Time-point Data Research Articles

Influence of Emulsion Lipid Droplet Crystallinity on Postprandial Endotoxin Transporters and Atherogenic And Inflammatory Profiles in Healthy Men - A Randomized Double-Blind Crossover Acute Meal Study.

Consumption of high-fat meals is associated with increased endotoxemia, inflammation, and atherogenic profiles, with repeated postprandial responses suggested as contributors to chronically elevated risk factors. However, effects of lipid solid versus liquid state specifically have not been investigated. This exploratory randomized crossover study tests the impact of lipid crystallinity on plasma levels of endotoxin transporters (lipopolysaccharide [LPS] binding protein [LBP] and soluble cluster of differentiation 14 [sCD14]) and select proinflammatory and atherogenic markers (tumor necrosis factor-alpha [TNF-α], C-reactive protein [CRP], interleukin-1-beta [IL-1β], interferon-gamma [IFN-γ], interleukin-6 [IL-6], soluble intercellular adhesion molecule [sICAM], soluble vascular cell adhesion molecule [sVCAM], monocyte chemoattractant protein-1 [MCP-1/CCL2], plasminogen activator inhibitor-1 [PAI-1], and fibrinogen). Fasted healthy men (n = 14, 28 ± 5.5 years, 24.1 ± 2.6kgm-2) consumed two 50g palm stearin oil-in-water emulsions tempered to contain either liquid or crystalline lipid droplets at 37°C on separate occasions with blood sampling at 0, 2-, 4-, and 6-h post-meal. Timepoint data, area under the curve, and peak concentration values are compared. Overall, no treatment effects are seen (p > 0.05). There are significant effects of time, with values decreasing from baseline, for TNF-α, MCP-1/CCL2, PAI-1, and fibrinogen (p < 0.05). Responder analysis pointed to differential treatment effects associated with some participant baseline characteristics but, overall, palm-stearin emulsion droplet crystallinity does not acutely affect plasma endotoxin transporters nor select inflammatory and atherogenic markers.

Parameter estimation from single patient, single time-point sequencing data of recurrent tumors.

In this study, we develop consistent estimators for key parameters that govern the dynamics of tumor cell populations when subjected to pharmacological treatments. While these treatments often lead to an initial reduction in the abundance of drug-sensitive cells, a population of drug-resistant cells frequently emerges over time, resulting in cancer recurrence. Samples from recurrent tumors present as an invaluable data source that can offer crucial insights into the ability of cancer cells to adapt and withstand treatment interventions. To effectively utilize the data obtained from recurrent tumors, we derive several large number limit theorems, specifically focusing on the metrics that quantify the clonal diversity of cancer cell populations at the time of cancer recurrence. These theorems then serve as the foundation for constructing our estimators. A distinguishing feature of our approach is that our estimators only require a single time-point sequencing data from a single tumor, thereby enhancing the practicality of our approach and enabling the understanding of cancer recurrence at the individual level.

Transient colonizing microbes promote gut dysbiosis and functional impairment

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS). We validated the continuation of this grouping, generating gut metagenomics data for additional time points from the same Swedish cohort. We evaluated the existence of PCS/TCS across different geographical regions and observed they are globally conserved features. To characterize PCS/TCS phenotypes, we performed bioreactor fermentation with faecal samples and metabolic modeling. Finally, using chronic disease gut metagenome and other multi-omics data, we identified roles of TCS in microbial dysbiosis and link with abnormal changes to host physiology.

Childhood Gender Diversity and Mental Health: Protocol for the Longitudinal, Observational Gender Journey Project.

