Chitosan/hesperidin nanoparticles formulation: a promising approach against ethanol-induced gastric ulcers via Sirt1/FOXO1/PGC-1α/HO-1 pathway.

Hesperidin (Hes) protects different organs from damage by acting as a potent antioxidant and anti-inflammatory. This study aims to evaluate the gastroprotective effects of free hesperidin and its chitosan nanoparticles (HNPs) against ethanol-induced gastric ulcers in rats, hypothesizing that HNPs will enhance bioavailability and therapeutic efficacy due to improved solubility and targeted delivery. HNPs were synthesized via ion gelation and characterized using TEM, SEM, and zeta potential analyses. Key assessments included gastric acidity, histological analysis, and markers of inflammation, oxidative stress, and apoptosis. HNPs significantly decreased gastric acidity, reduced inflammatory and apoptotic markers, and enhanced antioxidant enzyme activities compared to free hesperidin and esomeprazole. Furthermore, Sirt-1, PGC-1α, HO-1, and FOXO1 gene expression were also evaluated. HNPs raised Sirt-1, PGC-1α, HO-1, and downregulated FOXO1, and they suppressed the activities of NF-κB p65, COX-2, IL-1ß, CD86, FOXO1 P53, and caspase-3 and increased Sirt-1 activity. HNPs treatment notably restored antioxidant enzyme activity, reduced oxidative stress and inflammatory markers, and improved histological outcomes more effectively than free hesperidin and esomeprazole. These results indicate that chitosan nanoparticles significantly enhance the gastroprotective effects of hesperidin against ethanol-induced gastric ulcers, potentially offering a more effective therapeutic strategy. Further research should explore the clinical applications of HNPs in human subjects.

In vitro ADME, mouse pharmacokinetics of LD14b, and bioanalysis of a novel aß 17ß-HSD10 modulator for the treatment of Alzheimer's disease.

LD14b is an amyloid-ß (Aß) 17ß-hydroxysteroid dehydrogenase type 10 (Aß-17ß-HSD10) protein-protein interaction modulator that shows promising in vitro and ex vivo activity to rescue Aß-induced mitochondrial dysfunction, Aß-induced toxicity, and Aß-mediated inhibition of estradiol synthesis.The current study investigated in vitro human S9 fractions metabolic stability, apparent permeability, human and mouse plasma protein binding, in vivo pharmacokinetics, and tissue distribution in Balb/cJ mice. A fast (8-min), sensitive, reliable, and reproducible LC-MS/MS method was developed and validated over the dynamic range of 1-1000 ng/mL for the quantification of LD14b in different biological matrices (plasma, liver, kidney, brain, lungs, heart).LD14b was metabolically stable in human liver S9 fractions with 70% remaining after 90 minutes of incubation, showed intermediate apparent permeability of 3.55 × 10-06 cm/s and 6.16 × 10-06 cm/s for apical-to-basolateral (A-to-B) and basolateral-to-apical (B-to-A), respectively across the Caco-2 monolayer, and was medium/highly bound to human plasma proteins (84.1%), mouse plasma proteins (85.7%), and mouse brain homogenate (95.4%).LD14b showed an in vivo predicted % absorption of 52% in Balb/cJ mice and was well-distributed to the peripheral tissues (liver, kidney, lungs, and heart) including the brain.

Recent advancements toward the incremsent of drug solubility using environmentally-friendly supercritical CO2: a machine learning perspective.

Inadequate bioavailability of therapeutic drugs, which is often the consequence of their unacceptable solubility and dissolution rates, is an indisputable operational challenge of pharmaceutical companies due to its detrimental effect on the therapeutic efficacy. Over the recent decades, application of supercritical fluids (SCFs) (mainly SCCO2) has attracted the attentions of many scientists as promising alternative of toxic and environmentally-hazardous organic solvents due to possessing positive advantages like low flammability, availability, high performance, eco-friendliness and safety/simplicity of operation. Nowadays, application of different machine learning (ML) as a versatile, robust and accurate approach for the prediction of different momentous parameters like solubility and bioavailability has been of great attentions due to the non-affordability and time-wasting nature of experimental investigations. The prominent goal of this article is to review the role of different ML-based tools for the prediction of solubility/bioavailability of drugs using SCCO2. Moreover, the importance of solubility factor in the pharmaceutical industry and different possible techniques for increasing the amount of this parameter in poorly-soluble drugs are comprehensively discussed. At the end, the efficiency of SCCO2 for improving the manufacturing process of drug nanocrystals is aimed to be discussed.

