Individual Trajectories Research Articles

Unraveling urban dynamics: Scaling laws of human mobility across the cityscape divide

The scaling laws of human mobility are one of the key theories of human geography. They also have important policy implications for urban-rural integration and regional economic growth. Although scaling laws of human mobility have been widely discussed, the allometric growth between urban and rural areas is overlooked. This study aims to fill the gap by investigating scaling laws and power-law distribution across urban and rural areas during urban growth with individual people's trajectory information of 13 million mobile phone users. The analysis identified a turning point at a population of 1.8 million in the Greater Bay Area, where the growth rate of aggregate travel demand stabilizes. The results show that human mobility exhibits segmented allometric growth, with superlinear growth transitioning to sublinear beyond this turning point. The disparities of travel behaviour patterns between urban and rural populations increase as cities grow. These findings would enhance the existing knowledge of the allometric scaling of human mobility.

Changes in Medication Adherence Across the Posttransplant Period in Pediatric Organ Transplant Recipients.

Limited research has explored immunosuppressant medication adherence over time in pediatric transplant patients, who often struggle with posttransplant regimen adherence, resulting in poor outcomes. This study investigated the longitudinal growth in immunosuppressive medication levels following transplantation. Medication level variability index (MLVI) scores from tacrolimus blood levels of pediatric organ transplant recipients at a major medical center were analyzed. Linear mixed effect models (LMEM) assessed individual MLVI change trajectories and predictors of growth, exploring both linear and curvilinear growth patterns posttransplant. A sample of 181 patients with at least 4 years of MLVI data were analyzed. Growth curve modeling identified the cubic model as the best fit for the quarterly MLVI values, which significantly decreased within the first 2 years posttransplant before stabilizing. Gender significantly predicted MLVI change, with females showing greater MLVI decreases, while age at transplant did not significantly predict changes. Significant variation in MLVI among individual patients was found in all models. The study demonstrated a significant decrease in MLVI values over time, indicating improved medication adherence in pediatric transplant patients, with females exhibiting more adherent growth patterns than males. Future research should aim to identify pediatric patients at high risk of nonadherence.

Healthcare professionals beliefs and priorities for the rehabilitation of patients after ankle fracture surgery: A qualitative study

ObjectiveThe study aims to understand healthcare professionals’ (HCPs) beliefs and practices in the treatment and rehabilitation of patients after ankle fracture surgery, with the goal of informing new rehabilitation interventions based on these insights. BackgroundThere is considerable variation in postoperative rehabilitation advice given to patients with ankle fractures, leading to inconsistent care. Prior studies have primarily focused on patients' experiences, making it crucial to explore HCPs' perspectives to identify areas for intervention. MethodsThe study utilised semi-structured interviews with HCPs involved in the multicentre randomised controlled Weightbearing in Ankle Fractures (WAX) trial. Interviewees included physiotherapists, consultant trauma and orthopaedic surgeons, and trainee surgeons. Interviews were conducted between February 2020 and December 2021. Data were analysed using a mixed deductive and inductive approach, aligning with the Behavioural Change Wheel framework to translate findings into potential intervention strategies. Results18 Interviews were conducted, revealing discrepancies between patient and HCP beliefs about recovery, particularly regarding weight-bearing and managing physical symptoms like swelling and numbness. HCPs expressed varying beliefs on the safety of early weight-bearing and recognised historical practice and medicolegal concerns influencing rehabilitation advice. Themes highlighted the need for clearer communication, standardised advice, and the impact of HCPs' remarks on patients' recovery confidence. ConclusionsFindings underscore the mismatch between patient expectations and HCP guidance, emphasising the need for consensus on rehabilitation protocols. The study advocates for tailored rehabilitation pathways that address individual patient recovery trajectories, reduce dependency on HCPs, and encourage patient self-management.

Reexamining exposure from truck emissions considering daily movement of individuals

With the growing demand for urban freight transportation, trucks emit a large amount of pollutants such as particulate matters and nitrogen oxides, increasingly affecting public health. This study establishes a modelized air dispersion structure to simulate pollutant concentration distribution. By integrating multiple data sources including mobile phone signals and satellite images, we reconstruct the daily trajectories of individuals and further incorporate simulated pollution concentrations in calculating dynamic and static exposure of individuals to truck emissions. Econometric models considering spatial dependence are developed to evaluate the influencing factors and elucidate the mechanisms of pollutant exposure. Results show factors including freight demand, road network, residential and employment locations, personal commuting distance, and population age structure matter in assessing truck emission exposure. As a result, a mixture of vehicular emission standards, urban traffic control, land planning, and industrial policies is proposed to reduce truck pollutant exposure and safeguard public health.

