Cost-effectiveness analysis of metformin versus insulin in the treatment of gestational diabetes mellitus.

OBJECTIVE: Although there have been many studies on gestational diabetes mellitus (GDM) treatment, there is still a knowledge gap regarding the comparative cost-effectiveness of metformin and insulin in the treatment phase. Existing studies have focused on treatment efficacy and drug safety, but relatively little has been explored regarding cost-effectiveness analysis. In particular, no comprehensive study has evaluated the cost-effectiveness of metformin and insulin for GDM treatment. Therefore, this study aimed to fill this knowledge gap by conducting a cost-effectiveness analysis of these two treatments for GDM. METHODS: A decision-analytic model was used to compare the cost-effectiveness of metformin and insulin in China. Probabilities, costs, and utilities were derived from the literature. The cost and quality-adjusted life years (QALYs) were calculated using the roll-back method. The strategy was considered cost-effective if the incremental cost-effectiveness ratio (ICER) was below the willingness-to-pay (WTP) threshold of ¥242,938 per QALY. Sensitivity analyses were also conducted to assess the robustness of the results. RESULTS: The roll-back analysis indicated that insulin was not cost-effective compared to metformin, resulting in increased costs and decreased QALYs, with a negative ICER. These findings suggested that metformin is a cost-effective option than insulin. Furthermore, the sensitivity analysis showed that the model was robust. CONCLUSIONS: Compared with insulin, metformin is a cost-effective treatment option for GDM.

Effect of arsenic on the risk of gestational diabetes mellitus: a systematic review and meta-analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is a complication of pregnancy associated with numerous adverse outcomes. There may be a potential link between GDM and arsenic (As) exposure, but this hypothesis remains controversial. This meta-analysis summarizes the latest studies evaluating the association between As and GDM. METHODS: A comprehensive search of the PubMed, Embase, and Scopus databases up to September 2023 was performed. The pooled estimates with 95% CIs were presented using forest plots. Estimates were calculated with random effects models, and subgroup and sensitivity analyses were conducted to address heterogeneity. RESULTS: A total of 13 eligible studies involving 2575 patients with GDM were included in this meta-analysis. The results showed that women exposed to As had a significantly increased risk of GDM (OR 1.47, 95% CI: 1.11 to 1.95, P = 0.007). Subgroup analyses suggested that the heterogeneity might be attributed to the years of publication. In addition, sensitivity analysis confirmed the robust and reliable results. CONCLUSIONS: This analysis suggested that women exposed to As have a greater risk of GDM. However, the significant heterogeneity across studies requires careful interpretation. REGISTRATION: The PROSPERO registration ID is CRD42023461820.

Effect of probiotics on pregnancy outcomes in gestational diabetes: systematic review and meta-analysis.

OBJECTIVE: Gestational diabetes mellitus (GDM) is a prevalent complication during pregnancy associated with numerous adverse outcomes. There is emerging evidence suggesting the potential of probiotics as a therapeutic measure for GDM; however, existing studies have yielded contradictory results. This meta-analysis assessed the efficacy of probiotics on blood glucose management and pregnancy outcomes in patients with GDM. METHODS: A comprehensive search of the PubMed, Embase, and Cochrane databases was conducted up to August 22, 2023, to identify relevant studies. The primary outcomes focused on fasting blood glucose (FBG), fasting serum insulin (FSI), homeostasis model assessment of insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index (QUICKI). The secondary outcomes included various maternal and neonatal outcomes. RESULTS: This meta-analysis included 15 randomized controlled trials (RCTs), encompassing 1006 patients with GDM. The results showed that, compared to a placebo, probiotics demonstrated a significant reduction in FBG (MD - 2.58, 95% CI - 4.38 to - 0.79, p < 0.01), FSI (MD - 2.29, 95% CI - 3.40 to - 1.18, p < 0.01), HOMA-IR (MD - 0.56, 95% CI - 0.81 to - 0.32, p < 0.01), and birth weight (MD - 101.20, 95% CI - 184.62 to - 17.77, p = 0.02). Furthermore, it resulted in fewer neonatal intensive care unit (NICU) admissions (RR 0.60, 95% CI 0.40-0.89, p = 0.01), instances of hyperbilirubinemia (RR 0.31, 95% CI 0.16-0.61, p < 0.01), and elevated QUICKI (MD 0.01, 95% CI 0.00-0.01, p < 0.01). No significant impact was observed in the other analyzed outcomes. CONCLUSIONS: In conclusion, probiotics improve FBG, FSI, and HOMA-IR, and reduce the occurrence of neonatal hyperbilirubinemia, NICU admissions, and birth weight in the offspring of patients with GDM. However, the quality of the evidence, as per the GRADE approach, varies from high to low, necessitating further studies to consolidate these findings.

