110023 research outputs found
Sort by
Synthesis of Novel Suramin Analogs With Anti-Proliferative Activity via FGF1 and FGFRD2 Blockade
No full text[[abstract]]A promising approach in cancer therapy is the inhibition of cell proliferation using small molecules. In this study, we report the synthesis of suramin derivatives and their applications. We used NMR spectroscopy and docking simulations to confirm binding sites and three-dimensional models of the ligand-protein complex. The WST-1 assay was used to assess cell viability and cell proliferation in vitro to evaluate the inhibition of protein–protein interactions and to investigate the anti-proliferative activities in a breast cancer cell line. All the suramin derivatives showed anti-proliferative activity by blocking FGF1 binding to its receptor FGFRD2. The dissociation constant was measured by fluorescence spectroscopy. The suramin compound derivatives synthesized herein show potential as novel therapeutic agents for their anti-proliferative activity via the inhibition of protein–protein interactions. The cytotoxicity of these suramin derivatives was lower than that of the parent suramin compound, which may be considered a significant advancement in this field. Thus, these novel suramin derivatives may be considered superior anti-metastasis molecules than those of suramin
The significance of karyotyping and azoospermia factor analysis in patients with nonobstructive azoospermia or oligozoospermia
No full text[[abstract]]Objective
We present our study about the significance of karyotyping and azoospermia factor(AZF) analysis in patients with azoospermia or oligozoospermia.
Materials and methods
We retrospectively reviewed 141 Taiwanese patients with nonobstructive azoospermia and 45 Taiwanese patients with oligozoospermia at MacKay Memorial Hospital, Taiwan, from 2010 to 2021 to determine the significance of karyotyping and azoospermia factor analysis. The karyotyping was analyzed using the Giemsa banding method. The AZF microdeletions were determined using multiplex polymerase chain reaction using primers specifically flanking the AZF subregions.
Results
We found that 7.80% of patients with nonobstructive azoospermia had AZF microdeletions and 19.86% of patients with nonobstructive azoospermia had chromosomal anomalies or polymorphic variations. Furthermore, 4.44% of patients with oligozoospermia had AZF microdeletions, and 4.44% of patients with oligozoospermia had chromosomal anomalies or polymorphic variations.
Conclusion
In this study, 25.53% of patients with nonobstructive azoospermia and 8.88% of patients with oligozoospermia had abnormal findings. The significance of karyotyping and azoospermia factor analysis is more critical in patients with nonobstructive azoospermia than patients with oligozoospermia. Both karyotyping and AZF analysis could prevent delayed treatment for male infertility through accurate diagnosis and appropriate treatment. The number of our patients with AZFc microdeletion was also higher than that of patients with AZFa or AZFb. The spermatogenic potential may gradually decline in patients with AZFc microdeletion. The earlier is the diagnosis, the earlier will be the retrieval of testicular spermatozoa
The Willingness of Elderly Taiwanese Individuals to Accept COVID-19 Vaccines after the First Local Outbreak
No full text[[abstract]]Vaccination is the most effective intervention to prevent infection and subsequent complications from SARS-CoV-2. Because of their multiple comorbidities, the elderly population experienced the highest number of deaths from the COVID-19 pandemic. Although in most countries, older people have top priority for COVID-19 vaccines, their actual willingness and attitudes regarding vaccination are still unclear. Thus, we conducted a cross-sectional study to investigate their willingness, attitudes, awareness, and knowledge of COVID-19 through a web-based questionnaire after the first local outbreak of COVID-19 in Taiwan. A total of 957 questionnaires were completed, and 74.9% of elderly individuals were likely to receive COVID-19 vaccines. The results from a multiple logistic regression demonstrated that older people who need to visit the outpatient department and have a high level of concern about the safety of COVID-19 vaccines are prone to having a negative willingness to accept COVID-19 vaccines. The following items related to awareness of the COVID-19 pandemic were attributed to the acceptance of COVID-19 vaccines: "understanding the risk of being infected by SARS-CoV-2", "understanding the effectiveness of COVID-19 vaccines", "willingness to accept the COVID-19 vaccine for protecting others", and "safety of COVID-19 vaccines is a key factor for you to accept them". Furthermore, a positive association between COVID-19 vaccination and attitudes toward accepting booster doses of the COVID-19 vaccine was observed. Our results show that these factors could affect the willingness of older people to accept COVID-19 vaccines and that they are important for policymakers and medical staff to develop vaccination plans during the COVID-19 pandemic