A dual-level graph attention network and transformer for enhanced trajectory prediction under road network constraints

Predicting vehicle future trajectories enables various Location-Based Services (LBS), including traffic flow monitoring, vehicle route planning, etc. Vehicles are constrained to predefined road networks. Their traveling behaviors are influenced by both their own attributes and road network characteristics hidden in other vehicles’ travel histories. Most of the existing methods fail to sufficiently leverage such collaborative trajectory data under road network constraints. This paper proposes a novel model, called HGT-RN (Hierarchical Graph Attention Network and Transformer Networks for Enhanced Trajectory Prediction under Road Network Constraints), which exploits all vehicles’ trajectories and integrates road network constraints. Specifically, HGT-RN creates a dual-level Graph Attention Network (GAT) based on global traffic flow and local individual trajectory graph to learn trajectory embeddings: (i) Weighted-directional global traffic flow graph and Weighted-Directional GAT to learn the global-level trajectory embedding by aggregating the neighbors’ embeddings based on the spatial transitional relationships among road intersections over all vehicles’ trajectories, considering the preference of current trajectory; and (ii) Local individual trajectory graph attention network to learn the local-level trajectory embedding by modeling the transitions within the current trajectory at each intersection. When incorporating the trajectory embeddings into a transformer model for future trajectory prediction, a road network topology-aware loss function is designed to improve accuracy. Extensive experiments conducted on three city-scale real-world taxi trajectory datasets demonstrate that HGT-RN significantly outperforms existing baseline models. The code is available at https://github.com/zjy9826/HGT-RN.

ПОВЫШЕНИЕ МОТИВАЦИИ И РЕАЛИЗАЦИЯ ИНДИВИДУАЛЬНЫХ ОБРАЗОВАТЕЛЬНЫХ ТРАЕКТОРИЙ ПРИ ПОДГОТОВКЕ ПРОВИЗОРА

Junior year students of the specialty Pharmacy study basic biological and chemical disciplines, the knowledge they gain forms the foundation for mastering specialized pharmaceutical disciplines. Very often, students do not see the relationship between basic and specialized disciplines, their interest to learn decreases, and gaps in basic knowledge negatively affect mastering of specialized disciplines. The paper presents the results of the implementation of individual educational trajectories in the preparation of a pharmacist and increased motivation to study in students of the specialty Pharmacy as a result of the curriculum discipline “Introduction to the specialty” studied in the first year, as well as elective disciplines and project-based learning. The study was carried out by surveying 98% of the 1st to 4th-year students. According to the survey results, more than 70% of respondents had increased motivation to study basic disciplines and to master the specialty in general. A set of educational activities is proposed aimed at implementing individual educational trajectories in the preparation of a pharmacist, increasing the level of motivation for learning and professional determination in the specialty Pharmacy.

Integrating Scientific and Everyday Concepts: Student Leadership in a Language Learning Community

This study examines the role of everyday and scientific concepts in developing student leadership in a self-access learning center (SALC) in Japan. For this purpose, data from three student learning community leaders and one SALC faculty member participating in an 18-month ethnographic case study of the Learning Group (LG), a student-led learning community within a university-based SALC in central Japan, was reexamined according to a framework informed by concept-based learning. Data was first coded inductively utilizing reflective thematic analysis (Braun & Clarke, 2006) and subsequently deductively using communities of practice theory and the themes of scientific and everyday knowledge. This data highlights numerous ways three leaders of the LG had internalized concepts introduced to them through a SALC-based leadership course administered by a learning advisor (LA) and how this influenced not only their individual learning trajectories, but also the path of their community. Furthermore, the LG leaders were able to develop coherent management/facilitation guidelines for themselves and for future generations of leaders from the social mediation that collaborative group reflection and intentional reflective dialogue afforded. The implications of this study highlight the potential value within SALCs of learning advisors engaging in concept-based instructional approaches where explicit instruction is internalized through dialogic and communicative verbalization and through finding avenues for learners to apply scientific concepts to everyday practice.

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.

The revolution in high-throughput proteomics and AI.

