Category Archives: 研究發表

何奕儒助理教授研究團隊發表研究成果於Biomater Res.

連結網址：https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10324216/

Abstract

Background: Ischemic stroke-reperfusion (S/R) injury is a crucial issue in the protection of brain function after thrombolysis. The vasodilation induced by ultrasound (US)-stimulated microbubble cavitation has been applied to reduce S/R injury through sonoperfusion. The present study uses oxygen-loaded microbubbles (OMBs) with US stimulation to provide sonoperfusion and local oxygen therapy for the reduction of brain infarct size and neuroprotection after S/R.

Methods: The murine S/R model was established by photodynamic thrombosis and thrombolysis at the remote branch of the anterior cerebral artery. In vivo blood flow, partial oxygen pressure (pO2), and brain infarct staining were examined to analyze the validity of the animal model and OMB treatment results. The animal behaviors and measurement of the brain infarct area were used to evaluate long-term recovery of brain function.

Results: The percentage of blood flow was 45 ± 3%, 70 ± 3%, and 86 ± 2% after 60 min stroke, 20 min reperfusion, and 10 min OMB treatment, respectively, demonstrating sonoperfusion, and the corresponding pO2 level was 60 ± 1%, 76 ± 2%, and 79 ± 4%, showing reoxygenation. After 14 days of treatment, a 87 ± 3% reduction in brain infarction and recovery of limb coordination were observed in S/R mice. The expression of NF-κB, HIF-1α, IL-1β, and MMP-9 was inhibited and that of eNOS, BDNF, Bcl2, and IL-10 was enhanced, indicating activation of anti-inflammatory and anti-apoptosis responses and neuroprotection. Our study demonstrated that OMB treatment combines the beneficial effects of sonoperfusion and local oxygen therapy to reduce brain infarction and activate neuroprotection to prevent S/R injury.

謝仁俊教授研究團隊發表研究成果於Frontiers in Neuroscience

連結網址：https://www.frontiersin.org/articles/10.3389/fnins.2023.1179851/full

Introduction: Primary dysmenorrhea (PDM) is a common condition among women of reproductive age, characterized by menstrual pain in the absence of any organic causes. Previous research has established a link between the A118G polymorphism in the mu-opioid receptor (OPRM1) gene and pain experience in PDM. Specifically, carriers of the G allele have been found to exhibit maladaptive functional connectivity between the descending pain modulatory system and the motor system in young women with PDM. This study aims to explore the potential relationship between the OPRM1 A118G polymorphism and changes in white matter in young women with PDM.

Methods: The study enrolled 43 individuals with PDM, including 13 AA homozygotes and 30 G allele carriers. Diffusion tensor imaging (DTI) scans were performed during both the menstrual and peri-ovulatory phases, and tract-based spatial statistics (TBSS) and probabilistic tractography were used to explore variations in white matter microstructure related to the OPRM1 A118G polymorphism. The short-form McGill Pain Questionnaire (MPQ) was used to access participants’ pain experience during the MEN phase.

Results: Two-way ANOVA on TBSS analysis revealed a significant main effect of genotype, with no phase effect or phase-gene interaction detected. Planned contrast analysis showed that during the menstrual phase, G allele carriers had higher fractional anisotropy (FA) and lower radial diffusivity in the corpus callosum and the left corona radiata compared to AA homozygotes. Tractographic analysis indicated the involvement of the left internal capsule, left corticospinal tract, and bilateral medial motor cortex. Additionally, the mean FA of the corpus callosum and the corona radiata was negatively correlated with MPQ scales in AA homozygotes, but this correlation was not observed in G allele carriers. No significant genotype difference was found during the pain-free peri-ovulary phase.

Discussion: OPRM1 A118G polymorphism may influence the connection between structural integrity and dysmenorrheic pain, where the G allele could impede the pain-regulating effects of the A allele. These novel findings shed light on the underlying mechanisms of both adaptive and maladaptive structural neuroplasticity in PDM, depending on the specific OPRM1 polymorphism.