Prepubertal transgender, nonbinary, and gender-diverse (TGD) children (ie, those asserting gender identity, expressing gender-role behavior outside of culturally defined norms for their sex registered at birth, or both) are presenting in greater numbers to pediatric gender clinics across the United States and abroad. A large subset of TGD children experiences gender dysphoria, that is, distress that arises from the incongruence between gender identity and sex registered at birth. A lack of consensus exists regarding care for prepubertal TGD children due, in part, to a dearth of empirical research on longitudinal developmental trajectories of gender identity, role behavior, and gender dysphoria (when present). The objective of this National Institutes of Health-funded study is to provide evidence to inform clinical care for prepubertal TGD children by establishing a US longitudinal cohort (N=248) of prepubertal TGD children and their caregivers that is followed prospectively at 6-month intervals across 18 months. At each timepoint, clinical and behavioral data are collected via web-based visit from child and caregiver reporters. Latent class analysis, among other methods, is used to identify subgroups and longitudinally characterize the gender identity and gender-role behavior of TGD children. These models will define longitudinal patterns of gender identity stability and characterize the relationship between TGD classes and mental and behavioral health outcomes, including the moderating role of social gender transition (when present), on these associations. Baseline data collection (N=248) is complete, and the identification of TGD subgroups based on gender identity and expression using latent class analysis is anticipated in 2024. The completion of all 4 waves of data collection is anticipated in July 2024, coinciding with the start of a no-cost study extension period. We anticipate longitudinal analyses to be completed by winter 2024. Through a longitudinal observational design, this research involving prepubertal TGD children and their caregivers aims to provide empirical knowledge on gender development in a US sample of TGD children, their mental health symptomology and functioning over time, and how family initiated social gender transition may predict or alleviate mental health symptoms or diagnoses. The research findings have promise for clinicians and families aiming to ensure the best developmental outcome for these children as they develop into adolescents. DERR1-10.2196/55558.

The graded multidimensional geometry of phenotypic variation and progression in neurodegenerative syndromes.

Clinical variants of Alzheimer's disease and frontotemporal lobar degeneration display a spectrum of cognitive-behavioural changes varying between individuals and over time. Understanding the landscape of these graded individual-/group-level longitudinal variations is critical for precise phenotyping; however, this remains challenging to model. Addressing this challenge, we leverage the National Alzheimer's Coordinating Center database to derive a unified geometric framework of graded longitudinal phenotypic variation in Alzheimer's disease and frontotemporal lobar degeneration. We included three time-point, cognitive-behavioural and clinical data from 390 typical, atypical and intermediate Alzheimer's disease and frontotemporal lobar degeneration variants (114 typical Alzheimer's disease; 107 behavioural variant frontotemporal dementia; 42 motor variants of frontotemporal lobar degeneration; and 103 primary progressive aphasia patients). On this data, we applied advanced data-science approaches to derive low-dimensional geometric spaces capturing core features underpinning clinical progression of Alzheimer's disease and frontotemporal lobar degeneration syndromes. To do so, we first used principal component analysis to derive six axes of graded longitudinal phenotypic variation capturing patient-specific movement along and across these axes. Then, we distilled these axes into a visualisable 2D manifold of longitudinal phenotypic variation using Uniform Manifold Approximation and Projection. Both geometries together enabled the assimilation and inter-relation of paradigmatic and mixed cases, capturing dynamic individual trajectories, and linking syndromic variability to neuropathology and key clinical end-points such as survival. Through these low-dimensional geometries, we show that (i) specific syndromes (Alzheimer's disease and primary progressive aphasia) converge over time into a de-differentiated pooled phenotype, while others (frontotemporal dementia variants) diverge to look different from this generic phenotype; (ii) phenotypic diversification is predicted by simultaneous progression along multiple axes, varying in a graded manner between individuals and syndromes; and (iii) movement along specific principal axes predicts survival at 36 months in a syndrome-specific manner and in individual pathological groupings. The resultant mapping of dynamics underlying cognitive-behavioural evolution potentially holds paradigm-changing implications to predicting phenotypic diversification and phenotype-neurobiological mapping in Alzheimer's disease and frontotemporal lobar degeneration.

Characterization of gray matter volume changes from one week to 6 months after termination of electroconvulsive therapy in depressed patients

BackgroundIncreased gray matter volume (GMV) following electroconvulsive therapy (ECT) has been well-documented, with limited studies reporting a subsequent decrease in GMV afterwards. ObjectiveThis study characterized the reversion pattern of GMV after ECT and its association with clinical depression outcome, using multi-site triple time-point data from the Global ECT-MRI Research Collaboration (GEMRIC). Methods86 subjects from the GEMRIC database were included, and GMV in 84 regions-of-interest (ROI) was obtained from automatic segmentation of T1 MRI images at three timepoints: pre-ECT (T0), within one-week post-ECT (T1), and one to six months post-ECT (T2). RM-ANOVAs were used to assess longitudinal changes and LMM analyses explored associations between GMV changes and demographical and clinical characteristics. Results63 of the 84 ROIs showed a significant increase-and-decrease pattern (RM-ANOVA, Bonferroni corrected p < 0.00059). Post hoc tests indicated a consistent pattern in each of these 63 ROIs: significant increase from T0 to T1inGMV, followed by significant decrease from T1 to T2 and no difference between T0 and T2, except for both amygdalae, right hippocampus and pars triangularis, which showed the same increase and decrease but GMV at T2 remained higher compared to T0. No consistent relationship was found between GMV change pattern and clinical status. ConclusionThe GEMRIC cohort confirmed a rapid increase of GMV after ECT followed by reversion of GMV one to six months thereafter. The lack of association between the GMV change pattern and depression outcome scores implies a transient neurobiological effect of ECT unrelated to clinical improvement.