The recent capability to measure thousands of plasma proteins from a tiny blood sample has provided a new dimension of expansive data that can advance our understanding of human health. For example, the company SomaLogic has developed the means to measure more than 10,000 proteins and Thermo Fisher's Olink assays over 5400 proteins from as little as 2 μl. When these rich data are integrated with other layers of information from large patient cohorts, such as the UK Biobank's genetic, health, and lifestyle information from half a million participants, we get new insights about the underpinnings of disease, the aging process, and the potential ability to forecast an individual's health trajectory.

Sex-Dependent Effects of Cardiometabolic Health and APOE4 on Brain Age: A Longitudinal Cohort Study.

The aging population is growing faster than all other demographic strata. With older age comes a greater risk of health conditions such as obesity and high blood pressure (BP). These cardiometabolic risk factors (CMRs) exhibit prominent sex differences in midlife and aging, yet their influence on brain health in females vs males is largely unexplored. In this study, we investigated sex differences in relationships between BP, body mass index (BMI), and brain age over time and tested for interactions with APOE ε4 genotype (APOE4), a known genetic risk factor of Alzheimer disease. The sample included participants from 2 United Kingdom-based longitudinal birth cohorts, the Lothian Birth Cohort (1936) and Insight 46 (1946). Participants with MRI data from at least 1 time point were included to evaluate sex differences in associations between CMRs and brain age. The open-access software package brainageR 2.1 was used to estimate brain age for each participant. Linear mixed-effects models were used to assess the relationships between brain age, BMI, BP, and APOE4 status (i.e., carrier vs noncarrier) in males and females over time. The combined sample comprised 1,120 participants (48% female) with a mean age (SD) of 73 (0.72) years in the Lothian Birth Cohort and 71 (0.68) years in Insight 46 at the time point 1 assessment. Approximately 30% of participants were APOE4 carriers. Higher systolic and diastolic BP was significantly associated with older brain age in females only (β = 0.43-0.56, p < 0.05). Among males, higher BMI was associated with older brain age across time points and APOE4 groups (β = 0.72-0.77, p < 0.05). In females, higher BMI was linked to older brain age among APOE4 noncarriers (β = 0.68-0.99, p < 0.05), whereas higher BMI was linked to younger brain age among carriers, particularly at the last time point (β = -1.75, p < 0.05). This study indicates sex-dependent and time-dependent relationships between CMRs, APOE4 status, and brain age. Our findings highlight the necessity of sex-stratified analyses to elucidate the role of CMRs in individual aging trajectories, providing a basis for developing personalized preventive interventions.

Music, Exile, and Edward Said: An Interview with Layale Chaker

Abstract The following interview with Layale Chaker, conducted on 14 September 2023, delves into her unique journey as a Palestinian-Lebanese composer, highlighting the pivotal role of music in shaping her sense of “home” following the Lebanese Civil War. Drawing from her diverse musical upbringing, spanning community choirs to formal conservatory education, Chaker elucidates the disparity between institutional training and the lived musical experiences of the Arab world, informing her quest for authenticity in composition. Chaker recounts her involvement with the West-Eastern Divan Orchestra, founded by Daniel Barenboim and Edward Said, juxtaposed with her decision to pursue an individual artistic trajectory. Central to the conversation is her composition “En Présence de l'Absence – Homáge à Edward Saïd,” revealing a deeply personal connection to Said's legacy and a nuanced exploration of his ethos through music. The interview culminates with insights into Chaker's forthcoming opera, “Ruinous Gods,” co-crafted with playwright Lisa Schlesinger. Addressing the profound trauma of refugee children afflicted with uppgivenhetssyndrom (resignation syndrome), the opera promises a poignant musical narrative probing themes of parenthood, displacement, and societal obligation. Set for premiere at the 2024 Spoleto Festival USA, Chaker's work continues to blend artistry with advocacy, offering a resonant reflection on human resilience and responsibility.

Условия эффективной педагогической поддержки обучающихся в процессе их самоопределения в ситуациях активного и интерактивного обучения

Introduction. The tendency to increase the role of independent learning activities of students has actualized the search and implementation of effective conditions for their pedagogical support in the process of using active and interactive teaching methods. Theoretical analysis of the research allowed us to conclude that pedagogical support should be considered as a teacher’s creation of certain conditions for independent work of students in order to form incentives for self-determination through their choice of individual and/or group educational trajectories. Empirical analysis. To verify the assumption that active and interactive teaching methods have a significant potential for pedagogical support of the process of self-determination of students, a study was conducted with the participation of students of two groups of 1st year students of V. I. Razumovsky SSMU (N = 20), within the framework of teaching a theoretical discipline. Conclusion. The study allowed us to conclude that effective conditions of pedagogical support are: trusting dialogical interaction between teachers and students, pedagogical consulting of students at their request, organization of work on a group project using active and interactive methods of group learning interaction; providing an opportunity to develop and implement an individual educational trajectory within the framework of work on a group project.

