Impact Of Dynamic Changes Research Articles

Elicitation of Physician Opinions of the Impact of Dynamic Changes in Biomarkers on Perceived Relapse Propensity in ANCA-Associated Vasculitis: Impact of Individual Expert and Patient Characteristics

Elicitation of Physician Opinions of the Impact of Dynamic Changes in Biomarkers on Perceived Relapse Propensity in ANCA-Associated Vasculitis: Impact of Individual Expert and Patient Characteristics

Exposure of cumulative atherogenic index of plasma and the development of prediabetes in middle-aged and elderly individuals: evidence from the CHARLS cohort study

BackgroundThe impact of dynamic changes in the degree of atherosclerosis on the development of prediabetes remains unclear. This study aims to investigate the association between cumulative atherogenic index of plasma (CumAIP) exposure during follow-up and the development of prediabetes in middle-aged and elderly individuals.MethodsA total of 2,939 prediabetic participants from the first wave of the China Health and Retirement Longitudinal Study (CHARLS) were included. The outcomes for these patients, including progression to diabetes and regression to normal fasting glucose (NFG), were determined using data from the third wave. CumAIP was calculated as the ratio of the average AIP values measured during the first and third waves to the total exposure duration. The association between CumAIP and the development of prediabetes was analyzed using multivariable Cox regression and restricted cubic spline (RCS) regression.ResultsDuring a median follow-up period of 3 years, 15.21% of prediabetic patients progressed to diabetes, and 22.12% regressed to NFG. Among the groups categorized by CumAIP quartiles, the proportion of prediabetes progressing to diabetes gradually increased (Q1: 10.61%, Q2: 13.62%, Q3: 15.65%, Q4: 20.95%), while the proportion regressing to NFG gradually decreased (Q1: 23.54%, Q2: 23.71%, Q3: 22.18%, Q4: 19.05%). Multivariable-adjusted Cox regression showed a significant positive linear correlation between high CumAIP exposure and prediabetes progression, and a significant negative linear correlation with prediabetes regression. Furthermore, in a stratified analysis, it was found that compared to married individuals, those who were unmarried (including separated, divorced, widowed, or never married) had a relatively higher risk of CumAIP-related diabetes.ConclusionCumAIP is closely associated with the development of prediabetes. High CumAIP exposure not only increases the risk of prediabetes progression but also hinders its regression within a certain range. These findings suggest that monitoring and maintaining appropriate AIP levels may help prevent the deterioration of blood glucose levels.

Impact of dynamic changes of tumor marker in neoadjuvant chemotherapy-treated triple-negative gastric cancer patients: a multi-center study

BackgroundIndependent and valid prognostic predictors for locally advanced gastric cancer (LAGC) patients with non-elevated serum tumor markers (Triple-negative: CA199 < 37U/ml, CEA < 5 µg/ml and CA125 < 35U/ml) before and after neoadjuvant chemotherapy (NACT) remain unclear.MethodsA total of 352 LAGC patients treated with NACT(NLAGC) from two centers were included. Of the 156 were Triple-negative patients. CA72-4 trajectory groupings was defined as longitudinal changes in CA72-4 levels before and after NACT to identify different potential subgroups and to compare recurrence-free survival (RFS) and overall survival (OS) among subgroups. The predictive performance of the nomogram-trajectory was evaluated using the area under the receiver operating characteristic curve(AUC), decision curve analysis, and C-index.ResultsIn the Triple-negative patients, the Stable group had significantly worse 3-year OS than the Normal, Elevated, and Descend groups(3-year OS: 53.9% vs. 77.9% vs. 73.5% vs. 87.7%;P = 0.002). Cox multivariate analysis showed that CA72-4 trajectory groupings (Stable group: HR:3.442, 95%CI[1.574–7.528], P = 0.002) was an independent prognostic risk factor. In addition, the C-index and AUC values based on the nomogram-trajectory were significantly higher than those of ypTNM staging (C-index: 0.788 vs. 0.719,P < 0.001;AUC: 0.800 vs. 0.667,P < 0.001). Furthermore, The survival analysis revealed that the 3-year OS of the Low-Risk group of nomogram scores was significantly better than that of the High-Risk group(3-year OS:84.7% vs. 29.1%). And the Low-Risk group had the lower cumulative risk of recurrence (P < 0.001).ConclusionThe CA72-4 trajectory groupings were an independent prognostic factor for NLAGC Triple-negative patients. The predictive efficacy of the Nomogram-trajectory was significantly better than the ypTNM.