林志生教授研究團隊發表研究成果於Bioengineering

連結網址：https://www.mdpi.com/2306-5354/10/5/594

Abstract

This study aimed to investigate the use of organic fertilizers instead of modified f/2 medium for Chlorella sp. cultivation, and the extracted lutein of the microalga to protect mammal cells against blue-light irradiation. The biomass productivity and lutein content of Chlorella sp. cultured in 20 g/L fertilizer medium for 6 days were 1.04 g/L/d and 4.41 mg/g, respectively. These values are approximately 1.3- and 1.4-fold higher than those achieved with the modified f/2 medium, respectively. The cost of medium per gram of microalgal biomass reduced by about 97%. The microalgal lutein content was further increased to 6.03 mg/g in 20 g/L fertilizer medium when supplemented with 20 mM urea, and the cost of medium per gram lutein reduced by about 96%. When doses of ≥1 μM microalgal lutein were used to protect mammal NIH/3T3 cells, there was a significant reduction in the levels of reactive oxygen species (ROS) produced by the cells in the following blue-light irradiation treatments. The results show that microalgal lutein produced by fertilizers with urea supplements has the potential to develop anti-blue-light oxidation products and reduce the economic challenges of microalgal biomass applied to carbon biofixation and biofuel production.

麥如村助理教授研究團隊發表研究成果於Am J Cancer Res

連結網址：https://pubmed.ncbi.nlm.nih.gov/37293175/

Abstract

This study aimed to investigate the use of organic fertilizers instead of modified f/2 medium for Chlorella sp. cultivation, and the extracted lutein of the microalga to protect mammal cells against blue-light irradiation. The biomass productivity and lutein content of Chlorella sp. cultured in 20 g/L fertilizer medium for 6 days were 1.04 g/L/d and 4.41 mg/g, respectively. These values are approximately 1.3- and 1.4-fold higher than those achieved with the modified f/2 medium, respectively. The cost of medium per gram of microalgal biomass reduced by about 97%. The microalgal lutein content was further increased to 6.03 mg/g in 20 g/L fertilizer medium when supplemented with 20 mM urea, and the cost of medium per gram lutein reduced by about 96%. When doses of ≥1 μM microalgal lutein were used to protect mammal NIH/3T3 cells, there was a significant reduction in the levels of reactive oxygen species (ROS) produced by the cells in the following blue-light irradiation treatments. The results show that microalgal lutein produced by fertilizers with urea supplements has the potential to develop anti-blue-light oxidation products and reduce the economic challenges of microalgal biomass applied to carbon biofixation and biofuel production.

楊進木教授研究團隊發表研究成果於Environment International

連結網址：https://www.sciencedirect.com/science/article/pii/S0160412023003008?via%3Dihub

Abstract

Over 400,000 people are estimated to have been exposed to World Trade Center particulate matter (WTC_PM) since the attack on the Twin Towers in Lower Manhattan on September 11, 2001. Epidemiological studies have found that exposure to dust may cause respiratory ailments and cardiovascular diseases. However, limited studies have performed a systematic analysis of transcriptomic data to elucidate the biological responses to WTC_PM exposure and the therapeutic options. Here, we developed an in vivo mouse exposure model of WTC_PM and administered two drugs (i.e., rosoxacin and dexamethasone) to generate transcriptomic data from lung samples. WTC_PM exposure increased the inflammation index, and this index was significantly reduced by both drugs. We analyzed the transcriptomics derived omics data using a hierarchical systems biology model (HiSBiM) with four levels, including system, subsystem, pathway, and gene analyses. Based on the selected differentially expressed genes (DEGs) from each group, WTC_PM and the two drugs commonly affected the inflammatory responses, consistent with the inflammation index. Among these DEGs, the expression of 31 genes was affected by WTC_PM exposure and consistently reversed by the two drugs, and these genes included Psme2, Cldn18, and Prkcd, which are involved in immune- and endocrine-related subsystems and pathways such as thyroid hormone synthesis, antigen processing and presentation, and leukocyte transendothelial migration. Furthermore, the two drugs reduced the inflammatory effects of WTC_PM through distinct pathways, e.g., vascular-associated signaling by rosoxacin, whereas mTOR-dependent inflammatory signaling was found to be regulated by dexamethasone. To the best of our knowledge, this study constitutes the first investigation of transcriptomics data of WTC_PM and an exploration of potential therapies. We believe that these findings provide strategies for the development of promising optional interventions and therapies for airborne particle exposure.