A meta-analysis of metformin and insulin on maternal outcome and neonatal outcome in patients with gestational diabetes mellitus.

INTRODUCTION: The use of metformin for treating gestational diabetes mellitus (GDM) remains controversial because it can pass through the placenta. This meta-analysis aimed to compare the effects of metformin and insulin on maternal and neonatal outcomes in patients with GDM. METHODS: We conducted a comprehensive search of the PubMed, Embase, and Cochrane Library databases, focusing on randomized controlled trials (RCTs) that evaluated the impacts of metformin and insulin on both maternal and neonatal outcomes in patients with GDM. RESULTS: Twenty-four RCTs involving 4934 patients with GDM were included in this meta-analysis. Compared with insulin, metformin demonstrated a significant reduction in the risks of preeclampsia (RR 0.61, 95% CI 0.48 to 0.78, p < .0001), induction of labor (RR 0.90, 95% CI 0.82 to 0.98, p = .02), cesarean delivery (RR 0.91, 95% CI 0.85 to 0.98, p = .01), macrosomia (RR 0.67, 95% CI 0.53 to 0.83, p = .0004), neonatal intensive care unit (NICU) admission (RR 0.75, 95% CI 0.66 to 0.86, p < .0001), neonatal hypoglycemia (RR 0.55, 95% CI 0.48 to 0.63, p < .00001), and large for gestational age (LGA) (RR 0.80, 95% CI 0.68 to 0.94, p = .007). Conversely, metformin showed no significant impact on gestational hypertension (RR 0.84, 95% CI 0.67 to 1.06, p = .15), spontaneous vaginal delivery (RR 1.13, 95% CI 1.00 to 1.08, p = .05), emergency cesarean section (RR 0.94, 95% CI 0.77 to 1.16, p = .58), shoulder dystocia (RR 0.65, 95% CI 0.31 to 1.39, p = .27), premature birth (RR 0. 92, 95% CI 0.61 to 1.39, p = .69), polyhydramnios (RR 1.11, 95% CI 0.54 to 2.30, p = .77), birth trauma (RR 0.87, 95% CI 0.54 to 1.39, p = .56), 5-min Apgar score < 7 (RR 1.13, 95% CI 0.76 to 1.68, p = .55), small for gestational age (SGA) (RR 0.93, 95% CI 0.71 to 1.22, p = .62), respiratory distress syndrome (RDS) (RR 0.74, 95% CI 0.50 to 1.08, p = .11), jaundice (RR 1.09, 95% CI 0.95 to 1.25, p = .24) or birth defects (RR 0.80, 95% CI 0.37 to 1.74, p = .57). CONCLUSIONS: The findings suggest that metformin can reduce the risk of certain maternal and neonatal outcomes compared with insulin therapy for GDM. However, long-term follow-up studies of patients with GDM taking metformin and their offspring are warranted to provide further evidence.

A clinical phase I dose-finding design with adaptive shrinking boundaries for drug combination trials.