Theoretical investigations on modeling blood flow through vessel for understanding effectiveness of magnetic nanocarrier drug delivery systems.

For cancer therapy, the focus is now on targeting the chemotherapy drugs to cancer cells without damaging other normal cells. The new materials based on bio-compatible magnetic carriers would be useful for targeted cancer therapy, however understanding their effectiveness should be done. This paper presents a comprehensive analysis of a dataset containing variables x(m), y(m), and U(m/s), where U represents velocity of blood through vessel containing ferrofluid. The effect of external magnetic field on the fluid flow is investigated using a hybrid modeling. The primary aim of this research endeavor was to construct precise and dependable predictive models for velocity, utilizing the provided input variables. Several base models, including K-nearest neighbors (KNN), decision tree (DT), and multilayer perceptron (MLP), were trained and evaluated. Additionally, an ensemble model called AdaBoost was implemented to further enhance the predictive performance. The hyper-parameter optimization technique, specifically the BAT optimization algorithm, was employed to fine-tune the models. The results obtained from the experiments demonstrated the effectiveness of the proposed approach. The combination of the AdaBoost algorithm and the decision tree model yielded a highly impressive score of 0.99783 in terms of R2, indicating a strong predictive performance. Additionally, the model exhibited a low error rate, as evidenced by the root mean square error (RMSE) of 5.2893 × 10-3. Similarly, the AdaBoost-KNN model exhibited a high score of 0.98524 using R2 metric, with an RMSE of 1.3291 × 10-2. Furthermore, the AdaBoost-MLP model obtained a satisfactory R2 score of 0.99603, accompanied by an RMSE of 7.1369 × 10-3.

Structural, mechanical, barrier and antioxidant properties of pectin and xanthan gum edible films loaded with grapefruit essential oil.

This research focused on the development of films based on pectin and xanthan gum composite loaded with different concentrations of grapefruit essential oil (GFO). The fabricated films were characterized to assess the effect of GFO on the structural, mechanical, barrier, chemical, and antioxidant properties. The addition of GFO enhanced the functional properties of the films, as confirmed by FTIR analysis showing molecular interactions within the film matrix. SEM observations revealed that films with higher GFO content had a smoother, more compact structure with uniform oil distribution. Films loaded with oil demonstrated enhanced water resistance, as their decreased permeability ranged from 0.733 ± 0.009 to 0.561 ± 0.020 (g mm)/(m2.h.kPa). Additionally, these films showed a notable increase in tensile strength, ranging from 2.91 ± 0.19 to 8.55 ± 0.62 MPa. However, the addition of oil led to a reduction in the elongation at break of the films, which decreased from 52.84 ± 3.41 % to 12.68 ± 1.52 %, and a decline in transparency from 87.57 ± 0.65 % to 76.18 ± 1.12 %. Fabricated films exhibited enhanced antioxidant properties, as evidenced by increased DPPH• and ABTS•+ radical scavenging activities with the addition of GFO. The findings of the current study suggest that GFO is an effective natural additive for enhancing the physiochemical properties of pectin and xanthan gum-based films, making them more suitable for food packaging applications.

Fabrication of Nanocrystals for Enhanced Distribution of a Fatty Acid Synthase Inhibitor (Orlistat) as a Promising Method to Relieve Solid Ehrlich Carcinoma-Induced Hepatic Damage in Mice.