Traditional Chinese medicine formula T33 inhibits the proliferation of human colorectal cancer cells by inducing autophagy
No full text[[abstract]]Colorectal cancer (CRC) is a leading cause of cancer-related death globally. Although surgery is still the major method for CRC therapy, the adoption of alternative treatments, such as traditional Chinese medicine (TCM), for CRC treatment is increasing. Our previous study has indicated the anti-breast cancer activity of T33 (a TCM formula). Interestingly, a major ingredient in T33, Baishao (Paeoniae Radix Alba), was reported to have antiproliferative effects on CRC cells. Therefore, this study further validated the influences of T33 on HT-29 and Caco2 cells both in vitro and in vivo. Viability and migration assays were performed to analyze the influences of T33 on proliferation and migratory activity of HT-29 and Caco2 cells. Immunofluorescence (IF) staining and immunoblotting were performed to confirm T33-induced autophagy in HT-29 and Caco2 cells. Xenograft HT-29 tumors were generated to test the effects of T33 in vivo. Significantly reduced survival and migratory activity were observed in both HT-29 and Caco2 cells treated with T33 along with apparently increased LC3-II protein. Significantly decreased p62/SQSTM1 protein, increased LC3-II/LC3-I ratio, and elevated amounts of Atg7, Atg5, and Beclin-1 proteins were detected in both HT-29 and Caco2 cells treated with T33. Moreover, the volume of xenograft HT-29 tumors was significantly lower in mice receiving 200 or 600 mg/kg T33 than in control-treated mice. These findings indicate that T33 exerts anti-CRC activity by inducing autophagy and suggest the potential of T33 for CRC treatment
Comparison of Long-term Effects of Exergaming (Xbox one kinet) and Companionship Programs on Attitude Towards Dementia and the Older Adults Among Adolescents: A Quasi-experimental Longitudinal Study.
No full text[[abstract]]Background: Many studies have been performed on the use of intergenerational programs to improve the negative attitudes and misunderstandings of adolescents toward older people with dementia. However, the findings of these studies are inconclusive. The aim of this study was to compare the long-term effects of exergaming (Kinect) and companionship programs on attitudes toward dementia and the elderly among adolescents.
Methods: A quasi-experimental longitudinal design was used. A total of 200 adolescents aged 12-18 years old were recruited from nine schools in northern Taiwan. The adolescents were assigned to five different groups, namely, a 5-week exergaming group, a 5-week companion group, an 8-week exergaming group, an 8-week companion group, and a control group, using a single blinding procedure. Data collection was performed pretest, post-test and at 1, 3 and 6 months after the post-test. The long-term effects of the two programs (i.e., exergaming and companionship) were analyzed using a generalized estimating equation.
Results: Regarding attitudes toward dementia, the 8-week exergaming group had a significantly better attitude than the control group at the 6-month follow-up (p < 0.001). Similarly, the results of the 8-week companion group also showed a significantly improved attitude compared with the control group at the 6-month follow-up (p = 0.041). Regarding attitudes toward the elderly, the 8-week exergaming group had a significantly better attitude than the control group at the 6-month follow-up (p < 0.001). The 8-week companion group had a similar effect on better attitude compared with the control group at the 6-month follow-up (p = 0.016). Furthermore, the 5-week companion group showed a significant improvement compared with the control group at the 6-month follow-up (p = 0.004).
Conclusions: Spending companionship time with older adults is beneficial for improving the attitudes of adolescents toward the elderly. Furthermore, exergaming improves the attitudes of adolescents toward both dementia and older adults.