BACKGROUND: Combinations of drugs are becoming increasingly common in oncology treatment. In some cases, patients can benefit from the interaction between two drugs, although there is usually a higher risk of developing toxicity. Due to drug-drug interactions, multidrug combinations often exhibit different toxicity profiles than those of single drugs, leading to a complex trial scenario. Numerous methods have been proposed for the design of phase I drug combination trials. For example, the two-dimensional Bayesian optimal interval design for combination drug (BOINcomb) is simple to implement and has desirable performance. However, in scenarios where the lowest and starting dose is close to being toxic, the BOINcomb design may tend to allocate more patients to overly toxic doses, and select an overly toxic dose combination as the maximum tolerated dose combination. METHOD: To improve the performance of BOINcomb in the above extreme scenarios, we widen the range of variation of the boundaries by setting the self-shrinking dose escalation and de-escalation boundaries. We refer to the new design as adaptive shrinking Bayesian optimal interval design for combination drug (asBOINcomb). We conduct a simulation study to evaluate the performance of the proposed design using a real clinical trial example. RESULTS: Our simulation results show that asBOINcomb is more accurate and stable than BOINcomb, especially in some extreme scenarios. Specifically, in all ten scenarios, the percentage of correct selection is higher than the BOINcomb design within 30 to 60 patients. CONCLUSION: The proposed asBOINcomb design is transparent and simple to implement and can reduce the trial sample size while maintaining accuracy compared with the BOINcomb design.

Hepatotoxicity in immune checkpoint inhibitors: A pharmacovigilance study from 2014-2021.

Adverse events(AEs) related to hepatotoxicity have been reported in patients treated with immune checkpoint inhibitors (ICIs). As the number of adverse events increases, it is necessary to assess the differences in each immune checkpoint inhibitor regimen. The purpose of this study was to examine the relationship between ICIs and hepatotoxicity in a scientific and systematic manner. Data were obtained from the FDA Adverse Event Reporting System database (FAERS) and included data from the first quarter of 2014 to the fourth quarter of 2021. Disproportionality analysis assessed the association between drugs and adverse reactions based on the reporting odds ratio (ROR) and information components (IC). 9,806 liver adverse events were reported in the FAERS database. A strong signal was detected in older patients (≥65 years) associated with ICIs. hepatic adverse events were most frequently reported with Nivolumab (36.17%). Abnormal liver function, hepatitis, and autoimmune hepatitis were most frequently reported, and hepatitis and immune-mediated hepatitis signals were generated in all regimens. In clinical use, patients should be alert to these adverse effects, especially in elderly patients, who may be aggravated by the use of ICI.

Hepatobiliary calculi associated with ceftriaxone treatment: An analysis of FAERS data from 2004 to 2021.

INTRODUCTION: The role of gender, age, dose and other factors in the adverse reaction process of pseudocholelithiasis caused by ceftriaxone is controversial. In this study, we further explored potential risk factors using the FAERS database. METHODS: The reported odds ratio (ROR) and the information component (IC) of specific candidate factors were calculated by using the ROR method and the Bayesian confidence promotion neural network (BCPNN) method respectively to detect potential risk factors in adverse events(AEs) of ceftriaxone and hepatobiliary calculi(HBC). One candidate factor will be considered as a suspicious signal, or potential risk factors if its lower limit of 95% confidence interval of ROR (ROR025) is greater than 1 and its lower limit of 95% confidence interval of IC (IC025) is greater than 0. RESULTS: A total of 764 AEs of HBC were used to this analysis to evaluate candidate risk factors: Age group, Gender, Dose. Child (1-12 years): male ROR025 = 6.64, IC025 = 2.42, female ROR025 = 6.66, IC025 = 2.40. Adolescent group (12-18 years): male ROR025 = 5.47, IC025 = 2.08; elderly (≥65 years): female ROR025 = 1.25, IC025 = 0.22. CONCLUSIONS: Gender was not detected as a risk factor for HBC caused by ceftriaxone. However, Male infants, male children, female children, adolescent male, and elderly female were potential risk factors for HBC caused by ceftriaxone based on criteria ROR025 > 1 and IC025 > 0.

Dermatologic toxicities in epidermal growth factor receptor: a comprehensive pharmacovigilance study from 2013 to 2023.