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning

Lung cancer screening (LCS) using annual computed tomography (CT) scanning significantly reduces mortality by detecting cancerous lung nodules at an earlier stage. Deep learning algorithms can improve nodule malignancy risk stratification. However, they have typically been used to analyse single time point CT data when detecting malignant nodules on either baseline or incident CT LCS rounds. Deep learning algorithms have the greatest value in two aspects. These approaches have great potential in assessing nodule change across time-series CT scans where subtle changes may be challenging to identify using the human eye alone. Moreover, they could be targeted to detect nodules developing on incident screening rounds, where cancers are generally smaller and more challenging to detect confidently.Here, we show the performance of our Deep learning-based Computer-Aided Diagnosis model integrating Nodule and Lung imaging data with clinical Metadata Longitudinally (DeepCAD-NLM-L) for malignancy prediction. DeepCAD-NLM-L showed improved performance (AUC = 88%) against models utilizing single time-point data alone. DeepCAD-NLM-L also demonstrated comparable and complementary performance to radiologists when interpreting the most challenging nodules typically found in LCS programs. It also demonstrated similar performance to radiologists when assessed on out-of-distribution imaging dataset. The results emphasize the advantages of using time-series and multimodal analyses when interpreting malignancy risk in LCS.

Predictive modelling of student dropout risk: Practical insights from a South Korean distance university

Distance education supports lifelong learning and empowers individuals in rapidly changing societal conditions, yet it encounters high dropout rates due to a range of individual and societal obstacles. This study addresses the challenge of creating a practical prediction model by analyzing extensive real-world time-point data from a well-established online university in Seoul. Covering 144,540 instances from 2018 to 2022, the study integrates diverse datasets to compare the accuracy of models based on longitudinal, semester-wise, and gender-specific datasets. The demographic, academic, and online metrics identified significant dropout indicators, including age (particularly when binned), residential area, specific occupations, GPA, and LMS log metrics, using a stepwise backward elimination process. The study revealed that, despite societal changes, recent data from the last four semesters can be effectively used for stable prediction training. Gender-based analysis showed different factors influencing dropout risk for males and females. The Light Gradient Boosting Machine (LGBM) algorithm excelled in prediction accuracy, with the ROC-AUC metric affirming its superiority. However, logistic regression also showed its competitive performance and offered in-depth interpretation. In South Korea's distinct educational setting, merging advanced algorithms like LGBM with the interpretive strength of logistic regression is key for effective student support strategies.

Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma.

Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in examination time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient-echo-EPI sequence for T2*-sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors. Twenty-four consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, resting-sate functional MRI (rs-fMRI), and neurocognitive assessment. Voxelwise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the preprocessing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs, Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and nonimpaired patients. Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689 ± 0.118 (group/patient), 0.973/0.730 ± 0.124, and 0.935/0.665 ± 0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P = .97) or language networks (P = .30), but there was a difference in motor networks (P = .02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (sensitivity = 84.6%, specificity = 63.6%, receiver operating characteristic area under the curve (AUC) = 0.7762 ± 0.0954 (standard error), P = .0221) and performance was not significantly different from full rs-fMRI predictions (AUC = 0.8881 ± 0.0733 (standard error), P = .0013, P = .29 compared with pseudo-rs-fMRI). DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.

Improvement of Midpoint Imputation for Estimation of Median Survival Time for Interval-Censored Time-to-Event Data.

