Trajectories Of Progression Research Articles

Longitudinal multi-trajectory phenotypes of severe eosinophilic asthma on type 2 biologics treatment

BackgroundLimited understanding exists regarding the progression trajectory of severe eosinophilic asthma (SEA) patients on type 2 biologics therapies. ObjectiveWe aim to explore distinct longitudinal phenotypes of these patients based on crucial asthma biomarkers. MethodsWe enrolled 101 adult patients with SEA. Of these, 51 were treated with anti-IL5/IL5Rα or anti-IL5/IL5RαR antibody, and 50 with anti-IL-4Rα antibody. Multi-trajectory analysis, an extension of univariate group-based trajectory modeling, was used to categorize patients based on their trajectories of forced expiratory volume in 1 s (FEV1), blood eosinophil counts (BEC), and fractional exhaled nitric oxide (FeNO) levels at baseline, and after 1, 6, and 12 months of treatment. Associations between trajectory-based clusters and clinical parameters were examined. ResultsAmong anti-IL5/IL5Rα antibody-treated patients, 2 clusters were identified. The cluster characterized by higher baseline BEC and lower FEV1 showed a better response, with improvements in FEV1 and reductions in BEC over time. Among anti-IL-4Rα antibody-treated, 3 clusters were identified. Clusters with moderate BEC and FeNO at baseline demonstrated better improvements in FEV1 and reductions in FeNO, despite increased BEC during follow-up. Conversely, individuals with extremely low FeNO and high BEC at baseline were more likely to experience poorer progression, demonstrating an increase in FeNO and a reduction in FEV1. ConclusionTo optimally monitor treatment response in SEA patients on type 2 biologics, integrating longitudinal biomarker features is essential.

Association between remnant cholesterol and the trajectory of arterial stiffness progression

Objective: To explore the impact of baseline remnant cholesterol levels at a single time point and cumulative remnant cholesterol exposure on the progression trajectories of arterial stiffness. Methods: This prospective cohort study included 2 401 eligible participants from the Beijing Health Management Cohort who consecutively attended health examinations in 2010-2011, 2012-2013, and 2014-2015. The remnant cholesterol value measured in 2014-2015 served as the baseline remnant cholesterol level at a single time point. The cumulative exposure indices were calculated based on remnant cholesterol values from three health examinations from 2010 to 2015, including cumulative exposure, cumulative exposure burden, and duration of high remnant cholesterol exposure. Arterial stiffness was assessed by brachial-ankle pulse wave velocity (baPWV). The follow-up continued until December 31, 2019, with annual check-ups. During the follow-up period, a group-based trajectory model was employed to construct the progression trajectories of baPWV. The associations between the baseline remnant cholesterol level, cumulative exposure indices of remnant cholesterol and baPWV trajectories were examined using ordinal logistic regression models, adjusting for traditional cardiovascular risk factors and low-density lipoprotein cholesterol (LDL-C) levels. Results: The age of the 2 401 participants was 61 (54, 69) years, with 1 801 (75.01%) being male. The group-based trajectory model indicated that the best-fit model categorized the participants into three subgroups: low-rising group (1 036 individuals, 43.15%), moderate-rising group (1 137 individuals, 47.36%), and high-rising group (228 individuals, 9.50%). After adjusting for traditional cardiovascular risk factors, baseline remnant cholesterol levels at a single point (OR=1.170, 95%CI: 1.074-1.274), cumulative remnant cholesterol exposure (OR=1.194, 95%CI: 1.096-1.303), cumulative remnant cholesterol exposure burden (OR=1.270, 95%CI: 1.071-1.507), and high-remnant cholesterol exposure duration (6 years: OR=1.351, 95%CI: 1.077-1.695) were significantly associated with the risk of developing a poor baPWV progression trajectory. These results remained significant after adjusting for cumulative average LDL-C levels. The association between baseline remnant cholesterol levels and baPWV progression became insignificant after adjusting for cumulative remnant cholesterol levels (OR=1.053, 95%CI: 0.923-1.197), while the association between cumulative remnant cholesterol exposure and baPWV progression remained significant after adjusting for baseline remnant cholesterol levels (OR=1.145, 95%CI: 1.008-1.305). Conclusions: Higher levels of baseline remnant cholesterol and cumulative remnant cholesterol are independent risk factors for the progression of arterial stiffness. These associations remain significant even after adjusting for traditional cardiovascular risk factors and LDL-C levels. Furthermore, the effect of cumulative remnant cholesterol levels on the progression of arterial stiffness was stronger than the effect of baseline remnant cholesterol levels.

