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This paper introduces a novel approach for identifying dynamic triadic transformation processes, applied to five networks: three undirected and two directed. Our method significantly enhances the prediction accuracy of network ties. While balance theory offers insights into evolving patterns of triadic structures, its effects on overall network dynamics remain underexplored. Existing research often neglects the interaction between micro-level balancing mechanisms and overall network behavior. To bridge this gap, we develop a method for detecting dynamic triadic structures in signed networks, categorizing triangle transformations over two consecutive periods into formation and breakage. We analyze the impact of these structures on temporal network evolution by incorporating them into exponential random graph models across five networks of varying size, density, and directionality. To address the complexity of multi-layer networks derived from signed networks, we modify the temporal exponential random graph model framework. Our method significantly improves out-of-sample prediction accuracy for network ties, with additional predictive power from incorporating negative network information. These findings highlight the importance of considering the triadic transformation processes of balance triangles in studying temporal networks, validated across diverse datasets, warranting further research.

Gaussian random field theory has been used extensively for correcting the multiple comparisons problem in neuroimaging over the past few decades. Traditionally the global maximum Xmax of the field is used as the test statistic for thresholding, and it was proved to be the likelihood ratio test statistic when testing one signal in a Gaussian scale space random field. Nonetheless, it is not uncommon to test for more than one signal in practice. Hence, the primary purpose of the current study was to propose a new likelihood ratio test statistic Ymax for testing two signals simultaneously in fMRI images based on Gaussian random field theory. Monte Carlo simulation was used to approximate the probability of Ymax through the empirical distribution in two-dimensional images and its power was also assessed under different conditions, varying the levels of distance, amplitude, and scale of the signals. This study also sought to explore the result in scale space where the width of smoothing kernel was added as an extra dimension. Critical values were successfully obtained for Ymax using simulation. In scale space, the thresholds were more stringent than the ones with fixed kernel width, but it also revealed that the power of scale space Ymax was higher. In both scale space and fixed smoothing width, distance, amplitude and scale of the signals all had effect on the power of Ymax to some extent. Nonetheless, Ymax did not seem to surpass the other conventional test statistics in terms of power. The reason could be the limited conditions being simulated in the present study. Further investigation is required to provide more information about the behavior of Ymax.

Artificial intelligence (AI) for gastric cancer diagnosis has been discussed in recent years. The role of AI in early gastric cancer is more important than in advanced gastric cancer since early gastric cancer is not easily identified in clinical practice. However, to our knowledge, past syntheses appear to have limited focus on the populations with early gastric cancer. The purpose of this study is to evaluate the diagnostic accuracy of AI in the diagnosis of early gastric cancer from endoscopic images. We conducted a systematic review from database inception to June 2020 of all studies assessing the performance of AI in the endoscopic diagnosis of early gastric cancer. Studies not concerning early gastric cancer were excluded. The outcome of interest was the diagnostic accuracy (comprising sensitivity, specificity, and accuracy) of AI systems. Study quality was assessed on the basis of the revised Quality Assessment of Diagnostic Accuracy Studies. Meta-analysis was primarily based on a bivariate mixed-effects model. A summary receiver operating curve and a hierarchical summary receiver operating curve were constructed, and the area under the curve was computed. We analyzed 12 retrospective case control studies (n=11,685) in which AI identified early gastric cancer from endoscopic images. The pooled sensitivity and specificity of AI for early gastric cancer diagnosis were 0.86 (95% CI 0.75-0.92) and 0.90 (95% CI 0.84-0.93), respectively. The area under the curve was 0.94. Sensitivity analysis of studies using support vector machines and narrow-band imaging demonstrated more consistent results. For early gastric cancer, to our knowledge, this was the first synthesis study on the use of endoscopic images in AI in diagnosis. AI may support the diagnosis of early gastric cancer. However, the collocation of imaging techniques and optimal algorithms remain unclear. Competing models of AI for the diagnosis of early gastric cancer are worthy of future investigation. PROSPERO CRD42020193223; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=193223.

