Maternal weight, smoking, and diabetes provided early predictors of longitudinal body mass index growth patterns in childhood

AIM

The aim of this study was to identify factors affecting overweight growth development using extended body mass index (BMI) data combined with birth and maternal records from Finnish national registries.

METHODS

The longitudinal data consist of growth measurements of 7372 from six birth cohorts in Finland: 1974 (n = 1109), 1981 (n = 983), 1991 (n = 607), 1994-1995 (n = 829), 2001 (n = 821), and 2003-2004 (n = 3023). Anthropometric data were collected from birth to age 15 years from the health records. Pregnancy health data were included for the four most recent birth cohorts (n = 2810). A statistical method called trajectory analysis was used to identify different BMI development trajectories. Factors associated with abnormal growth tracks were analysed using logistic regression models.

RESULTS

High pre-pregnancy BMI, gestational diabetes mellitus, maternal smoking, and greater gestational weight gain than the Institute of Medicine (United States) recommendations were associated with the overweight growth track. Two of the trajectories didn't seem to follow the normal growth pattern: overweight growth track appeared to lead to overweight, while low birth BMI track showed accelerating growth after the adiposity rebound point of BMI growth.

CONCLUSION

These findings suggest that maternal overweight before pregnancy, excessive gestational weight gain, gestational diabetes mellitus, and smoking could potentially be associated with the risk of obesity in children.

MPI-parallelization of the grid inhomogeneous solvation theory calculation

The grid inhomogeneous solvation theory (GIST) method requires the often time-consuming calculation of water-water and water-solute energy on a grid. Previous efforts to speed up this calculation include using OpenMP, GPUs, and particle mesh Ewald. This article details how the speed of this calculation can be increased by parallelizing it with MPI, where trajectory frames are divided among multiple processors. This requires very little communication between individual processes during trajectory processing, meaning the calculation scales well to large processor counts. This article also details how the entropy calculation, which must happen after trajectory processing since it requires information from all trajectory frames, is parallelized via MPI. This parallelized GIST method has been implemented in the freely-available CPPTRAJ analysis software.

Active labour market policies in emerging adulthood may act as a protective factor against future depressiveness: an analysis of the long-term trajectories of depressive symptoms in the Northern Swedish Cohort

Introduction

Drawing upon the framework of life course epidemiology, this study aligns with research on the mental health consequences of significant social transitions during early adulthood. The focus is on the variation in initial labour market attachment and the development of depressiveness, assuming that a firm attachment is associated with decreasing depressiveness.

Methods

The baseline investigation of the studied cohort (n = 1,001) took place during their final year of compulsory schooling at age 16. Follow-up surveys were conducted at ages 18, 21, 30, and 43. Depressiveness was measured with a five-item score. Multiple trajectory analysis, incorporating five labour market statuses observed over seven half-year periods from ages 18 to 21, was employed to categorize the cohort into six distinct groups. Among these, 'All-time education,' 'From education to employment,' 'Education and employment,' and 'From employment to education' were considered to demonstrate firm labour market attachment. Meanwhile, 'Active labour market policy' and 'Unemployment' represented less firm attachment.

Results

The trajectory of depressive symptoms among the total cohort from age 16 to age 43 exhibited a 'broken stick' pattern, reaching its lowest point at age 21. This pattern was evident in all groups classified as having a firm attachment. A substantial decrease in depressiveness was also observed in the relatively weakly attached 'Active labour market policy' group, whereas no 'broken stick' pattern emerged in the 'Unemployment' group. The disparities in the levels of depressiveness observed at age 21 remained relatively stable across the measurements at ages 30 and 43.

Discussion

The results were as expected, except for the observed improvement in mental health within the 'Active labour market policy' group. Supported labour market attachment during emerging adulthood can enhance mental well-being similarly to regular mainstream attachment. In terms of policy recommendations, the consistently high levels of depressiveness within the 'Unemployment' group underscore the importance of reducing long-term and repeated unemployment in young age. The findings regarding the 'Active labour market policy' provide evidence of the intervention's benefits. While the primary goal of these measures is to create jobs for the unemployed, they also include elements that contribute to participants' mental health.

Relationship of Hoarding and Depression Symptoms in Older Adults

Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.

Predicting Health-Related Quality of Life Outcomes Following Major Scoliosis Surgery in Adolescents: A Latent Class Growth Analysis

STUDY DESIGN

Prospective cohort study.

OBJECTIVES

To identify patient trajectories of recovery defined by change in health-related quality of life (HRQOL) following surgery for adolescent idiopathic scoliosis (AIS). To explore possible predictors of trajectory membership.

METHODS

Adolescent patients scheduled to undergo spinal fusion for AIS were enrolled in the Post-Operative Recovery following Spinal Correction: Home Experience (PORSCHE) study. Responses to the Pediatric Quality of Life Inventory-version 4 (PedsQL-4.0) were collected prior to surgery and 4 to 6 weeks, 3, 6, and 12 months post-operatively. Latent class growth analyses identified patient subgroups based on their unique trajectories of physical health (PH) and psychosocial health (PSH) outcomes using the PedsQL-4.0 subscale scores. Predictors included demographic, clinical, and psychosocial factors.

RESULTS

Data from up to 190 patients were included (87.4% female; mean±SD age = 14.6 ± 1.9 years). Three trajectory subgroups were identified for PH and 4 trajectories were found for PSH, with a majority of patients scoring within the established range of healthy adolescents 12 months post-surgery. Increased child and parent pain catastrophizing, child trait anxiety and previous hospitalizations were associated with poorer PH outcomes, whereas increased child and parent pain catastrophizing, child state and trait anxiety, and parent state and trait anxiety were associated with poorer PSH trajectories.

CONCLUSIONS

The PH and PSH trajectories identified in this study and the factors associated with their membership may inform surgical decision-making for AIS while facilitating patient and family counselling regarding peri-operative recovery and expectations.

SPANA: Spatial decomposition analysis for cellular-scale molecular dynamics simulations

The rapid increase in computational power with the latest supercomputers has enabled atomistic molecular dynamics (MDs) simulations of biomolecules in biological membrane, cytoplasm, and other cellular environments. These environments often contain a million or more atoms to be simulated simultaneously. Therefore, their trajectory analyses involve heavy computations that can become a bottleneck in the computational studies. Spatial decomposition analysis (SPANA) is a set of analysis tools in the Generalized-Ensemble Simulation System (GENESIS) software package that can carry out MD trajectory analyses of large-scale biological simulations using multiple CPU cores in parallel. SPANA applies the spatial decomposition of a large biological system to distribute structural and dynamical analyses into individual CPU cores, which reduces the computational time and the memory size, significantly. SPANA opens new possibilities for detailed atomistic analyses of biomacromolecules as well as solvent water molecules, ions, and metabolites in MD simulation trajectories of very large biological systems containing more than millions of atoms in cellular environments.

Opioid therapy trajectories of patients with chronic non-cancer pain over 1 year of follow-up after initiation of short-acting opioid formulations

OBJECTIVE

This study compared opioid utilization trajectories of persons initiating tramadol, short-acting hydrocodone, or short-acting oxycodone, and it characterized opioid dose trajectories and type of opioid in persistent opioid therapy subsamples.

METHODS

A retrospective cohort study of adults with chronic non-cancer pain who were initiating opioid therapy was conducted with the IQVIA PharMetrics® Plus for Academics data (2008-2018). Continuous enrollment was required for 6 months before ("baseline") and 12 months after ("follow-up") the first opioid prescription ("index date"). Opioid therapy measures were assessed every 7 days over follow-up. Group-based trajectory modeling (GBTM) was used to identify trajectories for any opioid and total morphine milligram equivalent measures, and longitudinal latent class analysis was used for opioid therapy type.

RESULTS

A total of 40 276 tramadol, 141 023 hydrocodone, and 45 221 oxycodone initiators were included. GBTM on any opioid therapy identified 3 latent trajectories: early discontinuers (tramadol 39.0%, hydrocodone 54.1%, oxycodone 61.4%), late discontinuers (tramadol 37.9%, hydrocodone 39.4%, oxycodone 33.3%), and persistent therapy (tramadol 6.7%, hydrocodone 6.5%, oxycodone 5.3%). An additional fourth trajectory, intermittent therapy (tramadol 16.4%), was identified for tramadol initiators. Of those on persistent therapy, 2687 individuals were on persistent therapy with tramadol, 9169 with hydrocodone, and 2377 with oxycodone. GBTM on opioid dose resulted in 6 similar trajectory groups in each persistent therapy group. Longitudinal latent class analysis on opioid therapy type identified 6 latent classes for tramadol and oxycodone and 7 classes for hydrocodone.

CONCLUSION

Opioid therapy patterns meaningfully differed by the initial opioid prescribed, notably the presence of intermittent therapy among tramadol initiators and higher morphine milligram equivalents and prescribing of long-acting opioids among oxycodone initiators.