Peer Interaction Dynamics and Second Language Learning Trajectories During Study Abroad: A Longitudinal Investigation Using Dynamic Computational Social Network Analysis

AbstractUsing computational Social Network Analysis (SNA), this longitudinal study investigates the development of the interaction network and its influence on the second language (L2) gains of a complete cohort of 41 U.S. sojourners enrolled in a 3‐month intensive study‐abroad Arabic program in Jordan. Unlike extant research, our study focuses on students’ interactions with alma mater classmates, reconstructing their complete network, tracing the impact of individual students’ positions in the social graph using centrality metrics, and incorporating a developmental perspective with three measurement points. Objective proficiency gains were influenced by predeparture proficiency (negatively), multilingualism, perceived integration of the peer learner group (negatively), and the number of fellow learners speaking to the student. Analyses reveal relatively stable same‐gender cliques, but with changes in the patterns and strength of interaction. We also discuss interesting divergent trajectories of centrality metrics, L2 use, and progress; predictors of self‐perceived progress across skills; and the interplay of context and gender.

Efficacy of Radicava® IV (intravenous edaravone) in subjects with differing trajectories of disease progression in amyotrophic lateral sclerosis: Use of a novel statistical approach for post hoc analysis of a pivotal phase 3 clinical trial

IntroductionSubjects with amyotrophic lateral sclerosis (ALS) treated with Radicava® (edaravone) IV (intravenous; Mitsubishi Tanabe Pharma America [MTPA], hereafter “MTPA IV edaravone”) in Study MCI186‐19 had a significantly slower physical functional decline vs placebo-treated subjects as measured by the revised ALS Functional Rating Scale (ALSFRS-R) and analyzed by the linear mixed model for repeated measures (MMRM). This Study 19 post hoc analysis of MTPA IV edaravone-treated and placebo-treated subjects evaluated linear and nonlinear latent class mixed models defining trajectories based on identifying the model with the lowest Bayesian information criterion. The best model differentiated 4 nonlinear trajectories in ALS subjects. ALSFRS-R total score in MTPA IV edaravone-treated and placebo-treated subjects was evaluated for these 4 nonlinear latent class trajectory groups. MethodsDisease trajectories of MCI186‐19 MTPA IV edaravone-treated or placebo-treated ALS subjects who completed the double-blind period were investigated using latent class analysis (LCA) statistical models to identify potential unique nonlinear ALSFRS-R disease trajectories. ResultsALSFRS-R trajectories revealed 4 unique nonlinear trajectory latent classes per treatment group in MTPA IV edaravone-treated and placebo-treated ALS subjects completing the MCI186‐19 double-blind period. Latent classes 2‐4 had statistically significant slowing of ALSFRS-R total score decline in the predicted nonlinear trajectories of MTPA IV edaravone-treated vs placebo-treated ALS subjects. ConclusionsThis post hoc analysis suggests MTPA IV edaravone treatment results in slower ALSFRS-R decline vs placebo in most predicted nonlinear trajectories. LCA is a novel approach that may benefit future trial analyses.

