OBJECTIVE: The aim of this study was to measure trajectories of craving for methamphetamine during the course of pharmacotherapy trials for methamphetamine use disorder.
METHODS: Craving trajectories were identified using Group-Based Trajectory Modeling. The association of craving trajectories with drug use trajectories was examined using a dual trajectory model. Association of craving trajectories with other health and social outcomes was also examined. The study used pooled data from five randomized controlled pharmacotherapy trials for methamphetamine use disorder. A total of 866 adults with methamphetamine use disorder participated in randomized controlled pharmacotherapy trials.
METHODS: Craving was assessed weekly using the Brief Substance Craving Scale. Drug use was assessed using urine toxicology. Alcohol- and drug-related problems, as well as psychiatric, medical, legal, employment and relationship problems, were measured using the Addiction Severity Index.
RESULTS: A three-trajectory model with high, medium and low craving trajectories was selected as the most parsimonious model. Craving trajectories were associated with methamphetamine use trajectories in the course of trial; 88.4% of those in the high craving trajectory group had a consistently high frequency of methamphetamine use compared with 18.7% of those in the low craving group. High craving was also associated with less improvement in most other outcomes and higher rate of dropout from treatment. In turn, low craving was associated with a rapidly decreasing frequency of methamphetamine use, greater improvement in most other outcomes and a lower rate of dropout. Participants on modafinil daily and ondansetron 1 mg twice daily were less likely to be in the high craving group compared with those on placebo.
CONCLUSIONS: Trajectories of methamphetamine craving in the course of clinical trials for methamphetamine use disorder appear to be both highly variable and strongly associated with greater frequency of drug use, other drug-related outcomes and dropout from trials. Two medications, modafinil daily and ondansetron at a dose of 1 mg two times daily, appear to be associated with greater reduction in craving in the course of treatment compared with placebo. A decrease in methamphetamine craving shows promise as an early indicator of recovery from methamphetamine use disorder.

Unsupervised feature selection is a critical step for efficient and accurate analysis of single-cell RNA-seq data. Previous benchmarks used two different criteria to compare feature selection methods: (i) proportion of ground-truth marker genes included in the selected features and (ii) accuracy of cell clustering using ground-truth cell types. Here, we systematically compare the performance of 11 feature selection methods for both criteria. We first demonstrate the discordance between these criteria and suggest using the latter. We then compare the distribution of selected genes in their means between feature selection methods. We show that lowly expressed genes exhibit seriously high coefficients of variation and are mostly excluded by high-performance methods. In particular, high-deviation- and high-expression-based methods outperform the widely used in Seurat package in clustering cells and data visualization. We further show they also enable a clear separation of the same cell type from different tissues as well as accurate estimation of cell trajectories.

Molecular simulation (MD) is a crucial research domain within the life sciences, focusing on comprehending the mechanisms of biomolecular interactions at atomic scales. Protein simulation, as a critical subfield, often utilizes MD for implementation, with trajectory data play a pivotal role in drug discovery. The advancement of high-performance computing and deep learning technology becomes popular and critical to predict protein properties from vast trajectory data, posing challenges regarding data features extraction from the complicated simulation data and dimensionality reduction. Simultaneously, it is essential to provide a meaningful explanation of the biological mechanism behind dimensionality. To tackle this challenge, we propose a new unsupervised model named RevGraphVAMP to intelligently analyze the simulation trajectory. This model is based on the variational approach for Markov processes (VAMP) and integrates graph convolutional neural networks and physical constraint optimization to enhance the learning performance. Additionally, we introduce attention mechanism to assess the importance of key interaction region, facilitating the interpretation of molecular mechanism. In comparison to other VAMPNets models, our model showcases competitive performance, improved accuracy in state transition prediction, as demonstrated through its application to two public datasets and the Shank3-Rap1 complex, which is associated with autism spectrum disorder. Moreover, it enhanced dimensionality reduction discrimination across different substates and provides interpretable results for protein structural characterization.