BACKGROUND: Orlistat (ORL) is an effective irreversible inhibitor of the lipase enzyme, and it possesses anticancer effects and limited aqueous solubility. This study was designed to improve the aqueous solubility, oral absorption, and tissue distribution of ORL via the formulation of nanocrystals (NCs). METHODS: ORL-NC was prepared using the liquid antisolvent precipitation method (bottom-up technology), and it demonstrated significantly improved solubility compared with that of the blank crystals (ORL-BCs) and untreated ORL powder. The biodistribution and relative bioavailability of ORL-NC were investigated via the radiolabeling technique using Technetium-99m (99mTc). Female Swiss albino mice were used to examine the antitumor activity of ORL-NC against solid Ehrlich carcinoma (SEC)-induced hepatic damage in mice. RESULTS: The prepared NCs improved ORL's solubility, bioavailability, and tissue distribution, with evidence of 258.70% relative bioavailability. In the in vivo study, the ORL-NC treatment caused a reduction in all tested liver functions (total and direct bilirubin, AST, ALT, and ALP) and improved modifications in liver sections that were marked using hematoxylin and eosin staining (H&E) and immunohistochemical staining (Ki-67 and ER-α) compared with untreated SEC mice. CONCLUSIONS: The developed ORL-NC could be considered a promising formulation approach to enhance the oral absorption tissue distribution of ORL and suppress the liver damage caused by SEC.

Appropriateness of anticoagulation level in older adult patients on Warfarin: A multicenter retrospective study.

Warfarin is favored over newer direct oral anticoagulants (DOACs) for many older adults. However, its use necessitates rigorous monitoring due to the fine line between toxic and therapeutic doses. Few studies have evaluated the anticoagulation quality of warfarin among elderly patients in Saudi Arabia. This study aimed to assess and identify factors affecting the anticoagulation quality of warfarin using the time in the therapeutic range (TTR) among older adults attending two hospitals in Saudi Arabia. Additionally, we aimed to evaluate differences in the anticoagulation quality of warfarin when managed by pharmacists or physicians. This cross-sectional study was conducted at King Abdullah bin Abdulaziz University Hospital (KAAUH) and King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia. After calculating the TTR of each patient, the anticoagulation control level was determined using these values: a) good control: >70 %; b) intermediate control: 50-70 %; c) poor control: <50 %. A total of 132 patients prescribed warfarin therapy for different indications were included. Most patients (45.5 %) had poor control with TTRs < 50 %, while 18.2 % had intermediate control, and 36.4 % had good control. Our exploratory findings suggest that having three or more comorbidities was a significant factor associated with a poor TTR [odds ratio (OR) = 3.36; (95 % confidence interval 1.28-8.81); P = 0.014]. Thus, the anticoagulation quality of warfarin among older adult patients was poor in two Saudi Arabian tertiary hospitals, and the number of comorbidities was a potentially poor TTR predictor.

Anticancer potentials of metformin loaded coconut oil nanoemulsion on MCF-7, HepG2 and HCT-116 cell lines.

In order to load metformin in a nano formula and evaluate the produced nano form towards cancer cells, metformin was loaded on natural carrier coconut oil. The formed metformin-loaded coconut oil nanoemulsion was characterized by Zeta potential, particle size, drug content, drug release, and drug stability. The formed nanoemulsion was evaluated towards MCF-7, HepG2, and HCT-116 cell lines. Cell cycle analysis and apoptosis mechanism were studied. The nanoemulsion was created using deionized water, 1.5% Span 20, 1.5% Tween 80, 1.5% coconut oil, and 0.5% Metformin in an ultrasonicator to produce a homogenous solution. The anticancer activities of the metformin-loaded coconut nanoemulsion were highly improved compared to non-formulated metformin with IC50s of 8.3 ± 0.1 µg/ml, 12 ± 1.5 µg/ml, 2.685 ± 0.3 µg/ml for MCF-7, HepG2, and HCT-116 cell lines, respectively. There was a 76.5 ± 2.3 and 78.3 ± 3.2% increase in the number of apoptotic cells of MCF-7 and HepG2 cells after nanoemulsion treatment. This formula may be considered a new anticancer medication.