Epidermal growth factor receptor inhibitors (EGFRIs) induced cutaneous toxicity is a common adverse event (AE), although it is not as severe as major cancers, we still need to pay enough attention to them. Therefore, it is necessary to evaluate the diversity of EGFRI class drugs. The objective of this study was to conduct a scientific and systematic investigation into the correlation between EGFRI and cutaneous toxicities. The data accessed from the FDA adverse event reporting system database (FAERS) encompass a time frame spanning from January 2013 to March 2023. By utilizing reporting odds ratios (RORs), information components (ICs), proportional reporting ratios (PRRs), and chi-squared (χ2), the relationship between drugs and adverse reactions was evaluated through disproportionality analysis. Within the FAERS database, a total of 29,559 skin adverse events were recorded. A robust indication of the correlation between EGFRI and elderly patients (≥65 years) was identified. Among EGFRIs, erlotinib accounted for the largest proportion of skin adverse events (39.72%). Rash, dry skin, and pruritus ranked top among all preferred terms, and signals such as rash, skin lesions, and acneiform dermatitis were detected in every single drug. Clinicians should guide patients customize the treatment plan for each patient.

Benefits and Risks Associated with Low-Dose Aspirin Use for the Primary Prevention of Cardiovascular Disease: A Systematic Review and Meta-Analysis of Randomized Control Trials and Trial Sequential Analysis.

BACKGROUND: The role of aspirin in cardiovascular primary prevention remains controversial. Moreover, evidence for the potential benefits of aspirin in patients with high cardiovascular risk remains limited. OBJECTIVE: The aim of this study was to explore the role of low-dose aspirin in primary prevention. METHODS: The PubMed, EMBASE, Cochrane Library, and ClinicalTrials.gov databases were searched for randomized clinical trials (RCTs) from the date of inception to August 2021. The efficacy outcomes were major adverse cardiovascular events (MACE), myocardial infarction (MI), ischemic stroke (IS), all-cause mortality, and cardiovascular mortality, whereas safety outcomes were major bleeding, intracranial hemorrhage, and gastrointestinal (GI) bleeding. Subgroup analyses were based on different cardiovascular risks and diabetes statuses. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using the fixed- and random-effects models, and trial sequential analysis (TSA) was conducted to determine the robustness of the results. RESULTS: A total of 10 RCTs fulfilled the inclusion criteria. The use of aspirin was associated with a significant reduction in the risk of MACE (RR 0.89, 95% CI 0.84-0.93), MI (RR 0.86, 95% CI 0.78-0.95), and IS (RR 0.84, 95% CI 0.76-0.93); however, aspirin also increased the risk of safety outcomes, i.e. major bleeding (RR 1.42, 95% CI 1.26-1.60), intracranial hemorrhage (RR 1.33, 95% CI 1.11-1.59), and GI bleeding (RR 1.91, 95% CI 1.44-2.54). Subgroup analyses revealed that in the absence of a statistically significant interaction, a trend toward a net benefit of lower incidence of cardiovascular events (number needed to treat of MACE: high risk: 682 vs. low risk: 2191) and lesser risk of bleeding events (number needed to harm of major bleeding: high risk: 983 vs. low risk: 819) was seen in the subgroup of high cardiovascular risk. Meanwhile, the greater MACE reduction was also detected in the high-risk group of diabetes or nondiabetes patients. Furthermore, a post hoc subgroup analysis indicated a significant rate reduction in patients aged ≤ 70 years but not in patients aged > 70 years. TSA confirmed the benefit of aspirin for MACE up to a relative risk reduction of 10%. CONCLUSION: The current study demonstrated that the cardiovascular benefits of low-dose aspirin were equally balanced by major bleeding events. In addition, the potential beneficial effects might be seen in the population ≤ 70 years of age with high cardiovascular risk and no increased risk of bleeding.

The Material Basis and Mechanism of Xuefu Zhuyu Decoction in Treating Stable Angina Pectoris and Unstable Angina Pectoris.

