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Poly heterocyclic conjugates and their pharmaceutical uses
No full text[[abstract]]Compounds of Formula (I) shown below and a pharmaceutical composition containing one of the compounds:Each of the variables is defined herein. Also disclosed is a method of treating a condition associated with uncontrolled cell growth with a compound of Formula (I)
アミノチアゾール化合物及びその使用
No full text[[abstract]]Aminothiazole compounds of Formula (I) shown herein and pharmaceutical compositions containing one of such compounds
[[alternative]]Aminothiazole compounds and use thereof
No full text[[abstract]]Aminothiazole compounds of Formula (I) shown herein and pharmaceutical compositions containing one of such compounds
[[alternative]]CDGSH iron sulfur domain 2 activators and use thereof
No full text[[abstract]]本揭露提供一種異吲哚啉化合物及其醫藥組成物。還提供了治療Cisd2-不足相關病症的方法和防止阿黴素誘導之心臟毒性的方法
Combination of CAPE with enzalutamide or abiraterone suppresses drug-resistant prostate cancer via AR-V7 degradation
No full text[[abstract]]Enzalutamide (ENZ) and abiraterone (AA) are drugs targeting androgen receptor axis for treatment of metastatic castration-resistant prostate cancer (mCRPC). However, a majority of patients receiving these treatments will eventually acquire drug resistance, which is mainly caused by activation of AR splice variant 7 (AR-V7). We generated drug-resistant cancer cells, named ENZ-R and AA-R, to mimic the patients who receiving drug-resistance. Co-treatment with CAPE and ENZ or AA enhanced the inhibition of proliferation of ENZ-R and AA-R cells. Flow cytometry revealed combined treatment caused G2/M cell cycle arrest in drug-resistant CRPC cells. Micro-Western Array (MWA) showed different patterns of cell cycle- and metabolic-related protein in ENZ-R and AA-R cells under combined treatment of CAPE with ENZ or AA. In animal model, combined treatment of ENZ/AA with CAPE significantly reduced tumor growth of ENZ-R or AA-R xenografts by inhibition of protein level of AR-V7 in xenografts. In conclusions, combination of CAPE with ENZ/AA might be a potential therapy to treat drug-resistant PCa
The 40S ribosomal subunit recycling complex modulates mitochondrial dynamics and endoplasmic reticulum - mitochondria tethering at mitochondrial fission/fusion hotspots
No full text[[abstract]]The 40S ribosomal subunit recycling pathway is an integral link in the cellular quality control network, occurring after translational errors have been corrected by the ribosome-associated quality control (RQC) machinery. Despite our understanding of its role, the impact of translation quality control on cellular metabolism remains poorly understood. Here, we reveal a conserved role of the 40S ribosomal subunit recycling (USP10-G3BP1) complex in regulating mitochondrial dynamics and function. The complex binds to fission-fusion proteins located at mitochondrial hotspots, regulating the functional assembly of endoplasmic reticulum-mitochondria contact sites (ERMCSs). Furthermore, it alters the activity of mTORC1/2 pathways, suggesting a link between quality control and energy fluctuations. Effective communication is essential for resolving proteostasis-related stresses. Our study illustrates that the USP10-G3BP1 complex acts as a hub that interacts with various pathways to adapt to environmental stimuli promptly. It advances our molecular understanding of RQC regulation and helps explain the pathogenesis of human proteostasis and mitochondrial dysfunction diseases
Explore the role of growth factor Fgf2 in alcohol dependence
No full text[[abstract]]Background: Although several growth factors have been implicated in alcohol dependence (AD) [1], fibroblast growth factor 2 (FGF2) was hypothesized to play a role in an endogenous pathway contributing to the transition from moderate to excessive alcohol use in the development of AD. In this study, the FGF2 was further investigated for its association with a brain injury indicator, neurofilament light chain (NFL) [2], and inflammatory factor, C-C-motif chemokine ligand 11 (CCL11), to assess its role in AD and delirium tremens (DT). Aims & Objectives: In our previous report, a significant increase in CCL11 [3] and NFL [4] levels in was observed in patients with AD. Expanding on the results, we further examined the role