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.

The use of the QGIS tools to determine hydrological characteristics. The experience in higher education

The development of geo-information systems with open access significantly expands the information technology possibilities in the modern educational environment. The use of geoinformation technologies is especially important for STEM specialties, for whom mastering BIM technology is a significant advantage in the labor market. Quantum geographic information system QGIS is widely used by various STEM specialties to expand learning opportunities and gain practical experience of calculations in higher education both in Ukraine and abroad. Morphometric parameters calculation for Ulichka river by QGIS tools is represented in the article. The 1st year master's degree students used QGIS for hydrological calculations. The calculations performed on QGIS were compared with the reference data and cartographic materials of Google map. Calculations showed a high correspondence of the obtained results with reference literature. Modern geographic information systems with free code are not very complex, but require additional knowledge and work skills. Methodical materials and information about additional possibilities of QGIS tools encourage students to study related educational components and search for information on Internet resources, which contributes to the development of the individual student trajectory and stimulates the study of professional English vocabulary. The ability to obtain high-quality illustrative material in the form of scaled maps with reference to coordinates provides the possibility of further use of the obtained material in BIM designs on the Autodesk family software and to use the results in future attestation thesis.

Pedagogical conditions for developing the readiness of master's degree applicants for intercultural interaction in the process of professional (piano) training

The article defines and characterizes the pedagogical conditions for forming the readiness of master's degree applicants for intercultural interaction in the process of professional (piano) training. It is emphasized that the tasks of the modern professional training of the applicants of the piano master's degree are not only to ensure a high level of professional knowledge of students, but also their practical preparation for social life and self-realization as an individual. It is emphasized that the humanization of the process of formation of the readiness for intercultural interaction in applicants of the professional master's degree implies the use of the latest technologies, active teaching methods, which would form the motives of educational and artistic activity, contribute to the discovery and development of the creative potential of the education applicant, self-realization of his/her personality; included in the process of learning the sphere of emotions, contributed to the development of cooperation. It has been proven that in the process of forming value orientations in the conditions of a multicultural artistic and educational environment, individual support of piano master's students is successfully implemented through individual counseling, creation of a positive moral and psychological climate in classes, mentoring support of the artistic and educational process, building an individual educational trajectory. Considering the formation and transformation of music-pedagogical and artistic-aesthetic paradigms in the system of modern music education, it is emphasized that the change in the paradigm of music education involves a shift of emphasis from the development in applicants of a complex of special knowledge, abilities and skills, focused on the formation of professional multicultural competence in the conditions of intercultural interaction, which allows us to interpret the artistic and educational space as a unity of creative personalities, united by channels of musical communication, who feel a sense of empathy for each other, mutual interest, are capable of active creative joint activity, overcoming interaction problems, creating a cross-cultural space

Treatment trajectories for Danish individuals with type 2 diabetes in the era of emerging glucose-lowering therapies.

To analyse patterns of glucose-lowering therapies among people with type 2 diabetes (T2D) in Denmark from 2016 to 2023. We examined time trends in the clinical profiles of people with T2D who initiated different glucose-lowering therapy classes for the first time. We furthermore investigated individual-level treatment trajectories following first-ever glucose-lowering therapy in people with or without cardiorenal disease. The study utilized data from the nationwide Danish health registries and included all individuals who filled a first-ever prescription for metformin, dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), sodium-glucose co-transporter-2 inhibitors (SGLT-2is) or insulin, excluding those without HbA1c-confirmed T2D or probable type 1 diabetes. We included 260 393 individuals initiating a new glucose-lowering therapy class from 2016 to 2023, during which there were 6- and 3-fold increases in initiators of GLP-1RAs and SGLT-2is, respectively. The median HbA1c level at treatment initiation with GLP-1RAs or SGLT-2is decreased, from 67-68 mmol/mol in 2016-2017 to 57-58 mmol/mol in 2022-2023. Among individuals who initiated metformin as first-line therapy, the proportion who started additional glucose-lowering therapy within 2 years increased from 25% in 2016 to 40% in 2021. Among the 38% of individuals who had established cardiorenal disease when they initiated first-ever glucose-lowering therapy in 2020, 22% used SGLT-2is and 18% GLP-1RAs after 2.5 years, compared with 17% and 21% among initiators without cardiorenal disease, respectively. Our study documents a trend towards earlier T2D treatment intensification and an increase in the use of GLP-1RAs and SGLT-2is in Denmark. However, optimal T2D treatment is still not received by most individuals with early T2D and established cardiorenal disease.