陸志豪副教授研究團隊發表研究成果於 Antiviral Research

連結網址：https://www.sciencedirect.com/science/article/pii/S0166354223001316?dgcid=coauthor

Abstract

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication, which suggests that the Mpro is a critical target in the development of small molecules to treat COVID-19. This study used an in-silico prediction approach to investigate the complex structure of SARS-CoV-2 Mpro in compounds from the United States National Cancer Institute (NCI) database, then validate potential inhibitory compounds against the SARS-CoV-2 Mpro in cis- and trans-cleavage proteolytic assays. Virtual screening of ∼280,000 compounds from the NCI database identified 10 compounds with highest site-moiety map scores. Compound NSC89640 (coded C1) showed marked inhibitory activity against the SARS-CoV-2 Mpro in cis-/trans-cleavage assays. C1 strongly inhibited SARS-CoV-2 Mpro enzymatic activity, with a half maximal inhibitory concentration (IC50) of 2.69 μM and a selectivity index (SI) of >74.35. The C1 structure served as a template to identify structural analogs based on AtomPair fingerprints to refine and verify structure-function associations. Mpro-mediated cis-/trans-cleavage assays conducted with the structural analogs revealed that compound NSC89641 (coded D2) exhibited the highest inhibitory potency against SARS-CoV-2 Mpro enzymatic activity, with an IC50 of 3.05 μM and a SI of >65.57. Compounds C1 and D2 also displayed inhibitory activity against MERS-CoV-2 with an IC50 of <3.5 μM. Thus, C1 shows potential as an effective Mpro inhibitor of SARS-CoV-2 and MERS-CoV. Our rigorous study framework efficiently identified lead compounds targeting the SARS-CoV-2 Mpro and MERS-CoV Mpro.

王雲銘教授研究團隊發表研究成果於 Sensors and Actuators B: Chemical

連結網址：

https://www.sciencedirect.com/science/article/pii/S0925400523006755

Abstract

The COVID-19 pandemic has become a global catastrophe, affecting the health and economy of the human community. It is required to mitigate the impact of pandemics by developing rapid molecular diagnostics for SARS-CoV-2 virus detection. In this context, developing a rapid point-of-care (POC) diagnostic test is a holistic approach to the prevention of COVID-19. In this context, this study aims at presenting a real-time, biosensor chip for improved molecular diagnostics including recombinant SARS-CoV-2 spike glycoprotein and SARS-CoV-2 pseudovirus detection based on one-step-one-pot hydrothermally derived CoFeBDCNH2-CoFe2O4 MOF-nanohybrids. This study was tested on a PalmSens-EmStat Go POC device, showing a limit of detection (LOD) for recombinant SARS-CoV-2 spike glycoprotein of 6.68 fg/mL and 6.20 fg/mL in buffer and 10% serum-containing media, respectively. To validate virus detection in the POC platform, an electrochemical instrument (CHI6116E) was used to perform dose dependent studies under similar experimental conditions to the handheld device. The results obtained from these studies were comparable indicating the capability and high detection electrochemical performance of MOF nanocomposite derived from one-step-one-pot hydrothermal synthesis for SARS-CoV-2 detection for the first time. Further, the performance of the sensor was tested in the presence of Omicron BA.2 and wild-type D614G pseudoviruses.