of FGF2 in this cohort of AD patients. Method: A total of 224 AD patients and 117 non-AD reference controls were examined in this study. Their plasma NFL were measured using the parallel Simple Plex NFL Assay via the Ella instrument, following the manufacturers’ instructions. Additionally, their CCL11 and FGF2 levels were measured by Enzyme-linked Immunosorbent Assay (ELISA). Statistical analyses included the Mann-Whitney U test for comparing two groups, and Spearman's correlation analysis for assessing bivariate correlations. The receiver operating characteristic (ROC) curve was plotted to identify the area under the curve (AUC) for the levels of plasma FGF2, CCL11 and NFL in controls and patients with AD, or in those with DT and without DT (DT vs non-DT group). Results: The age and gender were matched between AD and controls. Plasma FGF2, CCL11 and NFL were significantly increased in AD patients (Mann-Whitney U test, all PCCL11 (AUC = 0.59)> FGF2 (AUC = 0.54). Furthermore, a subset of DT group, who self-reported a history of DT (HDT) in the past, exhibited an elevated FGF2 level than the control group (P=0.036). FGF2 levels were negatively correlated with CCL11 levels (Spearman’ s r=-0.167, P=0.031). Discussion & Conclusion: These results indicated that FGF2 may be function as an intermediate growth factor within the pathological pathway of AD. Compared to NFL and CCL11, FGF2 is less satisfactory to discriminate AD from controls or DT from non-DT. It exhibited a negative correlation with plasma CCL11 levels, suggesting potential role in the regulatory mechanisms
Association of healthy lifestyles and genetic risk with cognitive performance in older adults
No full text[[abstract]]Background: The prevalence of dementia among people aged 60 years and older is 7.54%, and the prevalence of mild cognitive impairment is 17.99% in Taiwan [1]. Both genetic risk and lifestyle play a pivotal role in cognitive function [2,3]. However, most previous studies focused on Western populations. There have been neither large-scale studies nor genome-wide risk profiling such as polygenic risk scores (PRS) studies in the Asian populations. It is still unclear whether the effect of healthy lifestyles on cognition varies by genetic risk. Aims & Objectives: This study aimed to investigate whether healthy lifestyles and PRS for Alzheimer’ s disease (AD-PRS) are associated with cognitive function performance, and to determine whether there is an interaction between healthy lifestyle and AD-PRS on cognitive function performance. Method: This study uses data from the Taiwan Biobank. In total, 23430 unrelated participants who were aged 60 years and older with Mini-Mental State Examination (MMSE), healthy lifestyles, and genotyping were included in the cross-sectional analyses. Healthy lifestyles include cigarette smoking, alcohol drinking, and physical activity. Among these participants, 6238 had follow-up data and were included in the longitudinal analyses. Cross-sectional associations between AD-PRS, healthy lifestyle, and MMSE at baseline were tested using multivariable linear regression analysis. Associations between AD-PRS, healthy lifestyle, and the changes in MMSE during follow-up were examined using multivariable linear regression analysis. We also tested the interaction between AD-PRS and healthy lifestyles on MMSE and the changes in MMSE. Results: In the cross-sectional analyses, participants with a high genetic risk (highest quintile) of AD-PRS had worse cognitive function performance compared with participants with a low genetic risk (lowest quintile) (β=-0.09, P-value=0.0441). Compared with the participants who never/seldom drink, the participants who were current drinkers had better cognitive function (β=0.16, P-value=0.0114). In the longitudinal analyses, there was no significant association between AD-PRS and the changes in MMSE. Compared with the participants who never/seldom drink at baseline, the participants who were currently drinking had lower MMSE decline during follow-up (β=-0.29, P-value=0.043). In both the cross-sectional analyses and longitudinal analyses, there was no significant interaction between AD-PRS and healthy lifestyles on cognitive performance. Discussion & Conclusion: AD-PRS was associated with cognitive performance at baseline. Drinking was associated with better cognitive performance at baseline and lower cognitive decline during follow-up. AD-PRS and healthy lifestyles might impact cognitive function independently
