13856 research outputs found
Sort by
[[alternative]]Fused Bicyclic and Tricyclic Pyrimidine Compounds as Tyrosine Kinase Inhibitors
No full text[[abstract]]본 명세서에서 정의된 화학식(I)의 접합 이환 또는 삼환 화합물이 개시된다. 또한, EGFR 키나아제 활성을 억제하는 방법과 이들 화합물로 암을 치료하는 방법이 개시된다
[[alternative]]Method and composition for treating hepatocellular carcinoma without viral infection by controlling the lipid homeostasis
No full text[[abstract]]本發明係提供一種用於治療無肝炎病毒感染病史之肝細胞癌(HCC)患者的方法與組成物。本發明特別是關於一種透過基因工程技術標靶調控與控制體內脂質平衡相關基因，尤其是藉由調控CD36的增幅或與ABCG4的缺失，來治療非因B型肝炎病毒及/或C型肝炎病毒感染引起之肝細胞癌(NBNC-HCC)患者的方法
Dipicolylamine derivatives and their pharmaceutical uses
No full text[[abstract]]Dipicolylamine compounds of Formula (I) set forth herein. Also disclosed are pharmaceutical compositions containing metal ions and these compounds. Further disclosed is a method for treating a condition associated with cells containing in -side-out phosphatidylserine, with these compounds
Compostos e composição farmacêutica
No full text[[abstract]]Compounds of formula (I): wherein R1, R2, R3, R4, R5, and X are defined herein. Also disclosed are pharmaceutical compositions and methods related to use of these compounds
Integrating a data curation artificial intelligence system to identify cancer registry data elements from unstructured electronic health records
No full text[[abstract]]Background:Cancer registry provides essential information to support precision medicine clinical practice and research. Traditionally, it requires cancer registrars’ manual abstraction from unstructured EHRs. The aim of this study is to demonstrate the performance of a hospital-based AI system in supporting cancer registry data element abstraction. Methods:A natural language processing system was designed with ensemble voting from 3 sub-systems (Hybrid Neural Symbolic System, Hierarchical Attention Network, and Statistical Principle-Based Approach) to incorporate different abstraction rules in cancer diagnosis, staging and treatment data elements. Patient reports were annotated with cancer registry concepts to facilitate the manual coding process. The recommended coding of 40 data elements is provided to cancer registrars for 16 major cancers (oral, salivary gland, nasopharyngeal, esophageal, stomach, colorectal, liver, laryngeal, lung, breast, cervical, uterus, ovarian, prostate, bladder, blood) through a visualization platform. The performance was evaluated using precision, recall, and Fβ-measure (Fβ). Results: There is total 229,375 reports (pathological, image and surgical notes) from 5451 patients. The average number of reports per person/cancer is 27.5 to 61.5 among different cancers. To emphasize the importance of precision, we use F(0.5)>0.85 as a performance target. There are 4 cancers (bladder, stomach, lung and prostate) with all 40 data elements reaching the target, 9 cancers with 30 to 39 elements, and 3 cancers (oral, salivary gland and breast) with less than 30 data elements. The developed AI system has been incorporated in eight hospitals for further prospective validations. Conclusions: An ensemble voting system from 3 incorporated sub-systems provides a resolution to the complexity from cancer registry abstraction rules. Our system develops coding recommendations for cancer registrars with feasible performance, and consequently, may improve the quality of coding practices and reduce the labor and time resources for data abstraction
[[alternative]]Comparative In vitro antibacterial activity of nemonoxacin and other fluoroquinolones in correlation with resistant mechanisms in contemporary methicillin-resistant <i>Staphylococcus aureus</i> blood isolates in Taiwan