Fabrication, assessment, and optimization of alendronate sodium nanoemulsion-based injectable in-situ gel formulation for management of osteoporosis.

Low bone mass, degeneration of bone tissue, and disruption of bone microarchitecture are all symptoms of the disease osteoporosis, which can decrease bone strength and increase the risk of fractures. The main objective of the current study was to use a phospholipid-based phase separation in-situ gel (PPSG) in combination with an alendronate sodium nanoemulsion (ALS-NE) to help prevent bone resorption in rats. The effect of factors such as concentrations of the ALS aqueous solution, surfactant Plurol Oleique CC 497, and Maisine CC oil on nanoemulsion characteristics such as stability index and globular size was investigated using an l-optimal coordinate exchange statistical design. Injectable PPSG with the best nanoemulsion formulation was tested for viscosity, gel strength, water absorption, and in-vitro ALS release. ALS retention in the rats' muscles was measured after 30 days. The droplet size and stability index of the optimal nanoemulsion were 90 ± 2.0 nm and 85 ± 1.9%, respectively. When mixed with water, the optimal ALS-NE-loaded PPSG became viscous and achieved 36 seconds of gel strength, which was adequate for an injectable in-situ formulation. In comparison with the ALS solution-loaded in-situ gel, the newly created optimal ALS-NE-loaded PPSG produced the sustained and regulated release of ALS; hence, a higher percentage of ALS remained in rats' muscles after 30 days. PPSG that has been loaded with an ALS-NE may therefore be a more auspicious, productive, and effective platform for osteoporosis treatment than conventional oral forms.

Application of CO2 Supercritical Fluid to Optimize the Solubility of Oxaprozin: Development of Novel Machine Learning Predictive Models.

Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO2) for particle engineering. SCCO2 has great potential for application as a green and eco-friendly technique to reach small crystalline particles with narrow particle size distribution. In this paper, an artificial intelligence (AI) method has been used as an efficient and versatile tool to predict and consequently optimize the solubility of oxaprozin in SCCO2 systems. Three learning methods, including multi-layer perceptron (MLP), Kriging or Gaussian process regression (GPR), and k-nearest neighbors (KNN) are selected to make models on the tiny dataset. The dataset includes 32 data points with two input parameters (temperature and pressure) and one output (solubility). The optimized models were tested with standard metrics. MLP, GPR, and KNN have error rates of 2.079 × 10-8, 2.173 × 10-9, and 1.372 × 10-8, respectively, using MSE metrics. Additionally, in terms of R-squared, they have scores of 0.868, 0.997, and 0.999, respectively. The optimal inputs are the same as the maximum possible values and are paired with a solubility of 1.26 × 10-3 as an output.

Fabrication and Evaluation of W/O Emulsion Loaded with Linum usitatissimum Seeds Extract for Anti-Leishmaniasis Efficacy.

Leishmaniasis, remains a serious health problem in many developing countries with thousands of new cases recorded annually. Novel therapies are required as existing treatment regimens are limited by their high cost, high toxicity, increased parasite resistance, patient's intolerance, and invasive means of long-duration administration. With several studies reporting the anti-leishmaniasis promise of medicinal plants, interest in plants and herbal drugs is attracting much attention worldwide. In this pilot study, we analysed extracts of Linum usitatissimum seeds (LU) to identify essential phytochemicals and test their activity against cutaneous leishmaniasis both in-vitro and in-vivo. We performed phytochemical screening of LU seeds extract as well as its in-vitro leishmanicidal and anti-amastigote assays. Water-in-oil cream containing 10% LU crude extract (10 mg/mL) was then prepared. The stability of the cream was evaluated for 28 days at 8 °C, 25 °C and 40 °C. In-vivo efficacy and safety of the cream was performed in 26 patients with cutaneous leishmaniasis who agreed to participate voluntarily in the study. The active treatment period lasted for 3 weeks, while the follow-up period was extended to 4 months. During the active study period, images of skin lesions were taken before and after treatment. Analyses of LU seeds extract confirmed the presence of terpenoids, flavonoids, tannins, alkaloids, and polyphenols. In-vitro studies showed significant activity against promastigote and intracellular amastigote forms of Leishmaniamajor. The cream was pharmaceutically stable, although some minor changes were noticed in relation to its physical characteristics. In-vivo assessment of the cream showed a 69.23% cure rate with no side effects, allergy, or irritation. We conclude that our newly developed water in oil cream containing 10% LU seeds extract could be an effective and safe topical anti-leishmanial medication for patients with CL.