Time-Resolved Infrared Spectroscopic Evidence for Interfacial pH-Dependent Kinetics of Formate Evolution on Cu Electrodes.

By deployment of rapid-scan (second time scale) electrochemical FT-IR reflection-absorption spectroscopy, we studied the reduction of CO2 in 0.1 M Na2SO4 in deuterated water at a pD of 3.7. We report on the impact of dynamic changes in the bicarbonate equilibrium concentration in the vicinity of a polycrystalline Cu electrode, induced by step changes in applied electrode potential. We correlate these changes in interfacial composition and concentrations of dissolved species to the formation rate of formate, and provide evidence for the following conclusions: (i) the kinetics for the conversion of dissolved CO2 to formate (formic acid) are fast, (ii) bicarbonate is also converted to formate, but with less favorable kinetics, and (iii) carbonate does not yield any formate. These results reveal that formate formation requires (mildly) acidic conditions at the interface for CO2 to undergo a proton-coupled conversion step, and we postulate that bicarbonate reduction to formate is driven by catalytic hydrogenation via in situ formed H2. Interestingly CO was not observed, suggesting that the kinetics of the CO2 to CO reaction are significantly less favorable than formate formation under the experimental conditions (pH and applied potential). We also analyzed the feasibility of pulsed electrolysis to enhance the (average) rate of formation of formate. While a short positive potential pulse enhances the CO2 concentration, this also leads to the formation of basic copper carbonates, resulting in electrode deactivation. These observations demonstrate the potential of rapid-scan EC-IRRAS to elucidate the mechanisms and kinetics of electrochemical reactions, offering valuable insights for optimizing catalyst and electrolyte performance and advancing CO2 reduction technologies.

The relationship between imaging-based body composition abnormalities and long-term mortality in patients with liver cirrhosis

BackgroundEmerging evidence on cirrhosis suggests a close correlation between abnormality in body composition characteristics and poor prognosis. This study aimed to evaluate the impact of dynamic changes in body composition on the prognostic outcomes in patients with cirrhosis. MethodsThis retrospective analysis included 158 patients diagnosed as cirrhosis from January 2018 to August 2023. Skeletal muscle mass, muscle quality, visceral and subcutaneous adiposity were evaluated using computed tomography (CT) imaging at the third lumbar vertebra level. Competing risk model was performed four different body composition status (i.e., normal, only sarcopenia, only myosteatosis, and combined status) for liver-related mortality. We also explored the relationship between the dynamic change in body composition and long-term prognosis by applying Gray’s test. ResultsOf the 158 cirrhotic patients (mean [SD] age, 57.1 [12.6] years), sarcopenia was present in 85 (60.1 %) patients, while 22 (13.9 %) patients had sarcopenic obesity and 68 (43.0 %) had myosteatosis. Patients solely diagnosed with sarcopenia exhibited a higher mortality rate compared to those with normal body composition (Gray’s test, P=0.006), while patients solely diagnosed with myosteatosis or with a combination of sarcopenia and myosteatosis did not reach statistical significance (Gray’s test, P=0.076; P=0.140). Multivariable analysis also revealed that VSR (HR=1.10 [1.01∼1.20]; P=0.028), sarcopenia (HR=2.73 [1.20∼6.22], P=0.017) and myosteatosis (HR=2.39 [1.10∼5.18], P=0.028) were significant independent predictors of liver-related deaths. Otherwise, patients exhibiting aggravating body composition during follow-up period were associated with a significantly higher mortality risk compared to those with normal or remission body composition status (HR=7.63 [1.12∼51.14]; P=0.036). ConclusionProgressive alterations in body composition status appears to be associated with liver-related mortality in individuals with liver cirrhosis. Focusing on the management of skeletal muscle, along with visceral and subcutaneous adiposity, may contribute to improving the prognosis of cirrhotic patients.

Hypoalbuminemia is Highly Prevalent in Patients with Periprosthetic Joint Infection and Strongly Associated with Treatment Failure.

