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In silico toxicogenomics methods are resource- and time-efficient approaches for inferring chemical–protein–disease associations with potential mechanism information for exploring toxicological effects. However, current in silico toxicogenomics systems make inferences based on only chemical–protein interactions without considering tissue-specific gene/protein expressions. As a result, inferred diseases could be overpredicted with false positives. In this work, six tissue-specific expression datasets of genes and proteins were collected from the Expression Atlas. Genes were then categorized into high, medium, and low expression levels in a tissue- and dataset-specific manner. Subsequently, the tissue-specific expression datasets were incorporated into the chemical–protein–disease inference process of our ChemDIS system by filtering out relatively low-expressed genes. By incorporating tissue-specific gene/protein expression data, the enrichment rate for chemical–disease inference was largely improved with up to 62.26% improvement. A case study of melamine showed the ability of the proposed method to identify more specific disease terms that are consistent with the literature. A user-friendly user interface was implemented in the ChemDIS system. The methodology is expected to be useful for chemical–disease inference and can be implemented for other in silico toxicogenomics tools.

Pharmacogenomics (PGx) holds the promise of personalizing medical treatments based on individual genetic profiles, thereby enhancing drug efficacy and safety. However, the current landscape of PGx research is hindered by fragmented data sources, time-consuming manual data extraction processes, and the need for comprehensive and up-to-date information. This study aims to address these challenges by evaluating the ability of Large Language Models (LLMs), specifically Llama3.1-70B, to automate and improve the accuracy of PGx information extraction from the FDA Table of Pharmacogenomic Biomarkers in Drug Labeling (FDA PGx Biomarker table), which is well-structured with drug names, biomarkers, therapeutic area, and related labeling texts. Our primary goal was to test the feasibility of LLMs in streamlining PGx data extraction, as an alternative to traditional, labor-intensive approaches. Llama3.1-70B achieved 91.4% accuracy in identifying drug-biomarker pairs from single labeling texts and 82% from mixed texts, with over 85% consistency in aligning extracted PGx categories from FDA PGx Biomarker table and relevant scientific abstracts, demonstrating its effectiveness for PGx data extraction. By integrating data from diverse sources, including scientific abstracts, this approach can support pharmacologists, regulatory bodies, and healthcare researchers in updating PGx resources more efficiently, making critical information more accessible for applications in personalized medicine. In addition, this approach shows potential of discovering novel PGx information, particularly of underrepresented minority ethnic groups. This study highlights the ability of LLMs to enhance the efficiency and completeness of PGx research, thus laying a foundation for advancements in personalized medicine by ensuring that drug therapies are tailored to the genetic profiles of diverse populations.

Pharmacovigilance plays a crucial role in ensuring the safety of pharmaceutical products. It involves the systematic monitoring of adverse events and the detection of potential safety concerns related to drugs. Manual literature screening for pharmacovigilance related articles is a labor-intensive and time-consuming task, requiring streamlined solutions to cope with the continuous growth of literature. The primary objective of this study is to assess the performance of Large Language Models (LLMs) in automating literature screening for pharmacovigilance, aiming to enhance the process by identifying relevant articles more effectively. This study represents a novel application of LLMs including OpenAI’s GPT-3.5, GPT-4, and Anthropic’s Claude2, in the field of pharmacovigilance, evaluating their ability to categorize medical publications as relevant or irrelevant for safety signal reviews. Our analysis encompassed N-shot learning, chain-of-thought reasoning, and evaluating metrics, with a focus on factors impacting accuracy. The findings highlight the promising potential of LLMs in literature screening, achieving a reproducibility of 93%, sensitivity of 97%, and specificity of 67% showcasing notable strengths in terms of reproducibility and sensitivity, although with moderate specificity. Notably, performance improved when models were provided examples consisting of abstracts, labels, and corresponding reasoning explanations. Moreover, our exploration identified several potential contributing factors influencing prediction outcomes. These factors encompassed the choice of key words and prompts, the balance of the examples, and variations in reasoning explanations. By configuring advanced LLMs for efficient screening of extensive literature databases, this study underscores the transformative potential of these models in drug safety monitoring. Furthermore, these insights gained from this study can inform the development of automated systems for pharmacovigilance, contributing to the ongoing efforts to ensure the safety and efficacy of pharmacovigilance products.