METHODS: Firstly, we used a network proximity approach to calculate and compare the effectiveness of the formula with that of Western drugs for each type of angina, including all targets and intersecting targets, from a topological perspective. Secondly, we compared the mechanisms of action of the two angina pectoris at three levels and five aspects, including conventional and modular analysis approaches. Thirdly, based on the unique functions of each angina in the complex heterogeneous network, we designed a reverse process for finding the material basis using dynamic, static, and enriched items as well as a total item. Finally, the designed inverse process, material basis, and mechanism of action were validated. RESULTS: The target network of Xuefu Zhuyu decoction is closer to the target network of each type of angina than that of Western drugs, and the intersection targets have a closer proximity. Comparison of the mechanisms of action showed that stable angina and unstable angina had 158 common targets, while the unique targets were 34 and 1, respectively. Modularity analysis showed that the GO similarity of target modules was highly correlated with KEGG similarity. We ended up with 67 compounds upregulated for stable angina and 47 compounds upregulated for unstable angina. Our results were validated by literature mining, high-volume molecular docking, and miRNA enrichment analysis. CONCLUSIONS: For both types of angina pectoris, Xuefu Zhuyu decoction is superior to Western drugs. A comparison of various aspects led to the unique mechanisms of action, from which the material basis of each type of angina was deduced.

A Complex Heterogeneous Network Model of Disease Regulated by Noncoding RNAs: A Case Study of Unstable Angina Pectoris.

MicroRNAs (miRNAs) are important types of noncoding RNAs, and there is a lack of holistic and systematic understanding of the functions they play in disease. We proposed a research strategy, including two parts network analysis and network modelling, to analyze, model, and predict the regulatory network of miRNAs from a network perspective, using unstable angina pectoris as an example. In the network analysis section, we proposed the WGCNA & SimCluster method using both correlation and similarity to find hub miRNAs, and validation on two datasets showed better results than the methods using correlation or similarity alone. In the network modelling section, we used six knowledge graph or graph neural network models for link prediction of three types of edges and multilabel classification of two types of nodes. Comparative experiments showed that the RotatE model was a good model for link prediction, while the RGCN model was the best model for multilabel classification. Potential target genes were predicted for hub miRNAs and validation of hub miRNA-target gene interactions, target genes as biomarkers and target gene functions were performed using a three-step validation approach. In conclusion, our study provides a new strategy to analyze and model miRNA regulatory networks.

Nephrotoxicity of Immune Checkpoint Inhibitors: A Disproportionality Analysis from 2013 to 2020.

Nephrotoxicity occasionally occurs during treatment with immune checkpoint inhibitors (ICIs). Few related studies compare the differences between these drugs. This study aimed to systematically characterize nephrotoxicity after ICI initiation. Data were extracted from the US FDA Adverse Event Reporting System (FAERS) database. Disproportionality analysis, including information components (ICs) and reporting odds ratios (RORs), was performed to determine the potential renal toxicity of ICIs. A total of 7,204 reports of renal adverse events (AEs) were identified in the FAERS database. Renal AEs were most commonly reported for nivolumab (46.84%). Strong signals were detected in male patients combined with ICIs. In the clinical application of ICIs, attention should be paid to patients, especially male patients, with acute kidney injury, nephritis, autoimmune nephritis and other nephrotoxic AEs. The use of ICIs is likely to aggravate their condition.

Development of an LC-MS/MS method for simultaneous quantitative analysis of macromolecular pharmaceutical adjuvant 2-hydroxypropyl-ß-cyclodextrin and active pharmaceutical ingredients butylphthalide in rat plasma.

Hydroxypropyl-ß-cyclodextrin, which possesses a high water solubility and low hemolycity, is widely used as a solubilizer and an excipient. It had also been reported that hydroxypropyl-ß-cyclodextrin has the activity of regulating lipid homeostasis. In order to further understand the metabolism, the primary focus was to establish a quantitative method for hydroxypropyl-ß-cyclodextrin. The analytes were extracted from plasma by protein precipitation with methanol and then carried out on a Waters CORTECS T3 column in the gradient elution of pure water and methanol. Finally, liquid chromatography-tandem mass spectrometry was applied in multiple reaction monitoring mode to complete the quantitative analysis of hydroxypropyl-ß-cyclodextrin. This validated method had been successfully applied to investigate the interaction between hydroxypropyl-ß-cyclodextrin and butylphthalide in vivo by optimizing the extraction reagent, simplifying the experimental procedure, and improving the sensitivity while considering the difference of drug chemical properties. Results showed that the inclusion of hydroxypropyl-ß-cyclodextrin with butylphthalide significantly improved the pharmacokinetic behavior of free body hydroxypropyl-ß-cyclodextrin and 3-n-butylphthalide in vivo. It had been implied that the metabolism of hydroxypropyl-ß-cyclodextrin and the drug active ingredients could impact each other. It will help better application of hydroxypropyl-ß-cyclodextrin and the developed method might lay the foundation for development of hydroxypropyl-ß-cyclodextrin as a treatment drug for brain diseases.