Background. Parkinson’s disease (PD) is a common neurodegenerative disease associated with accumulation of misfolding proteins and increased neuroinflammation, which may further impair the glymphatic system. The purpose of this study was to utilize diffusion tensor image analysis along the perivascular space (DTI-ALPS) to evaluate glymphatic system activity and its relationship with systemic oxidative stress status in PD patients. Methods. Magnetic resonance imaging and neuropsychological tests were conducted on 25 PD patients with normal cognition (PDN), 25 PD patients with mild cognitive impairment (PD-MCI), 38 PD patients with dementia (PDD), and 47 normal controls (NC). Oxidative stress status was assessed by plasma DNA level. Differences in ALPS-index among the subgroups were assessed and further correlated with cognitive functions and plasma DNA levels. Results. The PD-MCI and PDD groups showed significantly lower ALPS-index compared to normal controls. The ALPS-index was inversely correlated with plasma nuclear DNA, mitochondrial DNA levels, and cognitive scores. Conclusions. Lower diffusivity along the perivascular space, represented by lower ALPS-index, indicates impairment of the glymphatic system in PD patients. The correlation between elevated plasma nuclear DNA levels and lower ALPS-index supports the notion that PD patients may exhibit increased oxidative stress associated with glymphatic system microstructural alterations.

Background Systemic inflammation and white matter (WM) alterations have been noted as effects of Parkinson’s disease (PD). This study sought to evaluate WM integrity in PD patients using diffusion tensor imaging (DTI) and to assess its relationship with systemic inflammation. Methods Sixty-six patients with PD (23 men and 43 women) and 67 healthy volunteers (29 men and 38 women) underwent blood sampling to quantify inflammatory markers and DTI scans to determine fiber integrity. The inflammatory markers included leukocyte apoptosis, as well as cellular and serum adhesion molecules, in each peripheral blood sample. DTI-related indices [including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD)] were derived from DTI scans. The resulting FA maps were compared using voxel-based statistics to determine differences between the PD and control groups. The differences in the DTI indices, clinical severity, and inflammatory markers were correlated. Results Exploratory group-wise comparison between the two groups revealed that the PD patients exhibited extensive DTI index differences. Low FA accompanied by high RD and MD, without significant differences in AD, suggesting a demyelination process, were found in the parietal, occipital, cerebellar, and insular WM of the PD patients. The declined DTI indices were significantly correlated with increased clinical disease severity, adhesion molecules, and leukocyte apoptosis. Conclusions Patients with PD experience WM integrity damage in vulnerable regions, and these impairments are associated with increased disease severity and systemic inflammation. The possible interactions among them may represent variant neuronal injuries and their consequent processes in PD.

ObjectivesThe aim of this study was to evaluate the relationship between cognitive impairment and brain perfusion using arterial spin labelling (ASL) in end-stage renal disease (ESRD) patients undergoing PD.MethodsESRD patients undergoing PD were recruited. Laboratory screening, neuropsychological tests and ASL magnetic resonance imaging (MRI) were conducted prior to and after 6 months of PD. Age- and sex-matched normal subjects without ESRD served as the control group. Comparisons of regional CBF between ESRD patients before or after undergoing PD and normal controls were performed. Correlations between biochemical, neuropsychological and CBF data were also conducted to evaluate the relationships.ResultsESRD patients showed poor performance in many of the neuropsychological tests; PD improved cognition in some domains. Pre-PD patients had higher mean CBF than post-PD patients and normal controls, but no significant difference was found between the normal controls and post-PD patients. Negative correlations were observed pre-PD (regional CBF in left hippocampus vs. perseverative responses, r = -0.662, p = 0.014), post-PD (mean CBF vs. haemoglobin level, r = -0.766, p = 0.002), and before and after PD (change in CBF in the left putamen vs. change in haematocrit percentage, r = -0.808, p = 0.001).ConclusionBefore PD, ESRD patients had increased cerebral perfusion that was related to poorer executive function, especially in the left hippocampus. Post-PD patients performed better in some cognitive test domains than pre-PD patients. The degree of anaemia, i.e., haemoglobin level or haematocrit percentage, might predict cognitive impairment in PD patients.Key Points• In this study, ESRD patients before PD had cerebral hyperperfusion that was related to poorer executive function.• Post-PD patients performed better in some cognitive test domains than pre-PD patients did.• The degree of anaemia might predict cognitive impairment in PD patients.