The systemic error in the vertical component of handgun bullet trajectory reconstructions

Establishing the path or trajectory of a fired bullet is an often recurring part of shooting incident reconstruction. The current study describes how gravitational pull causes a systemic error on the vertical component of a trajectory reconstruction. Bullet drop, drop angle, and vertical offset are explained and calculated for 10 different handgun/ammunition combinations over a range of distances up to 100 m. The presented results are intended to provide forensic firearm examiners with a reference frame for the magnitude of error introduced on handgun bullet trajectory reconstructions over distance. Threshold values of 20 and 30 m are proposed as conservative distances up to where bullet trajectories can be modeled as straight lines with subsonic/transonic handgun bullets and with supersonic handgun bullets respectively. Both the bullet drop and vertical offset will be below 5 cm at these distances for those categories. The drop angle will be below 0.3°.

Assessing the performance of group-based trajectory modeling method to discover different patterns of medication adherence

It is well known that medication adherence is critical to patient outcomes and can decrease patient mortality. The Pharmacy Quality Alliance (PQA) has recognized and identified medication adherence as an important indicator of medication-use quality. Hence, there is a need to use the right methods to assess medication adherence. The PQA has endorsed the proportion of days covered (PDC) as the primary method of measuring adherence. Although easy to calculate, the PDC has however several drawbacks as a method of measuring adherence. PDC is a deterministic approach that cannot capture the complexity of a dynamic phenomenon. Group-based trajectory modeling (GBTM) is increasingly proposed as an alternative to capture heterogeneity in medication adherence. The main goal of this paper is to demonstrate, through a simulation study, the ability of GBTM to capture treatment adherence when compared to its deterministic PDC analogue and to the nonparametric longitudinal K-means. A time-varying treatment was generated as a quadratic function of time, baseline, and time-varying covariates. Three trajectory models are considered combining a cat's cradle effect, and a rainbow effect. The performance of GBTM was compared to the PDC and longitudinal K-means using the absolute bias, the variance, the c-statistics, the relative bias, and the relative variance. For all explored scenarios, we find that GBTM performed better in capturing different patterns of medication adherence with lower relative bias and variance even under model misspecification than PDC and longitudinal K-means.

Employment profiles of autistic people: An 8-year longitudinal study

LAY ABSTRACT

Autistic adults experience difficulties finding and keeping employment. However, research investigating reasons that might explain this difficulty produce mixed results. We gave a survey to 2449 autistic adults and used a statistic method to group them based on their employment status over 8 years. We identified four employment groups that best captured the experiences of autistic adults; this included a group that experienced stable unemployment, a group that experienced stable employment, a group that had high employment that reduced over time, and a group whose employment increased over the 8 years. Further analysis showed that those with fewer autistic traits, younger age, male gender, higher education, later diagnosis age and no co-occurring conditions were more likely to have stable employment. People whose employment changed over time were more likely to have a higher level of education than the stable unemployment group, and those in the increasing employment group were younger age and had no co-occurring conditions. These findings help us better understand that not all autistic adults' experiences of employment are the same, which helps focus where employment programmes and support may be most needed, for example, people who identify as women or have a co-occurring condition.

Impact of the baseline insulin resistance surrogates and their longitudinal trajectories on cardiovascular disease (coronary heart disease and stroke): a prospective cohort study in rural China

Background

This study aimed to assess the association of baseline insulin resistance (IR) surrogates and their longitudinal trajectories with cardiovascular diseases (CVD) to provide a useful reference for preventing CVD.

Methods

This study was a prospective cohort study conducted in the 51st Regiment of the Third Division of Xinjiang Corps. A total of 6362 participants were recruited in 2016 to conduct the baseline survey, and the follow-up surveys in 2019, 2020, 2021, and 2022. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD according to the baseline IR surrogates of metabolic insulin resistance score (METS-IR) and triglyceride-glucose (TyG) index. Cox regression models were used to assess the association between the baseline IR surrogates and CVD. The impact of the longitudinal trajectories of the IR surrogates on CVD was analyzed after excluding those with IR surrogate data measured ≤2 times. Based on the group-based trajectory model (GBTM), the trajectory patterns of IR surrogates were determined. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD in each trajectory group of METS-IR and TyG index. Cox regression models were used to analyze the association between different trajectory groups of each index and CVD. In addition, the Framingham model was utilized to evaluate whether the addition of the baseline IR surrogates increased the predictive potential of the model.

Results

Baseline data analysis included 4712 participants. During a median follow-up of 5.66 years, 572 CVD events were recorded (mean age, 39.42 ± 13.67 years; males, 42.9%). The cumulative CVD incidence increased with the ascending baseline METS-IR and TyG index quartiles (Q1-Q4). The hazard ratio and 95% confidence interval for CVD risk in Q4 of the METS-IR and TyG index were 1.79 (1.25, 2.58) and 1.66 (1.28, 2.17), respectively, when compared with Q1. 4343 participants were included in the trajectory analysis, based on the longitudinal change patterns of the METS-IR and TyG index, the following three trajectory groups were identified: low-increasing, moderate-stable, and elevated-increasing groups. Multivariate Cox regression revealed that the hazard ratio (95% confidence interval) for CVD risk in the elevated-increasing trajectory group of the METS-IR and TyG index was 2.13 (1.48, 3.06) and 2.63 (1.68, 4.13), respectively, when compared with the low-rising group. The C-index, integrated discrimination improvement value, and net reclassification improvement value were enhanced after adding the baseline METS-IR and TyG index values to the Framingham model (P<0.05).

Conclusions

Elevated baseline IR surrogates and their higher long-term trajectories were strongly associated with a high risk of CVD incidence in Xinjiang's rural areas. Regular METS-IR and TyG index monitoring can aid in the early detection of CVD-risk groups.

Early intervention and adding effective doses of EGb761 like Ginkgo extract slow down dementia progression: insights to the neurovascular unit

Background

Dementia is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and functional deterioration. Pharmacological interventions play a crucial role in managing dementia symptoms and potentially slowing down disease progression.

Objectives

This study aimed to investigate the impact of pharmacological interventions, including acetylcholinesterase inhibitors (AChEIs), memantine, and Gingko extract, on the progression of dementia, with a specific focus on mild cognitive impairment (MCI), Alzheimer's disease (AD), and non-Alzheimer dementias.

Methods

A total of 547 participants out of 3,547 cases in a specific dataset followed by the same author, including healthy controls, individuals with MCI, AD, and non-Alzheimer dementias, were included in this study. The follow-up duration was up to 211 months, allowing for a minimum 3 visits comprehensive assessment of disease progression. The treatment approaches included AChEIs, memantine, and combination therapy, with variations in the starting time for these treatments based on the dementia type.

Results

The use of AChEIs and memantine showed efficacy in improving cognitive function and overall function in individuals with MCI, AD, and non-AD dementias. Combination therapy EGb761 like Gingko extract with AChEIs and/or Memantine demonstrated a slower progression compared to AChEIs alone in individuals with prodromal dementia (MCI) and AD. The starting time for memantine and combination therapy was earlier in non-AD dementia cases compared to AD dementia cases and prodromal dementia.

Conclusion

Pharmacological interventions, particularly the use of AChEIs and memantine, can have a positive impact on cognitive function and overall function in individuals with dementia. The combination of AChEIs with EGb761 like Gingko extract may provide additional benefits in slowing down disease progression in AD cases. Early recognition and accurate classification of MCI subtypes are crucial, and the use of EGb761 like Gingko extract is recommended for symptomatic treatment. Future personalized risk predictions based on biomarker constellations may further enhance the multi-target treatment approaches of MCI and different dementia types.

Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data

Background

Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of cells per sample. The goal of a typical scRNA-seq analysis is to identify different cell subpopulations and their respective marker genes. Additionally, trajectory analysis can be used to infer the developmental or differentiation trajectories of cells.

Methods

This article demonstrates a comprehensive workflow for performing trajectory inference and time course analysis on a multi-sample single-cell RNA-seq experiment of the mouse mammary gland. The workflow uses open-source R software packages and covers all steps of the analysis pipeline, including quality control, doublet prediction, normalization, integration, dimension reduction, cell clustering, trajectory inference, and pseudo-bulk time course analysis. Sample integration and cell clustering follows the Seurat pipeline while the trajectory inference is conducted using the monocle3 package. The pseudo-bulk time course analysis uses the quasi-likelihood framework of edgeR.

Results

Cells are ordered and positioned along a pseudotime trajectory that represented a biological process of cell differentiation and development. The study successfully identified genes that were significantly associated with pseudotime in the mouse mammary gland.

Conclusions

The demonstrated workflow provides a valuable resource for researchers conducting scRNA-seq analysis using open-source software packages. The study successfully demonstrated the usefulness of trajectory analysis for understanding the developmental or differentiation trajectories of cells. This analysis can be applied to various biological processes such as cell development or disease progression, and can help identify potential biomarkers or therapeutic targets.