A systematic strategy for uncovering quality marker of Asari Radix et Rhizoma on alleviating inflammation based chemometrics analysis of components.

Asari Radix et Rhizoma (Asarum), a traditional Chinese medicine (TCM), has been applied in clinical generally. However, due to the lack of valid methods for Asarum quality control, inhomogenous quality and therapy issues have become severe with each passing day. In this study, we aimed to establish a comprehensive multi-system to explore the quality control markers underlying pharmaceutical effects based on chemometrics analysis on the total ingredients of Asarum. In brief, DNA barcoding technology was used to screen out the unadulterated herbs in the 15 batches Asarum collected from different origins. Then, the chemical profiles of volatile/nonvolatile components of 10 batches Asarum with definite resource were obtained by HPLC Q-TOF/MS and GC/MS. Combination with chemometrics methods, 14 characteristic ingredients and 4 qualitative and quantitative markers were figured out preliminarily. Moreover, correlation analysis between the characteristic ingredients and the cytokines integrating the virtual targets prediction of network pharmacology, 3 potential bioactive substance were ascertained. In conclusion, l-asarinin, 2-Methoxy-4-vinylphenol and safrole were considered as the potent candidates for quality control markers based on the comprehensive understanding for therapeutic effects and the chemical information of Asarum, which provided a novel perspective of the development for the quality control of TCM.

"Modeling-Prediction" Strategy for Deep Profiling of Lysophosphatidic Acids by Liquid Chromatography-Mass Spectrometry: Exploration Biomarkers of Breast Cancer.

Lysophosphatidic acids (LPAs) are important bioactive phospholipids consisting of various species involved in a wide array of physiological and pathological processes. However, LPAs were rarely identified in untargeted lipidomics studies because of the incompatibility with analytical methods. Moreover, in targeted studies, the coverages of LPAs remained unsatisfactorily low due to the limitation of reference standards. Herein, a "modeling-prediction" workflow for deep profiling of LPAs by liquid chromatography-mass spectrometry was developed. Multiple linear regression models of qualitative and quantitative parameters were established according to features of fatty acyl tails of the commercial standards to predict the corresponding parameters for unknown LPAs. Then 72 multiple reaction monitoring (MRM) transitions were monitored simultaneously and species of LPA 14:0, LPA 16:1, LPA 18:3, LPA 20:3 and LPA 20:5 were firstly characterized and quantified in plasma. Finally, the workflow was applied to explore the changes of LPAs in plasma of breast cancer patients compared with healthy volunteers. Multi-LPAs indexes with strong diagnostic ability for breast cancer were identified successfully using Student's t- test, orthogona partial least-squares discrimination analysis (OPLS-DA) and logistic regression- receiver operating characteristic (ROC) curve analysis. The proposed workflow with high sensitivity, high accuracy, high coverage and reliable identification would be a powerful complement to untargeted lipidomics and shed a light on the analysis of other lipids.