Pulmonary rehabilitation (PR) effectively improves symptoms and exercise ability in patients with stable chronic obstructive pulmonary disease (COPD). However, the effectiveness and timing of early PR on hospitalized patients with acute exacerbation of COPD (AECOPD) is still debated. This study conducted a meta-analysis to compare the outcome benefits between early PR and usual care for patient hospitalized due to AECOPD. A systematic search was performed for retrieving randomized control trials (RCTs) from the PubMed, Embase, and Cochrane library until November 2021. RCTs reporting early PR for AECOPD with hospitalization, either during admission or within four weeks of discharge, were enrolled for systematic review and meta-analysis. Twenty RCTs (1274 participants) were included. Early PR showed significantly improved readmission rate (ten trials, risk ratio 0.68, 95% confidence interval (CI) 0.50-0.92), 6-minute walking distance (6MWD, twelve trials, MD 59.73, 95% CI 36.34-83.12), St George's Respiratory Questionnaire score (eight trials, MD -10.65, 95% CI -14.78 to -6.52), Borg score (eight trials, MD -0.79, 95% CI -1.26 to -0.32), and modified Medical Research Council dyspnea scale (eight trials, MD -0.38, 95% CI -0.5 to -0.25). However, the trend of mortality (six trials, risk ratio 0.72, 95% CI 0.39-1.34) benefit was not significant. The subgroup analysis showed non-significant trends of better effect in early PR during admission than those after discharge for outcomes of 6MWD, quality of life, and dyspnea. However, non-significant trends of less benefits on mortality and readmission rate were found in early PR during the admission. Overall, early PR is beneficial for AECOPD with hospitalization, and there was no significant outcome difference between PR initiated during admission or within 4 weeks of discharge.

Background Systemic inflammation, neurocognitive impairments, and morphologic brain changes are associated with obstructive sleep apnea (OSA). Understanding their longitudinal evolution and interactions after surgical treatment provides clues to the pathogenesis of cognitive impairment and its reversibility. In the present study, we investigate clinical disease severity, systemic inflammation, cognitive deficits, and corresponding gray matter volume (GMV) changes in OSA, and the modifications following surgery. Methods Twenty-one patients with OSA (apnea-hypopnea index, AHI > 5) and 15 healthy volunteers (AHI < 5) underwent serial evaluation, including polysomnography, flow cytometry for leukocyte apoptosis categorization, cognitive function evaluation, and high-resolution brain scan. Disease severity, leukocyte apoptosis, cognitive function, and imaging data were collected to assess therapeutic efficacy 3 months after surgery. Results Pre-operatively, patients presented with worse cognitive function, worse polysomnography scores, and higher early leukocyte apoptosis associated with increased insular GMV. There was reduced GMV in the anterior cingulate gyrus before and after surgery in the cases compared to that in controls, suggesting an irreversible structural deficit. Post-operatively, there were significant improvements in different cognitive domains, including attention, executive and visuospatial function, and depression, and in early leukocyte apoptosis. There was also a significant decrease in GMVs after treatment, suggesting recovery from vasogenic edema in the precuneus, insula, and cerebellum. Improvement in early leukocyte apoptosis post-surgery predicted better recovery of precuneus GMV. Conclusions In OSA, increased disease severity and systemic inflammation can alter GMV in vulnerable regions. Surgical treatment may improve disease severity and systemic inflammation, with subsequent recovery in brain structures and functions.

