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This study delves into online assessments, focusing on their numerous advantages, including reducing paper usage and alleviating concerns surrounding the security of traditional examinations. The purpose of this study was to develop and test a model delineating the interplay between factors influencing the continuance intention to use online assessments and the influence on individual performance. A quantitative approach using an online survey was used to collect data from 222 graduate students from three major Palestinian universities. The research instrument was developed based on the finding of previous studies. Confirmatory factor analysis was employed to construct and validate the proposed model. The findings of this study revealed that perceived usefulness has a significant influence on the intention to continue using online assessment. The proposed model indicated that there is no direct or indirect relationship between perceived ease of use and the continuance intention to use online assessment. The main limitation of this study was its reliance on a purely quantitative approach. Therefore, a sequentional mixed methods approach van be a suggestion for future research and include all the higher education institutions in the Palestinian context.

Purpose: The goal of this study was to assess the potential real-world effect of the recently reported SC.24 trial on spine stereotactic body radiation therapy (SBRT) utilization. We estimated the proportion of patients treated with conventional radiation therapy (CRT) who would have been eligible for spine SBRT per trial inclusion criteria and analyzed the potential estimated increased costs to our institution. Methods and Materials: This was a retrospective review of patients who received spine CRT at our institution between August and October 2020. Data abstracted included demographics, SC.24 eligibility criteria, provider-reported pain response, and survival. A cost analysis and time survey was performed using institutional and provincial data. Results: Of 73 patients reviewed, 24 patients (33%) were eligible. The most common exclusion factors included irradiation of ≥3 consecutive spinal segments (n = 32, 44%), Eastern Cooperative Oncology Group performance status >2 (n = 17, 23%), and symptomatic spinal cord compression (n = 13, 18%). Of eligible patients, the mean age was 68.92 years, median spinal instability in neoplasia score was 8 (interquartile range, 7-9), and median Eastern Cooperative Oncology Group performance status was 2 (interquartile range, 1-2). The most common primary cancer types among eligible patients were lung (n = 10) and breast (n = 4). The median survival of eligible patients was 10 months (95% confidence interval, 4 months to not reached) with 58% surviving longer than 3 months. Of patients who had subjective pain documented after CRT, 54% had at least some response. The cost of spine SBRT was estimated at CA$4764.80 compared with $3589.10 for CRT, and tasks for spine SBRT took roughly 3 times as long as those for CRT. Conclusions: One-third of patients who received palliative spine CRT met eligibility criteria for SC.24. This possible expanded indication for spine SBRT can have a substantial effect on resource utilization. These data may be useful in guiding resource planning at institutions looking to commence a spine SBRT program.

Objectives: This study investigated science student teachers' self-esteem and their attitudes toward teaching science. Additionally, it explored the correlations between student teachers' self-esteem and various variables, such as gender, specialization, and accumulative average. Methods: The descriptive methodology was employed, and data was collected from a stratified random sample of 469 student teachers, completing their third and fourth academic years in science programs during the academic years 2020/2021. Two tools, a self-esteem scale and the attitudes toward science questionnaire, were used for data collection. Results: The findings indicated that student teachers' self-esteem and attitudes toward teaching science were moderate. Significant differences were observed in self-esteem and attitudes based on gender, accumulative average, and educational qualification. However, no significant differences were found based on the field of specialty. A significant correlational relationship between student teachers' self-esteem and attitudes toward teaching science was also established. Conclusions: The study highlights the importance of incorporating self-esteem into the professional standards for new science teachers and emphasizes the need to focus on educationally qualified graduates in science faculties who aspire to become science teachers.

