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Currently no study has investigated whether Web-based interactive technology can influence females to adopt healthy behaviors. We investigated how and under what conditions do Web-based interactivity influence vaccination intentions among young females.
In this randomized controlled trail, we conduct a 2 (mode of information presentation narrative vs. data visualization) × 2 (interactivity interactive information vs. noninteractive information) between-groups design. A total of 180 Chinese female undergraduate students who had never received HPV vaccination were randomly allocated to 4 experimental groups. Each participant was assessed for their information avoidance behavior and vaccination intention. The hypotheses were tested using a moderated mediation model. All analyses were performed using SPSS version 22.0 with probability set at 0.05 alpha level.
The indirect relationship between interactivity and behavioral intention though information avoidance was moderated by the mode of presentation. Under the narrative condition, interactivity (vs. non-interactivity) decreased information avoidance and increased the intention to receive HPV vaccination (B = -.23, SE = 0.10, P < 0.05). However, under data visualization condition, no significant difference was observed between the effects of interactivity and non-interactivity on intention.
The findings suggest that when young females experience difficulties in manipulating or understanding HPV-related information, their information-avoidance behavior is likely to increase. Rather than use interactive statistical or graphical information, young females are more likely to be persuaded by interactive narratives.
The findings suggest that when young females experience difficulties in manipulating or understanding HPV-related information, their information-avoidance behavior is likely to increase. Rather than use interactive statistical or graphical information, young females are more likely to be persuaded by interactive narratives.
Epilepsy was defined as an abnormal brain network model disease in the latest definition. From a microscopic perspective, it is also particularly important to observe the Mutual Information (MI) of the whole brain network based on different lead positions.
In this study, we selected EEG data from representative temporal lobe and frontal lobe epilepsy patients. Based on Phase Space Reconstruction and the calculation of MI indicator, we used Complex Network technology to construct a dynamic brain network function model of epilepsy seizure. At the same time, about the analysis of our network, we described the index changes and propagation paths of epilepsy discharge in different periods, and spatially monitors the seizure change process based on the analysis of the parameter characteristics of the complex network.
Our model portrayed the functional synergy between the various regions of the brain and the state transition during the seizure process. We also characterized the EEG synchronous propagation path and core nodes during seizures. The results shown the full node change path and the distribution of important indicators during the seizure process, which makes the state change of the seizure process more clearly.
In this study, we have demonstrated that synchronization-based brain networks change with time and space. The EEG synchronous propagation path and core nodes during epileptic seizures can provide a reference for finding the focus area.
In this study, we have demonstrated that synchronization-based brain networks change with time and space. The EEG synchronous propagation path and core nodes during epileptic seizures can provide a reference for finding the focus area.
Knee disorders are highly prevalent and may be a disabling condition. An accurate diagnosis is necessary to guide toward a rapid and efficient management of knee disorders. However, the ability to make a valid diagnosis is often complex for clinicians and evidence is mainly focused on clinician cognitive biases or errors produced during clinical reasoning. The aim of this secondary exploratory analysis is to identify patient-specific characteristics associated with diagnostic discordance between health care providers in making a diagnosis for a new knee disorder.
We performed a secondary analysis of a diagnostic study comparing the diagnostic ability of a physiotherapist to medical musculoskeletal specialists. Patients' socio-demographic, psychosocial and clinical characteristics were compared between the concordant and discordant diagnostic groups. Psychosocial symptoms were evaluated using the validated Kessler 6 (K6) questionnaire. We performed multivariable logistic regressions using the Bayesian Info diagnostic discordance. Other variables taken separately had less than 50% chance to be included in a model explaining diagnostic discordance and cannot be considered significant.
Our results suggest that depressive symptoms may increase the risk of knee diagnostic discordance. Clinicians may be more likely to make diagnostic errors and should be more cautious when evaluating patients with knee disorders suffering from psychological distress.
Our results suggest that depressive symptoms may increase the risk of knee diagnostic discordance. Clinicians may be more likely to make diagnostic errors and should be more cautious when evaluating patients with knee disorders suffering from psychological distress.
Semantic segmentation of white matter hyperintensities related to focal cerebral ischemia (FCI) and lacunar infarction (LACI) is of significant importance for the automatic screening of tiny cerebral lesions and early prevention of LACI. However, existing studies on brain magnetic resonance imaging lesion segmentation focus on large lesions with obvious features, such as glioma and acute cerebral infarction. Owing to the multi-model tiny lesion areas of FCI and LACI, reliable and precise segmentation and/or detection of these lesion areas is still a significant challenge task.
We propose a novel segmentation correction algorithm for estimating the lesion areas via segmentation and correction processes, in which we design two sub-models simultaneously a segmentation network and a correction network. The segmentation network was first used to extract and segment diseased areas on T2 fluid-attenuated inversion recovery (FLAIR) images. Consequently, the correction network was used to classify these areas at t test more types of tiny lesions at the same time.
Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists' reading of the electroencephalogram (EEG), which was time-consuming, inefficient, and subjective. In recent years, automatic epilepsy diagnosis of EEG by deep learning had attracted more and more attention. But the potential of deep neural networks in seizure detection had not been fully developed.
In this article, we used a one-dimensional convolutional neural network (1-D CNN) to replace the residual network architecture's traditional convolutional neural network (CNN). Moreover, we combined the Independent recurrent neural network (indRNN) and CNN to form a new residual network architecture-independent convolutional recurrent neural network (RCNN). Our model can achieve an automatic diagnosis of epilepsy EEG. Firstly, the important features of EEG were learned by using the residual network architecture of 1-D CNN. Then the rela seizures EEG.
Regional citrate anticoagulation (RCA) is an important local anticoagulation method during bedside continuous renal replacement therapy. To improve patient safety and achieve computer assisted dose monitoring and control, we took intensive care units patients into cohort and aiming at developing a data-driven machine learning model to give early warning of citric acid overdose and provide adjustment suggestions on citrate pumping rate and 10% calcium gluconate input rate for RCA treatment.
Patient age, gender, pumped citric acid dose value, 5% NaHCO
solvent, replacement fluid solvent, body temperature value, and replacement fluid PH value as clinical features, models attempted to classify patients who received regional citrate anticoagulation into correct outcome category. Four models, Adaboost, XGBoost, support vector machine (SVM) and shallow neural network, were compared on the performance of predicting outcomes. Prediction results were evaluated using accuracy, precision, recall and F1-score.
For ons to clinicians point-of-care.
Restoration of cervical lordosis after anterior discectomy and fusion is a desirable goal. Proper insertion of the vertebral distraction or Caspar pin can assist lordotic restoration by either putting the tips divergently or parallel to the index vertebral endplates. With inexperienced surgeons, the traditional free-hand technique for Caspar pin insertion may require multiple insertion attempts that may compromise the vertebral body and increase radiation exposure during pin localization. Our purpose is to perform a proof-of-concept, feasibility study to evaluate the effectiveness of a pin insertion aiming device for vertebral distraction pin insertion.
A Smith-Robinson approach and anterior cervical discectomy were performed from C3 to C7 in 10 human cadaveric specimens. Caspar pins were inserted using a novel pin insertion aiming device at C3-4, C4-5, C5-6, and C6-7. The angles between the cervical endplate slope and Caspar pin alignment were measured with lateral cervical imaging.
The average Superior Endplate-to-Caspar Pin angle (SE-CP) and the average Inferior Endplate-to-Caspar Pin angle (IE-CP) were 6.2 ± 2.0° and 6.3 ± 2.2° respectively. For the proximal pins, the SE-CP and the IE-CP were 4.0 ± 1.1°and 5.2 ± 2.4° respectively. For the distal pins, the SE-CP and the IE-CP were 7.7 ± 1.4° and 6.2 ± 2.0° respectively. No cervical endplate violations occurred.
The novel Caspar pin insertion aiming device can control the pin entry points and pin direction with the average SE-CP and average IE-CP of 6.2 ± 2.0° and 6.3 ± 2.2°, respectively. The study shows that the average different angles between the Caspar pin and cervical endplate are less than 7°.
The novel Caspar pin insertion aiming device can control the pin entry points and pin direction with the average SE-CP and average IE-CP of 6.2 ± 2.0° and 6.3 ± 2.2°, respectively. The study shows that the average different angles between the Caspar pin and cervical endplate are less than 7°.Objective To observe the efficacy and safety of humanized anti-BCMA chimeric antigen receptor modified (BCMA CAR) -T cell therapy after disease progression with their murine BCMA CAR-T cell therapy in patients with relapsed/refractory multiple myeloma (MM) . Methods Study participants underwent leukapheresis to collect T cells for BCMA CAR-T manufacturing. https://www.selleckchem.com/products/mv1035.html Patients were pretreated with intensive chemotherapy (fludarabine combined with cytarabine) before CAR-T therapy. Adverse events (AEs) , CAR DNA expansion, and cytokine were monitored. In vitro, transfection efficacy, specific cytotoxicity, and inflammatory response were detected when co-cultured with effector and target cells. Results Patient (PT) 1 and 2 achieved complete remission (CR) and disease stability at 3 months post murine CAR-T therapy. However, 16 and 18 months later, they experienced progression of disease (PD) , and patient 1 presented with extramedullary disease at PD. Both of the patients received humanized CAR-T therapy and achieved partial remission (PR) and very good partial remission (VGPR) post humanized CAR-T therapy.
Read More: https://www.selleckchem.com/products/mv1035.html
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