No full text[[abstract]]BackgroundNemonoxacin is a new quinolone with an antibacterial efficacy against methicillin-resistant Staphylococcus aureus (MRSA). Certain sequence types (STs) have been emerging in Taiwan, including fluoroquinolone-resistant ST8/USA300. It's an urgent need to determine nemonoxacin susceptibility against ST8/USA300 and other emerging lineages, if any. Additionally, molecular characterization of nemonoxacin resistance among different lineages has yet to be defined. MethodsNon-duplicated MRSA blood isolates from five hospitals during 2019-2020 were collected and genotyped by pulsed-field gel electrophoresis, and further correlated to their STs. Antimicrobial susceptibility testing for all antibiotics was performing by using Sensititre standard panel, except nemonoxacin by using agar dilution method. Selected isolates with nemonoxacin MICs >= 0.5 mg/mL were sequenced for quinolone resistance-determining regions (QRDRs). ResultsOverall, 915 MRSA isolates belonged to four major lineages, ST8 (34.2%), ST59 (23.5%), ST239 (13.9%), and clonal complex 45 (13.7%). Two-thirds of tested isolates were non-susceptible to moxifloxacin, especially ST8/USA300 and ST239. Of them, proportions of nemonoxacin non-susceptibility by a tentative clinical breakpoint (tCBP) of 1 mu g/mL among four major lineages appeared to be different (P = 0.06) and highest in ST239 (22.2%), followed by ST8/USA300 (13.5%). Among 89 isolates sequenced, 44.1% of ST8 and all ST239 isolates had >= 3 amino acid substitutions (AAS) in gyrA/parC (group A) or 2 AAS in gyrA/parC with additional AAS in gyrB/parE (group B). Compared to other AAS patterns, isolates in group A had the greatest non-susceptible proportions to nemonoxacin (86.9%; overall/pair-wised comparisons, P < 0.05). ConclusionsOur study confirmed ST8/USA300 MRSA has disseminated in Taiwan. Using a tCBP defined by a higher parenteral daily dosage, nemonoxacin retained potency against moxifloxacin non-susceptible isolates. Patterns of AAS in QRDRs among different lineages may contribute to difference of nemonoxacin susceptibility
Re-evaluating large for gestational age: Differential effects on perinatal outcomes in term and premature births
No full text[[abstract]]OBJECTIVE: Pregnancies with large-for-gestational-age (LGA) fetuses are associated with increased risks of various adverse perinatal outcomes. While existing research primarily focuses on term neonates, less is known about preterm neonates. This study aims to explore the risks of adverse maternal and neonatal perinatal outcomes associated with LGA in term neonates and neonates with different degrees of prematurity, compared to appropriate-for-gestational-age (AGA) neonates. METHODS: Using the Birth Reporting Databases (2007-2018) linked to Taiwan's National Health Insurance Research Database, we conducted a retrospective nationwide cohort study of singleton neonates delivered between 24 and 42 weeks of gestation. Based on gestational age at delivery, the enrolled neonates were classified into term (37-42 weeks of gestation), late preterm (34-36 weeks of gestation), moderate preterm (32-33 weeks of gestation), very preterm (28-31 weeks of gestation), and extremely preterm (24-27 weeks of gestation). LGA was defined by the 2013 World Health Organization (WHO) growth standard and the Taiwan growth standard. Perinatal outcomes were compared between LGA and AGA neonates across different gestational age groups. RESULTS: Among the 1,602,638 neonates, 44,359 were classified as LGA by the 2013 WHO growth standard. Compared to AGA neonates, LGA neonates in term and late preterm groups exhibited higher risks of primary cesarean section, prolonged labor, neonatal hypoglycemia, birth trauma, hypoxic ischemic encephalopathy, jaundice needing phototherapy, respiratory distress, neonatal intensive care unit (NICU) admission, newborn sepsis, and fetal death. However, most of these risks were not increased in moderate, very, and extremely preterm groups. Conversely, being LGA was associated with lower risks of primary cesarean section (very preterm group), jaundice needing phototherapy (moderate and very preterm groups), respiratory distress (moderate and very preterm groups), NICU admission (moderate and very preterm groups), newborn sepsis (very preterm group), retinopathy of prematurity (late, moderate, and very preterm groups), and bronchopulmonary dysplasia (very preterm group). These findings remained consistent when the Taiwan growth standard was applied. CONCLUSION: Being LGA is associated with increased risks of perinatal complications in term and late preterm neonates, but not in earlier preterm groups. These findings underscore the importance of tailoring management strategies for LGA neonates to consider different degrees of prematurity