ABSTRACT Clinical and in vivo studies have demonstrated a role for hepatitis B virus (HBV)-encoded HBsAg (hepatitis B surface antigen) in HBV-related hepatocellular carcinoma (HCC); however, the underlying mechanisms remain largely unknown. Here, we investigated the role of HBsAg in regulating long noncoding RNAs (lncRNAs) involved in HCC progression. Our analysis of microarray data sets identified LINC00665 as an HBsAg-regulated lncRNA. Furthermore, LINC00665 is upregulated in liver samples from HBV-infected patients as well as in HCC, specifically in HBV-related HCC liver samples. These findings were supported by our in vitro data demonstrating that HBsAg, as well as HBV, positively regulates LINC00665 in multiple HBV cell culture models. Next, we evaluated the oncogenic potential of LINC00665 by its overexpression and CRISPR interference (CRISPRi)-based knockdown in various cell-based assays. LINC00665 promoted cell proliferation, migration, and colony formation but inhibited cell apoptosis in vitro. We then identified the underlying mechanism of HBsAg-mediated regulation of LINC00665. We used immunofluorescence assays to show that HBsAg enhanced the nuclear translocation of NF-κB factors in HepG2 cells, confirming that HBsAg activates NF-κB. Inhibition of NF-κB signaling nullified HBsAg-mediated LINC00665 upregulation, suggesting that HBsAg acts through NF-κB to regulate LINC00665. Furthermore, the LINC00665 promoter contains NF-κB binding sites, and their disruption abrogated HBsAg-induced LINC00665 upregulation. Finally, HBsAg facilitated the enrichment of the NF-κB factors NF-κB1, RelA, and c-Rel in the LINC00665 promoter. Taken together, this work shows that HBsAg can drive hepatocarcinogenesis by upregulating oncogenic LINC000665 through the NF-κB pathway, thereby identifying a novel mechanism in HBV-related HCC. IMPORTANCE Hepatitis B virus (HBV) is a major risk factor for hepatocellular carcinoma (HCC). Numerous reports indicate an oncogenic role for HBV-encoded HBsAg; however, the underlying mechanisms are not well understood. Here, we studied the role of HBsAg in regulating lncRNAs involved in hepatocarcinogenesis. We demonstrate that HBsAg, as well as HBV, positively regulates oncogenic lncRNA LINC00665. The clinical significance of this lncRNA is highlighted by our observation that LINC00665 is upregulated in liver samples during HBV infection and HBV-related HCC. Furthermore, we show LINC00665 can drive hepatocarcinogenesis by promoting cell proliferation, colony formation, and cell migration and inhibiting apoptosis. Taken together, this work identified LINC00665 as a novel gene through which HBsAg can drive hepatocarcinogenesis. Finally, we show that HBsAg enhances LINC00665 levels in hepatocytes by activating the NF-κB pathway, thereby identifying a novel mechanism by which HBV may contribute to HCC.

Abstract Background Patients with high-risk prostate cancer are at increased risk of lymph node metastasis and are thought to benefit from whole pelvis radiotherapy (WPRT). There has been recent interest in the use of hypofractionated radiotherapy in treating prostate cancer. However, toxicity and cancer outcomes associated with hypofractionated WPRT are unclear at this time. This phase II study aims to investigate the impact in quality of life associated with hypofractionated WPRT compared to conventionally fractionated WPRT. Methods Fifty-eight patients with unfavourable intermediate-, high- or very high-risk prostate cancer will be randomized in a 1:1 ratio between high-dose-rate brachytherapy (HDR-BT) + conventionally fractionated (45 Gy in 25 fractions) WPRT vs. HDR-BT + hypofractionated (25 Gy in 5 fractions) WPRT. Randomization will be performed with a permuted block design without stratification. The primary endpoint is late bowel toxicity and the secondary endpoints include acute and late urinary and sexual toxicity, acute bowel toxicity, biochemical failure-, androgen deprivation therapy-, metastasis- and prostate cancer-free survival of the hypofractionated arm compared to the conventionally fractionated arm. Discussion To our knowledge, this is the first study to compare hypofractionated WPRT to conventionally fractionated WPRT with HDR-BT boost. Hypofractionated WPRT is a more attractive and convenient treatment approach, and may become the new standard of care if demonstrated to be well-tolerated and effective. Trial registration This trial was prospectively registered in ClinicalTrials.gov as NCT04197141 on December 12, 2019.

Nowadays, skin disease among humans has been a common disease, especially in America millions of people are suffering from various kinds of skin disease. Usually, these diseases have hidden dangers which lead to human not only lack of self-confidence and psychological depression but also a risk of skin cancer. Diagnosis of these kinds of diseases usually required medical experts with high-level instruments due to a lack of visual resolution in skin disease images. Moreover, manual diagnosis of skin disease is often subjective, time-consuming, and required more human effort. Thus, there is a need to develop a computer-aided system that automatically diagnoses the skin disease problem. Moreover, most of the existing works in skin disease used convolutional neural networks (CNN) with classical loss functions, which limit the model to learn discriminative features from skin images. Thus to address the above mention problem we proposed a new framework by fine-tuning layers of ResNet152 and InceptionResNet-V2 models with a triplet loss function. In the proposed framework, first, we learning the embedding from input images into Euclidean space by using deep CNN ResNet152 and InceptionResNet-V2 model. Second, we compute L-2 distance among corresponding images from euclidean space to learn discriminative features of skin disease images by using triplet loss function. Finally, classify the input images using these L-2 distances. Human face skin disease images used in the proposed framework are acquired from the Hospital in Wuhan China. Experiment results and their analysis shows the effectiveness of the proposed framework which achieve better accuracy than many existing works in skin disease tasks.