The role of hypoalbuminemia throughout the course of chronic periprosthetic joint infection (PJI) remains poorly understood. This study aimed to determine the prevalence and risk factors of hypoalbuminemia in periprosthetic joint infection (PJI) patients and to explore the association between hypoalbuminemia and treatment outcomes. This retrospective cohort study included 387 PJI cases who underwent two-stage exchange arthroplasty between January 2007 and August 2020, of which 342 were reimplanted. The mean follow-up period was 7.9 years. Multivariate logistic regression analyses were performed to identify risk factors for hypoalbuminemia and to assess the effect of hypoalbuminemia at 1st- and 2nd-stage exchange on the treatment outcome. Furthermore, the impact of dynamic changes in hypoalbuminemia was investigated. The prevalence of hypoalbuminemia at 1st- and 2nd-stage exchange was 22.2% and 4.7%, respectively. Patients with age ≥ 68 years and those with isolation of Staphylococcus aureus, Streptococcus, or Gram-negative bacteria exhibited a higher risk of hypoalbuminemia. Hypoalbuminemia at 1st-stage was significantly related to treatment failure (OR = 3.3), while hypoalbuminemia at 2nd-stage raised the OR to 10.0. Patients with persistent hypoalbuminemia at both the 1st- and 2nd-stage exchanges had a significantly higher rate of treatment failure than patients with hypoalbuminemia at the 1st-stage but normal albumin levels at the 2nd-stage exchange (55.6% vs 20.0%, p = 0.036). One in five patients with chronic PJI exhibits hypoalbuminemia. Hypoalbuminemia is more likely to develop in patients of advanced age and those infected by specific highly virulent organisms. Also, our results highlight the close association between hypoalbuminemia and treatment outcomes.

Evolving brain network dynamics in early childhood: Insights from modular graph metrics

Modular dynamic graph theory metrics effectively capture the patterns of dynamic information interaction during human brain development. While existing research has employed modular algorithms to examine the overall impact of dynamic changes in community structure throughout development, there is a notable gap in understanding the cross-community dynamic changes within different functional networks during early childhood and their potential contributions to the efficiency of brain information transmission. This study seeks to address this gap by tracing the trajectories of cross-community structural changes within early childhood functional networks and modeling their contributions to information transmission efficiency. We analyzed 194 functional imaging scans from 83 children aged 2 to 8 years, who participated in passive viewing functional magnetic resonance imaging sessions. Utilizing sliding windows and modular algorithms, we evaluated three spatiotemporal metrics—temporal flexibility, spatiotemporal diversity, and within-community spatiotemporal diversity—and four centrality metrics: within-community degree centrality, eigenvector centrality, between-community degree centrality, and between-community eigenvector centrality. Mixed-effects linear models revealed significant age-related increases in the temporal flexibility of the default mode network (DMN), executive control network (ECN), and salience network (SN), indicating frequent adjustments in community structure within these networks during early childhood. Additionally, the spatiotemporal diversity of the SN also displayed significant age-related increases, highlighting its broad pattern of cross-community dynamic interactions. Conversely, within-community spatiotemporal diversity in the language network exhibited significant age-related decreases, reflecting the network's gradual functional specialization. Furthermore, our findings indicated significant age-related increases in between-community degree centrality across the DMN, ECN, SN, language network, and dorsal attention network, while between-community eigenvector centrality also increased significantly for the DMN, ECN, and SN. However, within-community eigenvector centrality remained stable across all functional networks during early childhood. These results suggest that while centrality of cross-community interactions in early childhood functional networks increases, centrality within communities remains stable. Finally, mediation analysis was conducted to explore the relationships between age, brain dynamic graph metrics, and both global and local efficiency based on community structure. The results indicated that the dynamic graph metrics of the SN primarily mediated the relationship between age and the decrease in global efficiency, while those of the DMN, language network, ECN, dorsal attention network, and SN primarily mediated the relationship between age and the increase in local efficiency. This pattern suggests a developmental trajectory in early childhood from global information integration to local information segregation, with the SN playing a pivotal role in this transformation. This study provides novel insights into the mechanisms by which early childhood brain functional development impacts information transmission efficiency through cross-community adjustments in functional networks.

