated and decreased susceptibility to the plasma, respectively. Therefore, our findings reveal for the first time that S. agalactiae utilizes a metabolic trick to respond to plasma killing as a result of serum resistance, which may be reverted or enhanced by exogenous malic acid and adenosine, respectively, suggesting that the metabolic trick can be regulated by metabolites.

Limonoids with an oxygen bridge between C(1) and C(29) from the seeds of a Krishna mangrove, Xylocarpus granatum.

Ten limonoids, named granatumins L-U (1-10, resp.), were isolated from the seeds of an Indian mangrove, Xylocarpus granatum, collected in the estuary of Krishna, Andhra Pradesh. The structures of these compounds were established on the basis of spectroscopic data. The relative configuration of granatumin L (1) was confirmed by a single-crystal X-ray diffraction analysis. Granatumins L-T (1-9, resp.) belong to the small group of limonoids with an oxygen bridge between C(1) and C(29), while granatumin U (10) is a 28-Me-oxidized mexicanolide. This is the first report of limonoids with an O-bridge between C(1) and C(29) from the Indian X. granatum. The pronounced structural diversity of limonoids from this mangrove might originate from environmental factors.

Decandrinin, an unprecedented C9-spiro-fused 7,8-seco-ent-abietane from the Godavari mangrove Ceriops decandra.

Decandrinin (1), an unprecedented C9-spiro-fused 7,8-seco-ent-abietane, was obtained from the bark of an Indian mangrove, Ceriops decandra, collected in the estuary of Godavari, Andhra Pradesh. The constitution and the relative configuration of 1 were determined by HRMS (ESI) and extensive NMR investigations, and the absolute configuration by circular dichroism (CD) and optical-rotatory dispersion (ORD) spectroscopy in combination with quantum-chemical calculations. Decandrinin is the first 7,8-seco-ent-abietane.

Biomimetic affinity membrane roll column for rapid purification of C-reactive protein.

To in-depth explore the action mechanism of C-reactive protein (CRP) and precisely study its signaling pathways, it is essential to acquire high-purity CRP while preserving its intact structure and functionality. In this study, we propose and fabricate a high-density 2-methacryloyloxyethyl phosphorylcholine (MPC)-modified membrane roll column (MPC-MRC) using a surface-initiated atom transfer radical polymerization (SI-ATRP) approach, which can overcome these limitations (long incubation time and low adsorption capacity) of conventional enrichment materials. The MPC-MRC incorporates a high-density 2-hydroxyethyl methacrylate polymer brush to prevent non-specific protein adsorption and multiple MPC polymer brush layers for high-performance enrichment of CRP in the company of calcium ions. Furthermore, the MPC-MRC exhibits high permeability, hydrophilicity, and mechanical strength. Compared to previous technologies, this novel material demonstrates significantly higher CRP binding capacity (310.3 mg/g), shorter processing time (only 15 min), and lower cost (only 12 USD/column). Notably, the MPC-MRC enables fast and effective purification of CRP from both human and rat serum, exhibiting good selectivity, recovery (> 91.3 %), and purity (> 95.2 %). Thus, this proposed purification approach based on MPC-MRC holds great potential for target protein enrichment from complex samples, as well as facilitating in-depth studies of its biological functions.

Efficient Machine Reading Comprehension for Health Care Applications: Algorithm Development and Validation of a Context Extraction Approach.

BACKGROUND: Extractive methods for machine reading comprehension (MRC) tasks have achieved comparable or better accuracy than human performance on benchmark data sets. However, such models are not as successful when adapted to complex domains such as health care. One of the main reasons is that the context that the MRC model needs to process when operating in a complex domain can be much larger compared with an average open-domain context. This causes the MRC model to make less accurate and slower predictions. A potential solution to this problem is to reduce the input context of the MRC model by extracting only the necessary parts from the original context. OBJECTIVE: This study aims to develop a method for extracting useful contexts from long articles as an additional component to the question answering task, enabling the MRC model to work more efficiently and accurately. METHODS: Existing approaches to context extraction in MRC are based on sentence selection strategies, in which the models are trained to find the sentences containing the answer. We found that using only the sentences containing the answer was insufficient for the MRC model to predict correctly. We conducted a series of empirical studies and observed a strong relationship between the usefulness of the context and the confidence score output of the MRC model. Our investigation showed that a precise input context can boost the prediction correctness of the MRC and greatly reduce inference time. We proposed a method to estimate the utility of each sentence in a context in answering the question and then extract a new, shorter context according to these estimations. We generated a data set to train 2 models for estimating sentence utility, based on which we selected more precise contexts that improved the MRC model's performance. RESULTS: We demonstrated our approach on the Question Answering Data Set for COVID-19 and Biomedical Semantic Indexing and Question Answering data sets and showed that the approach benefits the downstream MRC model. First, the method substantially reduced the inference time of the entire question answering system by 6 to 7 times. Second, our approach helped the MRC model predict the answer more correctly compared with using the original context (F1-score increased from 0.724 to 0.744 for the Question Answering Data Set for COVID-19 and from 0.651 to 0.704 for the Biomedical Semantic Indexing and Question Answering). We also found a potential problem where extractive transformer MRC models predict poorly despite being given a more precise context in some cases. CONCLUSIONS: The proposed context extraction method allows the MRC model to achieve improved prediction correctness and a significantly reduced MRC inference time. This approach works technically with any MRC model and has potential in tasks involving processing long texts.

Effect of anionic groups in zwitterionic hydrophilic stationary phases on their chromatographic characteristics.