Abstract Background Stereotactic ablative radiotherapy (SABR) has emerged as a new treatment option for patients with oligometastatic disease. SABR delivers precise, high-dose, hypofractionated radiotherapy, and achieves excellent rates of local control for primary tumors or metastases. A recent randomized phase II trial evaluated SABR in a group of patients with a small burden of oligometastatic disease (mostly with 1–3 metastatic lesions), and found that SABR was associated with benefits in progression-free survival and overall survival. The goal of this phase III trial is to assess the impact of SABR in patients with 4–10 metastatic cancer lesions. Methods One hundred and fifty-nine patients will be randomized in a 1:2 ratio between the control arm (consisting of standard of care palliative-intent treatments), and the SABR arm (consisting of standard of care treatment + SABR to all sites of known disease). Randomization will be stratified by two factors: histology (Group 1: prostate, breast, or renal; Group 2: all others), and type of pre-specified systemic therapy (Group 1: immunotherapy/targeted; Group 2: cytotoxic; Group 3: observation). SABR is to be completed within 2 weeks, allowing for rapid initiation of systemic therapy. Recommended SABR doses are 20 Gy in 1 fraction, 30 Gy in 3 fractions, or 35 Gy in 5 fractions, chosen to minimize risks of toxicity. The primary endpoint is overall survival, and secondary endpoints include progression-free survival, time to development of new metastatic lesions, quality of life, and toxicity. Translational endpoints include assessment of circulating tumor cells, cell-free DNA, and tumor tissue as prognostic and predictive markers, including assessment of immunological predictors of response and long-term survival. Discussion This study will provide an assessment of the impact of SABR on clinical outcomes and quality of life, to determine if long-term survival can be achieved for selected patients with 4–10 oligometastatic lesions. Trial registration Clinicaltrials.gov identifier: NCT03721341. Date of registration: October 26, 2018.

Deep learning algorithms have achieved remarkable results in the natural language processing(NLP) and computer vision. Hence, a trend still going on to use these algorithms, such as convolution and recurrent neural networks, for text analytic task to extract useful information. Features extraction is one of the important reasons behind the success of these networks. Moreover passing features from one layer to another layer within the network and one network to another network have done. However multilevel and multitype features fusion remains unexplored in sentiment analysis. So, in this paper, we use three datasets to display the advantages of extracting and fusing multilevel as well as multitype features from different neural networks. Multilevel features are from different layers of the same network, and multitype features are from different network architectures. Experiment results demonstrate that the proposed model based on multilevel and multitype weighted features fusion outperforms than many exiting works with an accuracy of 80.2%, 48.2%, and 87.0% on MR, SST1, and SST2 datasets respectively.

Abstract Background Cytoreductive nephrectomy is thought to improve survival in metastatic renal cell carcinoma (mRCC). As many patients are ineligible for major surgery, we hypothesized that SABR could be a safe alternative. Methods In this dose-escalation trial, inoperable mRCC patients underwent SABR targeting the entire affected kidney. Toxicity (CTCAE v3.0), quality of life (QoL), renal function, and tumour response (RECIST v1.0) were assessed. Results Twelve patients of mostly intermediate (67%) or poor (25%) International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) prognostic class, median KPS of 70%, and median tumour size of 8.7 cm (range: 4.8–13.8) were enrolled in successive dose cohorts of 25 (n = 3), 30 (n = 6), and 35 Gy (n = 3) in 5 fractions. SABR was well tolerated with 3 grade 3 events: fatigue (2) and bone pain (1). QoL decreased for physical well-being (p = 0.016), but remained unchanged in other domains. SABR achieved a median tumour size reduction of − 17.3% (range: + 5.3 to − 54.4) at 5.3 months. All patients progressed systemically and median OS was 6.7 months. Crude median follow-up was 5.8 months. Conclusions In non-operable mRCC patients, renal-ablative SABR to 35 Gy in 5 fractions yielded acceptable toxicity, renal function preservation, and stable QoL. SABR merits further prospective investigation as an alternative to cytoreductive nephrectomy. Trial Registration ClinicalTrials.gov NCT02264548. Registered July 22 2014 – Retrospectively registered: https://clinicaltrials.gov/ct2/show/NCT02264548