Trajectories of change among highly challenging patients in intensive long-term psychoanalytic psychotherapy

OBJECTIVES

This study aimed to identify and describe trajectories of change in distress among highly challenging patients who had received long and intensive psychoanalytic psychotherapy.

METHODS

The longitudinal version of the K-means algorithm was applied to the outcome measures data of 74 patients treated in four public mental health centers. The patients were measured five times at 6-month intervals for three outcome measures.

RESULTS

For the OQ45 and Symptom Checklist-90, one trajectory was marked by a lower initial distress level. In this trajectory, the improvement occurred in the first half of the measurements, with a plateau thereafter. A second trajectory was characterized by higher initial severity and an improvement, mainly in the second part of the measurements. For the Beck Depression Inventory, one trajectory was marked by lower initial distress. In this group, the improvement occurred throughout the entire period. The remaining patients were characterized by higher initial distress and a decreased level of distress in the last part of treatment. They began to improve only during the third year of therapy.

CONCLUSION

The response to treatment is not uniform in long-term treatment for highly challenging patients. A significant number of patients require a longer period of therapy to ignite improvement.

Single-cell dissection of cellular and molecular features underlying mesenchymal stem cell therapy in ischemic acute kidney injury

Mesenchymal stem cells (MSCs) exert beneficial therapeutic effects in acute kidney injury (AKI), while the detailed repair mechanism remains unclear. Herein, we probed the underlying mechanisms of MSC therapy in AKI by performing unbiased single-cell RNA sequencing in IRI model with/without MSC treatment. Our analyses uncovered the tubular epithelial cells (TECs) and immune cells transcriptomic diversity and highlighted a repair trajectory involving renal stem/progenitor cell differentiation. Our findings also suggested that profibrotic TECs expressing pro-fibrotic factors such as Zeb2 and Pdgfb promoted the recruitment of inflammatory monocytes and Th17 cells to injured kidney tissue, inducing TGF-β1 secretion and renal fibrosis. Finally, in addition to activating the repair properties of renal progenitor/stem cells, we uncovered a role for MSC-derived miR-26a-5p in mediating the therapeutic effects of MSCs by inhibiting Zeb2 expression and suppressing pro-fibrotic TECs and its subsequent recruitment of immune cell subpopulations. These findings may help to optimize future AKI treatment strategies.

Screening single-cell trajectories via continuity assessments for cell transition potential

Advances in single-cell sequencing and data analysis have made it possible to infer biological trajectories spanning heterogeneous cell populations based on transcriptome variation. These trajectories yield a wealth of novel insights into dynamic processes such as development and differentiation. However, trajectory analysis relies on an assumption of trajectory continuity, and experimental limitations preclude some real-world scenarios from meeting this condition. The current lack of assessment metrics makes it difficult to ascertain if/when a given trajectory deviates from continuity, and what impact such a divergence would have on inference accuracy is unclear. By analyzing simulated breaks introduced into in silico and real single-cell data, we found that discontinuity caused precipitous drops in the accuracy of trajectory inference. We then generate a simple scoring algorithm for assessing trajectory continuity, and found that continuity assessments in real-world cases of intestinal stem cell development and CD8 + T cells differentiation efficiently identifies trajectories consistent with empirical knowledge. This assessment approach can also be used in cases where a priori knowledge is lacking to screen a pool of inferred lineages for their adherence to presumed continuity, and serve as a means for weighing higher likelihood trajectories for validation via empirical studies, as exemplified by our case studies in psoriatic arthritis and acute kidney injury. This tool is freely available through github at qingshanni/scEGRET.

Captive Animal Behavior Study by Video Analysis

Three video analysis-based applications for the study of captive animal behavior are presented. The aim of the first one is to provide certain parameters to assess drug efficiency by analyzing the movement of a rat. The scene is a three-chamber plastic box. First, the rat can move only in the middle room. The rat's head pose is the first parameter needed. Secondly, the rodent could walk in all three compartments. The entry number in each area and visit duration are the other indicators used in the final evaluation. The second application is related to a neuroscience experiment. Besides the electroencephalographic (EEG) signals yielded by a radio frequency link from a headset mounted on a monkey, the head placement is a useful source of information for reliable analysis, as well as its orientation. Finally, a fusion method to construct the displacement of a panda bear in a cage and the corresponding motion analysis to recognize its stress states are shown. The arena is a zoological garden that imitates the native environment of a panda bear. This surrounding is monitored by means of four video cameras. We have applied the following stages: (a) panda detection for every video camera; (b) panda path construction from all routes; and (c) panda way filtering and analysis.

Unravelling human hematopoietic progenitor cell diversity through association with intrinsic regulatory factors

Hematopoietic stem and progenitor cell (HSPC) transplantation is an essential therapy for hematological conditions, but finer definitions of human HSPC subsets with associated function could enable better tuning of grafts and more routine, lower-risk application. To deeply phenotype HSPCs, following a screen of 328 antigens, we quantified 41 surface proteins and functional regulators on millions of CD34+ and CD34- cells, spanning four primary human hematopoietic tissues: bone marrow, mobilized peripheral blood, cord blood, and fetal liver. We propose more granular definitions of HSPC subsets and provide new, detailed differentiation trajectories of erythroid and myeloid lineages. These aspects of our revised human hematopoietic model were validated with corresponding epigenetic analysis and in vitro clonal differentiation assays. Overall, we demonstrate the utility of using molecular regulators as surrogates for cellular identity and functional potential, providing a framework for description, prospective isolation, and cross-tissue comparison of HSPCs in humans.

Prenatal Weight Change Trajectories and Perinatal Outcomes among Twin Gestations

OBJECTIVE

 Despite an increase in twin pregnancies in recent decades, the Institute of Medicine twin weight gain recommendations remain provisional and provide no guidance for the pattern or timing of weight change. We sought to characterize gestational weight change trajectory patterns and examine associations with birth outcomes in a cohort of twin pregnancies.

STUDY DESIGN

 Prenatal and delivery records were examined for 320 twin pregnancies from a maternal-fetal medicine practice in Austin, TX 2011-2019. Prenatal weights for those with >1 measured weight in the first trimester and ≥3 prenatal weights were included in analyses. Trajectories were estimated to 32 weeks (mean delivery: 33.7 ± 3.3 weeks) using flexible latent class mixed models with low-rank thin-plate splines. Associations between trajectory classes and infant outcomes were analyzed using multivariable Poisson or linear regression.

RESULTS

 Weight change from prepregnancy to delivery was 15.4 ± 6.3 kg for people with an underweight body mass index, 15.4 ± 5.8 kg for healthy weight, 14.7 ± 6.9 kg for overweight, and 12.5 ± 6.4 kg for obesity. Three trajectory classes were identified: low (Class 1), moderate (Class 2), or high gain (Class 3). Class 1 (24.7%) maintained weight for 15 weeks and then gained an estimated 6.6 kg at 32 weeks. Class 2 (60.9%) exhibited steady gain with 13.5 kg predicted total gain, and Class 3 (14.4%) showed rapid gain across pregnancy with 21.3 kg predicted gain. Compared to Class 1, Class 3 was associated with higher birth weight z-score (β = 0.63, 95% confidence interval [CI]: 0.31,0.96), increased risk for large for gestational age (IRR = 5.60, 95% CI: 1.59, 19.67), and birth <32 weeks (IRR = 2.44, 95%CI: 1.10, 5.4) that was attenuated in sensitivity analyses. Class 2 was associated with moderately elevated birth weight z-score (β = 0.24, 95%CI: 0.00, 0.48, p = 0.050).

CONCLUSION

 Gestational weight change followed a low, moderate, or high trajectory; both moderate and high gain patterns were associated with increased infant size outcomes. Optimal patterns of weight change that balance risk during the prenatal, perinatal, and neonatal periods require further investigation, particularly in high-risk twin pregnancies.

KEY POINTS

· A majority gained weight below IOM twin recommendations.. · Three patterns of GWC across pregnancy were identified.. · Moderate or high GWC was associated with infant size..

Recent Advances in Single-Molecule Tracking and Imaging Techniques

Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

Predictors of herpes zoster severity and immune responses according to pain trajectories: A community-based prospective cohort study

The authors aimed to identify determinants of the clinical course of herpes zoster and immunological responses, focusing on pain trajectories. This prospective community-based cohort study involved the analysis of responses to a valid pain survey provided by 375 patients diagnosed with herpes zoster based on clinical symptoms and virus identification by polymerase chain reaction. The authors analyzed most patients for humoral/cell-mediated immune response against varicella-zoster virus at the onset and 3 months post-onset. Six months post-initial visit, patients self-reported pain on a scale of 0 (no pain) to 5 (extremely strong pain) at up to 18 time points. Moreover, the pain trajectories were traced using group-based trajectory modeling. Subsequently, the authors used analysis of covariance to explore predictors and the humoral/cell-mediated immune response according to the pain trajectories. In addition, humoral/cell-mediated immune responses were assessed among each trajectory using paired t tests. Amon the five identified trajectories, two were isolated that particularly developed postherpetic neuralgia, with or without severe acute pain. Cancer therapy and corticosteroid use before herpes zoster onset specifically predicted postherpetic neuralgia without severe acute pain. In contrast, prescription of nonsteroidal anti-inflammatory drugs was uniquely associated with postherpetic neuralgia accompanied by severe acute pain. The aforementioned trajectories with postherpetic neuralgia showed increased antibodies and decreased cell-mediated immunity compared with those without postherpetic neuralgia. The authors could successfully distinguish between postherpetic neuralgia trajectories with and without severe acute pain. The identified key predictors and immunological responses against varicella-herpes zoster contribute further evidence to our understanding of the clinical features of herpes zoster and postherpetic neuralgia.