Viscoelastic stiffening of gelatin hydrogels for dynamic culture of pancreatic cancer spheroids

The tumor microenvironment (TME) in pancreatic adenocarcinoma (PDAC) is a complex milieu of cellular and non-cellular components. Pancreatic cancer cells (PCC) and cancer-associated fibroblasts (CAF) are two major cell types in PDAC TME, whereas the non-cellular components are enriched with extracellular matrices (ECM) that contribute to high stiffness and fast stress-relaxation. Previous studies have suggested that higher matrix rigidity promoted aggressive phenotypes of tumors, including PDAC. However, the effects of dynamic viscoelastic matrix properties on cancer cell fate remain largely unexplored. The focus of this work was to understand the effects of such dynamic matrix properties on PDAC cell behaviors, particularly in the context of PCC/CAF co-culture. To this end, we engineered gelatin-norbornene (GelNB) based hydrogels with a built-in mechanism for simultaneously increasing matrix elastic modulus and viscoelasticity. Two GelNB-based macromers, namely GelNB-hydroxyphenylacetic acid (GelNB-HPA) and GelNB-boronic acid (GelNB-BA), were modularly mixed and crosslinked with 4-arm poly(ethylene glycol)-thiol (PEG4SH) to form elastic hydrogels. Treating the hybrid hydrogels with tyrosinase not only increased the elastic moduli of the gels (due to HPA dimerization) but also concurrently produced 1,2-diols that formed reversible boronic acid-diol bonding with the BA groups on GelNB-BA. We employed patient-derived CAF and a PCC cell line COLO-357 to demonstrate the effect of increasing matrix stiffness and viscoelasticity on CAF and PCC cell fate. Our results indicated that in the stiffened environment, PCC underwent epithelial-mesenchymal transition. In the co-culture PCC and CAF spheroid, CAF enhanced PCC spreading and stimulated collagen 1 production. Through mRNA-sequencing, we further showed that stiffened matrices, regardless of the degree of stress-relaxation, heightened the malignant phenotype of PDAC cells. Statement of significanceThe pancreatic cancer microenvironment is a complex milieu composed of various cell types and extracellular matrices. It has been suggested that stiffer matrices could promote aggressive behavior in pancreatic cancer, but the effect of dynamic stiffening and matrix stress-relaxation on cancer cell fate remains largely undefined. This study aimed to explore the impact of dynamic changes in matrix viscoelasticity on pancreatic ductal adenocarcinoma (PDAC) cell behavior by developing a hydrogel system capable of simultaneously increasing stiffness and stress-relaxation on demand. This is achieved by crosslinking two gelatin-based macromers through orthogonal thiol-norbornene photochemistry and post-gelation stiffening with mushroom tyrosinase. The results revealed that higher matrix stiffness, regardless of the degree of stress relaxation, exacerbated the malignant characteristics of PDAC cells.

Dynamic Cluster Zoning of Arch Dam Deformation Considering Changing Working Conditions

Arch dam deformation has regional characteristics, and clustering is a common method of regional classification for arch dams. Traditional methods ignore the impact of dynamic changes in temperature and water level. Besides, the noise of deformation data is detrimental to mining potential information. The objective is to devise a dynamic cluster zoning method for arch dams, which considers the changing working conditions under the coupling of water level and temperature in this study. First, the deformation periods are classified by K‐means clustering, and the arch dam deformation series are denoised using a sparrow search algorithm‐optimized variational mode decomposition combined with wavelet threshold (SSA–VMD–WT) denoising method. The arch dam measuring points for different periods are then clustered. The engineering case study demonstrates that the SSA–VMD–WT denoising method improves the reliability of deformation data. The dynamic cluster zoning method reasonably describes the deformation regularity of the arch dam under different working conditions.

Single-cell immune profiling of mouse liver aging reveals Cxcl2+ macrophages recruit neutrophils to aggravate liver injury.