Supercontinuum-tailoring multicolor imaging reveals spatiotemporal dynamics of heterogeneous tumor evolution

Tumor heterogeneity and tumor evolution contribute to cancer treatment failure. To understand how selective pressures drive heterogeneous tumor evolution, it would be useful to image multiple important components and tumor subclones in vivo. We propose a supercontinuum-tailoring two-photon microscope (SCT-TPM) and realize simultaneous observation of nine fluorophores with a single light beam, breaking through the ‘color barrier’ of intravital two-photon fluorescence imaging. It achieves excitation multiplexing only by modulating the phase of fiber supercontinuum (SC), allowing to capture rapid events of multiple targets with maintaining precise spatial alignment. We employ SCT-TPM to visualize the spatiotemporal dynamics of heterogeneous tumor evolution under host immune surveillance, particularly the behaviors and interactions of six tumor subclones, immune cells and vascular network, and thus infer the trajectories of tumor progression and clonal competition. SCT-TPM opens up the possibility of tumor lineage tracking and mechanism exploration in living biological systems.

The characterization of serum proteomics and metabolomics across the cancer trajectory in chronic hepatitis B‐related liver diseases

AbstractHepatocellular carcinoma (HCC) is a deadly cancer that emerges from a continuous progression of liver cells from normal to abnormal, often following infections by hepatitis B/C viruses (HBV/HCV), liver fibrosis, and liver cirrhosis (LC), ultimately culminating in cancer. However, there is currently limited systematic molecular analysis of biomarkers at different stages of HCC progression using multi‐omics approaches. We carried out an innovative pipeline by utilizing targeted proteomics and metabolomics to identify potential biomarkers for early detection of HCC in 316 participants, including healthy adults and patients diagnosed with HBV, HCV, LC, and HCC from three independent cohorts. We first established a detailed database of candidate biomarkers for HCC containing 3059 proteins and 103 metabolites, and identified pivotal candidates implicated in the progressive trajectory of liver cancers. Through our developed DeepPRM, scheduled multiple reaction monitoring (MRM)‐targeted approach, and machine learning‐based computational pipeline, we identified an eight‐biomolecular‐based combination with an accuracy rate of 91.43% for early diagnosis of HCC, and a 12‐biomolecular‐based combination with an accuracy rate of 80.00% for detecting changes in HBV–LC progression. These two biomarker combinations significantly improved accuracy compared to traditional tumor biomarkers. Our extensive analysis provides valuable proteomic and metabolomic data resources that will contribute to a deeper understanding of liver disease progression and enhance the identification of potential therapeutic targets.

Progression trajectories from prodromal to overt synucleinopathies: a longitudinal, multicentric brain [18F]FDG-PET study

The phenoconversion trajectory from idiopathic/isolated Rapid eye movement (REM) sleep behavior disorder (iRBD) towards either Parkinson’s Disease (PD) or Dementia with Lewy Bodies (DLB) is currently uncertain. We investigated the capability of baseline brain [18F]FDG-PET in differentiating between iRBD patients eventually phenoconverting to PD or DLB, by deriving the denovoPDRBD-related pattern (denovoPDRBD-RP) from 32 de novo PD patients; and the denovoDLBRBD-RP from 30 de novo DLB patients, both with evidence of RBD at diagnosis. To explore [18F]FDG-PET phenoconversion trajectories prediction power, we applied these two patterns on a group of 115 iRBD patients followed longitudinally. At follow-up (25.6 ± 17.2 months), 42 iRBD patients progressed through overt alpha-synucleinopathy (21 iRBD-PD and 21 iRBD-DLB converters), while 73 patients remained stable at the last follow-up visit (43.2 ± 27.6 months). At survival analysis, both patterns were significantly associated with the phenoconversion trajectories. Brain [18F]FDG-PET is a promising biomarker to study progression trajectories in the alpha-synucleinopathy continuum.

