Comtrifosides A and B, two new triterpenoid saponins from the leaves of Combretum trifoliatum.

The phytochemical composition of the Combretum trifoliatum leaves was studied for the first time. Two new triterpenoid saponins, named comtrifoside A (1) and comtrifoside B (2), together with two other saponins (3-4) were purified by variously chromatographic techniques. For the first time, compound 3 was informed from the Combretum genus, as well as all of the isolated compounds (1-4) were reported from C. trifoliatum. The chemical structures of them were clearly characterised using extensive UV-VIS, IR, HRMS-ESI, and NMR experimental data. The in vitro anti-inflammatory activities of 1 & 2 were examined against NO overproduction in LPS activation of RAW264.7.

Xanthine oxidase inhibition study of isolated secondary metabolites from Dolichandrone spathacea (Bignoniaceae): In vitro and in silico approach.

Xanthine oxidase (XO) has been widely recognized as a pivotal enzyme in developing hyperuricemia, primarily contributing to the excessive production of uric acid during purine metabolism in the liver. One of the standard treatment approaches involves reducing uric acid levels by inhibiting XO activity. In this study, the leaf extract of Dolichandrone spathacea, traditionally used in folk medicine, was found to inhibit XO activity in the ethyl acetate and butanol fractions at a concentration of 100 µg/mL, their values were 78.57 ± 3.85 % (IC50 = 55.93 ± 5.73 µg/ml) and 69.43 ± 8.68 % (IC50 = 70.17 ± 7.98 µg/ml), respectively. The potential XO inhibitory components were isolated by bioactivity assays and the HR-ESI-MS and NMR spectra system. The main constituents of leaf extracts of Dolichandrone spathacea, six compounds, namely trans-4-methoxycinnamic acid (3), trans-3,4-dimethoxycinnamic acid (4), p-coumaric acid (5), martynoside (6), 6-O-(p-methoxy-E-cinnamoyl)-ajugol (7), and scolymoside (17), were identified as potent XO inhibitors with IC50 values ranging from 19.34 ± 1.63 µM to 64.50 ± 0.94 µM. The enzyme kinetics indicated that compounds 3-5, 7, and 17 displayed competitive inhibition like allopurinol, while compound 6 displayed a mixed-type inhibition. Computational studies corroborated these experimental results, highlighting the interactions between potential metabolites and XO enzyme. The hydrogen bonds played crucial roles in the binding interaction, especially, scolymoside (17) forms a hydrogen bond with Mos3004, exhibited the lowest binding energy (-18.3286 kcal/mol) corresponding to the lowest IC50 (19.34 ± 1.63 µM). Furthermore, nine compounds were isolated for the first time from this plant. In conclusion, Dolichandrone spathacea and its constituents possess the potential to modulate the xanthine oxidase enzyme involved in metabolism.

Prevalence and drug susceptibility of clinical Candida species in nasopharyngeal cancer patients in Vietnam.

In the nature, Candida species are normal inhabitants and can be observed in a wide variety of vertebrates. In humans, especially for cancer patients who fall prey to opportunistic pathogens, this group of susceptible multi-drug resistant and biofilm-forming yeasts, are among the commonest ones. In this study, Candida species in 76 oral lesion samples from Vietnamese nasopharyngeal-cancer patients were isolated, morphologically identified using CHROMagar™, germ tube formation, and chlamydospore formation tests, and molecularly confirmed by PCR-RFLP. The drug susceptibility of these isolates was then tested, and the gene ERG11 was DNA sequenced to investigate the mechanism of resistance. The results showed that Candida albicans remained the most prevalent species (63.16% of the cases), followed by Candida glabrata, Candida tropicalis, and Candida krusei. The rates of resistance of non-albicans Candida for tested drugs were 85.71%, 53.57%, and 57.14% to fluconazole, clotrimazole, and miconazole, respectively. Although the drug-resistance rate of Candida albicans was lower than that of non-albicans Candida, it was higher than expected, suggesting an emerging drug-resistance phenomenon. Furthermore, ERG11 DNA sequencing revealed different mutations (especially K128T), implying the presence of multiple resistance mechanisms. Altogether, the results indicate an alarming drug-resistance situation in Candida species in Vietnamese cancer patients and emphasize the importance of species identification and their drug susceptibility prior to treatment.

miRNAs as biomarkers of therapeutic response to HER2-targeted treatment in breast cancer: A systematic review.