Comparing temporal dynamics of compositional reorganization in long-term studies of birds and fish

The composition of ecological assemblages has changed rapidly over the past century. Compositional reorganization rates are high relative to rates of alpha diversity change, creating an urgent need to understand how this compositional reorganization is progressing. We developed a quantitative framework for comparing temporal trajectories of compositional reorganization and applied it to two long-term bird and marine fish datasets. We then evaluated how the number and magnitude of short-term changes relate to overall rates of change. We found varied trajectories of turnover across birds and fish, with linear directional change predominating in birds and non-directional change more common in fish. The number of changes away from the baseline was a more consistent correlate of the overall rate of change than the magnitude of such changes, but large unreversed changes were found in both fish and birds, as were time series with accelerating compositional change. Compositional reorganization is progressing through a complex mix of temporal trajectories, including both threshold-like behaviour and the accumulation of repeated, linear change.

Retinopathy prevalence, incidence and trajectories in type 2 diabetes: The Fremantle diabetes study phase II

AIMS

To determine diabetic retinopathy (DR) prevalence, incidence, and whether distinct trajectories are associated with DR-complicating Type 2 diabetes.

METHODS

Retinal photographs from Fremantle Diabetes Study Phase II (FDS2) participants with Type 2 diabetes recruited in 2008-2011 and who attended biennial assessments for up to 6 years were graded as no DR, mild non-proliferative DR (NPDR), moderate NPDR or severe NPDR/proliferative DR. Baseline DR prevalence, and the cumulative incidence of moderate NPDR or worse in those without DR at baseline, were calculated. Group-based DR trajectory modelling was performed. Logistic regression determined independent associates of incident moderate NPDR or worse and trajectory group membership.

RESULTS

Of 1521 participants (mean age 65.6 years, 52.1% males, median diabetes duration 9.0 years; 98% of all FDS2 participants with Type 2 diabetes) with gradable baseline photographs, 563 (37.0%) had DR. During a median 6.1 years of follow-up, 23 (3.2%) without baseline DR developed at least moderate NPDR (crude incidence 6.1/1000 person-years) with HbA1c the sole independent predictor (odds ratio [95% CI]: 1.62 [1.30-2.02] per 1% [11 mmol/mol] increase). Trajectory analysis showed two distinct groups, those with baseline/persistent DR (20%) and those remaining DR free (80%). Longer diabetes duration, insulin use, higher mean HbA1c , higher mean systolic blood pressure and higher mean urinary albumin: creatinine ratio all increased the odds (p ≤ 0.014) of being in the persistent DR trajectory group.

CONCLUSIONS

The low incidence of at least moderate NPDR reflects the trajectory analysis. The currently recommended biennial retinal screening frequency for individuals without DR could potentially be extended.

Finding a Husband: Using Explainable AI to Define Male Mosquito Flight Differences

Mosquito-borne diseases account for around one million deaths annually. There is a constant need for novel intervention mechanisms to mitigate transmission, especially as current insecticidal methods become less effective with the rise of insecticide resistance among mosquito populations. Previously, we used a near infra-red tracking system to describe the behaviour of mosquitoes at a human-occupied bed net, work that eventually led to an entirely novel bed net design. Advancing that approach, here we report on the use of trajectory analysis of a mosquito flight, using machine learning methods. This largely unexplored application has significant potential for providing useful insights into the behaviour of mosquitoes and other insects. In this work, a novel methodology applies anomaly detection to distinguish male mosquito tracks from females and couples. The proposed pipeline uses new feature engineering techniques and splits each track into segments such that detailed flight behaviour differences influence the classifier rather than the experimental constraints such as the field of view of the tracking system. Each segment is individually classified and the outcomes are combined to classify whole tracks. By interpreting the model using SHAP values, the features of flight that contribute to the differences between sexes are found and are explained by expert opinion. This methodology was tested using 3D tracks generated from mosquito mating swarms in the field and obtained a balanced accuracy of 64.5% and an ROC AUC score of 68.4%. Such a system can be used in a wide variety of trajectory domains to detect and analyse the behaviours of different classes, e.g., sex, strain, and species. The results of this study can support genetic mosquito control interventions for which mating represents a key event for their success.

Context-dependent gene regulatory network reveals regulation dynamics and cell trajectories using unspliced transcripts

Gene regulatory networks govern complex gene expression programs in various biological phenomena, including embryonic development, cell fate decisions and oncogenesis. Single-cell techniques are increasingly being used to study gene expression, providing higher resolution than traditional approaches. However, inferring a comprehensive gene regulatory network across different cell types remains a challenge. Here, we propose to construct context-dependent gene regulatory networks (CDGRNs) from single-cell RNA sequencing data utilizing both spliced and unspliced transcript expression levels. A gene regulatory network is decomposed into subnetworks corresponding to different transcriptomic contexts. Each subnetwork comprises the consensus active regulation pairs of transcription factors and their target genes shared by a group of cells, inferred by a Gaussian mixture model. We find that the union of gene regulation pairs in all contexts is sufficient to reconstruct differentiation trajectories. Functions specific to the cell cycle, cell differentiation or tissue-specific functions are enriched throughout the developmental process in each context. Surprisingly, we also observe that the network entropy of CDGRNs decreases along differentiation trajectories, indicating directionality in differentiation. Overall, CDGRN allows us to establish the connection between gene regulation at the molecular level and cell differentiation at the macroscopic level.

Tree functional composition, functional diversity, and aboveground biomass show dissimilar trajectories in a tropical secondary forest restored through assisted natural regeneration

The growing trend of agricultural abandonment requires an understanding of the development of secondary forests on old fields in the context of restoration. However, few studies examine the regeneration trajectories of functional composition and functional diversity in afrotropical secondary forests. We tested how functional composition, diversity, and aboveground biomass (AGB) change with age and determined restoration success for a secondary forest restored through assisted natural regeneration in Uganda. We assessed the influence of distance to forests on regeneration. We sampled trees in 63 plots (2000 m² each) in the secondary forest (16-22-year old) and five plots in an old-growth forest in 2011, 2014 and 2017. We computed functional composition (community-weighted means-CWM) and diversity using categorical (habitat type, dispersal mode, fruit size, and successional group) and continuous traits (wood density and maximum height) of the species and calculated AGB. The secondary forest showed dissimilar trajectories of functional composition, diversity, and AGB. After 16-22 years, the secondary forest had not yet reached equivalent values of most attributes of functional composition, diversity and AGB in the old-growth forest. The distance to forests had a negative effect on CWM of forest-dependent species, nonpioneer light demanders, and functional divergence and a positive effect on CWM of pioneer species. We show that assisted natural regeneration can enhance the functional composition, functional diversity, and AGB of degraded forests and that continued monitoring is needed to attain full recovery. In planning passive restoration, sites closer to existing forests should be prioritized in order to achieve faster recovery.

Source Area of the Immigrant Population of Beet Webworm (Lepidoptera: Crambidae) in Northern Xinjiang, China

The beet webworm, Loxostege sticticalis (Linnaeus) (Lepidoptera: Crambidae), is a destructive pest inhabiting the northern temperate zone. In Xinjiang, China, this species has only occasionally infested certain areas, but has been causing severe damage since 2005. Early studies showed that most of the outbreak populations in northern Xinjiang are immigrant populations. However, the specific source area is still unknown. In this study, we determined the source area of the immigrant population of L. sticticalis in northern Xinjiang from 2010 to 2013 using daily monitoring data of L. sticticalis adults; we explained the causation of why an overwintering area of L. sticticalis could build up in Central Asia. Results showed that the direct source area of L. sticticalis in northern Xinjiang was eastern Kazakhstan, and the initial source area could be traced further to Altai Krai, Russia. Both regions were located at the foothills of the westernmost portion of Altai Mountains. The thermal conditions in these regions could not support L. sticticalis development for two generations before 1990. Hence, a few cocoons could be formed in the autumn. Influenced by global warming, L. sticticalis in these regions could complete two whole generations most years after 2001. The increased generation number, combined with sufficient precipitation, and mountainous terrain in the westernmost portion of Altai Mountains have created an overwintering area for L. sticticalis.