Novel, Group-Based Trajectories of Labor Progress in Nulliparous Women With Low-Risk Pregnancies

ObjectiveTo characterize labor progress among nulliparous women by applying group-based trajectory analysis and examining predictors of group membership. DesignRetrospective observational. SettingAn existing biobank and database from a birth hospital in Western Pennsylvania. ParticipantsNulliparous women with low-risk pregnancies at term gestation with singleton fetuses in vertex presentation (N = 401). MethodsWe characterized labor progress by applying group-based trajectory analysis. We conducted a multinomial logistic regression analysis to examine the relationships among labor trajectory groups and various demographic and clinical variables. ResultsWe identified three trajectories of labor in the group-based trajectory analyses: precipitously progressing (n = 76, 20.1%), average (n = 245, 59.1%), and slow progress (n = 80, 20.7%). Only gestational age at birth significantly predicted trajectory group membership, and an increased gestational age was associated with greater odds of belonging to the slower progress group (OR = 1.43, 95% CI [1.06, 1.92]). ConclusionWe identified multiple trajectories of labor progress in a sample of nulliparous women with low-risk pregnancies at term gestation. Gestational age may help predict the trajectory of labor.

Association of Short-term Pain and Chronic Pain Intensity With Cardiometabolic Multimorbidity Progression: A Multistate Markov Model Analysis.

The impact of pain intensity on the progression trajectories of cardiometabolic multimorbidity (CMM) is not well understood. We attempted to dissect the relationship of short-term pain (STP) and chronic pain intensity with the temporal progression of CMM. We conducted a prospective cohort study based on the UK Biobank participants. Incident cases of cardiometabolic diseases (CMDs) were identified based on self-reported information and multiple health-related records in the UK Biobank. CMM was defined as the occurrence of at least 2 CMDs, including heart failure (HF), ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D). The pain intensity was categorized into 5 levels based on pain duration and the number of sites involved, including chronic widespread pain (CWSP), chronic multilocation pain (CMLP), chronic single-location pain (CSLP), STP, and free-of-pain (FOP). Multistate models were used to assess the impact of pain intensity on the CMM trajectories from enrollment to initial cardiometabolic disease (ICMD), subsequently to CMM, and ultimately to death. A total of 429,145 participants were included. Over the course of a 12.8-year median follow-up, 13.1% (56,137/429,145) developed ICMD, 19.6% (10,979/56,137) further progressed to CMM, and a total of 5.3% (22,775/429,145) died. Compared with FOP, CMLP (hazard ratio [HR], 1.11; 95% confidence interval [CI], 1.06-1.17) and CWSP (HR, 1.26; 95% CI, 1.13-1.42) elevated the risk of transitioning from ICMD to CMM. STP (HR, 0.89; 95% CI, 0.82-0.96), CSLP (HR, 0.88; 95% CI, 0.82-0.95), and CMLP (HR, 0.87; 95% CI, 0.81-0.93) lowered the risk of transition from ICMD to mortality, and STP also reduced the risk of transition from enrollment to mortality (HR, 0.94; 95% CI, 0.89-0.98). The results of disease-specific transitions revealed that the influence of pain intensity varied across transitional stages. Specifically, CMLP and CWSP heightened the risk of conversion from T2D or IHD to CMM, whereas only CWSP substantially elevated the transition risk from HF to CMM. Our results highlighted reductions in chronic pain may mitigate both the onset and progression of CMM, potentially having an important impact on future revisions of cardiometabolic and pain-related guidelines.

Approaches to Early Parkinson's Disease Subtyping.