BACKGROUND: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.
METHODS: We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a \"backward-looking\" trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.
RESULTS: Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10-11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1-3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75-65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).
CONCLUSIONS: Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect.

This paper undertakes an analysis and discussion of the methodological challenges and insights derived from three longitudinal qualitative studies, all conducted in Chile during the COVID-19 pandemic and subject to comprehensive theoretical-methodological reflection processes centred on their respective designs. This analysis makes a significant contribution to interdisciplinary discussions within social research, with a particular emphasis on longitudinal trajectories. First, we present a comparative analysis of three studies in social work, utilising Saldaña\'s questions addressing changes and learning in longitudinal studies. The first study explores the labour trajectories of researchers, the second focuses on the educational trajectories of students, and the last examines therapeutic alliance trajectories between social workers and families within the child protection system. Following this, we delve into the methodological decisions made by the research group during the execution of these longitudinal studies. This encompasses an examination of participant involvement, temporal definitions of the adopted designs, and the most suitable methodological tools for analysing change processes over time. The outcomes of this comparative analysis reveal the distinctive characteristics of the three longitudinal studies, providing insights into how the time dimension is explored within them. We highlight key criteria essential for consideration in longitudinal qualitative research, particularly regarding participants and methodology. In conclusion, we advocate for an expanded reflection within the realm of longitudinal qualitative methodology, encompassing aspects such as design choices, approaches to data analysis, integration of technology in information processing, and strategies for maintaining participant engagement.

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.

BACKGROUND: The association between exposure to air pollutants and cardiovascular disease (CVD) trajectory in individuals with circadian syndrome remains inconclusive.
METHODS: The individual exposure levels of air pollutants, including particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM with aerodynamic diameter ≤ 10 μm (PM10), PM2.5 absorbance, PM with aerodynamic diameter between 2.5 μm and 10 μm, nitrogen dioxide (NO2), nitrogen oxides (NOx), and air pollution score (overall air pollutants exposure), were estimated for 48,850 participants with circadian syndrome from the UK Biobank. Multistate regression models were employed to estimate associations between exposure to air pollutants and trajectories from circadian syndrome to CVD/CVD subtypes (including coronary heart disease [CHD], atrial fibrillation [AF], heart failure [HF], and stroke) and death. Mediation roles of CVD/CVD subtypes in the associations between air pollutants and death were evaluated.
RESULTS: After a mean follow-up time over 12 years, 12,570 cases of CVD occurred, including 8192 CHD, 1693 AF, 1085 HF, and 1600 stroke cases. In multistate model, per-interquartile range increment in PM2.5 (hazard ratio: 1.08; 95 % confidence interval: 1.06, 1.10), PM10 (1.04; 1.01, 1.06), PM2.5 absorbance (1.04; 1.02, 1.06), NO2 (1.07; 1.03, 1.11), NOx (1.08; 1.04, 1.12), or air pollution score (1.06; 1.03, 1.08) was associated with trajectory from circadian syndrome to CVD. Significant associations between the above-mentioned air pollutants and trajectories from circadian syndrome and CVD to death were observed. CVD, particularly CHD, significantly mediated the associations of PM2.5, NO2, NOx, and air pollution score with death.
CONCLUSIONS: Long-term exposure to air pollutants during circadian syndrome was associated with subsequent CVD and death. CHD emerged as the most prominent CVD subtype in CVD progression driven by exposure to air pollutants during circadian syndrome. Our study highlights the importance of controlling air pollutants exposure and preventing CHD in people with circadian syndrome.