Migration Dynamics of Fall Armyworm Spodoptera frugiperda (Smith) in the Yangtze River Delta

The Yangtze River Delta, located in East China, is an important passage on the eastern pathway of the northward migration of fall armyworm Spodoptera frugiperda (Smith) in China, connecting China's year-round breeding area and the Huang-Huai-Hai summer maize area. Clarifying the migration dynamics of S. frugiperda in the Yangtze River Delta is of great significance for the scientific control and prevention of S. frugiperda in the Yangtze River Delta, even in the Huang-Huai-Hai region and Northeast China. This study is based on the pest investigation data of S. frugiperda in the Yangtze River Delta from 2019 to 2021, combining it with the migration trajectory simulation approach and the synoptic weather analysis. The result showed that S. frugiperda migrated to the Yangtze River Delta in March or April at the earliest, and mainly migrated to the south of the Yangtze River in May, which can be migrated from Guangdong, Guangxi, Fujian, Jiangxi, Hunan and other places. In May and June, S. frugiperda migrated further into the Jiang-Huai region, and its source areas were mainly distributed in Jiangxi, Hunan, Zhejiang, Jiangsu, Anhui and Hubei provinces. In July, it mainly migrated to the north of Huai River, and the source areas of the insects were mainly distributed in Jiangsu, Anhui, Hunan, Hubei and Henan. From the south of the Yangtze River to the north of the Huai River, the source areas of S. frugiperda were constantly moving north. After breeding locally, S. frugiperda can not only migrate to other regions of the Yangtze River Delta, but also to its surrounding provinces of Jiangxi, Hunan, Hubei, Henan, Shandong and Hebei, and even cross the Shandong Peninsula into Northeast China such as Liaoning and Jilin provinces. Trajectory simulation showed that the emigrants of S. frugiperda from the Yangtze River Delta moved northward, westward and eastward as wind direction was quite diverse in June-August. This paper analyzes the migration dynamics of S. frugiperda in the Yangtze River Delta, which has important guiding significance for the monitoring, early warning and the development of scientific prevention and control strategies for whole country.

Trajectories of 24-Hour Physical Activity Distribution and Relationship with Dyslipidemia

The association between physical activity (PA) and dyslipidemia is well known, but the relationship between a temporal pattern of PA and dyslipidemia remain unknown. Here, we aimed to identify the intensity and temporal patterns of PA clustered by the trajectory model and their relationship with dyslipidemia. The participants were 701 adults (305 males) aged 18−60 years undergoing continuous measurement of PA with Actigraph GT3X+ accelerometers for at least 3 days. A trajectory analysis was applied based on moderate-to-vigorous intensity physical activity (MVPA) accumulated values over every period per day. The association between PA and dyslipidemia was estimated using a logistic regression model. Four distinct PA trajectory groups in the population were identified (continued low, stable and moderate, late increasing, and early increasing). Specifically, the “moderate and stable group” was associated with a decreased rate of high TG (p < 0.05) and the “moderate and stable group” and “late increasing group” were associated with decreased rates of low HDL-C (p < 0.05). In conclusion, there were four activity trajectory groups in this population and the continued low PA trajectory was associated with a high prevalent rate of an abnormal lipid profile, and continued and moderate activity or late afternoon increasing activity might have lower HDL-C distribution.

Longitudinal online diaries with dental practitioners and dental care professionals during the COVID-19 pandemic: A trajectory analysis

Introduction

The COVID-19 pandemic resulted in a series of significant changes and adjustments within dentistry, as dental professionals dealt with temporary closures of dental practices, increased use of personal protective equipment, a reduction of clinical procedures, and extensions to training programmes. Recent research has illustrated the impact of the pandemic on the dental profession, indicating that many dental professionals felt emotionally exhausted and experienced significant uncertainty and anxiety. This qualitative study aimed to understand how these experiences and emotions changed over the course of six months, in dental trainees and primary dental care staff in Scotland.

Methods

A longitudinal diary study was conducted (June-December 2020) with dental trainees and primary dental care staff. The diary asked respondents to answer three questions related to their emotional exhaustion, on a weekly basis. There was also an open question asking respondents to describe any significant issues or concerns they had experienced during the preceding week because of the impact of the COVID-19 pandemic on their work or training. This qualitative data was explored using a trajectory analysis approach to determine specifically changes over time.

Results

The trajectory analysis revealed several key concerns prevalent amongst respondents, and how they fluctuated over the six months. Concerns included: the impact of the pandemic on respondents' future careers and on dentistry more generally; adapting to new working environments; the impact on their patients' dental treatment and oral health; the impact on their health and wellbeing; financial considerations and adjusting to new safety measures as part of the remobilization of dental services.

Discussion

In the second half of 2020, as the UK was adjusting to the introduction of new COVID-19 safety measures in everyday life, the dental profession were grappling with significant changes to their working environment, including PPE, redeployment, use of aerosol generating procedures (AGPs), and timelines for re-opening practices. This longitudinal diary study has shown some parts of the dental profession in Scotland expressed very varied and personal concerns and anxieties related to COVID-19. Respondents' candor in their diary entries revealed explicit, frequent and high levels of uncertainty and worry related to their training and career. Collectively, the data corpus highlighted the emotional toll these anxieties have taken on the dental professions in Scotland.

Conclusion

These findings demonstrate the need for (a) increased provision of mental health and wellbeing support services for dental staff and (b) the study of the linkage between organization of pandemic management to the working practices of staff delivering services. Interventions, at various levels, should take into consideration the fluctuating nature of dental professionals' concerns and anxieties over time, to address both immediate and longer-term issues.

Genome-Scale Metabolic Modeling Reveals Sequential Dysregulation of Glutathione Metabolism in Livers from Patients with Alcoholic Hepatitis

Alcoholic hepatitis (AH) is the most severe form of alcoholic liver disease for which there is no efficacious treatment aiding most patients. AH manifests differently in individuals, with some patients showing debilitating symptoms more so than others. Previous studies showed significant metabolic dysregulation associated with AH. Therefore, we sought to analyze how the activity of metabolic pathways differed in the liver of patients with varying degrees of AH severity. We utilized a genome-scale metabolic modeling approach that allowed for integration of a generic human cellular metabolic model with specific RNA-seq data corresponding to healthy and multiple liver disease states to predict the metabolic fluxes within each disease state. Additionally, we performed a systems-level analysis of the transcriptomic data and predicted metabolic flux data to identify the regulatory and functional differences in liver metabolism with increasing severity of AH. Our results provide unique insights into the sequential dysregulation of the solute transport mechanisms underlying the glutathione metabolic pathway with increasing AH disease severity. We propose targeting of the solute transporters in the glutathione pathway to mimic the flux activity of the healthy liver state as a potential therapeutic intervention for AH.

The Source Areas and Migratory Pathways of the Fall Armyworm Spodoptera frugiperda (Smith) in Sichuan Province, China

The Sichuan Province, located in Southwest China, is one of China's main maize-producing areas, and is also an important node along the north-south migratory pathways that pests follow within China. After its invasion, the fall armyworm (FAW), Spodoptera frugiperda (Smith), was found in 70.81% of all counties in Sichuan. However, FAW source areas and their migratory pathways into Sichuan remain unclear. This study simulated FAW sources and their migratory pathways into Sichuan during 2020 and 2021 using the trajectory simulation platform HYSPLIT with flight behavior parameters. Additionally, the seasonal horizontal wind field was also analyzed with the meteorological graphics processing software GrADS. The results showed that sporadic FAW migration into Sichuan began in April. By May, FAWs were found in much of the Sichuan Basin and moved further north and west in June. Except for year-round breeding areas, FAW sources varied monthly and expanded northward and eastward. The source areas were concentrated in Yunnan, Guizhou, Chongqing, and Myanmar on the western pathway of national migration and also in Vietnam, Guangxi, and Hunan of the eastern pathway. At various times, parts of Sichuan have also served as sources for other parts of Sichuan. FAWs migrated to Sichuan from the source areas via 6 potential pathways, 1 pathway into southwest Sichuan and 5 pathways into the Sichuan basin. The southwestern airflow from the Bay of Bengal, the southeastern airflow controlled by the western Pacific subtropical high, and the local topographically influenced airflow could provide the airflow needed for FAW migration. This work provides new information that can assist the monitoring and warning of the presence of FAW and support integrated management strategies for this pest in Sichuan and throughout China.

Immigration Pathways of White-Backed Planthopper in the Confluence Area of the Two Monsoon Systems

The white-backed planthopper, WBPH, Sogatella furcifera (Horváth) is a plant pest that migrates long-distances. The migration pathway of WBPH in eastern China coincides with the north-south round trip of the East Asian monsoon. However, in Yunnan China, which is affected by two monsoon systems, the migration pathway is unclear. Light-trap data and analysis of female ovarian development showed that the peak period of immigration of WBPH into western Yunnan was earlier than in eastern Yunnan. Using meteorological reanalysis data and flight parameters of WBPH, trajectory modeling showed that there are two immigration pathways to Yunnan. One is from Myanmar to western Yunnan, and the other is from Vietnam and Laos to eastern Yunnan. The reason for the differences in source areas and immigration pathways between eastern and western Yunnan is that the west wind prevails in western Yunnan and is controlled by South Asian monsoon, while southwesterly winds prevail in eastern Yunnan due to the combined influence of South Asian monsoon and East Asian monsoon. The results indicate that WBPH invades Yunnan via two pathways under a two-monsoon system. These data will allow earlier prediction and population management of WBPH.