Parkinson's disease (PD) unfolds with pathological processes and neurodegeneration well before the emergence of noticeable motor symptoms, providing a window for early identification. The extended prodromal phase allows the use of risk stratification measures and prodromal markers to pinpoint individuals likely to develop PD. Importantly, a growing body of evidence emphasizes the heterogeneity within prodromal and clinically diagnosed PD. The disease likely comprises distinct subtypes exhibiting diverse clinical manifestations, pathophysiological mechanisms, and patterns of α-synuclein progression in the central and peripheral nervous systems. There is a pressing need to refine the definition and early identification of these prodromal subtypes. This requires a comprehensive strategy that integrates genetic, pathological, imaging, and multi-omics markers, alongside careful observation of subtle motor and non-motor symptoms. Such multi-dimensional classification of early PD subtypes will improve our understanding of underlying disease pathophysiology, improve predictions of clinical endpoints, progression trajectory and medication response, contribute to drug discovery and personalized medicine by identifying subtype-specific disease mechanisms, and facilitate drug trials by reducing confounding effects of heterogeneity. Here we explore different subtyping methodologies in prodromal and clinical PD, focusing on clinical, imaging, genetic and molecular subtyping approaches. We also emphasize the need for refined, theoretical a priori disease models. These will be prerequisite to understanding the biological underpinnings of biological subtypes, which have been defined by large scale data-driven approaches and multi-omics fingerprints.

Adult Socioeconomic Position Mediates the Association between Childhood Socioeconomic Position and Later-Life Frailty Trajectory: A Nationally Representative Cohort Study

Abstract Background and Objectives Early life risk factors influence the aging process in the short term and shape its trajectory in the long term. We aim to 1) explore the association between childhood socioeconomic position and frailty trajectories and 2) test whether adult socioeconomic position mediates the association between childhood socioeconomic position and frailty trajectories. Research Design and Methods We analysed four waves of the China Health and Retirement Longitudinal Study data. The frailty index was estimated based on the number of individual deficits across 40 indicator variables. Principal component analysis was used to generate childhood socioeconomic position and adult socioeconomic position. Group-based trajectory models were used to identify the patterns of frailty trajectories over time. Causal mediation analysis was conducted to determine whether the adult socioeconomic position mediated the association between childhood socioeconomic position and frailty trajectories. Results We identified three distinct trajectories of frailty progression. Low childhood socioeconomic position was significantly associated with “High and increasing frailty trajectory” (OR = 1.76, 95%CI 1.38-2.23; adjusted OR = 1.55, 95%CI 1.22-1.97). About 30% of the childhood socioeconomic position effect on rising frailty trajectory was mediated through the adult socioeconomic position, and there is a significant gender disparity in the mediating effect of adult socioeconomic position (18% among men and 51% among women, respectively). Discussion and Implications Our findings suggest that policies that initially benefit children will yield well-being benefits as they reach adulthood. Promoting ongoing childhood socioeconomic position advantages increases the likelihood of delaying frailty progression in later life. This study underscores the critical importance of addressing social determinants of health throughout one's life course to foster healthy aging and diminish health disparities in later stages of life.

Trajectories of Short-Term Post-Traumatic Stress Disorder Symptoms in Patients with Post-Intensive Care Syndrome: A Longitudinal Observational Study.

Post-traumatic stress disorder (PTSD) is a major psychiatric health issue among intensive care unit (ICU) survivors with post-intensive care syndrome (PICS). Although early PTSD intervention has been demonstrated to decrease the risk of progression from acute to chronic PTSD, information on the progression trajectory of short-term PTSD symptoms and modifiable risk factors in PICS patients is limited. This study aimed to explore the clinical progression trajectories of short-term PTSD symptoms and the associated factors in PICS patients by conducting a prospective longitudinal observational study. This study was conducted at a tertiary hospital in China. The impact of event scale-revised was used to collect data on the PTSD symptoms of patients at 1, 2, 3, and 4 months post-discharge from the ICU. The latent growth mixture model was used to construct trajectory models for PTSD symptoms and multivariate logistic regression was used to determine the factors associated with the trajectories. A total of 130 ICU survivors with PICS completed the 4-month short-term follow-up. Our results showed that PTSD symptoms in PICS patients manifested as three trajectories, namely, moderate chronic (n = 17, 13.1%), recovery (n = 25, 19.2%), and resilience (n = 88, 67.7%). Compared with the resilience trajectory, age and female were identified as risk factors for the moderate chronic trajectory, while prolonged ICU stay was a risk factor for the recovery trajectory. Our study showed that short-term PTSD symptoms in PICS patients manifested as moderate chronic, recovery, and resilience trajectories. Additionally, our results showed that PTSD screening should be conducted for critically ill patients, especially younger, female, or long-term ICU patients, immediately after their discharge from the ICU.