Methods for phenotyping adult patients with acute kidney injury: a systematic review.

Acute kidney injury (AKI) is a multifaceted disease characterized by diverse clinical presentations and mechanisms. Advances in artificial intelligence have propelled the identification of AKI subphenotypes, enhancing our capacity to customize treatments and predict disease trajectories. We conducted a systematic review of the literature from 2017 to 2022, focusing on studies that utilized machine learning techniques to identify AKI subphenotypes in adult patients. Data were extracted regarding patient demographics, clustering methodologies, discriminators, and validation efforts from selected studies. The review highlights significant variability in subphenotype identification across different populations. All studies utilized clinical data such as comorbidities and laboratory variables to group patients. Two studies incorporated biomarkers of endothelial activation and inflammation into the clinical data to identify subphenotypes. The primary discriminators were comorbidities and laboratory trajectories. The association of AKI subphenotypes with mortality, renal recovery and treatment response was heterogeneous across studies. The use of diverse clustering techniques contributed to variability, complicating the application of findings across different patient populations. Identifying AKI subphenotypes enables clinicians to better understand and manage individual patient trajectories. Future research should focus on validating these phenotypes in larger, more diverse cohorts to enhance their clinical applicability and support personalized medicine in AKI management.

Difference in trajectories according to early amyloid accumulation in cognitively unimpaired elderly.

Amyloid β (Aβ), a major biomarker of Alzheimer's disease, leads to tau accumulation, neurodegeneration and cognitive decline. Modelling the trajectory of Aβ accumulation in cognitively unimpaired (CU) individuals is crucial, as treatments targeting Aβ are anticipated. The evolution of Aβ levels was investigated to determine whether it could lead to classification into different groups by studying longitudinal Aβ changes in older CU individuals, and differences between the groups were compared. A total of 297 CU participants were included from the Alzheimer's Disease Neuroimaging Initiative database, and these participants underwent apolipoprotein E (APOE) genotyping, neuropsychological testing, brain magnetic resonance imaging, and an average of 3.03 follow-up 18F-florbetapir positron emission tomography scans. Distinct Aβ trajectory patterns were classified using latent class growth analysis, and longitudinal cognitive performances across these patterns were assessed with a linear mixed effects model. The optimal model consisted of three classes, with a high entropy value of 0.947. The classes were designated as follows: class 1, non-accumulation group (n = 197); class 2, late accumulation group (n = 70); and class 3, early accumulation group (n = 30). The late accumulation and early accumulation groups had more APOE ε4 carriers than the non-accumulation group. The longitudinal analysis of cognitive performance revealed that the early accumulation group showed the steepest decline (modified Preclinical Alzheimer's Cognitive Composite with digit symbol substitution [mPACCdigit], p < 0.001; modified Preclinical Alzheimer's Cognitive Composite with trails B [mPACCtrailsB], p < 0.001) and the late accumulation group showed a steeper decline (mPACCdigit, p = 0.014; mPACCtrailsB, p = 0.007) compared to the non-accumulation group. Our study showed the heterogeneity of Aβ accumulation trajectories in CU older individuals. The prognoses for cognitive decline differ according to the Aβ trajectory patterns.

Transcriptomic profiles in major depressive disorder: the role of immunometabolic and cell-cycle-related pathways in depression with different levels of inflammation.