Progression-free survival (PFS) is used to evaluate treatment effects in cancer clinical trials. Disease progression (DP) in patients is typically determined by radiological testing at several scheduled tumor-assessment time points. This produces a discrepancy between the true progression time and the observed progression time. When the observed progression time is considered as the true progression time, a positively biased PFS is obtained for some patients, and the estimated survival function derived by the Kaplan-Meier method is also biased. While the midpoint imputation method is available and replaces interval-censored data with midpoint data, it unrealistically assumes that several DPs occur at the same time point when several DPs are observed within the same tumor-assessment interval. We enhanced the midpoint imputation method by replacing interval-censored data with equally spaced timepoint data based on the number of observed interval-censored data within the same tumor-assessment interval. The root mean square error of the median of the enhanced method is almost always smaller than that of the midpoint imputation regardless of the tumor-assessment frequency. The coverage probability of the enhanced method is close to the nominal confidence level of 95% in most scenarios. We believe that the enhanced method, which builds upon the midpoint imputation method, is more effective than the midpoint imputation method itself.

Stability of child appetitive traits and association with diet quality at 5 years and 9–11 years old: Findings from the ROLO longitudinal birth cohort study

BackgroundWe explored change in child appetitive traits from 5 to 9–11 years old and examined associations between appetitive traits at both timepoints and child diet quality.MethodsThis is secondary analyses of the ROLO longitudinal birth cohort study, including mother-child dyads from the 5 and 9–11-year old follow-up. The Children’s Eating Behaviour Questionnaire measured child appetitive traits, with 167 children having matched data for both timepoints. The Healthy Eating Index (HEI) measured diet quality. Linear mixed models and multiple linear regression were completed.ResultsMean (SD) score for ‘Emotional Overeating’ (1.63 (0.51) vs. 1.99 (0.57), p = <0.001) and ‘Enjoyment of Food’ (3.79 (0.72) vs. 3.98 (0.66), p = <0.001) increased from 5 to 9–11 years. Mean score for ‘Desire to Drink’ (2.63 (0.94) vs. 2.45 (0.85), p = 0.01), ‘Satiety Responsiveness (3.07 (0.66) vs. 2.71 (0.66), p = <0.001), ‘Slowness Eating’ (3.02 (0.77) vs. 2.64 (0.78), p = <0.001), and ‘Food Fussiness’ (3.00 (1.04) vs. 2.81 (0.96), p = 0.001) decreased. At 5-years-old, ‘Food Responsiveness’ and ‘Enjoyment of Food’ were positively associated with HEI and ‘Desire to Drink’, ‘Satiety Responsiveness’ and ‘Food Fussiness’ were negatively associated with HEI. At 9–11-years, ‘Enjoyment of Food’ was positively and ‘Desire to Drink’ and ‘Food ‘Fussiness’ were negatively associated with HEI.ConclusionsFood approach appetitive traits increased over time, whereas food avoidant appetitive traits tended to decrease. At both time points ‘Food Fussiness’ and ‘Desire to Drink” were inversely associated with HEI. Further research on how appetitive traits track over childhood and how this relates to dietary quality and weight is warranted.

Health-related quality of life in patients with triple-class exposed relapsed and refractory multiple myeloma treated with idecabtagene vicleucel or standard regimens: patient-reported outcomes from the phase 3, randomised, open-label KarMMa-3 clinical trial