Immune cells play a crucial role in liver aging. However, the impact of dynamic changes in the local immune microenvironment on age-related liver injury remains poorly understood. We aimed to characterize intrahepatic immune cells at different ages to investigate key mechanisms associated with liver aging. We carried out single-cell RNA sequencing on mouse liver tissues at 4 different ages, namely, the newborn, suckling, young, and aged stages. The transcriptomic landscape, cellular classification, and intercellular communication were analyzed. We confirmed the findings by multiplex immunofluorescence staining, flow cytometry, in vitro functional experiments, and chimeric animal models. Nine subsets of 89,542 immune cells with unique properties were identified, of which Cxcl2+ macrophages within the monocyte/macrophage subset were preferentially enriched in the aged liver. Cxcl2+ macrophages presented a senescence-associated secretory phenotype and recruited neutrophils to the aged liver through the CXCL2-CXCR2 axis. Through the secretion of IL-1β and TNF-α, Cxcl2+ macrophages stimulated neutrophil extracellular traps formation. Targeting the CXCL2-CXCR2 axis limited the neutrophils migration toward the liver and attenuated age-related liver injury. Moreover, the relationship between Cxcl2+ macrophages and neutrophils in age-related liver injury was further validated by human liver transplantation samples. This in-depth study illustrates that the mechanism of Cxcl2+ macrophage-driven neutrophil activation involves the CXCL2-CXCR2 axis and provides a potential therapeutic strategy for age-related liver injury.

Modeling Long and Short Term User Preferences by Leveraging Multi-Dimensional Auxiliary Information for Next POI Recommendation

Next Point-of-Interest (POI) recommendation has shown great value for both users and providers in location-based services. Existing methods mainly rely on partial information in users’ check-in sequences, and are brittle to users with few interactions. Moreover, they ignore the impact of multi-dimensional auxiliary information such as user check-in frequency, POI category on user preferences modeling and the impact of dynamic changes in user preferences over different time periods on recommendation performance. To address the above limitations, we propose a novel method for next POI recommendation by modeling long and short term user preferences with multi-dimensional auxiliary information. In particular, the proposed model includes a static LSTM module to capture users’ multi-dimensional long term static preferences and a dynamic meta-learning module to capture users’ multi-dimensional dynamic preferences. Furthermore, we incorporate a POI category filter into our model to comprehensively simulate users’ preferences. Experimental results on two real-world datasets demonstrate that our model outperforms the state-of-the-art baseline methods in two commonly used evaluation metrics.

A Study on the Impact of Dynamic Visitor Demand on the Digital Transformation of Enterprises—Considerations Based on the Regional Innovation Environment and the Level of Big Data

To explore the impact of dynamic changes in tourist demand on the digital transformation of tourism enterprises, this paper starts with demand-side changes, environmental influences, and technical support, based on theories of supply and demand equilibrium, regional innovation environment, technology gaps, and comparative advantage, and conducts a multiple regression analysis using a two-way fixed effects model on data from China’s Shanghai, Shenzhen and New Third Board-listed tourism companies, as well as 31 provincial administrative regions. The study found that dynamic changes in tourist demand significantly impacted the digital transformation of tourism enterprises. In addition, the regional innovation environment and the level of big data also contributed positively to the relationship between tourist demand and the digital transformation of enterprises. For regions with different tourism resource endowments, there is heterogeneity in the impact of dynamic changes in tourist demand on the digital transformation of enterprises. Finally, recommendations for practitioners regarding the digital transformation of enterprises are provided based on this. We suggest that enterprises should pay attention to the changing needs of travelers. They should also consider the regional innovation environment and the level of big data as key resources to facilitate transformation. This will help accelerate digital transformation in tourism.

Interday Stability of Taxi Travel Flow in Urban Areas

Taxi travel flow patterns and their interday stability play an important role in the planning of urban transportation and public service facilities. Existing studies pay little attention to the stability of the travel flow patterns between days, and it is difficult to consider the impact of dynamic changes in daily travel demand analysis when supporting related decision making. Taxi trajectory data have been widely used in urban taxi travel-pattern analysis. This paper uses the taxi datasets of Shenzhen and New York to analyze and compare the interday stability of the taxi travel spatial structure and the flow volume based on the improved Levenshtein algorithm and geographic flow theory. The results show that (1) interday differences in taxi travel flow are obvious in both spatial structure and flow volume, high-frequency origin–destination (OD) trips are relatively stable; (2) the ODs between the central urban area and surrounding areas exhibit high traffic volume and high interday stability, and the ODs starting or ending at an airport exhibit high traffic stability; (3) one week’s data can describe 86% of the overall travel structure and 84% of travel flow in Shenzhen, and one week’s New York data can describe 73% of travel structure and 76% of travel flow. There are differences in the travel patterns of people in different cities, and the representativeness of datasets in different cities will be different. These findings can help to better understand the outcomes of taxi travel patterns derived from a relatively short period of data to avoid potential misuse in related decision making.