Urinary BA Indices as Prognostic Biomarkers for Complications Associated with Liver Diseases.

Hepatobiliary diseases and their complications cause the accumulation of toxic bile acids (BA) in the liver, blood, and other tissues, which may exacerbate the underlying condition and lead to unfavorable prognosis. To develop and validate prognostic biomarkers for the prediction of complications of cholestatic liver disease based on urinary BA indices, liquid chromatography-tandem mass spectrometry was used to analyze urine samples from 257 patients with cholestatic liver diseases during a 7-year follow-up period. The urinary BA profile and non-BA parameters were monitored, and logistic regression models were used to predict the prognosis of hepatobiliary disease-related complications. Urinary BA indices were applied to quantify the composition, metabolism, hydrophilicity, and toxicity of the BA profile. We have developed and validated the bile-acid liver disease complication (BALDC) model based on BA indices using logistic regression model, to predict the prognosis of cholestatic liver disease complications including ascites. The mixed BA and non-BA model was the most accurate and provided higher area under the receiver operating characteristic (ROC) and smaller akaike information criterion (AIC) values compared to both non-BA and MELD (models for end stage liver disease) models. Therefore, the mixed BA and non-BA model could be used to predict the development of ascites in patients diagnosed with liver disease at early stages of intervention. This will help physicians to make a better decision when treating hepatobiliary disease-related ascites.

Bile acid indices as biomarkers for liver diseases II: The bile acid score survival prognostic model.

BACKGROUND: Cholestatic liver diseases are characterized by an accumulation of toxic bile acids (BA) in the liver, blood and other tissues which lead to progressive liver injury and poor prognosis in patients. AIM: To discover and validate prognostic biomarkers of cholestatic liver diseases based on the urinary BA profile. METHODS: We analyzed urine samples by liquid chromatography-tandem mass spectrometry and investigated the use of the urinary BA profile to develop survival models that can predict the prognosis of hepatobiliary diseases. The urinary BA profile, a set of non-BA parameters, and the adverse events of liver transplant and/or death were monitored in 257 patients with cholestatic liver diseases for up to 7 years. The BA profile was characterized by calculating BA indices, which quantify the composition, metabolism, hydrophilicity, formation of secondary BA, and toxicity of the BA profile. We have developed and validated the bile-acid score (BAS) model (a survival model based on BA indices) to predict the prognosis of cholestatic liver diseases. RESULTS: We have developed and validated a survival model based on BA (the BAS model) indices to predict the prognosis of cholestatic liver diseases. Our results demonstrate that the BAS model is more accurate and results in higher true-positive and true-negative prediction of death compared to both non-BAS and model for end-stage liver disease (MELD) models. Both 5- and 3-year survival probabilities markedly decreased as a function of BAS. Moreover, patients with high BAS had a 4-fold higher rate of death and lived for an average of 11 mo shorter than subjects with low BAS. The increased risk of death with high vs low BAS was also 2-4-fold higher and the shortening of lifespan was 6-7-mo lower compared to MELD or non-BAS. Similarly, we have shown the use of BAS to predict the survival of patients with and without liver transplant (LT). Therefore, BAS could be used to define the most seriously ill patients, who need earlier intervention such as LT. This will help provide guidance for timely care for liver patients. CONCLUSION: The BAS model is more accurate than MELD and non-BAS models in predicting the prognosis of cholestatic liver diseases.

Bile acid indices as biomarkers for liver diseases I: Diagnostic markers.