Sustainable Maritime Transport: A Review of Intelligent Shipping Technology and Green Port Construction Applications

With the global economy’s relentless growth and heightened environmental consciousness, sustainable maritime transport emerges as a pivotal development trajectory for the shipping sector. This study systematically analyzes 478 publications searched in the Web of Science Core Collection, from 2000 to 2023, utilizing bibliometric methods to investigate the application areas in sustainable development within the shipping industry. This study begins with an analysis of annual publication trends, which reveals a substantial expansion in research endeavors within this discipline over recent years. Subsequently, a comprehensive statistical evaluation of scholarly journals and a collaborative network assessment are conducted to pinpoint the foremost productive journals, nations, organizations, and individual researchers. Furthermore, a keyword co-occurrence methodology is applied to delineate the core research themes and emerging focal points within this domain, thereby outlining potential research directions for future research. In addition, drawing on the keyword co-occurrence analysis, the advancements in intelligent shipping technologies and green port construction applications within sustainable maritime transport are discussed. Finally, the review discusses the existing challenges and opportunities of sustainable maritime transport from a theoretical and practical perspective. The research shows that, in terms of intelligent shipping technology, data security and multi-source data are the focus that people need to pay attention to in the future; a trajectory prediction for different climates and different ship types is also an area for future research. In terms of green ports, Cold Ironing (CI) is one of the key points of the green port strategy, and how to drive stakeholders to build sustainable green ports efficiently and economically is the future developmental direction. This review serves to enhance researchers’ comprehension of the current landscape and progression trajectory of intelligent shipping technologies, thereby fostering the continued advancement and exploration in this vital domain.

Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach.

Although the involvement of progressive brain alterations in epilepsy was recently suggested, individual patients' trajectories of white matter (WM) disruption are not known. We investigated the disease progression patterns of WM damage and its associations with clinical metrics. We examined the cross-sectional diffusion tensor imaging (DTI) data of 155 patients with unilateral temporal lobe epilepsy (TLE) and 270 age/gender-matched healthy controls, and we then calculated the average fractional anisotropy (FA) values within 20 WM tracts of the whole brain. We used the Subtype and Stage Inference (SuStaIn) program to detect the progression trajectory of FA changes and investigated its association with clinical parameters including onset age, disease duration, drug-responsiveness, and the number of anti-seizure medications (ASMs). The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). This pattern was replicated when analyzing TLE with hippocampal sclerosis (n = 50) and TLE with no lesions (n = 105) separately. Further-progressed stages were associated with longer disease duration (p < 0.001) and a greater number of ASMs (p = 0.001). the disease progression model based on WM tracts may be useful as a novel individual-level biomarker.

How does family resilience develop among stroke survivors and their caregivers? A mixed-method study using a chain mediating model