The COVID-19 pandemic has significantly affected health care professionals, especially nurses, who have experienced elevated levels of stress, burnout, and physical health challenges. In the postpandemic era, supporting their well-being is crucial. Gamification, which is the application of game design elements in nongame contexts, has emerged as a promising strategy to promote engagement in health behaviors. This study explores the use of a gamified mobile app to support self-health management among nurses recovering from the COVID-19 experience. This study aimed to evaluate the preliminary efficacy of a gamified mobile app for promoting self-health management among nurses who experienced the COVID-19 pandemic. The study examined whether gamification could enhance engagement, improve physical health outcomes, and encourage sustainable behavior change. A single-arm pre-post intervention study was conducted using a user-centered design. The app was developed based on the Octalysis framework and goal-setting theory, incorporating personalized exercise prescriptions and health monitoring features. Nurses from a regional hospital in Hsinchu, Taiwan, participated in the 8-week intervention. Data were collected through interviews, pre- and postintervention surveys, and app usage analytics. Key outcomes included changes in step counts, BMI, and user engagement. After the intervention, BMI classification improved significantly. The proportion of participants classified as obese decreased from 38.5% (90/234) to 13.7% (32/234), and the proportion of those classified as overweight increased from 24.8% (58/234) to 34.6% (81/234). Overall, the combined proportion of overweight or obese participants declined from 63.2% (148/234) to 48.3% (113/234), and that of participants with normal BMI increased from 18.4% (43/234) to 33.8% (79/234) (χ =29.98; P<.001). Octalysis tool results showed strong motivational engagement, with the highest scores in development and accomplishment (mean 7.29), epic meaning and calling (mean 7.05), and empowerment of creativity and feedback (mean 6.55). The gamified mobile app demonstrated promising efficacy in enhancing self-health management among nurses in the post-COVID era by increasing physical activity and improving BMI. Gamification elements, such as achievement, purpose, and feedback, were effective in sustaining engagement. Further studies are recommended to assess long-term outcomes and broader applicability.

Despite the distant metastasis of cervical cancer cells being a prominent cause of mortality, neither the metastasis capacity nor the in vitro conditions mimicking adhesion of cervical cancer cells to endothelial cells have been fully elucidated. Circulating metastatic cancer cells undergo transendothelial migration and invade normal organs in distant metastasis; however, the putative molecular mechanism remains largely uncertain. In this study, we describe the use of an in vitro parallel-plate flow chamber to simulate the dynamic circulation stress on cervical cancer cells and elucidate their vascular adhesion and metastasis. We isolate the viable and shear stress-resistant (SSR) cervical cancer cells for mechanistic studies. Remarkably, the identified SSR-HeLa and SSR-CaSki exhibited high in vitro adhesive and metastatic activities. Hence, a consistently suppressed miR-128 level was revealed in SSR cell clones compared to those of parental wild-type (WT) cells. Overexpressed miR-128 attenuated SSR-HeLa cells’ adherence to human umbilical cord vein endothelial cells (HUVECs); in contrast, suppressed miR-128 efficiently augmented the static adhesion capacity in WT-HeLa and WT-CaSki cells. Hence, amplified miR-128 modestly abolished in vitro SSR-augmented HeLa and CaSki cell movement, whereas reduced miR-128 aggravated the migration speed in a time-lapse recording assay in WT groups. Consistently, the force expression of miR-128 alleviated the SSR-enhanced HeLa and CaSki cell mobility in a wound healing assay. Notably, miR-128 mediated SSR-enhanced HeLa and CaSki cells’ adhesion and metastasis through suppressed ITGA5, ITGB5, sLex, CEACAM-6, MMP9, and MMP23 transcript levels. Our data provide evidence suggesting that miR-128 is a promising microRNA that prevented endothelial cells’ adhesion and transendothelial migration to contribute to the SSR-enhanced adhesion and metastasis progression under a parallel-plate flow chamber system. This indicates that the nucleoid-based miR-128 strategy may be an attractive therapeutic strategy to eliminate tumor cells resistant to circulation shear flow, prevent vascular adhesion, and preclude subsequent transendothelial metastasis.