Trial registration: Chinese Clinical Trial Registry: ChiCTR2100053003 . Retrospectively registered on 07/11/2021
Enhancement of Osteoblast Function through Extracellular Vesicles Derived from Adipose-Derived Stem Cells
No full text[[abstract]]Adipose-derived stem cells (ADSCs) are a type of mesenchymal stem cell that is investigated in bone tissue engineering (BTE). Osteoblasts are the main cells responsible for bone formation in vivo and directing ADSCs to form osteoblasts through osteogenesis is a research topic in BTE. In addition to the osteogenesis of ADSCs into osteoblasts, the crosstalk of ADSCs with osteoblasts through the secretion of extracellular vesicles (EVs) may also contribute to bone formation in ADSC-based BTE. We investigated the effect of ADSC-secreted EVs (ADSC-EVs) on osteoblast function. ADSC-EVs (size ≤ 1000 nm) were isolated from the culture supernatant of ADSCs through ultracentrifugation. The ADSC-EVs were observed to be spherical under a transmission electron microscope. The ADSC-EVs were positive for CD9, CD81, and Alix, but β-actin was not detected. ADSC-EV treatment did not change survival but did increase osteoblast proliferation and activity. The 48 most abundant known microRNAs (miRNAs) identified within the ADSC-EVs were selected and then subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The GO analysis revealed that these miRNAs are highly relevant to skeletal system morphogenesis and bone development. The KEGG analysis indicated that these miRNAs may regulate osteoblast function through autophagy or the mitogen-activated protein kinase or Ras-related protein 1 signaling pathway. These results suggest that ADSC-EVs enhance osteoblast function and can contribute to bone regeneration in ADSC-based BTE
A practical App for quickly calculating the number of people using machine learning and convolutional neural networks
No full text[[abstract]]: Calculating the number of people is often necessary and repeated in real life. As the
number of people increases, the calculation is time-consuming. Efficiently calculating the number
of people is helpful to human life. In this article, we propose a valuable app to quickly calculate
the number of people in a photo by a convolutional neural network (CNN). Initially, suspected face
areas are segmented into micro-blocks. The segmented blocks are then confirmed through the CNN
by rejecting the segmented micro-blocks without the human face to ensure the detection accuracy
of the face area. The experimental results reveal that the proposed app can efficiently calculate the
number of people. The world is now seriously threatened by the COVID-19 epidemic. The proposed
app can help quickly calculate the number of people, avoid crowd gathering, and cause the risk of
group infections
Face-recognition System Design and Manufacture
No full text[[abstract]]The theory of face recognition is mainly from the idea of feature vectors. The face image is converted into a series of numbers to form a feature vector. For a feature vector of a face image, its content includes various features, such as: face height, face width, average face color, lips width, and nose height. The face-recognition operation is to compare the input of the feature vector of a face image with a large number of feature vectors in a dataset to identify the personal identity.The face recognition system in this paper is mainly implemented in the Python environment. Face generation is achieved by selfie of face. The image is cut to retain the part of the face, and stored in the database. Comparing the face image input with those saved in the dataset, if the similarity value passes the threshold value of true. The program will show the face image identification. Otherwise, the system will display a false message. The face recognition system is completed and the experimental results show the correct face-recognition. Finally the laptop Webcam is used to take the face image, and the result of comparison is also correct
Optimal Energy-Centric Resource Allocation and Offloading Scheme for Green Internet of Things Using Machine Learning
No full text[[abstract]]Resource allocation and offloading in green Internet of Things (IoT) relies on the multi-level heterogeneous platforms. The energy expenses of the platform determine the reliability of green IoT based services and applications. This manuscript introduces a decisive energy management scheme for optimal resource allocation and offloading along with energy constraints. This scheme handles both the allocation and energy-cost in a balanced manner through deterministic task offloading. In particular, resource allocation solution for non-delay tolerant green IoT applications is focused by confining the failures of discrete tasks through neural learning. The dropout process augmented with the learning process improves the feasible conditions for resource handling and task offloading among the active IoT service providers. Through extensive simulations the performance of the proposed scheme is analyzed and energy consumption, failure rate, processing, and completion time metrics are used for a comparative study. Further, the optimal utilization and on-demand dissipation of such stored resources help to improve the sustainability of green power and communication technologies in the smart city environment
PANNER: POS-Aware Nested Named Entity Recognition Through Heterogeneous Graph Neural Network
No full text[[abstract]]Nested named entity recognition (Nested NER) in knowledge graph (KG) aims at obtaining all meaningful entities, including nested entities for sentences in longer text region. Those obtained entities are to facilitate downstream applications, such as relation extraction, entity resolution, and coreference resolution. This task, however, is challenging not only because of the demand to detect the boundary of the entity but also due to the complexity of those hierarchically nested entities. Since a substantial amount of work has been made to Flat NER (or Nested NER), a few of them can explicitly acquire the position of the entity and utilize the grammatical construction of text. In this work, we propose PANNER, a POS-aware Nested NER model, to solve all the above issues. Specifically, we first construct a heterogeneous graph by introducing the part-of-speech (POS) information of the word. Second, we design a dilated random walk (DRW) algorithm based on a grammatical path to sample a fixed size of neighbors for each node. Third, we aggregate the message from different types of neighbors through an attention mechanism. Finally, we use a bidirectional decoding module to recognize and categorize all the flat and nested entities based on the node embedding in a layer-wise manner. Our extensive experiments show the effectiveness of PANNER in both flat and nested NER