Chimeric antigen receptor T-cell therapy idecabtagene vicleucel (ide-cel) showed significantly improved progression-free survival compared with standard regimens in adults with relapsed and refractory multiple myeloma who had received two to four previous regimens in the ongoing phase 3 KarMMa-3 trial (NCT03651128). This study analysed patient-reported outcomes (PROs), a KarMMa-3 secondary endpoint. In the randomised, open-label, phase 3 KarMMa-3 trial, 386 patients in hospitals (≥18 years of age, with measurable disease and an Eastern Cooperative Oncology Group performance status score of 0 or 1, who had received two to four previous regimens-including an immunomodulatory agent, a proteasome inhibitor, and daratumumab-and had documented disease progression after receiving their last dose of the last therapy) were randomly assigned to ide-cel (n=254) or standard regimens (daratumumab, pomalidomide, and dexamethasone; daratumumab, bortezomib, and dexamethasone; ixazomib, lenalidomide, and dexamethasone; carfilzomib and dexamethasone; or elotuzumab, pomalidomide, and dexamethasone; n=132). Patients were expected to complete the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life C30 Questionnaire (QLQ-C30), Multiple Myeloma Module (QLQ-MY20), EQ 5 dimensions (EQ-5D), and EQ-5D visual analogue scale (VAS) at baseline and follow-up timepoints (data cutoff April 18, 2022). PROs included nine prespecified primary domains: EORTC QLQ-C30 GHS-quality of life (QoL), physical functioning, cognitive functioning, fatigue, and pain; QLQ-MY20 disease symptoms and side effects of treatment; and five-level EQ-5D (EQ-5D-5L) index score and EQ-5D visual VAS. Differences in overall least-squares mean changes from baseline to month 20 were analysed using post-hoc constrained longitudinal data analysis. Time to confirmed improvement or deterioration from baseline was analysed using Cox proportional hazard models. Patients were randomly assigned between May 6, 2019, and April 8, 2022. Overall, the median age was 63 years (IQR 55-68); 151 (39%) patients were female; and 250 (65%) patients were White, 36 (9%) Black or African American, 19 (5%) Hispanic or Latino, 12 (3%) Asian, and seven (2%) of other race. The median follow-up was 18·6 months (IQR 14·0-26·4). PRO compliance was higher than 75% throughout. Overall least-squares mean changes from baseline favoured ide-cel with Hedges' g effect sizes from 0·3 to 0·7 for most domains. Patients in the ide-cel group showed statistically significant and clinically meaningful improvements across the primary PRO domains of interest, with the exception of QLQ-MY20 disease symptoms, side effects of treatment, and EQ-5D-5L index score, which showed improvement across assessment visits but did not exceed the within-group minimally important difference thresholds. The ide-cel group had shorter times to clinically meaningful improvement than the standard regimens group in QLQ-C30 domains except in role functioning, diarrhoea, and financial difficulties; in QLQ-MY20 domains except body image; and in EQ-5D-VAS. Ide-cel offers improved health-related quality of life compared with standard regimens for patients with relapsed and refractory multiple myeloma after previous lines of therapy. The PRO data highlight the extended QoL benefits of a one-time infusion with ide-cel compared with continuous treatment with standard regimens in the treatment of triple-class exposed patients with relapsed and refractory multiple myeloma. 2seventy bio and Celgene, a Bristol Myers Squibb Company.

Limitations of two time point data for understanding individual differences in longitudinal modeling — What can difference reveal about change?

Emerging neuroimaging studies investigating changes in the brain aim to collect sufficient data points to examine trajectories of change across key developmental periods. Yet, current studies are often constrained by the number of time points available now. We demonstrate that these constraints should be taken seriously and that studies with two time points should focus on particular questions (e.g., group-level or intervention effects), while complex questions of individual differences and investigations into causes and consequences of those differences should be deferred until additional time points can be incorporated into models of change. We generated underlying longitudinal data and fit models with 2, 3, 4, and 5 time points across 1000 samples. While fixed effects could be recovered on average even with few time points, recovery of individual differences was particularly poor for the two time point model, correlating at r = 0.41 with the true individual parameters - meaning these scores share only 16.8% of variance As expected, models with more time points recovered the growth parameter more accurately; yet parameter recovery for the three time point model was still low, correlating around r = 0.57. We argue that preliminary analyses on early subsets of time points in longitudinal analyses should focus on these average or group-level effects and that individual difference questions should be addressed in samples that maximize the number of time points available. We conclude with recommendations for researchers using early time point models, including ideas for preregistration, careful interpretation of 2 time point results, and treating longitudinal analyses as dynamic, where early findings are updated as additional information becomes available.

A short-interval longitudinal study of associations between psychological distress and hippocampal grey matter in early adolescence

This study of Australian adolescents (N = 88, 12-13-years-old) investigated the relationship between hippocampal grey matter volume (GMV) and self-reported psychological distress (K10) at four timepoints, across 12 months. Participants were divided into two groups; those who had K10 scores between 10 and 15 for all four timepoints were categorised as “low distress” (i.e., control group; n = 38), while participants who had K10 scores of 16 or higher at least once over the year were categorised as “moderate-high distress” (n = 50). Associations were tested by GEE fitting of GMV and K10 measures at the same time point, and in the preceding and subsequent timepoints. Analyses revealed smaller preceding left GMV and larger preceding right GMV were associated with higher subsequent K10 scores in the “moderate-high distress” group. This was not observed in the control group. In contrast, the control group showed significant co-occurring associations (i.e., at the same TP) between GMV and K10 scores. The “moderate-high distress” group experienced greater variability in distress. These results suggest that GMV development in early adolescence is differently associated with psychological distress for those who experience “moderate-high distress” at some point over the year, compared to controls. These findings offer a novel way to utilise short-interval, multiple time-point longitudinal data to explore changes in volume and experience of psychological distress in early adolescents. The results suggest hippocampal volume in early adolescence may be linked to fluctuations in psychological distress.