BackgroundDiabetic patients are at risk of severe urinary tract infections (UTIs). Due to the emerging resistance rates to fluoroquinolones and β-lactams, we aimed to evaluate the effectiveness of β-lactams versus fluoroquinolones as empirical therapy for diabetic patients hospitalized for UTIs.MethodsA retrospective cohort study was conducted in a medical center in Taiwan between 2016 and 2018. Patients with type 2 diabetes, aged ≥20 and hospitalized for UTIs were enrolled. Patients with UTI diagnosis within one year before the admission, co-infections at the admission, or ≥2 pathogens in the urine cultures were excluded. The primary outcome was empiric treatment failure.Results298 patients were followed for at least 30 days after the admission. Escherichia coli (61.07%) was the most common pathogen. The resistance rates of the pathogens to levofloxacin were 28.52% and 34.22% according to the historical Clinical and Laboratory Standards Institute (CLSI) breakpoints and the updated 2019 CLSI breakpoints, respectively. The resistance rates of ceftazidime and cefepime were 21.81% and 11.41%, respectively. Empirical β-lactams were associated with less treatment failure compared to fluoroquinolones (adjusted OR = 0.32, 95% CI = 0.17-0.60). Beta-lactams were associated with less treatment failure than fluoroquinolones when appropriatness was determined by the pre-2019 CLSI breakpoints but not the 2019 CLSI breakpoints.ConclusionsIn diabetic patients hospitalized for UTIs, β-lactams were associated with less empiric treatment failure compared to fluoroquinolones when the resistance rate to fluoroquinolone is higher than β-lactams. The updated 2019 CLSI breakpoint for fluoroquinolone was better than pre-2019 CLSI breakpoints to correlate with treatment outcomes for hospitalized UTIs in diabetic patients.

Abstract Background The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. Methods To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. Results A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. Conclusions The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

The aim of this study was to design oil in water (O/W) microemulsion formulations for the topical administration of azelaic acid. The permeability of azelaic acid through rat skin and the anti-inflammatory activities of the formulations were conducted to examine the efficacy of the designed formulations. Skin irritation and stability tests were also performed. The permeability of azelaic acid was significantly increased by using O/W microemulsions as carriers. The edema index of ear swelling percentage was significantly recovered by the 5% drug-loaded formulation and a 20% commercial product, demonstrating that the experimental formulation possessed comparable effect with the commercial product on the improvement of inflammation. The experimental formulation did not cause significant skin irritation compared to the negative control group. Moreover, the drug-loaded formulation also showed thermodynamic stability and chemical stability after storage for 30 days. In conclusion, the O/W microemulsion was a potential drug delivery carrier for azelaic acid topical application.

This study explores the amounts of common chemical ultraviolet (UV) filters (i.e., avobenzone, bemotrizinol, ethylhexyl triazone, octocrylene, and octyl methoxycinnamate) in cosmetics and the human stratum corneum. An ultrasound–vortex-assisted dispersive liquid–liquid microextraction (US–VA–DLLME) method with a high-performance liquid chromatography–diode array detector was used to analyze UV filters. A bio-derived solvent (i.e., anisole) was used as the extractant in the US–VA–DLLME procedure, along with methanol as the dispersant, a vortexing time of 4 min, and ultrasonication for 3 min. The mass-transfer rate of the extraction process was enhanced due to vortex-ultrasound combination. Various C18 end-capped columns were used to investigate the separation characteristics of the UV filters, with XBridge BEH or CORTECS selected as the separation column. Calibration curves were constructed in the 0.05–5 μg/mL (all filters except octocrylene) and 0.1–10 μg/mL (octocrylene) ranges, and excellent analytical linearities with coefficients of determination (r2) above 0.998. The developed method was successfully used to analyze sunscreen. Moreover, experiments were designed to simulate the sunscreen-usage habits of consumers, and the cup method was used to extract UV filters from the human stratum corneum. The results suggest that a makeup remover should be employed to remove water-in-oil sunscreens from skin.