Trajectories of psychological distress among individuals exposed to the 9/11 World Trade Center disaster

BACKGROUND

Individuals present in lower Manhattan during the 9/11 World Trade Center (WTC) disaster suffered from significant physical and psychological trauma. Studies of longitudinal psychological distress among those exposed to trauma have been limited to relatively short durations of follow-up among smaller samples.

METHODS

The current study longitudinally assessed heterogeneity in trajectories of psychological distress among WTC Health Registry enrollees - a prospective cohort health study of responders, students, employees, passersby, and residents in the affected area (N = 30 839) - throughout a 15-year period following the WTC disaster. Rescue/recovery status and exposure to traumatic events of 9/11, as well as sociodemographic factors and health status, were assessed as risk factors for trajectories of psychological distress.

RESULTS

Five psychological distress trajectory groups were found: none-stable, low-stable, moderate-increasing, moderate-decreasing, and high-stable. Of the study sample, 78.2% were classified as belonging to the none-stable or low-stable groups. Female sex, being younger at the time of 9/11, lower education and income were associated with a higher probability of being in a greater distress trajectory group relative to the none-stable group. Greater exposure to traumatic events of 9/11 was associated with a higher probability of a greater distress trajectory, and community members (passerby, residents, and employees) were more likely to be in greater distress trajectory groups - especially in the moderate-increasing [odds ratios (OR) 2.31 (1.97-2.72)] and high-stable groups [OR 2.37 (1.81-3.09)] - compared to the none-stable group.

CONCLUSIONS

The current study illustrated the heterogeneity in psychological distress trajectories following the 9/11 WTC disaster, and identified potential avenues for intervention in future disasters.

Associations Between the Prevalence, Treatment, Control of Hypertension and Cognitive Trajectories Among Chinese Middle-Aged and Older Adults

OBJECTIVE

To investigate the associations between the prevalence, treatment, control of hypertension, and trajectories of cognitive performance among Chinese middle-aged and older adults.

DESIGN

An 8-year longitudinal study.

SETTING

China.

PARTICIPANTS

Chinese middle-aged and older adults.

MEASUREMENTS

Data from the China Health and Retirement Longitudinal Study were utilized. Group-based trajectory modeling was performed to identify heterogeneous trajectories of episodic memory and executive function. Multinomial logistic regression models were established to examine the relationships between hypertension status and cognitive trajectories, stratified by sex.

RESULTS

Three episodic memory trajectories and four executive function trajectories were identified in males and females. Hypertension prevalence was associated with worse episodic memory and executive function trajectories in females. Compared with treated hypertensives, untreated hypertensives were more likely to have worse executive function trajectories, both in males and females. Among male treated hypertensives, those with uncontrolled blood pressure (BP) had worse episodic memory trajectories compared with their counterparts with controlled at standard targets, while females with uncontrolled BP demonstrated worse executive function trajectories compared with females controlled at standard targets. There was basically no significant difference in cognitive trajectory memberships between individuals with controlled hypertension corresponding to intensive or standard BP targets.

CONCLUSIONS

The prevalence of hypertension was associated with worse cognitive trajectories, and the treatment and control of hypertension were related to more favorable cognitive trajectories. Intensive BP control target was not associated with additional benefit beyond the recognized protective effect of standard BP targets on cognitive trajectories.

White blood cell count trajectory and mortality in septic shock: a historical cohort study

PURPOSE

Septic shock is associated with a mortality of 20-40%. The white blood cell count (WBC) at hospital admission correlates with prognosis in septic shock. Here, we explore whether the trajectory of WBC after admission provides further information about outcomes. We aimed to identify groups of patients with different WBC trajectories and the association of WBC trajectory with mortality.

METHODS

We included adult patients with septic shock in two academic intensive care units (ICU) in Winnipeg, MB, Canada between 2006 and 2012. We used group-based trajectory analysis to group patients according to their WBC patterns over the first seven days in the ICU. Our primary analysis was the association of WBC trajectory group on 30-day mortality using multivariable Cox proportional hazards regression.

RESULTS

We included 917 patients with septic shock. The final model identified seven distinct WBC trajectories. The rising WBC trajectory was independently associated with increased mortality (hazard ratio, 3.41; 95% confidence interval, 1.86 to 6.26; P < 0.001) compared with the stable WBC trajectory.

CONCLUSION

In patients with septic shock, distinct and clinically relevant groups can be identified by analyzing WBC trajectories. A rising WBC trajectory was associated with higher mortality.

Associations of spousal and non-spousal caregiving with six-year trajectories of depressive symptoms among older women in the Caregiver-Study of Osteoporotic Fractures study

Objectives:Caregiving and becoming widowed are risk factors for depression in older adults, but few studies have examined their combined effect on depressive symptom trajectories. In a cohort of older women (mean age = 80.7 years) from the Caregiver-Study of Osteoporotic Fractures, we used latent class growth curve modeling to identify trajectories of depressive symptoms over approximately six years.Method:We used multinomial logistic regression to assess the relative odds of four depressive symptom trajectories (consistently low, consistently moderate, moderate/increasing, and consistently high), among three groups: spousal caregivers (n = 149), non-spousal caregivers (n = 157), and non-caregivers (n = 422). We also repeated this analysis with combined caregiving status and widowhood as the exposure.Results:Compared to non-caregivers, spousal caregivers had greater relative odds of consistently high versus consistently low depressive symptoms (adjusted odds ratio [aOR] = 3.6, 95% confidence interval [CI]: 1.9, 6.5). Non-spousal caregivers did not differ from non-caregivers in depressive trajectories. Compared to non-caregivers who did not become widowed, both widowed and non-widowed spousal caregivers had greater relative odds of consistently high versus consistently low depressive symptoms (aOR = 4.9, 95% CI: 1.9, 12.7 and aOR = 3.0, 95% CI: 1.5, 6.0, respectively). Non-widowed spousal caregivers, but not widowed spousal caregivers, had a non-statistically-significant trend toward increased relative odds of moderate/increasing depressive symptoms (aOR = 1.5, 95% CI: 0.7, 3.4).Conclusion:Spousal caregiving and widowhood, but not non-spousal caregiving, are associated with trajectories reflecting greater depressive symptoms over time. Informal caregiving is common among older women, and women caring for spouses should be monitored for depression, both during caregiving and after spousal loss.Supplemental data for this article can be accessed online at https://doi.org/10.1080/13607863.2021.1950611.

Single Cell Dissection of Epithelial-Immune Cellular Interplay in Acute Kidney Injury Microenvironment

Background

Understanding the acute kidney injury (AKI) microenvironment changes and the complex cellular interaction is essential to elucidate the mechanisms and develop new targeted therapies for AKI.

Methods

We employed unbiased single-cell RNA sequencing to systematically resolve the cellular atlas of kidney tissue samples from mice at 1, 2 and 3 days after ischemia-reperfusion AKI and healthy control. The single-cell transcriptome findings were validated using multiplex immunostaining, western blotting, and functional experiments.

Results

We constructed a systematic single-cell transcriptome atlas covering different AKI timepoints with immune cell infiltration increasing with AKI progression. Three new proximal tubule cells (PTCs) subtypes (PTC-S1-new/PTC-S2-new/PTC-S3-new) were identified, with upregulation of injury and repair-regulated signatures such as Sox9, Vcam1, Egr1, and Klf6 while with downregulation of metabolism. PTC-S1-new exhibited pro-inflammatory and pro-fibrotic signature compared to normal PTC, and trajectory analysis revealed that proliferating PTCs were the precursor cell of PTC-S1-new, and part of PTC-S1-new cells may turn into PTC-injured and then become fibrotic. Cellular interaction analysis revealed that PTC-S1-new and PTC-injured interacted closely with infiltrating immune cells through CXCL and TNF signaling pathways. Immunostaining validated that injured PTCs expressed a high level of TNFRSF1A and Kim-1, and functional experiments revealed that the exogenous addition of TNF-α promoted kidney inflammation, dramatic injury, and specific depletion of TNFRSF1A would abrogate the injury.

Conclusions

The single-cell profiling of AKI microenvironment provides new insight for the deep understanding of molecular changes of AKI, and elucidates the mechanisms and developing new targeted therapies for AKI.