Breast cancer is the most common type of lethal cancer in women globally. Women have a 1 in 8 chance of developing breast cancer in their lifetime. Among the four primary molecular subtypes (luminal A, luminal B, HER2+, and triple-negative), HER2+ accounts for 20-25 % of all breast cancer and is rather aggressive. Although the treatment outcome of HER2+ breast cancer patients has been significantly improved with anti-HER2 agents, primary and acquired drug resistance present substantial clinical issues, limiting the benefits of HER2-targeted treatment. MicroRNAs (miRNAs) play a central role in regulating acquired drug resistance. miRNA are single-stranded, non-coding RNAs of around 20-25 nucleotides, known for essential roles in regulating gene expression at the post-transcriptional level. Increasing evidence has demonstrated that miRNA-mediated alteration of gene expression is associated with tumorigenesis, metastasis, and tumor response to treatment. Comprehensive knowledge of miRNAs as potential markers of drug response can help provide valuable guidance for treatment prognosis and personalized medicine for breast cancer patients.

Omics-based deep learning approaches for lung cancer decision-making and therapeutics development.

Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecular tests, the advent of robust and scalable techniques for nucleic acid analysis has revolutionized biological research and medicinal practice in lung cancer treatment. In response to the demands for minimally invasive procedures and technology development over the past decade, many types of multi-omics data at various genome levels have been generated. As omics data grow, artificial intelligence models, particularly deep learning, are prominent in developing more rapid and effective methods to potentially improve lung cancer patient diagnosis, prognosis and treatment strategy. This decade has seen genome-based deep learning models thriving in various lung cancer tasks, including cancer prediction, subtype classification, prognosis estimation, cancer molecular signatures identification, treatment response prediction and biomarker development. In this study, we summarized available data sources for deep-learning-based lung cancer mining and provided an update on recent deep learning models in lung cancer genomics. Subsequently, we reviewed the current issues and discussed future research directions of deep-learning-based lung cancer genomics research.

ALDH2 as a potential stem cell-related biomarker in lung adenocarcinoma: Comprehensive multi-omics analysis.

Lung adenocarcinoma (LUAD) is the most prevalent lung cancer and one of the leading causes of death. Previous research found a link between LUAD and Aldehyde Dehydrogenase 2 (ALDH2), a member of aldehyde dehydrogenase gene (ALDH) superfamily. In this study, we identified additional useful prognostic markers for early LUAD identification and targeting LUAD therapy by analyzing the expression level, epigenetic mechanism, and signaling activities of ALDH2 in LUAD patients. The obtained results demonstrated that ALDH2 gene and protein expression significantly downregulated in LUAD patient samples. Furthermore, The American Joint Committee on Cancer (AJCC) reported that diminished ALDH2 expression was closely linked to worse overall survival (OS) in different stages of LUAD. Considerably, ALDH2 showed aberrant DNA methylation status in LUAD cancer. ALDH2 was found to be downregulated in the proteomic expression profile of several cell biology signaling pathways, particularly stem cell-related pathways. Finally, the relationship of ALDH2 activity with stem cell-related factors and immune system were reported. In conclusion, the downregulation of ALDH2, abnormal DNA methylation, and the consequent deficit of stemness signaling pathways are relevant prognostic and therapeutic markers in LUAD.

The Distribution of Autoantibodies by Age Group in Children with Type 1 Diabetes versus Type 2 Diabetes in Southern Vietnam.