One new dibenzocycloheptene, validinol (1), and one butanolide firstly isolated from the natural source, validinolide (2), together with 17 known compounds were isolated from the stem of Cinnamomum validinerve. Among the isolates, lincomolide A (3), secosubamolide (7), and cinnamtannin B1 (19) exhibited potent inhibition on both superoxide anion generation (IC50 values of 2.98 ± 0.3 µM, 4.37 ± 0.38 µM, and 2.20 ± 0.3 µM, respectively) and elastase release (IC50 values of 3.96 ± 0.31 µM, 3.04 ± 0.23 µM, and 4.64 ± 0.71 µM, respectively) by human neutrophils. In addition, isophilippinolide A (6), secosubamolide (7), and cinnamtannin B1 (19) showed bacteriostatic effects against Propionibacterium acnes in in vitro study, with minimal inhibitory concentration (MIC) values at 16 μg/mL, 16 μg/mL, and 500 μg/mL, respectively. Further investigations using the in vivo ear P. acnes infection model showed that the intraperitoneal administration of the major component cinnamtannin B1 (19) reduced immune cell infiltration and pro-inflammatory cytokines TNF-α and IL-6 at the infection sites. The results demonstrated the potential of cinnamtannin B1 (19) for acne therapy. In summary, these results demonstrated the anti-inflammatory potentials of Formosan C. validinerve during bacterial infections.

Neolitsea species, medicinal plants belonging to Lauraceae, contain rich alkaloids, steroids, sesquiterpenoids, and triterpenoids which possess antimicrobial, antioxidant, and anti-inflammatory bioactivities. However, species differences in the immunomodulatory effects and evidence pertaining to the effects of Neolitsea species on adaptive immunity are scarce. This study aimed to evaluate the immunomodulatory properties of ten Taiwanese Neolitsea plants on T helper (Th) cell functionality, especially Th1 and Th2. Most of the 29 crude extracts of Neolitsea were not toxic to splenocytes, except N. buisanensis roots. N. aciculata and N. villosa leaf extracts possessed differential immunomodulatory effects on Th1/Th2 balance. N. aciculata var. variabillima and N. hiiranensis leaf extracts attenuated both Th1 and Th2 cytokines while N. konishii dramatically suppressed IFN-γ production. As N. aciculata var. variabillima and N. konishii leaf extracts significantly attenuated Th1 functionality, we further evaluated their effects on CD4 cells under CD3/CD28 stimulation. N. aciculata var. variabillima significantly suppressed IFN-γ, IL-10, and IL-17, demonstrating the broad suppressive effects on T helper cells; N. konishii significantly suppressed IFN-γ and IL-10 production, while the production of IL-17 was not altered. Collectively, these data demonstrated that leaf extracts of Taiwanese Neolitsea species contain phytochemicals with potentials to be developed as selective immunomodulators.

Background T cells play a pivotal role in the adaptive immunity that participates in a wide range of immune responses through a complicated cytokine network. Imbalance of T-cell responses is involved in several immune disorders. Neolitsea species, one of the biggest genera in the family Lauraceae, have been employed widely as folk medicines for a long time in Asia. Previous phytochemical investigations revealed the abundance of terpenes in the leaves of N. hiiranensis, an endemic Neolitsea in Taiwan, and demonstrated anti-inflammatory activities. However, the effect of N. hiiranensis on the functionality of immune cells, especially T cells, is still unclear. In this study, we utilize in vitro and in vivo approaches to characterize the effects of leaves of N. hiiranensis and its terpenoids on adaptive immune responses. Methods Dried leaves of N. hiiranensis were extracted three times with cold methanol to prepare crude extracts and to isolate its secondary metabolites. The ovalbumin (OVA)-sensitized BALB/c mice were administrated with N. hiiranensis extracts (5–20 mg/kg). The serum and splenocytes of treated mice were collected to evaluate the immunomodulatory effects of N. hiiranensis on the production of OVA-specific antibodies and cytokines. To further identify the N. hiiranensis-derived compounds with immunomodulatory potentials, OVA-primed splenocytes were treated with compounds isolated from N. hiiranensis by determining the cell viability, cytokine productions, and mRNA expression in the presence of OVA in vitro. Results Crude extracts of leaves of N. hiiranensis significantly inhibited IL-12, IFN-γ, and IL-2 cytokine productions as well as the serum levels of antigen-specific IgM and IgG2a in vivo. Two of fourteen selected terpenoids and one diterpenoid derived from the leaves of N. hiiranensis suppressed IFN-γ in vitro. In addition, β-caryophyllene oxide attenuated the expression of IFN-γ, T-bet, and IL-12Rβ2 in a dose-dependent manner. N. hiiranensis-derived β-caryophyllene oxide inhibited several aspects of adaptive immune responses, including T-cell differentiation, IFN-γ production, and Th1-assocaited genes. Conclusion As IFN-γ is the key cytokine secreted by T helper-1 cells and plays a pivotal role in Th1 immune responses, our results suggested that the N. hiiranensis and its terpenoids may possess potential therapeutic effects on Th1-mediated immune disorders.

