Objective To explore the influencing factors of the usage behavior of the scientific research management system and provide references for hospitals in constructing scientific research management systems. Methods Data were collected through questionnaires in April 2024. Based on the unified theory of acceptance and use of technology (UTAUT), the information system success model, and the self-efficacy theory, a research model on the influencing factors of the usage behavior of the scientific research management system among medical staff was constructed from the dual perspectives of users and information systems. The structural equation model was utilized to explore the influencing factors of the usage behavior of the scientific research management system. Results A total of 527 questionnaires were collected. Among them, there were 157 males and 370 females. The overall Cronbach α coefficient of the questionnaire was 0.916, and the KMO value was 0.896. For Bartlett’s test of sphericity (P<0.001). The composite reliability of each latent variable was greater than 0.7, and the average variance extracted was greater than 0.5. Therefore, this questionnaire had good reliability and validity. The research showed that information quality, performance expectancy, effort expectancy, and system quality all had significant positive impacts on the usage intention of users of the scientific research management system (P<0.05). Meanwhile, facilitating conditions and usage intention both had significant positive impacts on the usage behavior of users (P<0.05). Conclusions The construction of the scientific research management system should be guided by management needs, comprehensively sort out the general scientific research work needs of medical staff. Through the apply information-based means, various forms of training, and strengthening policy guidance, the aim is to improve the intelligence level of system operations, enhance the convenience of user self-service, and promote the effective construction of the ecosystem of the scientific research management system.
With the range of application of computational biology and systems biology gradually expanding, the complexity of the bioprocess models is also increased. To address this difficult problem, it is required to introduce positive alternative analysis method to cope with it. Taking the dynamic model of the epidemic control process as research object, we established an evaluation model in our laboratory. Firstly, the model was solved with nonlinear programming method. The results were shown to be good. Based on biochemical systems theory, the ODE dynamic model was transformed into S-system. The eigen values of the model showed that the system was stable and contained oscillation phenomenon. Next the sensitivities of rate constant and logarithmic gains of the three key parameters were analyzed, as well as the robust of the system. The result indicated that the biochemical systems theory could be applied in different fields more widely.
Abstract There have been many types of bone-grafting operation dealing with the congenital pseudarthrosis of the tibia (CPAT), but the failure rate is fairly high. Since 1990, 2 children with CPAT, who had received repeated bone-grafting operation in failure, were treatedaccordingto the Ilizarovs theory and its related technique. The essentials of the operation were: (1) Thorough resection of abnormal bone tissues at pseudarthrosis might freshen the ends of the bone and facilitate bone union. (2) The firm fixation and constant compression force to the bone ends might promote bone healing. (3) The tibial lengthening was performed by osteotomy at the upper tibia. The pseudarthrosis was united in 2～3 months after operation. The patients were followed up from 1 to 3 years, and it was found that the remodelling of thebone was good, no recurrence occured. The advantages were: (1) The bone grafting was no longer necessary. (2) It could give a chance to equalizethe limb length. (3) It could enable early weight bearing and functional exercise.
Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.
Since 2015, when the day surgery mode was officially reckoned and supported by the National Health Commission, the day surgery model has entered the new period of rapid development. But at the same time, challenges in the vacancy of the evaluation indexes of the medical quality and safety of day surgery still pose obstacles to its growth. At present, there is no nationally unified evaluating index or appraising system for the day surgery-related medical quality and safety. In this paper, based on structure-process-outcome theory, the day surgery practice and involved researching literature were retrieved, reviewed, and analyzed. Also, the practice model at West China Hospital of Sichuan University (a pioneer day surgery hospital in China) was comprehensively compared with the National Clinical Improvement System. From the aspect of day surgery medical quality and safety evaluation indicators, it is hoped to provide an evidence-based method and evaluation of day surgery, and a theoretical basis for establishing policies and data reference.
Developmental and epileptic encephalopathy (DEE) is a group of diseases that severely affects the neurological development of children, characterized by frequent seizures and significant neurodevelopmental impairments. These diseases not only impact the quality of life of affected children but also impose a heavy burden on families and society. In recent years, the development of brain network theory has provided a new perspective on understanding the pathological mechanisms of DEE, especially the role of structural and functional brain networks in the process of epilepsy. This review systematically summarized the research progress of structural and functional brain networks in DEE, highlighted their importance in seizure activity, disease progression, and prognosis evaluation.