OBJECTIVE: To evaluate the association between psychosocial stress (PS) trajectories and pubertal outcomes of girls and boys in a Chinese cohort (2015-2022).
METHODS: Pubertal outcomes of 732 girls and 688 boys were physically examined every 6 months. Stressful life events were repeatedly assessed 7 times. Group-Based Trajectory Model was fitted for the optimum trajectories of total PS and PS from 5 sources. Cox model adjusted for age, BMI and socioeconomic factors was used to evaluate the association.
RESULTS: Compared to the \"low, gradual decline\" trajectory, the \"moderate, gradual decline\" trajectory of total PS was associated with late menarche (HR: 0.816, 95% CI: 0.677-0.983), late pubic hair development (HR: 0.729, 95% CI: 0.609-0.872) and late axillary hair development (HR: 0.803, 95% CI: 0.661 - 0.975) in girls. Girls following the \"high, rise then decline\" trajectory of PS from family life demonstrated delayed axillary hair development (HR: 0.752, 95% CI: (0.571-0.990). As for boys, the \"high, rise then decline\" trajectory of PS from academic adaptation (HR: 0.670, 95% CI: 0.476 - 0.945) and life adaptation (HR: 0.642, 95% CI: 0.445 - 0.925) was associated with late axillary hair development. Boys in the \"moderate, gradual decline\" trajectory of PS from peer relationship was at risk of early testicular development (HR: 1.353, 95% CI: 1.108 - 1.653).
CONCLUSIONS: Chronic PS may be associated with delayed onset of several pubertal signs in both girls and boys. It may also accelerate testicular development of boys, indicating its varying impact on pubertal timing during early and later stages.

OBJECTIVE: White blood cells (WBC) play an important role in the inflammatory response of the body. Elevated WBC counts on admission in patients with subarachnoid hemorrhage (SAH) correlate with a poor prognosis. However, the role of longitudinal WBC trajectories based on repeated WBC measurements during hospitalization remains unclear. We explored the association between different WBC trajectory patterns and in-hospital mortality.
METHODS: We analyzed a cohort of consecutive patients with SAH between 2012 and 2020. Group-based trajectory modeling (GBTM) was used to group the patients according to their white blood cell patterns over the first 4 days. Stabilized inverse probability treatment weighting (sIPTW) was used to balance baseline demographic and clinical characteristics. We analyzed the association between the WBC trajectory groups and in-hospital mortality using a Cox proportional hazards model.
RESULTS: In total, 506 patients with SAH were included in this retrospective cohort. The final model identified two distinct longitudinal WBC trajectories. After adjusting for confounding factors, multivariate regression analysis suggested that an elevated longitudinal WBC trajectory increased the risk of in-hospital mortality (hazard ratio [HR], 2.476; 95% confidence interval [CI] 1.081-5.227; P = 0.024) before sIPTW, and (HR, 2.472; 95%CI 1.489-4.977; P = 0.018) after sIPTW.
CONCLUSIONS: In patients with SAH, different clinically relevant groups could be identified using WBC trajectory analysis. The WBC count trajectory-initially elevated and then decreased- may lead to an increased risk of in-hospital mortality following SAH.

UNASSIGNED: The postpartum period is a critical phase in which postpartum women experience dynamic changes in their physiology, psychology, and family status.
UNASSIGNED: This study investigated the changes in women\'s quality of life (QoL) during the first, third, and sixth months of the postpartum period and their associated factors.
UNASSIGNED: A single-group repeated-measure design was used to collect data from 282 postpartum women recruited from a regional hospital in Taiwan. We used the brief World Health Organization Quality of Life scale, Social Support Scale, and Edinburgh Postnatal Depression Scale to assess postpartum women\'s quality of life, social support, and postpartum depressive symptoms, respectively. The data were analyzed using trajectory analysis and generalized estimating equations.
UNASSIGNED: The trajectory analysis indicated that postpartum women could be categorized into low, medium, and high QoL groups. Although the medium and high QoL groups maintained stable QoL levels, the low QoL group experienced a linear decrease in QoL over time. Moreover, the determinants of postpartum women\'s QoL were immigrant status, employment status, family type, social support, and postpartum depression.
UNASSIGNED: Health care providers should assess these determinants of postpartum QoL in perinatal women to identify those at risk of low postpartum quality of life. Early assessment and intervention by health care providers could significantly improve the health status of women after childbirth.