DeepP: Deep Learning Multi-Program Prefetch Configuration for the IBM POWER 8

Current multi-core processors implement sophisticated hardware prefetchers, that can be configured by application (PID), to improve the system performance. When running multiple applications, each application can present different prefetch requirements, hence different configurations can be used. Setting the optimal prefetch configuration for each application is a complex task since it does not only depend on the application characteristics but also on the interference at the shared memory resources (e.g., memory bandwidth). In his paper, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DeepP</i> , a deep learning approach for the IBM POWER8 that identifies at run-time the best prefetch configuration for each application in a workload. To this end, the neural network predicts the performance of each application under the studied prefetch configurations by using a set of performance events. The prediction accuracy of the network is improved thanks to a dynamic training methodology that allows learning the impact of dynamic changes of the prefetch configuration on performance. At run-time, the devised network infers the best prefetch configuration for each application and adjusts it dynamically. Experimental results show that the proposed approach improves performance, on average, by 5.8%, 6.7%, and 15.8% compared to the default prefetch configuration across different 6-, 8-, and 10-application workloads, respectively.

Evaluating the Impact of Dynamic Changes in Grasslands on the Critical Ecosystem Service Value of Yanchi County in China from 2000 to 2015

Grasslands are the basis for sustainable development in the northern farming-pastoral transition zone of China, with functions of human production, living, and ecology. Large-scale human activities inevitably lead to significant changes in grasslands, resulting in significant impacts on ecosystem services. To this end, we quantitatively estimated the ecosystem services value in each positive succession process (the improvement in the coverage or area of grasslands) and negative succession process (the degradation in the coverage or area of grasslands). The results indicated that (1) grasslands showed an improving trend from 2000 to 2015. The grassland improvement from low to high coverage dominated the positive succession process. Grassland degradation from high to low coverage dominated the negative succession process. (2) The total ecosystem services value increased by 25,294.87 × 104 yuan from 2000 to 2015. The grassland improvement from low to high coverage was the most important process that led to the increase in ecosystem service value. The degradation between grasslands and non-grasslands was the key process that led to the decrement in ecosystem services value. (3) The impact of grassland dynamics on the regional ecosystem service value showed significant spatial heterogeneity at the town scale. The results will provide some implications for the sustainable development of grassland ecosystem services to improve human well-being.

Validation and prognostic value of EZ-ALBI score in patients with intermediate-stage hepatocellular carcinoma treated with trans-arterial chemoembolization