With the change of COVID-19, the prevention and control of COVID-19 infection epidemic entered a new stage in December 2022. How to quickly complete the emergency treatment of a large number of patients in a short period of time, and ensure that patients in emergency department can get rapid and effective medical treatment has always been an urgent problem that emergency department need to solve. The Department of Emergency Medicine of West China Hospital of Sichuan University has adopted patient-oriented management measures based on the core idea of the new public management theory, and has achieved remarkable results. Therefore, this article summarizes the workflow and nursing management strategies of the emergency department rescue area of West China Hospital of Sichuan University in dealing with the batch treatment of COVID-19 infected patients, including optimizing and correcting the environment layout of the ward, implementing the “secondary triage” mode in the rescue area, adding an inter-hospital referral platform for critical patients with COVID-19 emergency, building a conventional COVID-19 reserve material repository in the emergency department, setting up a field office for multi-department joint emergency admission service, optimizing emergency transport services for patients with COVID-19, scientific scheduling and reasonable human resource management, and providing humanistic care for employees, in order to provide reference for the management practice of the emergency department.
Objective To investigate the differences in the topology of functional brain networks between populations with good spatial navigation ability and those with poor spatial navigation ability. Methods From September 2020 to September 2021, 100 college students from PLA Army Border and Coastal Defense Academy were selected to test the spatial navigation ability. The 25 students with the highest spatial navigation ability were selected as the GN group, and the 25 with the lowest spatial navigation ability were selected as the PN group, and their resting-state functional MRI and 3D T1-weighted structural image data of the brain were collected. Graph theory analysis was applied to study the topology of the brain network, including global and local topological properties. Results The variations in the clustering coefficient, characteristic path length, and local efficiency between the GN and PN groups were not statistically significant within the threshold range (P>0.05). The brain functional connectivity networks of the GN and PN groups met the standardized clustering coefficient (γ)>1, the standardized characteristic path length (λ)≈1, and the small-world property (σ)>1, being consistent with small-world network property. The areas under curve (AUCs) for global efficiency (0.22±0.01 vs. 0.21±0.01), γ value (0.97±0.18 vs. 0.81±0.18) and σ value (0.75±0.13 vs. 0.64±0.13) of the GN group were higher than those of the PN group, and the differences were statistically significant (P<0.05); the between-group difference in AUC for λ value was not statistically significant (P>0.05). The results of the nodal level analysis showed that the AUCs for nodal clustering coefficients in the left superior frontal gyrus of orbital region (0.29±0.05 vs. 0.23±0.07), the right rectus gyrus (0.29±0.05 vs. 0.23±0.09), the middle left cingulate gyrus and its lateral surround (0.22±0.02 vs. 0.25±0.02), the left inferior occipital gyrus (0.32±0.05 vs. 0.35±0.05), the right cerebellar area 3 (0.24±0.04 vs. 0.26±0.03), and the right cerebellar area 9 (0.22±0.09 vs. 0.13±0.13) were statistically different between the two groups (P<0.05). The differences in AUCs for degree centrality and nodal efficiency between the two groups were not statistically significant (P>0.05). Conclusions Compared with people with good spatial navigation ability, the topological properties of the brains of the ones with poor spatial navigation ability still conformed to the small-world network properties, but the connectivity between brain regions reduces compared with the good spatial navigation ability group, with a tendency to convert to random networks and a reduced or increased nodal clustering coefficient in some brain regions. Differences in functional brain network connectivity exist among people with different spatial navigation abilities.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.
Brain functional network changes over time along with the process of brain development, disease, and aging. However, most of the available measurements for evaluation of the difference (or similarity) between the individual brain functional networks are for charactering static networks, which do not work with the dynamic characteristics of the brain networks that typically involve a long-span and large-scale evolution over the time. The current study proposes an index for measuring the similarity of dynamic brain networks, named as dynamic network similarity (DNS). It measures the similarity by combining the “evolutional” and “structural” properties of the dynamic network. Four sets of simulated dynamic networks with different evolutional and structural properties (varying amplitude of changes, trend of changes, distribution of connectivity strength, range of connectivity strength) were generated to validate the performance of DNS. In addition, real world imaging datasets, acquired from 13 stroke patients who were treated by transcranial direct current stimulation (tDCS), were used to further validate the proposed method and compared with the traditional similarity measurements that were developed for static network similarity. The results showed that DNS was significantly correlated with the varying amplitude of changes, trend of changes, distribution of connectivity strength and range of connectivity strength of the dynamic networks. DNS was able to appropriately measure the significant similarity of the dynamics of network changes over the time for the patients before and after the tDCS treatments. However, the traditional methods failed, which showed significantly differences between the data before and after the tDCS treatments. The experiment results demonstrate that DNS may robustly measure the similarity of evolutional and structural properties of dynamic networks. The new method appears to be superior to the traditional methods in that the new one is capable of assessing the temporal similarity of dynamic functional imaging data.