BackgroundWalsh's family resilience theory indicated that families could foster resilient outcomes among their members when they are facing changes or crises. However, little is known about family resilience among Chinese stroke survivors and their caregivers. ObjectivesTo explore the direct and indirect relationships between the family resilience of stroke survivors, perceived social support, self-perceived burden, self-efficacy, and the burden on their principal caregivers, and to examine the journey of adapting to family resilience among stroke survivors. DesignAn explanatory sequential mixed-method study. MethodsA quantitative assessment of perceived social support, self-perceived burden, self-efficacy, and family resilience was conducted among a cohort of stroke survivors. For a deeper understanding of the family resilience formation process, semi-structured, in-depth interviews were undertaken with a purposefully selected subset of participants, consisting of 15 stroke survivors and their principal caregivers who met the study criteria. Data analysis encompassed descriptive statistics, mediation models, and content analysis to integrate and interpret both quantitative and qualitative data. ResultsIn a comprehensive hospital in Guangdong Province, China, 379 participants—229 men (60.4%) and 150 women (39.6%)—completed a cross-sectional questionnaire survey. The quantitative phase revealed significant statistical differences (p < 0.05) in total family resilience scores among stroke survivors related to various factors, such as age, marital status, educational level, occupational status, average monthly income per capita, first-time onset, and types of stroke. Self-perceived burden and self-efficacy partially mediate the relationship between perceived social support and family resilience, contributing to a sequential chain-mediated effect. During the qualitative phase, in-depth interviews revealed a progressive trajectory from the initial shock of diagnosis through the ongoing presence of stress and challenges to the ultimate development of family resilience and an adaptive perspective toward the future. ConclusionsExploring the factors influencing family resilience in stroke survivors could assist healthcare professionals developing interventions to enhance family resilience and lessen the burden on principal caregivers from individual, family, and social perspectives.

Profiles of disease progression and predictors of mortality in Colombian patients with amyotrophic lateral sclerosis: a comprehensive longitudinal study

Objective: This study aimed to assess the prognostic value of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) in predicting mortality and characterizing disease progression patterns in ALS patients in Colombia. Methods: We conducted a retrospective longitudinal analysis of 537 ALS patients from the Roosevelt Institute Rehabilitation Service between October 2008 and October 2022. The study excluded nine patients due to incomplete data, resulting in 528 individuals in the analysis. ALS diagnoses were confirmed using the revised El Escorial and Gold Coast criteria. Disease progression was assessed using the ALSFRS-R, and mortality data were sourced from follow-up calls and a national database. Statistical analysis included Cox proportional hazards models to identify mortality predictors and Growth Mixture Modeling (GMM) to explore ALS progression trajectories. Results: The majority of the cohort (63.8%) deceased within the 84-month follow-up period. Survival analysis revealed that each point increase in the ALSFRS-R rate was associated with a 2.22-fold (95% CI =1.99–2.48, p < 0.001) increased risk of mortality. In the population with data from two clinical visits, the ALSFRS-R rate based on initial assessments predicted mortality more effectively over 36 months than the rate based on two evaluations. GMM identified three distinct progression trajectories: slow, intermediate, and rapid decliners. Conclusions: The ALSFRS-R rate, derived from self-reported symptom onset, significantly predicts mortality, underscoring its value in clinical assessments. This study highlights the heterogeneity in disease progression among Colombian ALS patients, indicating the necessity for personalized treatment approaches based on individual progression trajectories. Further studies are needed to refine these predictive models and improve patient management and outcomes.

Effect of leisure activity on frailty trajectories among Chinese older adults: a 16-year longitudinal study

BackgroundWhile the significant association between leisure activities and frailty risk among older adults is well-established, the impact of integrated leisure activity scores and different categories of them on frailty trajectories over time remains unclear.MethodsThis study utilized longitudinal data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which enrolled participants aged 65 years and older between 2002 and 2018. Frailty trajectories were derived using group-based trajectory modelling, and based on these trajectories, subjects were classified into various categories. Leisure activity was measured by integrated scores as well as three distinct categories: physically, cognitively, and socially stimulating activity. The effect of leisure activity on frailty trajectories was examined using multinomial logistic regression.ResultsBy analysing data from 2,299 older adults, three frailty trajectories were identified: non-frail, moderate progressive, and high progressive. The results indicated that an increase in the score of integrated leisure activity was associated with 11% (odds ratio [OR] 0.89; 95% Confidence Interval [CI] 0.85–0.93) and 14% (OR 0.86; 95% CI 0.80–0.91) decrease in the likelihood of being in the moderate and high progressive frailty trajectories, respectively. Engaging in physically stimulating activity lowered the odds of belonging to the moderate and high progressive trajectory by 43% (OR 0.57; 95% CI 0.40–0.81; OR 0.57; 95% CI 0.36–0.92, respectively). Participation in socially stimulating activity showed a lower odd of being in the moderate progressive trajectory (OR 0.68; 95% CI 0.49–0.93) and the high progressive trajectory (OR, 0.61; 95% CI, 0.39–0.95). The effects of leisure activities on frailty trajectories were observed not to vary by age, education level and retirement status.ConclusionsThis study suggests that older adults should be encouraged to increase both the amount and variety of their leisure activities. Physically stimulating activities should be considered the primary choice, followed by socially and cognitively stimulating activities.