BackgroundHeterogeneity of liver function and tumor burden in intermediate-stage hepatocellular carcinoma (HCC) results in different outcomes after transarterial chemoembolization (TACE). Easy albumin-bilirubin (EZ-ALBI), a simplified albumin-bilirubin (ALBI) score, has recently been proposed as a new prognostic score for HCC. This study aimed to validate the EZ-ALBI score and evaluate the impact of dynamic changes in patients with intermediate-stage HCC undergoing TACE.MethodsAll patients with HCC treated with TACE at King Chulalongkorn Memorial Hospital, Bangkok, Thailand, between January 2015 and December 2019 were prospectively enrolled. Intermediate-stage HCC was defined as Barcelona Clinic Liver Cancer (BCLC) stage B or unresectable single HCC with size > 5 cm in BCLC stage A. EZ-ALBI and ALBI scores were calculated and stratified into three different grades. Overall survival (OS) and prognostic factors were assessed using the Kaplan–Meier curve and Cox proportional hazard model. Decision analysis curves were used to evaluate the clinical utility of the predictive scores.ResultsAmong 672 patients with HCC treated with TACE, 166 patients with intermediate-stage HCC who met the eligibility criteria were enrolled. The median OS of all patients in the cohort was 21 months. A good correlation between the EZ-ALBI and ALBI scores was observed (correlation coefficient 1.000, p < 0.001). The baseline EZ-ALBI grades 1, 2, and 3 were 24.5%, 70%, and 5.5%, respectively. EZ-ALBI grade can stratify patients with significantly different prognoses (p = 0.002). Baseline EZ-ALBI grade 2, 3, and serum alpha-fetoprotein > 20 ng/ml were significantly associated with OS [hazard ratio (HR) 2.20 (95% confidence interval [CI] 1.24–3.88, p = 0.007), 3.26 (95% CI 1.24–8.57, p = 0.016), and 1.77 (95% CI 1.10–2.84, p = 0.018), respectively]. Following TACE, 42 (29.6%) patients had a worsening EZ-ALBI grade. However, the EZ-ALBI grade migration was not significantly correlated with OS. EZ-ALBI and ALBI score provided improved discriminatory ability (Harrell’s concordance index 0.599 and 0.602, respectively) and better net benefit compared with Child-Turcotte-Pugh and Model for End-stage Liver Disease scores.ConclusionsThe baseline EZ-ALBI score demonstrated good predictive performance for survival and a strong correlation with conventional ALBI scores. Both the EZ-ALBI and ALBI scores outperformed other prognostic models in patients with intermediate-stage HCC receiving TACE. However, the dynamic change in the EZ-ALBI grade after TACE was not associated with postprocedural survival.

How does network position influence project performance in Chinese megaprojects? An inter-organizational conflict-based perspective

PurposeThis study aims to explore the relationship between network position, various types of inter-organizational conflicts and project performance in the context of megaprojects.Design/methodology/approachCentrality and structural holes were used to represent network position. A theoretical model was developed, and a structured questionnaire survey was conducted with construction professionals involved in megaprojects. A total of 291 valid responses were obtained, which were analyzed via structural equation modeling.FindingsThe results showed that centrality negatively impacts project performance, while structural holes do not significantly impact project performance. Centrality negatively affects task conflicts, but positively affects process conflicts and relationship conflicts. Structural holes positively impact task conflicts, but negatively impact both process conflicts and relationship conflicts. Task conflict and relationship conflict exert constructive and destructive effects on project performance, respectively, while process conflict does not significantly impact project performance. Task conflict and relationship conflict play mediating roles. Task conflict weakens while relationship conflict strengthens the relationship between centrality and project performance. Task conflict strengthens while relationship conflict weakens the relationship between structure hole and project performance.Research limitations/implicationsThis study provides a reference for the implementation of network governance, inter-organizational conflict management and project performance management in megaprojects. However, the impact of dynamic changes of inter-organizational conflicts and network position on project performance has not been discussed in the context of megaprojects. Future research may explore the impact of dynamic changes of conflicts and network position on project implementation.Originality/valueThis study increases the current understanding of the impact of network position on project performance. Moreover, a new direction for network governance in the context of megaprojects is provided. This study also verified both the constructive and destructive effects of conflicts and the mediating role they play, thus supplementing the literature on inter-organizational conflict management in the construction field.