[[alternative]]Estimating and characterizing spatiotemporal distributions of elemental PM2.5 using an ensemble machine learning approach in Taiwan
No full text[[abstract]]This paper presents an ensemble machine learning approach that combines Generalized Additive Model (GAM) with eXtreme Gradient Boosting (XGBoost) to estimate and characterize the spatiotemporal distributions of elemental PM2.5 in Taiwan. Daily field measurements of 12 PM2.5 elemental components were collected from 28 air quality monitoring stations between June 2021 and May 2022. Time-variant meteorological factors and timeinvariant land-use patterns were incorporated as predictors. Results showed that the ensemble model effectively captured spatial variations in elemental PM2.5 levels, as demonstrated by the identification of numerous timeinvariant features using Shapley additive explanations analysis. A comparative analysis was conducted with a model using only XGBoost, which outperformed the ensemble model with higher cross-validated R2 and lower prediction errors. While the XGBoost-only model is recommended for exposure prediction, the ensemble model offers superior interpretability for investigating air pollution sources and aids in formulating air quality strategies from a spatial perspective
Effects of different mechanisms on antimicrobial resistance in Pseudomonas aeruginosa: A strategic system for evaluating antibiotics against gram-negative bacteria
No full text[[abstract]]Our previous studies constructed a strategic system for testing antibiotics against specific resistance mechanisms using Klebsiella pneumoniae and Acinetobacter baumannii. However, it lacked resistance mechanisms specifically expressed only in Pseudomonas species. In this study, we constructed this system using Pseudomonas aeruginosa. In-frame deletion, site-directed mutagenesis, and plasmid transformation were used to generate genetically engineered strains with various resistance mechanisms from two fully susceptible P. aeruginosa strains. Antimicrobial susceptibility testing was used to test the efficacy of antibiotics against these strains in vitro. A total of 31 engineered strains with various antimicrobial resistance mechanisms from P. aeruginosa KPA888 and ATCC 27853 were constructed, and the same antibiotic resistance mechanism showed a similar effect on the MICs of the two strains. Compared to the parental strains, the engineered strains lacking porin OprD or lacking the regulator genes of efflux pumps all showed a ≥4-fold increase on the MICs of some of the 19 antibiotics tested. Mechanisms due to GyrA/ParC mutations and β-lactamases also contributed to their corresponding resistance as previously published. The strains constructed in this study possess well-defined resistance mechanisms and can be used to screen and evaluate the effectiveness of antibiotics against specific resistance mechanisms in P. aeruginosa. Building upon our previous studies on K. pneumoniae and A. baumannii, this strategic system, including a P. aeruginosa panel, has been expanded to cover almost all the important antibiotic resistance mechanisms of gram-negative bacteria that are in urgent need of new antibiotics.IMPORTANCEIn this study, an antibiotic assessment system for P. aeruginosa was developed, and the system can be expanded to include other key pathogens and resistance mechanisms. This system offers several benefits: (i) compound design: aid in the development of compounds that can bypass or counteract resistance mechanisms, leading to more effective treatments against specific resistant strains; (ii) combination therapies: facilitate the exploration of combination therapies, where multiple antibiotics may work synergistically to overcome resistance and enhance treatment efficacy; and (iii) targeted treatments: enable healthcare providers to prescribe more targeted treatments, reducing unnecessary antibiotic use and helping to slow the spread of antibiotic resistance. In summary, this system could streamline the development process, reduce costs, increase the success rate of new antibiotics, and help prevent and control antimicrobial resistance