Analysis of Urban Built Environment Impacts on Outdoor Physical Activities-A Case Study in China

Outdoor physical activities can promote public health and they are largely influenced by the built environment in different urban settings. Understanding the association between outdoor physical activities and the built environment is important for promoting a high quality of life. Existing studies typically focus on one type of outdoor activity using interview-based small samples and are often lack of systematic understanding of the activities' intensity and frequency. In this study, we intend to gain deeper insight into how the built environment influences physical activities using the data extracted from individual's wearables and other open data sources for integrated analysis. Multi-linear regression with logarithm transformation is applied to perform the analysis using the data from Changsha, China. We found that built environment impacts on outdoor physical activities in Changsha are not always consistent with similar studies' results in other cities. The most effective measures to promote outdoor physical activities are the provision of good arterial and secondary road networks, community parks, among others in Changsha. The results shed light on future urban planning practices in terms of promoting public health.

Single-Cell Transcriptomics Identifies Heterogeneity of Mouse Mammary Gland Fibroblasts With Distinct Functions, Estrogen Responses, Differentiation Processes, and Crosstalks With Epithelium

Fibroblasts have been shown to be one of the essential players for mammary gland organization. Here, we identify two major types of mouse mammary gland fibroblasts through single-cell RNA sequencing analysis: Dpp4 ⁺ fibroblasts and Dpp4 ^- fibroblasts. Each population exhibits unique functional characteristics as well as discrete localization in normal mouse mammary glands. Remarkably, estrogen, a crucial mediator of mammary gland organization, alters the gene expression profiles of fibroblasts in a population-specific manner, without distinct activation of estrogen receptor signaling. Further integrative analysis with the inclusion of five other publicly available datasets reveals a directional differentiation among the mammary gland fibroblast populations. Moreover, the combination with the mouse mammary epithelium atlas allows us to infer multiple potential interactions between epithelial cells and fibroblasts in mammary glands. This study provides a comprehensive view of mouse mammary gland fibroblasts at the single-cell level.

Self-Regulation Development Among Young Spanish-English Dual Language Learners

Despite strong evidence self-regulation skills are critical for school readiness, there remains a dearth of longitudinal studies that describe developmental trajectories of self-regulation, particularly among low-resource and underrepresented populations such as Spanish-English dual-language learners (DLLs). The present study examined individual differences in trajectories of self-regulation among 459 Spanish-English DLLs who were Hispanic from four different samples and three geographic locations in the U.S. Self-regulation was assessed in all samples using repeated administration of the Head-Toes-Knees-Shoulders (HTKS) task from early childhood through early elementary school. Results of latent growth curve analyses revealed that growth was best represented by quadratic trajectories. Latent class growth analyses captured significant individual differences in self-regulation trajectories. One group of children (41%) started with higher HTKS scores and displayed rapid early growth in performance. A similar percentage of children (41%) displayed intermediate growth in self-regulation, starting with lower HTKS scores but displaying rapid growth commencing arrange 4.5 years. Finally, about 18% of the sample did not display growth in HTKS performance until after entry to elementary school, around age 6 years. Girls were half as likely as boys to be in this later developing group. Likewise, children from families at the upper end of the socioeconomic distribution in this low-income sample were significantly less likely to be in the later developing group relative to children from families with lower SES. Study findings indicate the importance of monitoring growth rates in self-regulation as a means of identifying children at risk for entering school without the requisite self-regulation skills.

Parental influences on marijuana use in emerging adulthood

The purpose of this study was to gain a clearer understanding of the relation between parental relationship qualities and overall emerging adulthood (EA) marijuana use processes. The present study drew from an ethnically and socioeconomially diverse sample of EAs (ages 19-22) and their parents (n = 470) from the Pacific Northwest region. This study used parent-report and child-report data to capture measures of parenting and EA marijuana use outcomes. Latent Class Growth Analysis (LCGA) was used to model trajectories of marijuana use and risk factor analyses were used to examine how marijuana group membership varied by covariates and parental relationship qualities. Results revealed that lower levels of family cohesion and quality of parent-child communication were more likely to predict membership in the high-using groups and moderate-decreasing user groups in comparison to low-to-non users. Results also indicated that lower levels of frequency of parent-child communication were more likely to predict membership in the high-users group compared to the low-to-non users. Regarding parent knowledge of marijuana use, trends toward congruence and underestimation of EA marijuana use predicted membership in the high-using and moderate-decreasing groups compared to the low-to-non users. Study results indicate EAs in their early 20s may be more likely to engage in healthy decision-making regarding marijuana use in an environment that includes warm, supportive parent-child relationships where parents are aware of their EAs use without focusing on their EA's perceptions of risk. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Global Disability Trajectories Over the First Decade Following Combat Concussion

OBJECTIVE

To examine global disability trajectories in US military with and without traumatic brain injury (TBI) over the first decade following deployment to identify risk profiles for better intervention stratification, hopefully reducing long-term cost.

SETTING

Patients and participants were enrolled in combat or directly following medical evacuation at the time of injury and followed up every 6 months for 10 years.

PARTICIPANTS

There are 4 main groups (n = 475), 2 primary and 2 exploratory: (1) combat-deployed controls without a history of blast exposure "non-blast- control" (n = 143), (2) concussive blast TBI "'blast-TBI" (n = 236) (primary), (3) combat-deployed controls with a history of blast exposure "blast-control" (n = 54), and (4) patients sustaining a combat concussion not from blast "non-blast-TBI" (n = 42) (exploratory).

DESIGN

Prospective, observational, longitudinal study.

MAIN MEASURES

Combat concussion, blast exposure, and subsequent head injury exposure over the first decade post-deployment. Global disability measured by the Glasgow Outcome Scale Extended (GOSE).

RESULTS

Latent class growth analysis identified 4 main trajectories of global outcome, with service members sustaining combat concussion 37 to 49 times more likely to be in the worse disability trajectories than non-blast-controls (blast-TBI: odds ratio [OR] = 49.33; CI, 19.77-123.11; P < .001; non-blast-TBI: OR = 37.50; CI, 10.01-140.50; P < .001). Even blast-exposed-controls were 5 times more likely to be in these worse disability categories compared with non-blast-controls (OR = 5.00; CI, 1.59-15.99; P = .007). Adjustment for demographic factors and subsequent head injury exposure did not substantially alter these odds ratios.

CONCLUSIONS

Very high odds of poor long-term outcome trajectory were identified for those who sustained a concussion in combat, were younger at the time of injury, had lower education, and enlisted in the Army above the risk of deployment alone. These findings help identify a risk profile that could be used to target early intervention and screen for poor long-term outcome to aid in reducing the high public health cost and enhance the long-term quality of life for these service members following deployment.

Limited Changes in Lifestyle Behaviours after Non-Muscle Invasive Bladder Cancer Diagnosis

The aim of our study was to investigate adherence to lifestyle recommendations and lifestyle changes after diagnosis in patients with non-muscle invasive bladder cancer (NMIBC). Second, we aimed to identify distinct trajectories of lifestyle change and their correlates. We analysed data of 935 patients with NMIBC from a prospective cohort study at six weeks (evaluating pre-diagnostic lifestyle), three months, and fifteen months after diagnosis. An overall lifestyle score (range 0-7) was calculated based on the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations focusing on diet, body mass index, and physical activity. Linear mixed models were used to analyse absolute lifestyle changes over time. Distinct trajectories of change were identified with latent class trajectory models. We found an overall lifestyle score of 3.3 which remained constant over time. The largest lifestyle changes were observed for the consumption of red and processed meat (-96 g/week) and fruit and vegetables (-38 g/day). Two to four trajectory groups were identified for each single lifestyle behaviour. Correlates differed per trajectory group. In conclusion, adherence to the WCRF/AICR recommendations was low. Small to moderate changes in and different trajectories of single lifestyle behaviours were observed. Effective strategies for lifestyle improvement are warranted.

Alcohol and Cannabis Use Trajectories and Outcomes in a Sample of Hispanic, White, and Asian Sexual and Gender Minority Emerging Adults

Substance use disproportionately affects health and psychosocial outcomes for some racial/ethnic groups, but few longitudinal studies examine the extent to which sexual and gender minority (SGM) emerging adults of different racial/ethnic groups may experience disparities in outcomes at similar levels of alcohol or cannabis use. This study used five waves of annual survey data (spanning 2015 (average age 18) to 2020 (average age 23)) from an ongoing longitudinal cohort study of emerging adults. In the subset of 359 SGM emerging adults, separate sequelae of change models assessed differences in trajectories of alcohol or cannabis use (past 30-day frequency) and multiple health and psychosocial outcomes across Hispanic, Asian, and White individuals. White SGM emerging adults showed higher baseline levels of alcohol and cannabis frequency compared to Hispanic and Asian peers, but all groups showed similar rates of change (slope) over time. We observed few racial/ethnic differences in SGM emerging adult outcomes at the same levels of alcohol or cannabis use; that is, racial/ethnic groups showed similar patterns on most health and psychosocial outcomes; however, some differences emerged. For example, Asian respondents reported less engagement in sex with casual partners after using alcohol, marijuana, or other drugs compared to their White peers, at the same levels of alcohol use (β = −0.579, p = 0.03) or cannabis use (β = −0.737, p = 0.007). Findings underscore a need to consider multiple outcome domains and factors beyond additive stress in examining the effects of substance use across different groups of SGM individuals. More longitudinal studies with large, contemporary, and diverse samples of SGM emerging adults are needed to better characterize similarities and differences in patterns of substance use and use-related consequences in relation to intersecting SGM, racial/ethnic, and other identities.