Genetic and biomarker modulation of arterial stiffness change in the SardiNIA population cohort.

Arterial stiffness (AS), quantified by pulse wave velocity (PWV), arises due to impaired arterial elastic tissue and smooth muscle dysfunction. We aimed to examine the longitudinal association of genetic, lipid and inflammation biomarkers with PWV and how these associations may change with aging. We utilized genotype and four time-point biomarker data from the SardiNIA cohort [n = 6,301; mean baseline age 43.3 (SD 17.3); 58% females]. To investigate the association of PWV with genetic variants, lipid, and inflammation biomarkers, we employed linear mixed modeling, using age as the time scale. Biomarkers exhibiting significant longitudinal associations were categorized into tertiles and individuals within the second tertile or those with heterozygous alleles were excluded, leaving a cohort of 2,000 individuals. This cohort was further divided into four risk groups: low genetic and low biomarker (L-L), low genetic and high biomarker (L-H), high genetic and low biomarker (H-L), and high genetic and high biomarker risk (H-H). Subsequent analyses focused on these risk groups to assess their association to PWV with time. Using the complete dataset, we found a significant longitudinal association of total cholesterol (TC), triglycerides (TG), fibrinogen (FGN), and total white blood cell count (TWBC) with PWV, all with p < 3.33 × 10-3. After grouping, individuals with homogeneous risk alleles of SNP rs3742207 and high baseline TG levels (H-H group) exhibited a 1.39-fold higher PWV (m/s) (95% CI, 1.17-1.64, p = 1.21 × 10-4) compared to the L-L group. Similarly, individuals in the H-H group of rs3742207-TWBC combination showed 1.75 times higher PWV (95% CI, 1.48-0.2.07, p = 1.01 × 10-10) compared to the L-L group. Similar patterns were observed for groups based on SNP rs7152623-TWBC risk. Furthermore, these associations became more pronounced with increasing age (p < 3.33 × 10-3). The longitudinal association of TG and TWBC biomarkers with PWV varied by SNPs rs3742207 and rs7152623 genotype. Further studies are warranted to investigate the function of genetics, lipids, and inflammation biomarkers on PWV change.

COGNITIVE IMPAIRMENT AMONG OLDER ADULTS WITH INTERSECTING SEXUAL, GENDER, RACIAL, AND ETHNIC MINORITY IDENTITIES

Abstract Emerging research shows Lesbian, gay, bisexual, transgender, and queer (LGBTQ) older adults experience higher prevalence of cognitive impairment when compared to their heterosexual and cisgender peers of a similar age. The same is true for racial and ethnic minority older adults when compared to their White counterparts. Little is known about the cognitive health of older adults with intersecting sexual, gender, racial, and ethnic minority identities, highlighting a critical gap in gerontological research that requires further investigation. This study utilizes four time-point data from the first longitudinal study of a racially and ethnically diverse sample of LGBTQ older adults. Multilevel mixed models accounting for intersecting sexual, gender, racial, and ethnic identities were applied to examine subgroup differences in cognitive impairment as well as risk and protective factors after controlling for confounding factors. Black and Hispanic LGBTQ minority older adults (b=5.20, p&amp;lt;.01; b=4.05, p&amp;lt;.01) experience higher levels of cognitive impairment over time when compared to their White LGBTQ peers. Day-to-day discrimination targeting the confluence of sexual/gender and racial/ethnic minority status (b=2.78, p&amp;lt;.05) was positively associated with higher cognitive impairment. Community engagement (b=-.46, p&amp;lt;.05) was negatively associated with cognitive impairment regardless of race and ethnicity whereas network size was exclusively negatively associated with cognitive impairment for Black LGBTQ older adults. The overall findings demonstrate racial and ethnic differences in cognitive impairment among LGBTQ older adults and illuminate the importance of culturally tailored interventions that account for intersectionality, social connectivity, and discrimination to promote cognitive health for specific subgroups.