BACKGROUND: Hepatobiliary diseases result in the accumulation of toxic bile acids (BA) in the liver, blood, and other tissues which may contribute to an unfavorable prognosis. AIM: To discover and validate diagnostic biomarkers of cholestatic liver diseases based on the urinary BA profile. METHODS: We analyzed urine samples by liquid chromatography-tandem mass spectrometry and compared the urinary BA profile between 300 patients with hepatobiliary diseases vs 103 healthy controls by statistical analysis. The BA profile was characterized using BA indices, which quantifies the composition, metabolism, hydrophilicity, and toxicity of the BA profile. BA indices have much lower inter- and intra-individual variability compared to absolute concentrations of BA. In addition, BA indices demonstrate high area under the receiver operating characteristic curves, and changes of BA indices are associated with the risk of having a liver disease, which demonstrates their use as diagnostic biomarkers for cholestatic liver diseases. RESULTS: Total and individual BA concentrations were higher in all patients. The percentage of secondary BA (lithocholic acid and deoxycholic acid) was significantly lower, while the percentage of primary BA (chenodeoxycholic acid, cholic acid, and hyocholic acid) was markedly higher in patients compared to controls. In addition, the percentage of taurine-amidation was higher in patients than controls. The increase in the non-12α-OH BA was more profound than 12α-OH BA (cholic acid and deoxycholic acid) causing a decrease in the 12α-OH/ non-12α-OH ratio in patients. This trend was stronger in patients with more advanced liver diseases as reflected by the model for end-stage liver disease score and the presence of hepatic decompensation. The percentage of sulfation was also higher in patients with more severe forms of liver diseases. CONCLUSION: BA indices have much lower inter- and intra-individual variability compared to absolute BA concentrations and changes of BA indices are associated with the risk of developing liver diseases.

Direct and indirect quantification of phosphate metabolites of nucleoside analogs in biological samples.

Nucleoside reverse transcriptase inhibitors (NRTIs) are prodrugs that require intracellular phosphorylation to active triphosphate nucleotide metabolites (NMs) for their pharmacological activity. However, monitoring these pharmacologically active NMs is challenging due to their instability, high hydrophilicity, and their low concentrations in blood and tissues. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the gold standard technique for the quantification of NRTIs and their phosphorylated NMs. In this review, an overview of the publications describing the quantitative analysis of intracellular and total tissue concentration of NMs is presented. The focus of this review is the comparison of the different approaches and challenges associated with sample collection, tissue homogenization, cell lysis, cell counting, analyte extraction, sample storage conditions, and LC-MS analysis. Quantification methods of NMs via LC-MS can be categorized into direct and indirect methods. In the direct LC-MS methods, chromatographic retention of the NMs is accomplished by ion-exchange (IEX), ion-pairing (IP), hydrophilic interaction (HILIC), porous graphitic carbon (PGC) chromatography, or capillary electrophoresis (CE). In indirect methods, parent nucleosides are 1st generated from the dephosphorylation of NMs during sample preparation and are then quantified by reverse phase LC-MS as surrogates for their corresponding NMs. Both approaches have advantages and disadvantages associated with them, which are discussed in this review.

Species differences in bile acids I. Plasma and urine bile acid composition.

Maintenance of bile acid (BA) homeostasis is essential to achieve their physiologic functions and avoid their toxic effects. The marked differences in BA composition between preclinical safety models and humans may play a major role in the poor prediction of drug-induced liver injury using preclinical models. We compared the composition of plasma and urinary BAs and their metabolites between humans and several animal species. Total BA pools and their composition varied widely among different species. Highest sulfation of BAs was observed in human and chimpanzee. Glycine amidation was predominant in human, minipig, hamster and rabbit, while taurine amidation was predominant in mice, rat and dogs. BA profiles consisted primarily of tri-OH BAs in hamster, rat, dog and mice, di-OH BAs in human, rabbit and minipig, and mono-OH BA in chimpanzee. BA profiles comprised primarily hydrophilic and less toxic BAs in mice, rat, pig and hamster, while it primarily comprised hydrophobic and more toxic BAs in human, rabbit and chimpanzee. Therefore, the hydrophobicity index was lowest in minipig and mice, while it was highest in rabbit, monkey and human. Glucuronidation and glutathione conjugation were low in all species across all BAs. Total concentration of BAs in urine was up to 10× higher and more hydrophilic than plasma in most species. This was due to the presence of more tri-OH, amidated, sulfated and primary BAs, in urine compared to plasma. In general, BA profiles of chimpanzee and monkeys were most similar to human, while minipig, rat and mice were most dissimilar to human.