Transcriptomic profiles are important indicators for molecular mechanisms and pathways involved in major depressive disorder (MDD) and its different phenotypes, such as immunometabolic depression. We performed whole-transcriptome and pathway analyses on 139 individuals from the observational, case-control, BIOmarkers in DEPression (BIODEP) study, 105 with MDD and 34 controls. We divided MDD participants based on levels of inflammation, as measured by serum high-sensitivity C-reactive protein (CRP), in n = 39 'not inflamed' (CRP < 1 mg/L), n = 31 with 'elevated CRP' (1-3 mg/L), and n = 35 with 'low-grade inflammation' (>3 mg/L). We performed whole-blood RNA sequencing using Illumina NextSeq 550 and statistical analyses with the Deseq2 package for R statistics (RUV-corrected) and subsequent pathway analyses with Ingenuity Pathway Analysis. Immunometabolic pathways were activated in individuals with CRP > 1 mg/L, although surprisingly the CRP 1-3 group showed stronger immune activation than the CRP > 3 group. The main pathways identified in the comparison between CRP < 1 group and controls were cell-cycle-related, which may be protective against immunometabolic abnormalities in this 'non-inflamed' depressed group. We further divided MDD participants based on exposure and response to antidepressants (n = 47 non-responders, n = 37 responders, and n = 22 unmedicated), and identified specific immunomodulatory and neuroprotective pathways in responders (especially vs. non-responders), which could be relevant to treatment response. In further subgroup analyses, we found that the specific transcriptional profile of responders is independent of CRP levels, and that the inhibition of cell-cycle-related pathways in MDD with CRP < 1 mg/L is present only in those who are currently depressed, and not in the responders. The present study demonstrates immunometabolic and cell-cycle-related transcriptomic pathways associated with MDD and different (CRP-based and treatment-based) MDD phenotypes, while shedding light on potential molecular mechanisms that could prevent or facilitate an individual's trajectory toward immunometabolic depression and/or treatment-non-responsive depression. The recognition and integration of these mechanisms will facilitate a precision-medicine approach in MDD.

A Remote Patient Monitoring System with Feedback Mechanisms using a Smartwatch: Concept, Implementation and Evaluation based on the activeDCM Randomized Controlled Trial.

Technological advances allow recording and sharing of health-related data in a patient-centric way using smartphones and wearables. Secure sharing of such patient-generated data with physicians would enable a dense management of individual health trajectories, monitoring of risk factors and asynchronous feedback. However, most Remote Patient Monitoring (RPM) systems currently available are not fully integrated into hospital IT systems or lack the patient-centric design. The objective was to conceptualize and implement a user-friendly, reusable, interoperable and secure RPM system incorporating asynchronous feedback mechanisms, using a broadly available consumer wearable (Apple Watch). Additionally, the study sought to evaluate factors influencing patient acceptance of such systems. The RPM system requirements were established through focus group sessions. Subsequently, a system concept was designed and implemented using an iterative approach, ensuring technical feasibility from the beginning. To assess clinical feasibility, the system was employed as part of the activeDCM prospective, randomized, interventional study focusing on Dilated Cardiomyopathy (DCM). Each patient used the system for at least 12 months. The System Usability Scale (SUS) was employed to measure usability from a subjective patient perspective. Additionally, an evaluation was conducted on the objective wearable interaction frequency as well as the completeness of transmitted data, classified into Sensor-based Health Data (SHD) and Patient Reported Outcome Measures (PROM). Descriptive statistics using boxplots, along bootstrapped multiple linear regression with a 95% confidence interval (CI) were utilized for evaluation, analyzing the influence of age, sex, device experience and intervention group membership. The RPM system consists of four interoperable components: patient-devices, data-server, data-viewer and notification-service. The evaluation of the system was conducted with 95 consecutive DCM patients (female: 28 of 95 (29%), age: 50±12 years) completing the activeDCM study protocol. The wearable/ smartphone application of the system achieved a mean SUS score of 78±17, which was most influenced by device experience. 83 of 95 patients (87%) could integrate the wearable application (very) well into their daily routine and 67 of 95 (70%) saw a benefit of the RPM system for management of their health condition. Patients interacted on average with the wearable on 61%±26% of days enrolled in the study, corresponding to 239±99 of 396±39 days. SHD was available on average for 78%±23% of days and PROM data 64%±27% of weeks enrolled in the study, corresponding to 307±87 of 396±39 days and 35±15 of 56±5 weeks, respectively. Wearable interaction frequency, SHD and PROM completeness were most influenced by intervention group membership. Our results mark a first step towards integrating RPM systems, based on a consumer wearable device for primary patient input, into standardized clinical workflows. They can serve as a blueprint for creating a user-friendly, reusable, interoperable and secure RPM system, that can be integrated into patients' daily routines. ClinicalTrials.gov-Identifier: NCT04359238.