247 In Vitro Characterization of Equine Fore- and Midgut Digestion

Abstract Considerable advancements can be made in the field of equine nutrition and diet formulation, by improved feed characterization and the development of nutritional models, including in vitro models, to describe nutrient degradation. Methodologically, literature values for in vitro small intestine incubation times are widely variable ranging from 2 to 18 h. While some incubation times are selected to represent approximate mean retention times, conversely, insufficient in vitro incubation times and sampling time points could prohibit or result in inaccuracies characterizing nutrient degradability characteristics, ultimately affecting both degradability and digestion values and their use. The objective of this trial was to assess whether macronutrient degradability plateaus when digested for 2 h in a simulated gastric environment plus 8, 12, or 16 h in a simulated small intestinal environment. To replicate in vivo digestion, a pepsin-pancreatin approach was selected. The first step of this method replicates the gastric environment. Ten g of each test ingredient are weighed into beakers containing 60 mL hydrochloric acid (HCl; 0.1 M) and 0.4 g pepsin (~2,500 U/g) solution. Beakers are then covered and incubated for 2 h at 39 ℃ under constant stirring. One mL aliquots of the digestion liquid are sampled at 0, 5, 10, 20, 30 60, 90 and 120 min after the start of the gastric simulation. Before replicating intestinal digestion, samples are neutralized with sodium hydroxide and the pH is increased to 7. The second step of this method replicates the small intestinal environment. Fifty mL of pancreatin-phosphate buffer (350 U/g protease, 6,000 FIP U/g lipase, 7,500 U/g amylase) is added to the beakers, which are then covered and incubated for either 8, 12, or 16 h at 39 ℃ under constant stirring. One mL aliquots of the digestion liquid are sampled at 0, 5, 10, 20, 30 60, 90, 120, 150, 180 min and thereafter hourly up until the end of digestion (480, 720, or 960 min). Aliquot samples are analyzed for starch via a glucose assay, protein via o-phthalaldehyde assay, and lipids via gas chromatography. A model will is fit to the time point data to determine degradation rates and degradable fractions of the digested samples. Results from these analyses go beyond estimating gross nutrient and digestible nutrient values and inform on the rate of degradation of nutrients of equine feedstuffs and the impact of in vitro methodology. The resulting degradability values will be used in a mechanistic model of equine digestion which will inform precision feeding. Ultimately this will improve how we feed horses to reduce nutrient excretion into the environment and reduce the risk of metabolic conditions such as laminitis.

The Diversity of FLT3-ITD and the Prognostic Impact in Adult Acute Myeloid Leukemia