Asian children are increasingly being diagnosed with type 1 diabetes (T1D) or type 2 diabetes (T2D), and the presence of coexisting islet autoimmune antibodies complicate diagnosis. Here, we aimed to determine the prevalence of islet cell autoantibodies (ICAs) and glutamic acid decarboxylase 65 autoantibodies (GADAs) in children with T1D versus T2D living in Vietnam. This cross-sectional study included 145 pediatric patients aged 10.3 ± 3.6 years, with 53.1% and 46.9% having T1D and T2D, respectively. ICAs were reported in only 3.9% of pediatric T1Ds, which was not significantly different from the 1.5% of those with T2D. Older children with T1D were positive for either ICAs, or ICAs and GADAs (5-9 and 10-15 years), whereas only a small proportion of children aged 0-4 years were positive for GADAs (18%). Notably, 27.9% of children with T2D aged 10-15 were positive for GADAs, and all were classified as overweight (n = 9) or obese (n = 10). GADAs were more commonly observed in T1D patients younger than four years than ICAs, which were more prevalent in older children (5-15 years). Even though few children with T2D carried ICAs and GADAs, finding a better biomarker or an appropriate time to confirm diabetes type may require further investigation.

On the road to explainable AI in drug-drug interactions prediction: A systematic review.

Over the past decade, polypharmacy instances have been common in multi-diseases treatment. However, unwanted drug-drug interactions (DDIs) that might cause unexpected adverse drug events (ADEs) in multiple regimens therapy remain a significant issue. Since artificial intelligence (AI) is ubiquitous today, many AI prediction models have been developed to predict DDIs to support clinicians in pharmacotherapy-related decisions. However, even though DDI prediction models have great potential for assisting physicians in polypharmacy decisions, there are still concerns regarding the reliability of AI models due to their black-box nature. Building AI models with explainable mechanisms can augment their transparency to address the above issue. Explainable AI (XAI) promotes safety and clarity by showing how decisions are made in AI models, especially in critical tasks like DDI predictions. In this review, a comprehensive overview of AI-based DDI prediction, including the publicly available source for AI-DDIs studies, the methods used in data manipulation and feature preprocessing, the XAI mechanisms to promote trust of AI, especially for critical tasks as DDIs prediction, the modeling methods, is provided. Limitations and the future directions of XAI in DDIs are also discussed.

Combining an Autophagy Inhibitor, MPT0L145, with Abemaciclib Is a New Therapeutic Strategy in GBM Treatment.

Glioblastoma multiforme (GBM) is the most malignant brain tumor in the world, only 25% of GBM patients were alive one year after diagnosis. Although Temozolamide combined with radiation therapy more effectively prolonged the survival rate than radiation alone, the overall survival rate is still dismal. Therefore, a new therapeutic strategy is urgently needed. CDK4/6 inhibitors are newly FDA-approved agents to treat HR-positive, HER2-negative advanced, and metastatic breast cancers, and preclinical results showed that CDK4/6 inhibitors significantly reduced cell proliferation and tumor growth. However, several studies have suggested that CDK4/6 inhibitor-induced non-genetic changes caused treatment failure, including autophagy activation. Therefore, this study aimed to combine an autophagy inhibitor, MPT0L145, with abemaciclib to improve therapeutic efficiency. The use of abemaciclib effectively inhibited cell proliferation via suppression of RB phosphorylation and induced autophagy activation in GBM cancer cells. MPT0L145 treatment alone not only blocked autophagy activation, but also induced generation of ROS and DNA damage in a concentration-dependent manner. Importantly, MPT0L145 had a comparable penetration ability to TMZ in our blood brain barrier permeability assay. Combined MPT0L145 with abemaciclib significantly reduced cell proliferation, suppressed RB phosphorylation, and increased ROS production. In conclusion, the data suggested that blocking autophagy by MPT0L145 synergistically sensitized GBM cancer cells to abemaciclib and represents a potential therapeutic strategy for treating GBM in the future.

Quantification and Optimization of Ethanolic Extract Containing the Bioactive Flavonoids from Millettia pulchra Radix.

Millettia pulchra is traditionally used for treating diseases, including joint pain, fever, anemia, and allergies. It is also a potential resource of natural flavonoid derivatives, which represents major constituents of this plant. This study aimed to isolate the major compounds from M. pulchra radix, develop and validate the HPLC-PDA method to determine their contents, and optimize its extraction. Four major flavonoid derivatives (karanjin, lanceolatin B, 2",2"-dimethylpyrano-[5″,6″:7,8]-flavone, and pongamol) were isolated using silica gel column chromatography, crystallization techniques in large amounts with high purities (>95%). A simple, accurate high-performance liquid chromatography-photodiode array (HPLC-PDA) detection method has been developed and validated with significantly statistical impacts according to International Conference on Harmonization (ICH) guidelines. The Response Surface Methodology (RSM), Artificial Neural Network (ANN) models were employed to predictive performance and optimization of the extraction process. The optimized conditions for the extraction of major flavonoids were: extraction time (twice), solvent/material ratio (9.5), and ethanol concentration (72.5%). Our research suggests an effective method, which will be helpful for quality control in the pharmaceutical development of this species.