The structure of zwitterion has great impact on the separation properties of zwitterionic hydrophilic stationary phases. To better understand the role of anionic groups of zwitterions, a novel carboxybetaine-based zwitterionic monolithic column was first prepared through thermo-initiated copolymerization of functional monomer (3-acrylamidopropyl)-dimethyl-(2-carboxymethyl) ammonium (CBAA) and crosslinker ethylene dimethacrylate (EDMA) within 100 µm ID capillary. The optimal poly(CBAA-co-EDMA) monolithic column exhibited satisfactory mechanical and chemical stability, good repeatability, high column efficiency (96,000 plates/m), and excellent separation performance for different classes of polar compounds (i.e., phenols, monophosphate nucleotides, urea and allantoin). A comparative study was then performed among three zwitterionic hydrophilic stationary phases containing different anionic groups, i.e. poly(CBAA-co-EDMA) (carboxybetaine), poly(2-{2-(methacryloyloxy) ethyldimethylammonium}ethyl n-butyl phosphate-co-EDMA) (phosphocholine), and poly(N,N-dimethyl-N-(3-methacrylamidopropyl)-N-(3-sulfopropyl) ammonium betaine-co-EDMA) (sulfobetaine) using benzoic acid derivatives, amine compounds, nucleobases and nucleosides as model analytes. The carboxybetaine-based monolithic column exhibited much higher positive zeta-potential and hydrophilicity, which endows it with a stronger retention capacity for acidic and neutral compounds, but sulfobetaine-based monolithic column exhibited much higher selectivity and retention capacity for the amines. Moreover, their enrichment efficiencies for N-glycopeptides were also evaluated based on their different hydrophilicity, and it was observed that the poly(CBAA-co-EDMA) monolithic material captured 4-8 times more N-glycopeptides compared to the other two materials.

Mimotope peptide modified pompon mum-like magnetic microparticles for precise recognition, capture and biotransformation analysis of rituximab in biological fluids.

Due to low immobilized ligand density, limited binding capacity, and severe interference from serum proteins, developing ideal peptide-based biomaterials for precise recognition and in vivo analysis of biopharmaceuticals remains a huge challenge. In this study, mimotope peptide modified pompon mum-like biomimetic magnetic microparticles (MMPs, 3.8 µm) that mimic the specific functionalities of CD20 on malignant B cells were developed for the first time. Benefit from the numerous ligand binding sites (Ni2+) on the pompon mum-like MMPs, these novel materials achieved ≥10 times higher peptide ligand densities (>2300 mg/g) and antibody binding capacities (1380 mg/g) compared to previous reported biomaterials. Leveraging the high specificity of the mimotope peptide, rituximab can be precisely recognized and enriched from cell culture media or serum samples. We also established an LC‒MS/MS method using the MMPs for tracking rituximab biotransformation in patient serum. Intriguingly, deamidation of Asn55 and Asn33, as well as oxidation of Met81 and Met34 were observed at the key complementarity determining regions of rituximab, which could potentially influence antibody function and require careful monitoring. Overall, these versatile biomimetic MMPs demonstrate superior recognition and enrichment capabilities for target antibodies, offering interesting possibilities for biotransformation analysis of biopharmaceuticals in patient serum.

Jiangu formula: A novel osteoclast-osteoblast coupling agent for effective osteoporosis treatment.

BACKGROUND: The discovering of an osteoclast (OC) coupling active agent, capable of suppressing OC-mediated bone resorption while concurrently stimulating osteoblast (OB)-mediated bone formation, presents a promising strategy to overcome limitations associated with existing antiresorptive agents. However, there is a lack of research on active OC coupling agents. PURPOSE: This study aims to investigate the potential of Jiangu Formula (JGF) in inhibiting OCs while maintaining the OCOB coupling function. METHODS: The anti-osteoporosis efficacy of JGF was evaluated in osteoporosis models induced by ovariectomy in C57BL/6 mouse and SD rats. The effect of JGF on OCs was evaluated by detecting its capacity to inhibit OC differentiation and bone resorption in an in vitro osteoclastogenesis model induced by RANKL. The OCOB coupling activity of JGF was evaluated by measuring the secretion levels of OC-derived coupling factors, OB differentiation activity of MC3T3-E1 interfered with conditioned medium, and the effect of JGF on OC inhibition and OB differentiation in a C3H10T1/2-RAW264.7 co-culture system. The mechanism of JGF was studied by network pharmacology and validated using western blot, immunofluorescence (IF), and ELISA. Following that, the active ingredients of JGF were explored through a chemotype-assembly approach, activity evaluation, and LC-MS/MS analysis. RESULTS: JGF inhibited bone resorption in murine osteoporosis without compromising the OCOB coupling effect on bone formation. In vitro assays showed that JGF preserved the coupling effect of OC on OB differentiation by maintaining the secretion of OC-derived coupling factors. Network analysis predicted STAT3 as a key regulation point for JGF to exert anti-osteoporosis effect. Further validation assays confirmed that JGF upregulated p-STAT3(Ser727) and its regulatory factors IL-2 in RANKL-induced RAW264.7 cells. Moreover, 23 components in JGF with anti-OC activity identified by chemotype-assembly approach and verification experiments. Notably, six compounds, including ophiopogonin D, ginsenoside Re, ginsenoside Rf, ginsenoside Rg3, ginsenoside Ro, and ononin were identified as OC-coupling compounds. CONCLUSION: This study first reported JGF as an agent that suppresses bone loss without affecting bone formation. The potential coupling mechanism of JGF involves the upregulation of STAT3 by its regulators IL-2. Additionally, the chemotype-assembly approach elucidated the activity compounds present in JGF, offering a novel strategy for developing an anti-resorption agent that preserves bone formation.