Species differences in bile acids II. Bile acid metabolism.

One of the mechanisms of drug-induced liver injury (DILI) involves alterations in bile acid (BA) homeostasis and elimination, which encompass several metabolic pathways including hydroxylation, amidation, sulfation, glucuronidation and glutathione conjugation. Species differences in BA metabolism may play a major role in the failure of currently used in vitro and in vivo models to predict reliably the DILI during the early stages of drug discovery and development. We developed an in vitro cofactor-fortified liver S9 fraction model to compare the metabolic profiles of the four major BAs (cholic acid, chenodeoxycholic acid, lithocholic acid and ursodeoxycholic acid) between humans and several animal species. High- and low-resolution liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance imaging were used for the qualitative and quantitative analysis of BAs and their metabolites. Major species differences were found in the metabolism of BAs. Sulfation into 3-O-sulfates was a major pathway in human and chimpanzee (4.8%-52%) and it was a minor pathway in all other species (0.02%-14%). Amidation was primarily with glycine (62%-95%) in minipig and rabbit and it was primarily with taurine (43%-81%) in human, chimpanzee, dog, hamster, rat and mice. Hydroxylation was highest (13%-80%) in rat and mice followed by hamster, while it was lowest (1.6%-22%) in human, chimpanzee and minipig. C6-ß hydroxylation was predominant (65%-95%) in rat and mice, while it was at C6-α position in minipig (36%-97%). Glucuronidation was highest in dog (10%-56%), while it was a minor pathway in all other species (<12%). The relative contribution of the various pathways involved in BA metabolism in vitro were in agreement with the observed plasma and urinary BA profiles in vivo and were able to predict and quantify the species differences in BA metabolism. In general, overall, BA metabolism in chimpanzee is most similar to human, while BA metabolism in rats and mice is most dissimilar from human.

Quantitative analysis of endogenous compounds.

Accurate quantitative analysis of endogenous analytes is essential for several clinical and non-clinical applications. LC-MS/MS is the technique of choice for quantitative analyses. Absolute quantification by LC/MS requires preparing standard curves in the same matrix as the study samples so that the matrix effect and the extraction efficiency for analytes are the same in both the standard and study samples. However, by definition, analyte-free biological matrices do not exist for endogenous compounds. To address the lack of blank matrices for the quantification of endogenous compounds by LC-MS/MS, four approaches are used including the standard addition, the background subtraction, the surrogate matrix, and the surrogate analyte methods. This review article presents an overview these approaches, cite and summarize their applications, and compare their advantages and disadvantages. In addition, we discuss in details, validation requirements and compatibility with FDA guidelines to ensure method reliability in quantifying endogenous compounds. The standard addition, background subtraction, and the surrogate analyte approaches allow the use of the same matrix for the calibration curve as the one to be analyzed in the test samples. However, in the surrogate matrix approach, various matrices such as artificial, stripped, and neat matrices are used as surrogate matrices for the actual matrix of study samples. For the surrogate analyte approach, it is required to demonstrate similarity in matrix effect and recovery between surrogate and authentic endogenous analytes. Similarly, for the surrogate matrix approach, it is required to demonstrate similar matrix effect and extraction recovery in both the surrogate and original matrices. All these methods represent indirect approaches to quantify endogenous compounds and regardless of what approach is followed, it has to be shown that none of the validation criteria have been compromised due to the indirect analyses.