An integrated serum and urinary metabonomic research of Rhizoma Curcumae-Rhizoma Sparganii drug pair in hysteromyoma rats based on UPLC-Q-TOF-MS analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Rhizoma Curcumae and Rhizoma Sparganii (RCRS), a celebrated traditional Chinese medicine drug pair, has been used to treat hysteromyoma (HY). AIM OF THE STUDY: We aimed to identify the endogenous biomarkers of RCRS against HY. MATERIALS AND METHODS: HY rat model was established by injecting intramuscularly estradiol benzoate and progesterone injection from inner thigh in sequence. Body weight, uterus morphological indexes, immunohistochemistry (IHC) and hematoxylin and eosin (HE) staining experiments were used to evaluate the efficacy of RCRS (The rats were treated with RCRS extract, which was made by soxhlet reflux method. The rats were administrated intragastrically with 2 mL of RCRS extract). UPLC-Q-TOF-MS based metabonomics was adopted to analyze the serum and urine biomarkers from HY rats before and after RCRS treatment. Principle component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were utilized to identify differences of metabolic profiles in rats among the four groups. RESULTS: 16 potential biomarkers from serum and 18 potential biomarkers from urine in both positive and negative mass spectrometry detection modes were identified, primarily related to Linoleic acid metabolism and Glyoxylate and dicarboxylate metabolism. RCRS drug pair has therapeutic effects on rats with HY via the regulation of multiple metabolic pathways. CONCLUSIONS: This study provides a useful method to get insight into the integrated metabonomic mechanism of RCRS drug pair on HY rats.

Quantitative metabolomics for investigating the value of polyamines in the early diagnosis and therapy of colorectal cancer.

As an important biomarker for cancer, polyamine levels in body fluid could be employed for monitoring the colorectal cancer (CRC), however the role of polyamines in the development and therapeutics phases of CRC remains uncertain. In this paper, the relationship between polyamines and CRC development and therapeutics had been investigated by the study of changes in plasma polyamine levels during the precancerous, developmental and treatment phases of CRC. After inducing CRC in Wistar rats by intraperitoneal injection of 1, 2-dimethylhydrazine, the animals were given a traditional Chinese medicine, Aidi injections. Firstly, the polyamine levels in the plasma of CRC, healthy and medicated rats were measured by UHPLC-MS/MS assay. In addition, Lasso regression analysis was used for screening and confirming the key markers, which can be employed for distinguishing the healthy and CRC rats as well as the CRC and medication rats. The results obtained showed that polyamine metabolism had been disrupted by CRC but returned to normal levels following Aidi injections and, in particular, putrescine and agmatine were closely correlated with CRC. Our results demonstrate the potential value of plasma polyamine metabolic profiling during the early diagnosis and medical treatment of CRC. Also, the integrated method of polyamine metabolite target analysis and lasso regression analysis can be applied in metabolomics for seeking the differential metabolites.

GC-MS method for determination and pharmacokinetic study of seven volatile constituents in rat plasma after oral administration of the essential oil of Rhizoma Curcumae.

Rhizoma Curcumae (RC) is perennial herbaceous plant mainly present in China, India and Malaysiabelong, which is belong to the family Zingiberaceae. The rhizomes of RC have been used as a famous traditional Chinese medicine for the treatment of syndrome of blood stasis. A selective, sensitive and accurate gas chromatography-mass spectroscopy (GC-MS) method was developed and validated in this paper for the simultaneous determination and pharmacokinetic study of α-Pinene, 1,8-Cineole, Borneol, ß-Elemene, Curcumol, Germacrone, and Curdione in rat plasma. The GC-MS system was operated under selected ion monitoring (SIM) mode using a DB-5 (30m×0.25mm (ID)×0.25µm (film thickness)) column. Linearity, intra-day and inter-day precisions, accuracy, extraction recovery and stability were used to validate the current GC/MS assay. The lowest limit of quantifications (LLOQ) of α-Pinene, 1,8-Cineole, Borneol, ß-Elemene, Curcumol, Germacrone, Curdione were 2.71ng/mL, 7.76ng/mL, 3.37ng/mL, 21.68ng/mL, 40.21ng/mL, 24.84ng/mL and 47.78ng/mL respectively. After oral administration 1.0g/kg of RC rhizomes to the rats, the maximum plasma concentration (Cmax) was 34.72±9.97ng/mL for α-Pinene, 99.86±5.54ng/mL for 1,8-Cineole, 16.10±3.37ng/mL for Borneol, 248.98±86.19ng/mL for ß-Elemene, 673.75±104.15ng/mL for Curcumol, 2353.64±637.83ng/mL for Germacrone and 2420.04±708.51ng/mL for Curdione. The time to reach the maximum plasma concentration (Tmax) was 2.33±0.29h for α-Pinene, 0.67±0.29h for 1,8-Cineole, 1.33±0.58h for Borneol, 1.83±0.76h for ß-Elemene, 0.83±0.29h for Curcumol, 0.89±0.98h for Germacrone and 1.17±0.76h for Curdione. In this study, a validated GC-MS method for simultaneous determination of seven volatile oil compounds in rat plasma after oral administration of the extract of RC rhizomes and research on their pharmacokinetics was validated. The recovery and stability results were satisfactory in this study.