Time course of symptoms in posttraumatic stress disorder with delayed expression: A systematic review

OBJECTIVE

To examine the hypothesis that PTSD with delayed expression in some cases occurs without subthreshold PTSD symptoms above background levels bridging the gap between the traumatic exposure(s) and the clinical diagnosis.

METHODS

We performed systematic searches of peer-reviewed papers in English referenced in Pubmed, Embase, or PsycINFO and ascertained 34 prospective studies of PTSD symptom trajectories identified by latent class growth statistical modeling. Studies with delayed and low-stable trajectories provided appropriate data for this study. We computed the difference between the delayed trajectory PTSD symptom sumscore and the low-stable PTSD sumscore at the observed points in time after the traumatic event(s).

RESULTS

In 29 study populations, the latent class growth analyses displayed delayed trajectories, and in these, we identified 110 data points (% PTSD sumscore difference/months since traumatic exposure). The median PTSD symptom sumscore was 25% higher during the initial 6 months among individuals in the delayed trajectory compared to those in low-stable trajectory. From this level, the difference widened and reached a plateau of 40-50% higher. The variation was large, and the baseline participation rate and loss to follow-up were exceeding 25% in the majority of the studies. Heterogeneity of populations, measures, and analyses precluded formal meta-analysis.

CONCLUSION

Delayed PTSD is preceded by PTSD symptoms during the first year in most cases. Still, few individuals may experience an asymptomatic delay. The results underpin the rationale for monitoring PTSD symptoms and may inform forensic assessments in that delayed PTSD without symptoms bridging the traumatic event is rare.

NMR and MD Analysis of the Bonding Interaction of Vancomycin with Muramyl Pentapeptide

The article describes an NMR spectroscopy study of interactions between vancomycin and a muramyl pentapeptide in two complexes: vancomycin and a native muramyl pentapeptide ended with D-alanine (MPP-D-Ala), and vancomycin and a modified muramyl pentapeptide ended with D-serine (MPP-D-Ser). The measurements were made in a 9:1 mixture of H₂O and D₂O. The obtained results confirmed the presence of hydrogen bonds previously described in the literature. At the same time, thanks to the pentapeptide model used, we were able to prove the presence of two more hydrogen bonds formed by the side chain amino group of L-lysine and oxygen atoms from the vancomycin carboxyl and amide groups. This type of interaction has not been described before. The existence of these hydrogen bonds was confirmed by the ¹H NMR and molecular modeling. The formation of these bonds incurs additional through-space interactions, visible in the NOESY spectrum, between the protons of the L-lysine amino group and a vancomycin-facing hydrogen atom in the benzylic position. The presence of such interactions was also confirmed by molecular dynamics trajectory analysis.

Women's trajectories of postpartum depression and social support: A repeated-measures study with implications for evidence-based practice

BACKGROUND

Postpartum depression is one of the most common psychological disorders of women after childbirth. Despite the importance of social support as an influencing factor, there have been few studies on the trends and characteristics of social support as it relates to postpartum depression.

AIMS

To explore the trends in postpartum depression and social support, to cross-analyze the correlation between the postpartum depression trajectory and the social support trajectory, and to investigate predictors of changes in postpartum depression trajectories.

METHODS

A prospective repeated-measure study and convenience sampling were used to recruit 230 women at 1, 3, and 6 months after childbirth. Structured questionnaires were used for data collection. Trajectory analysis was used to explore the trajectories of postpartum depression and social support during the 6 months after childbirth, and polynomial logistic regression was used to explore predictors of the trajectory of postpartum depression.

RESULTS

Postpartum depression was at its most serious in the third month after childbirth, showing patterns of low-risk, moderate-risk, and high-risk trajectories. Social support also showed low, moderate, and high patterns, and the trajectory of postpartum depression was significantly related to the trajectory of social support. The predictors of moderate-risk and high-risk postpartum depression were also found in this study.

LINKING EVIDENCE TO ACTION

Postpartum mental health education and online learning systems should be used to increase social support for women after childbirth and reduce the incidence of postpartum depression.

Trajectory Analysis of Orthostatic Hypotension in Parkinson's Disease: Results From Parkinson's Progression Markers Initiative Cohort

Background: Orthostatic hypotension (OH) in Parkinson’s disease (PD) can lead to falls, impair quality of life, and increase mortality. A trajectory analysis of OH could be useful to predict and prevent the hypotension incidence early.

Methods: The longitudinal data of 660 patients with PD with disease duration up to 12 years were extracted from an integrated PD database. We used latent class mixed modeling (LCMM) to identify patient subgroups, demonstrating trajectories of changes in orthostatic blood pressure (BP) over time. The optimal number of subgroups was selected by several criteria including the Bayesian Information Criterion. Baseline information comparison between groups and backward stepwise logistic regression were conducted to define the distinguishing characteristics of these subgroups and to investigate the predictors for BP trajectory.

Results: We identified three trajectories for each orthostatic change of systolic blood pressure (ΔSBP), namely, Class 1 (i.e., the increasing class) consisted of 18 participants with low ΔSBP that increased continuously during the follow-up; Class 2 (i.e., the low-stable class) consisted of 610 participants with low ΔSBP that remained low throughout the follow-up; and Class 3 (i.e., the high-stable class) consisted of 32 participants with high ΔSBP at baseline that was relatively stable throughout the follow-up. Several parameters differed among subgroups, but only male sex [odds ratio (OR) = 4.687, 95% confidence interval (CI) = 1.024–21.459], lower supine diastolic blood pressure (DBP) (OR = 0.934, 95% CI = 0.876–0.996), and lower level of total protein at baseline (OR = 0.812, 95% CI = 0.700–0.941) were significant predictors of an increasing ΔSBP trajectory.

Conclusion: This study provides new information on the longitudinal development of ΔSBP in patients with PD with distinct trajectories of rapidly increasing, low-stable, and high-stable class. The parameters such as male sex, lower supine DBP, and lower total proteins help to identify the rapidly increasing class.

Cardiorenal Risk Profiles Among Data-Driven Type 2 Diabetes Sub-Phenotypes: A Post-Hoc Analysis of the China Health and Nutrition Survey

BACKGROUND AND AIM

Evidence about recently proposed data-driven clusters of type 2 diabetes (T2D) is mainly about its prognostic effects and Western populations. We tested the applicability of this clustering approach among the Chinese population. We further investigated the cardiorenal risk profiles among different T2D sub-phenotypes cross-sectionally and before diabetes diagnosis.

METHODS

With the use of data from the China Health and Nutrition Survey (1989-2009), 6,728 participants with available fasting blood samples and completed questionnaires in the 2009 survey were included. Glycemic statuses (normoglycemia, prediabetes, and new-onset T2D) were defined according to the 2020 American Diabetes Association criteria. Data-driven cluster analysis was conducted among new-onset T2D based on five variables: age at onset, body mass index (BMI), hemoglobin A1c, homeostasis model estimates of β-cell function, and insulin resistance. Linear regression models were used to cross-sectionally examine the differences of cardiorenal risk factors (body fat distribution, blood pressure, lipid profiles, and kidney function) between glycemic statuses. Mixed-effects models were used to explore a maximum of 20-year trajectories of cardiovascular risk factors (body fat distribution and blood pressure) before diabetes diagnosis.

RESULTS

Among 557 (8.3%) new-onset T2D, four sub-phenotypes were found, with 57 (10.2%) assigned to the severe insulin-resistant diabetes (SIRD), 72 (12.9%) to the severe insulin-deficient diabetes (SIDD), 167 (30.0%) to the mild obesity-related diabetes (MOD), and 261 (46.9%) to the mild age-related diabetes (MARD). People clustered within different T2D sub-phenotypes had different cardiorenal risk profiles. Three T2D sub-phenotypes (SIRD, SIDD, and MOD) had worse cardiorenal abnormalities, while the risk burden in the MARD sub-phenotype was similar to that in prediabetes. Compared with people with other T2D sub-phenotypes, people in the MOD sub-phenotype had a faster increment in BMI, waist, upper arm circumference, and triceps skinfold up to 10 years before diagnosis. Blood pressure was less distinct in different T2D sub-phenotypes; however, SIDD and MOD clusters had higher blood pressure levels before diabetes diagnosis.

CONCLUSIONS

Data-driven T2D sub-phenotyping is applicable in the Chinese population. Certain sub-phenotypes such as MARD only have a minor cardiorenal risk burden, and distinct cardiovascular risk development occurs long before diabetes diagnosis. Our findings can help improve early prevention and targeted treatment for diabetes.