Triterpene glycosides and phenylpropane derivatives from Staurogyne concinnula possessing anti-angiogenic activity.

After anti-angiogenic activity screening, the potential n-butanol layer partitioned from the ethanol extract of Staurogyne concinnula was conducted. Further purification by Diaion HP20 column and preparative HPLC chromatography, four undescribed triterpenoid saponin derivatives, along with the known baptisiasaponin I, and four known phenylpropanoid glycosides were isolated and characterized from n-butanol layer. The structures of isolated compounds were elucidated by ESI-MS, 1D, and 2D MNR data. Biological evaluation revealed that baptisiasaponin I possessed significant anti-angiogenic effects (IC50 4.0 ± 0.2 µM). Further mechanism of action of baptisiasaponin I by inhibition of integrin/FAK/paxillin signaling pathway and its downstream effectors as MMP2 and MMP9 are also presented.

Arenarosides A-G, Polyhydroxylated Oleanane-Type Saponins from Polycarpaea arenaria and their Cytotoxic and Antiangiogenic Activities.

Seven new polyhydroxylated oleanane-type triterpene saponins, arenarosides A-G (1-7), together with four known compounds, were isolated from an ethanol extract of the aerial parts of the Vietnamese plant Polycarpaea arenaria. The chemical structures of the newly isolated oleanane saponins were elucidated on the basis of spectroscopic and spectrometric analysis, especially 2D NMR and HRMS. Biological evaluation revealed that 3, 4, 6, and 7 showed moderate activities against four human cancer cell lines (A549, HTC116, PC3, and RT112) with IC50 values of 6.0-9.9 µM, and 3, 4, 5, and 7 also displayed promising antiangiogenesis effects with IC50 values <5 µM in the test system used. Among the isolates, arenaroside D (4) exhibited the most potent inhibitory effects, not only in cancer cell proliferation but also in angiogenic activities. Preliminary SAR studies revealed that the presence of an acetyl group at C-22 in oleanane-type triterpene saponins increases these bioactivities.

Bioassay-Guided Isolation and HPLC Quantification of Antiproliferative Metabolites from Stahlianthus Thorelii.

In folk medicine, Stahlianthus thorelii Gagnep. has been used to treat diseases related to inflammation, ulcers, and cancer. There are no reports concerning the chemical components and bioactivities of S. thorelii; thus, this study aims to explore the phytochemicals, quantify the main compounds, and test the anticancer activity of isolates from S. thorelii. Dried rhizomes were extracted with 95% ethanol and, then, partitioned, fractionated, and isolated. On the basis of the result of the antiproliferative activity of the fractions, seven isolates were yielded and were identified by spectroscopic analyses. The inhibition of cancer proliferation was determined by an MTT assay and the deployed IC50 to value their efficacy. Seven compounds containing one new C-benzylated dihydrochalcone derivative, thorechalcone A (1) and 2-7 were isolated from S. thorelii. In terms of the bioactivity, compounds 1 and 3 displayed promising antiproliferative activity (WiDr, A549, and HepG2), with IC50 values <40 µM. The HPLC-UV method of quantification of two major compounds (3 and 4) was also validated. This study presented the isolations of antiproliferative potentials of new chalcone and known flavonoid derivatives from S. thorelii. The validated simple, accurate, and rapid HPLC method could be deployed for the quality control of herbal drugs.

New Dammarane-type Saponins from Gynostemma pentaphyllum.

Six new dammarane-type saponins, gypenosides CP1-6 (16), along with 19 known compounds 7⁻25, were isolated and characterized from the aerial parts of Gynostemma pentaphyllum. Among these compounds, eight dammarane-type saponins, 2, 5, 6, 7, 11, 12, 13, and 15, exhibited the greatest antiproliferative effects against two human tumor cell lines (A549 and HepG2).