This paper presents the analysis of real-life medical big data obtained from a hospital in central China from 2013 to 2015 for risk assessment of cerebral infarction disease. We propose a new recurrent convolutional neural network (RCNN)-based disease risk assessment multimodel by utilizing structured and unstructured text data from the hospital. In the proposed model, the convolutional layer becomes a bidirectional recurrent neural network by utilizing the intra-layer recurrent connection within the convolutional layer. Each neuron within convolutional layer receives feedforward and recurrent inputs from the previous unit and neighborhood, respectively. In addition to step-by-step recurrent operation, the region of context capture increases, thereby facilitating fine-grain feature extraction. Furthermore, we use a data parallelism approach over multimodel data during training and testing of the proposed model. Results show that the data parallelism approach leads to fast conversion speed. The RCNN-based model works differently from the traditional convolutional neural network and other typical methods. The proposed model exhibits a prediction accuracy of 96.02%, which is higher than those of typical existing methods.

In this paper, we propose a laser actuated microgripper that can be activated remotely for micromanipulation applications. The gripper is based on an optothermally actuated polymeric chevron-shaped structure coated with optimized metallic layers to enhance its optical absorbance. Gold is used as a metallic layer due to its good absorption of visible light. The thermal deformation of the chevron-shaped actuator with metallic layers is first modeled to identify the parameters affecting its behavior. Then, an optimal thickness of the metallic layers that allows the largest possible deformation is obtained and compared with simulation results. Next, microgrippers are fabricated using conventional photolithography and metal deposition techniques for further characterization. The experiments show that the microgripper can realize an opening of 40 µm, a response time of 60 ms, and a generated force in the order of hundreds of µN. Finally, a pick-and-place experiment of 120 µm microbeads is conducted to confirm the performance of the microgripper. The remote actuation and the simple fabrication and actuation of the proposed microgripper makes it a highly promising candidate to be utilized as a mobile microrobot for lab-on-chip applications.

Researchers have developed a cell stretching device to mimic the in vivo mechanical environment in vitro in order to investigate cell mechanotransduction. Cyclic stretch is involved in lengthening and relaxation phases. Cells may respond to mechanical stimulation rapidly within a few seconds, and sudden disruption of cell cytoskeletons may also occur at any point in any phase of cyclic stretch. However, until now, no research has been done to establish a method of collecting cell images at the two phases of cyclic stretch. Because image processing is time-consuming, it is difficult to adjust focus and collect high-resolution images simultaneously at the two phases during the process. In this study, a three-motorized-stage system was developed to meet the requirements. The results demonstrated that linear compensation is effective for cell imaging, and it is applicable to have a feed-forward control method without image processing. A method was then developed to determine the maximum displacement of the target in the horizontal and vertical directions, and the linear compensation waveforms were designed using the C program automatically and immediately before stretching. Further, the cyclic stretch was applied to cells using the three motorized stages, and clear phase-contrast cell imaging (30 fps) were obtained almost at any point in time. Detailed cell changes such as sudden disruption of cell–cell junctions, not only long-term cell response, were observed. Therefore, our study established a methodology to greatly improve the time resolution of imaging of cyclic stretch for the research of detailed cellular mechanotransduction.

We propose a microrobotic platform for single motile microorganism observation and investigation. The platform utilizes a high-speed online vision sensor to realize real-time observation of a microorganism under a microscopic environment with a relatively high magnification ratio. A microfluidic chip was used to limit the vertical movement of the microorganism and reduce the tracking system complexity. We introduce a simple image processing method, which utilizes high-speed online vision characteristics and shows robustness against image noise to increase the overall tracking performance with low computational time consumption. The design also considers the future integration of a stimulation system using microtools. Successful long-time tracking of a freely swimming microorganism inside of a microfluidic chip for more than 30 min was achieved notwithstanding the presence of noises in the environment of the cell. The specific design of the platform, particularly the tracking system, is described, and the performance is evaluated and confirmed through basic experiments. The potential of the platform to apply mechanical stimulation to a freely swimming microorganism is demonstrated by using a 50-µm-thick microtool. The proposed platform can be used for long-term observation and to achieve different kinds of stimulations, which can induce new behavior of the cells and lead to unprecedented discoveries in biological fields.