НАУКОВО-МЕТОДИЧНИЙ ПІДХІД ДО ОЦІНЮВАННЯ БЮДЖЕТНИХ ДИСБАЛАНСІВ

Анотація. Зосереджено увагу на неоднозначності ставлення вчених-економістів до незбалансованості державного бюджету. Обґрунтовано розуміння збалансованого за доходами і видатками державного бюджету відповідно до концепції «здорових фінансів». Виявлено недоліки концепції «здорових фінансів», зокрема те, що щорічне балансування доходів і видатків бюджету виключає, чи значною мірою зменшує можливості антициклічного, стабілізувального впливу фіскальної політики держави. Актуалізовано увагу на особливостях концепції хронічного бюджетного дефіциту і специфіці дефіцитного фінансування державних витрат у рамках концепції контрциклічного регулювання. Водночас доведено, що збалансованість бюджету є другорядною проблемою за концепцією функціональних фінансів. З’ясовано, що дефіцит бюджету може спричинювати як позитивні, так і негативні соціально-економічні ефекти, залежно від обставин, у яких дефіцит сформований. Виділено та охарактеризовано різновиди дефіциту державного бюджету, а саме: номінальний дефіцит, реальний дефіцит, операційний дефіцит первинний дефіцит, фактичний дефіцит, прихований дефіцит, квазіфіскальний дефіцит, сукупний дефіцит, активний дефіцит, пасивний дефіцит, вимушений дефіцит, свідомий дефіцит, структурний дефіцит і циклічний дефіцит. Доведено, що основним завданням держави є досягнення його збалансованості, тобто підтримка балансу доходів і витрат держави. Розглянуто підхід до оцінювання дисбалансу бюджету за допомогою застосування нерівності Коші та сформовано алгоритм оцінювання дисбалансу бюджету. Доведено, що забезпечення бюджетної збалансованості можливо в таких напрямах: поліпшення якості планування основних показників бюджету; розширення дохідної бази; оптимізація / секвестр видатків бюджету; цільове фінансування; підвищення ефективності управління державною власністю, бюджетного контролю; запровадження бюджетування, орієнтованого на результат, та аудиту ефективності використання бюджетних коштів; удосконалення міжбюджетних відносин; управління державним боргом. Розвинуто науково-методичний підхід до оцінювання дисбалансу, зокрема Зведеного бюджету в частині обґрунтування граничного значення показника міри дисбалансу, що ґрунтується на застосуванні нерівності Коші, а також визначення впливу факторів динамічних змін дисбалансу бюджету на основі застосування методу ланцюгових підстановок. Перевагами такого науково-методичного підходу є можливість порівняння оцінки дисбалансу бюджетів, що суттєво різняться за обсягом фінансових ресурсів, як перерозподіляються через бюджет, оскільки такі оцінки є відносними, що дозволяє нівелювати ефект масштабу бюджету. Ключові слова: бюджетна система, бюджет, бюджетний дефіцит, дефіцитне фінан­сування, бюджетна збалансованість, оцінювання дисбалансу, контрциклічне регулювання економіки. Формул: 3; рис.: 1; табл.: 1; бібл.: 10.

THE ROLE OF ADAPTIVE POTENTIAL OF YOUTH IN CONDITIONS OF SOCIAL ANXIETY

The article examines the impact of dynamic changes in political, socioeconomic conditions on the life of youth. In such a situation, young people show signs of anxiety, social insecurity and pessimistic views on the future. Profound changes are taking place in the formation of motives for life, in primary needs, social positions and life values, leading to an exacerbation of the need for security and, at the same time, to a limitation of its satisfaction, which is the most important condition for normal life, development, selfaffirmation and self-expression of young people. The psychological safety of young people is ensured through socio-psychological adaptation due to the adaptive potential. As a result of the study, the features of the perception of social anxiety in young people and the manifestation of adaptive potential in extreme conditions were revealed. A comparative analysis of similar phenomena in the CIS countries, Europe and Israel was also carried out.

Changes in metabolic syndrome affect the health-related quality of life of community-dwelling adults

Metabolic syndrome (MetS) is associated with cardiovascular diseases, type 2 diabetes, chronic renal diseases, and all-cause mortality. Furthermore, MetS is associated with poor health-related quality of life (HRQOL). However, the impact of dynamic changes in MetS on changes in the HRQOL was not previously explored. This was an eight-year, prospective cohort study in which 906 middle-aged adults from Shipai, Taipei in northern Taiwan were enrolled during 2009–2010 (baseline). Of those sampled, 427 participants completed the follow-up investigation after 8 years. The HRQOL was measured using the Short Form Health Survey (SF-36). Other variables including age, sex, marital status, level of education, smoking, alcohol consumption, baseline body mass index, and changes in physical activity were adjusted. Compared with adults who never experienced MetS, adults with persistent MetS had a negative change in mental HRQOL (β − 4.20, 95% CI − 7.54 to − 0.86, p = 0.01). The negative changes of persistent MetS on the HRQOL were in the domains of vitality and mental health (β − 4.42, 95% CI − 8.10 to − 0.73 and β − 3.47, 95% CI − 6.90 to − 0.04, respectively). Women and overweight adults were vulnerable to the detrimental effects of persistent MetS. For better HRQOL, more resources should be devoted to reversing MetS in public health.