INNOVATIVE BUSINESS MODELS IN THE CIRCULAR ECONOMY: AN ANALYSIS OF GOOD PRACTICES FOR ELECTRICAL AND ELECTRONIC EQUIPMENT ON THE EUROPEAN CIRCULAR ECONOMY STAKEHOLDER PLATFORM

The pervasive integration of electronic technologies in the contemporary digital landscape underscores the significance of electrical and electronic equipment (EEE). Beyond their utility in daily life, certain components within EEE, hold classification as critical raw materials (CRMs) and transforms cities into urban mines. This issue highlights the necessity of optimizing its sustainable consumption and production patterns at all stages of the life cycle and across various sectors. The optimization of the complete product life cycle serves as a foundational pillar of the circular economy (CE). While the transition from a linear to a CE has been a longstanding objective promoted by the EU, a comprehensive mapping elucidating potential shortcoming in the effective implementation of this transition in Europe for the field of EEE remains elusive. This paper seeks to investigate the state-of-the-art of CE good practices for EEEs in Europe, shedding light on potential strengths and challenges to be addressed. To obtain an empirical perspective, the European Circular Economy Stakeholder Platform (ECESP) serves as a tool to delineate the trajectory of progress throughout the transition to a CE. The analysis encompasses both life cycle phases and the production sector. The findings underscore a prevailing focus on the product's end-of-life phase and sectors associated with recycling and waste management, while the initial life cycle phase remains underexplored in terms of eco-design solutions or innovative processes. On a positive note, several instances of new business models have emerged, redirecting consumption emphasis towards services.

Distinct clinical trajectories of gastrointestinal progression among patients with systemic sclerosis.

Systemic sclerosis (SSc) is heterogeneous in its clinical presentation. Common manifestations cluster together, defining unique subgroups. This investigation aims to characterize gastrointestinal (GI) phenotypes and determine whether they can be distinguished by temporal progression. We examine a well-established SSc patient cohort with a modified Medsger GI severity score measured over time to determine heterogeneity in disease progression. Growth mixture models estimate each patient's phenotype and disease severity trajectory over time. We compare the characteristics of estimated phenotypes using non-parametric statistics and linear and logistic regression to compare patient characteristics between phenotypes while adjusting for disease duration. We examined 2696 SSc patients with at least two Medsger GI scores, identifying four unique phenotypes. The most common phenotype (n = 2325) ("Stable") had an average score of 1 that was consistent over time. Two phenotypes were progressive ["Early Progressive" (n = 142) and "Late Progressive" (n = 115)] with an initial average score of 1. The Early Progressive group increased initially and stabilized, and the Late Progressive group worsened slowly over time. A fourth phenotype ["Early Severe GI"; (n = 114)] had an initial average Medsger GI score just below 3 with high mortality and improving GI severity over time. Clinically distinct GI phenotypes exist among patients with SSc. These phenotypes are not only distinguished by GI and extra-intestinal SSc clinical complications, but they are also temporally distinct. Distinct autoantibody profiles are associated strongly with more severe GI disease.

Identification and validation of anti-protein arginine methyltransferase 5 (PRMT5) antibody as a novel biomarker for systemic sclerosis (SSc)

ObjectivesIn the complex panorama of autoimmune diseases, the characterisation of pivotal contributing autoantibodies that are involved in disease progression remains challenging. This study aimed to employ a global antibody profiling...