ST6GAL1-mediated sialylation of PECAM-1 promotes a transcellular diapedesis-like process that directs lung tropism of metastatic breast cancer
No full text[[abstract]]Metastasis is the leading cause of mortality in breast cancer, with lung metastasis being particularly detrimental. Identification of the processes determining metastatic organotropism could enable the development of approaches to prevent and treat breast cancer metastasis. Here, we found that lung-tropic and non-lung-tropic breast cancer cells differ in their response to sialic acids, affecting the sialylation of surface proteins. Lung-tropic cells showed higher levels of ST6GAL1, while non-lung-tropic cells had more ST3GAL1. ST6GAL1-mediated α-2,6-sialylation, unlike ST3GAL1-mediated α-2,3-sialylation, increased lung metastasis by promoting cancer cell migration through pulmonary endothelial layers and reducing junction protein levels. α-2,6-sialylated PECAM-1 on breast cancer cells facilitated extravasation through the pulmonary endothelium, a critical step in lung metastasis. Knockdown of ST6GAL1 or PECAM-1 significantly reduced lung metastasis. Human pulmonary endothelium displayed high PECAM-1 levels. Through transhomophilic interaction with pulmonary PECAM-1, α-2,6-sialylated PECAM-1 on ST6GAL1-positive cancer cells increased pulmonary extravasation in a diapedesis-like, cell-autonomous manner. Additionally, lung-tropic cells and their exosomes increased the permeability of pulmonary endothelial cells, promoting metastasis in a non-cell-autonomous manner. Analysis of human breast cancer samples showed a correlation between elevated ST6GAL1/PECAM-1 expression and lung metastasis. These results suggest that targeting ST6GAL1-mediated α-2,6-sialylation could be a potential therapeutic strategy to prevent lung metastasis in breast cancer patients
Composite microRNA-genetic risk score model links to migraine and implicates its pathogenesis
No full text[[abstract]]The neurobiological mechanisms driving the ictal-interictal fluctuations and the chronification of migraine remain elusive. We aimed to construct a composite genetic-microRNA model that could reflect the dynamic perturbations of the disease course and inform the pathogenesis of migraine. We prospectively recruited four groups of participants, including interictal episodic migraine (i.e., headache-free for > 72 hrs apart from prior and subsequent attacks), ictal episodic migraine (i.e., during moderate to severe migraine attacks), chronic migraine, and controls in the discovery cohort. Next-generation sequencing (NGS) was used for microRNA profiling. The candidate microRNAs were validated with quantitative PCR (qPCR) in an independent validation cohort. Biological pathways associated with the microRNA regulome and interaction networks were explored. In addition, all participants received genotyping with the Axiom Genome-Wide Array TWB chip. A composite model was established, combining disease-associated microRNAs and genetic risk scores (GRS) indicative of genetic susceptibility, with the objective of differentiating migraine from controls using a binary outcome. From a total of 120 participants in the discovery cohort and 197 participants in the validation cohort, we identified disease-state microRNA signatures (including miR-183, miR-25, and miR-320) that were ubiquitously higher or lower in patients with migraine compared to controls. We have also validated four disease-activity miRNA signatures (miR-1307-5p, miR-6810-5p, let-7e, and miR-140-3p) that were differentially expressed only during the ictal stage of episodic migraine. Functional analysis suggested that prolactin and estrogen signaling pathways might play important roles in the pathogenesis. Moreover, the composite microRNA-GRS model differentiated patients from controls, achieving a positive predictive value of over 90%. To conclude, we developed a composite microRNA-genetic risk score model, which may serve as a predictive tool for identifying high-risk individuals. Our findings may help illuminate potential pathogenic mechanisms underlying the dysfunctional allostasis of migraine and pave the way for future precision medicine