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs.

Staphylococcus aureus initiates infections and produces virulence factors, including superantigens (SAgs), at mucosal surfaces. The SAg, Toxic Shock Syndrome Toxin-1 (TSST-1) induces cytokine secretion from epithelial cells, antigen presenting cells (APCs) and T lymphocytes, and causes toxic shock syndrome (TSS). This study investigated the mechanism of TSST-1-induced secretion of proinflammatory cytokines from human vaginal epithelial cells (HVECs) and determined if curcumin, an anti-inflammatory agent, could reduce TSST-1-mediated pathology in a rabbit vaginal model of TSS. TSST-1 caused a significant increase in NF-κB-dependent transcription in HVECs that was associated with increased expression of TNF- α, MIP-3α, IL-6 and IL-8. Curcumin, an antagonist of NF-κB-dependent transcription, inhibited IL-8 production from ex vivo porcine vaginal explants at nontoxic doses. In a rabbit model of TSS, co-administration of curcumin with TSST-1 intravaginally reduced lethality by 60% relative to 100% lethality in rabbits receiving TSST-1 alone. In addition, TNF-α was undetectable from serum or vaginal tissue of curcumin treated rabbits that survived. These data suggest that the inflammatory response induced at the mucosal surface by TSST-1 is NF-κB dependent. In addition, the ability of curcumin to prevent TSS in vivo by co-administration with TSST-1 intravaginally suggests that the vaginal mucosal proinflammatory response to TSST-1 is important in the progression of mTSS.

Background. Kawasaki disease (KD) is characterized by systemic vasculitis of unknown etiology. Our previous studies showed expression of CD40 ligand on CD4+ T cells correlated to the coronary artery lesion (CAL) and disease progress in KD. Other studies from Japan suggested the role of CD40L in the pathogenesis of CAL, and this might help explain the excessive number of males affected with KD but cannot be reproduced by Taiwanese population. This study was conducted to investigate the CD40 polymorphism in KD and CAL formation. Methods. A total of 950 subjects (381 KD patients and 569 controls) were investigated to identify 2 tagging single-nucleotide polymorphisms (tSNPs) of CD40 (rs4810485 and rs1535045) by using the TaqMan allelic discrimination assay. Results. A significant association was noted with regards to CD40 tSNPs (rs1535045) between controls and KD patients (P=0.0405, dominant model). In KD patients, polymorphisms of CD40 (rs4810485) showed significant association with CAL formation (P=0.0436, recessive model). Haplotype analysis did not yield more significant results between polymorphisms of CD40 and susceptibility/disease activity of KD. Conclusions. This study showed for the first time that polymorphisms of CD40 are associated with susceptibility to KD and CAL formation, in the Taiwanese population.

BACKGROUND:Glycerol monolaurate (GML), a 12 carbon fatty acid monoester, inhibits Staphylococcus aureus growth and exotoxin production, but is degraded by S. aureus lipase. Therefore, dodecylglycerol (DDG), a 12 carbon fatty acid monoether, was compared in vitro and in vivo to GML for its effects on S. aureus growth, exotoxin production, and stability. METHODOLOGY/PRINCIPAL FINDINGS:Antimicrobial effects of GML and DDG (0 to 500 microg/ml) on 54 clinical isolates of S. aureus, including pulsed-field gel electrophoresis (PFGE) types USA200, USA300, and USA400, were determined in vitro. A rabbit Wiffle ball infection model assessed GML and DDG (1 mg/ml instilled into the Wiffle ball every other day) effects on S. aureus (MN8) growth (inoculum 3x10(8) CFU/ml), toxic shock syndrome toxin-1 (TSST-1) production, tumor necrosis factor-alpha (TNF-alpha) concentrations and mortality over 7 days. DDG (50 and 100 microg/ml) inhibited S. aureus growth in vitro more effectively than GML (p