李宗夷教授研究團隊發表研究成果於Briefings in Bioinformatics

連結網址：https://pubmed.ncbi.nlm.nih.gov/36810579/

Abstract

Phosphorylation is an essential mechanism for regulating protein activities. Determining kinase-specific phosphorylation sites by experiments involves time- consuming and expensive analyzes. Although several studies proposed computational methods to model kinase-specific phosphorylation sites, they typically required abundant experimentally verified phosphorylation sites to yield reliable predictions. Nevertheless, the number of experimentally verified phosphorylation sites for most kinases is relatively small, and the targeting phosphorylation sites are still unidentified for some kinases. In fact, there is little research related to these understudied kinases in the literature. Thus, this study aims to create predictive models for these understudied kinases. A kinase-kinase similarity network was generated by merging
the sequence-, functional-, protein-domain- and ‘STRING’-related similarities. Thus, besides sequence data, protein-protein interactions and functional pathways were also considered to aid predictive modelling. This similarity network was then integrated with a classification of kinase groups to yield highly similar kinases to a specific understudied type of kinase. Their experimentally verified phosphorylation sites were leveraged as positive sites to train predictive models. The experimentally verified phosphorylation sites of the understudied kinase were used for validation. Results demonstrate that 82 out of 116 understudied kinases were predicted with adequate performance via the proposed modelling strategy, achieving a balanced accuracy of 0.81, 0.78, 0.84, 0.84, 0.85, 0.82, 0.90, 0.82 and 0.85, for the ‘TK’, ‘Other’, ‘STE’, ‘CAMK’, ‘TKL’, ‘CMGC’, ‘AGC’, ‘CK1’ and ‘Atypical’ groups, respectively. Therefore, this study demonstrates that web-like predictive networks can reliably capture the underlying patterns in such understudied kinases by harnessing relevant sources of similarities to predict their specific phosphorylation sites.

何信瑩教授研究團隊發表研究成果於Human Genetics and Genomics Advances

連結網址：https://pubmed.ncbi.nlm.nih.gov/37124139/

Abstract

The ability to detect cancer at an early stage in patients who would benefit from effective therapy is a key factor in increasing survivability. This work proposes an evolutionary supervised learning method called CancerSig to identify cancer stage-specific microRNA (miRNA) signatures for early cancer predictions. CancerSig established a compact panel of miRNA signatures as potential markers from 4,667 patients with 15 different types of cancers for the cancer stage prediction, and achieved a mean performance: 10-fold cross-validation accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of 84.27% ± 6.31%, 0.81 ± 0.12, 0.80 ± 0.10, and 0.80 ± 0.06, respectively. The pan-cancer analysis of miRNA signatures suggested that three miRNAs, hsa-let-7i-3p, hsa-miR-362-3p, and hsa-miR-3651, contributed significantly toward stage prediction across 8 cancers, and each of the 67 miRNAs of the panel was a biomarker of stage prediction in more than one cancer. CancerSig may serve as the basis for cancer screening and therapeutic selection.

李宗夷教授研究團隊發表研究成果於Microbiology Spectrum

連結網址：https://pubmed.ncbi.nlm.nih.gov/37042778/

Abstract

In clinical microbiology, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is frequently employed for rapid microbial identification. However, rapid identification of antimicrobial resistance (AMR) in Escherichia coli based on a large amount of MALDI-TOF MS data has not yet been reported. This may be because building a prediction model to cover all E. coli isolates would be challenging given the high diversity of the E. coli population. This study aimed to develop a MALDI-TOF MS-based, data-driven, two-stage framework for characterizing different AMRs in E. coli. Specifically, amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM) were used. In the first stage, we split the data into two groups based on informative peaks according to the importance of the random forest. In the second stage, prediction models were constructed using four different machine learning algorithms-logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The findings demonstrate that XGBoost outperformed the other four machine learning models. The values of the area under the receiver operating characteristic curve were 0.62, 0.72, 0.87, 0.72, and 0.72 for AMC, CAZ, CIP, CRO, and CXM, respectively. This implies that a data-driven, two-stage framework could improve accuracy by approximately 2.8%. As a result, we developed AMR prediction models for E. coli using a data-driven two-stage framework, which is promising for assisting physicians in making decisions. Further, the analysis of informative peaks in future studies could potentially reveal new insights. IMPORTANCE Based on a large amount of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli. Five antibiotics, including amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM), were considered for the two-stage model training, and the values of the area under the receiver operating characteristic curve (AUC) were 0.62 for AMC, 0.72 for CAZ, 0.87 for CIP, 0.72 for CRO, and 0.72 for CXM. Further investigations revealed that the informative peak m/z 9714 appeared with some important peaks at m/z 6809, m/z 7650, m/z 10534, and m/z 11783 for CIP and at m/z 6809, m/z 10475, and m/z 8447 for CAZ, CRO, and CXM. This framework has the potential to improve the accuracy by approximately 2.8%, indicating a promising potential for further research.