An integrative investigation of the toxicity of Aconiti kusnezoffii radix and the attenuation effect of its processed drug using a UHPLC-Q-TOF based rat serum and urine metabolomics strategy.

Aconiti kusnezoffii radix (AKR), the root of Aconitum kusnezoffii Reichb., is commonly used in the treatment of the rheumatoid arthritis. However, the clinical application is limited due to its potential toxicity. Therefore, to investigate the mechanism of its potential neurotoxicity and nephrotoxicity, a comprehensive metabolomics study combined with serum biochemistry and histopathology measurements was carried out. A UHPLC-Q-TOF mass spectrometry based metabolomics approach was applied to characterize the AKR toxicity, while the toxicity attenuation effects of Aconiti kusnezoffii radix cocta (AKRC) on Wistar rats were also investigated. Two chromatographic techniques involving reversed-phase chromatography and hydrophilic interaction chromatography were combined for the serum and urine detection, which balanced the integrity and selectivity of the two matrices. Principal component analysis was used to determine the groups, and principal component analysis discriminant analysis was carried out to confirm the important variables. Then, the developed integrative toxicity evaluation method was applied to assess the toxicity of AKR and the attenuation effect of AKRC. The highly sensitive and specific toxic biomarkers, which can provide practical bases were identified for the diagnosis of the neurotoxicity and nephrotoxicity induced by AKR. In all, a total of 19 putative biomarkers were characterized, and related metabolic pathways were identified. The study demonstrated that the established metabolomics strategy is a powerful approach for investigating the mechanisms of herbal toxicity and the attenuation effect of a processing method and would provide medical solutions for other toxic herbal medications and further clinical evidence on how AKR improves symptoms of rheumatoid arthritis patients.

An Investigation on the Quantitative Structure-Activity Relationships of the Anti-Inflammatory Activity of Diterpenoid Alkaloids.

Diterpenoid alkaloids are extracted from plants. These compounds have broad biological activities, including effects on the cardiovascular system, anti-inflammatory and analgesic actions, and anti-tumor activity. The anti-inflammatory activity was determined by carrageenan-induced rat paw edema and experimental trauma in rats. The number of studies focused on the determination, quantitation and pharmacological properties of these alkaloids has increased dramatically during the past few years. In this work we built a dataset composed of 15 diterpenoid alkaloid compounds with diverse structures, of which 11 compounds were included in the training set and the remaining compounds were included in the test set. The quantitative chemistry parameters of the 15 diterpenoid alkaloids compound were calculated using the HyperChem software, and the quantitative structure-activity relationship (QSAR) of these diterpenoid alkaloid compounds were assessed in an anti-inflammation model based on half maximal effective concentration (EC50) measurements obtained from rat paw edema data. The QSAR prediction model is as follows: log ( E C 50 ) = - 0.0260 × SAA + 0.0086 × SAG + 0.0011 × VOL - 0.0641 × HE - 0.2628 × LogP - 0.5594 × REF - 0.2211 × POL - 0.1964 × MASS + 0.088 × BE + 0.1398 × HF (R² = 0.981, Q² = 0.92). The validated consensus EC50 for the QSAR model, developed from the rat paw edema anti-inflammation model used in this study, indicate that this model was capable of effective prediction and can be used as a reliable computational predictor of diterpenoid alkaloid activity.