Introduction FLT3 internal tandem duplication (ITD) is commonly detected in patients with acute myeloid leukemia (AML) and is known to confer poor prognosis. It has different insertion numbers, mutation burden, insertion sizes, insertion sites and insertion nucleotide sequences, showing complex diversity. However, the guideline of AML did not sufficiently consider the impact of the diversity of FLT3-ITD on treatment responses, and previous studies have not been consistent with the impact of FLT3-ITD diversity on clinical prognosis. In this study we examined the diversity of FLT3-ITD and correlated these parameters with clinical outcome in adult AML. In addition, we revealed the correlation between FLT3-ITD and drug resistance through evolutionary trajectories in primary resistant patients. Methods We included adult patients from 2016-2021 at Henan Cancer Hospital with newly diagnosed adult AML. next generation sequencing (NGS) was performed for all patients at diagnosis. The FLT3-ITD was also detected using conventional methods based on PCR, with a cut-off of 3% for positivity. The comparative analysis of NGS and PCR was done to validate the diversity of FLT3-ITD. Whole genome sequencing (WGS) data for multiple time points were used to analyze clonal evolution. Data were collected by chart review. The chi-squared or Fisher's exact test, Mann-Whitney U test, log-rank and Cox regression analyses were performed. Results Among 406 newly diagnosed adult AML patients, 24.4% (99/406) patients were detected with FLT3-ITD. The FLT3-ITD diversity was validated by NGS and PCR data from 90 FLT3-ITD positive patients. 61.1% (55/90) patients had single FLT3-ITD (sFLT3-ITD) (31M/24F, median age 46 at diagnosis, range 18-64), and 38.9% (35/90) patients carried multiple FLT3-ITDs (mFLT3-ITD) at the same time (23M/12F, median age 47 at diagnosis, range 19-64). A total of 161 FLT3-ITDs were detected, with a median mutation burden of 21.51% (0.71-93.21%) and a median insertion length of 36bp (9-189 bp). 80.20% of FLT3-ITD insertions were in the near-membrane region, and 45.54% of FLT3-ITD insertions contained exogenous nucleic acid sequences. Patients with mFLT3-ITD had a significantly lower CR rate than those with sFLT3-ITD (25.7% vs 60.0%, p=0.001), while the CR rate of patients with sFLT3-ITD was similar to patients without FLT3-ITD (60.0% vs 58.6%, p=0.521). In the setting of NPM1, the CR rate of patients with sFLT3-ITD+NPM1 mut improved significantly when compared to patients with sFLT3-ITD+NPM1 wild (76.9% vs 44.8%, p=0.015). Unfortunately, the state of NPM1 had no impact on the CR rate of patients with mFLT3-ITD. After a median follow-up of 38.9 months, the median overall survival (OS) has not been reached for patients with a single FLT3-ITD, and the median OS for patients with multiple FLT3-ITDs was only 12.4 months (95 CI, 3.8 to 20.9) ( p=0.028). Multivariate analysis confirmed its prognostic significance on CR rate (HR 2.13, 95% CI, 1.38-4.20, p=0.020) but not on OS. The mutation burden, insertion sizes, insertion sites and insertion nucleotide sequences of FLT3-ITD had no significant impact on the CR rate or OS. To explore the clonal architecture of mFLT3-ITD, single cell DNA sequencing on one patient showed that respective FLT3-ITD variants were detected in completely separated cell populations. This suggested that mFLT3-ITD independently occurred in different subclone. WGS data of persistent primary resistant patients at multiple time points were used to analyze the evolutionary trajectory under chemotherapy. We observed complete separation of evolving trajectory of different FLT3-ITD variants over the course of chemo-treatment. Importantly, FLT3-ITD subclone of diagnosis evolved into the dominant clone at resistance. Conclusion In summary, by exploring the impact of the FLT3-ITD diversity on clinical prognosis and the evolutionary trajectory of mFLT3-ITD, the FLT3-ITD number may be a biomarker to refine the risk stratification and further identify adverse populations among FLT3-ITD positive AML patients.

Identifying Plant Age to Determine Production Trend of Oil Palm Fresh Fruit Bunches

The productivity management of oil palm plantations is carried out by analyzing various influencing factors, but the growing conditions of oil palms are one of the causes of fluctuations in oil palm production. This paper aims to identify post-harvest increases in oil palm productivity. Productivity depends on the number of clusters and the weight of fresh fruit bunches (FFB) produced yearly. The methods of this study were conducted using a targeted sampling technique using available production data for plant time points from 4 to 13 years of age. The total plant sample was 636 ha in Central Kalimantan. As a result, plant growth factors can significantly impact oil palm productivity as measured by the components of oil palm plant production: fresh bunch production per hectare, average bunch weight, and the number of oil palm bunches. FFB tonnage and mean bunch weight increase each year from age 3 to age 13, according to a quadratic regression pattern, whereas the number of palm clusters, in contrast, decreases in number with increasing plant age. This study was intended to serve as a reference and source of information for making production decisions for oil palm plantations to achieve optimal results.

Obesity and Ankle Fractures: Are Outcomes and Complications Really Worse?

Category: Ankle; Trauma Introduction/Purpose: Existing literature has established that obese patients have nearly double the risk of sustaining an ankle fracture when compared to a non-obese population. However, few studies have investigated obesity’s effect on fracture complications and patient reported outcomes (PROs) when patients are stratified by fracture type. Furthermore, as the average body mass index (BMI) of our population steadily rises, it becomes prudent to investigate variations in complications rates and patient reported outcomes in various stages of obesity. The aim of this study is to identify trends in complication rates and patient reported outcome scores among patients of different BMI before and after dividing by fracture complexity. Methods: We retrospectively assessed clinical and surgical data from 595 patients who underwent ankle fracture surgery at a single institution between 2017 and 2021 for surgical related complications. All patients had a minimum of 18 months follow up (mean-42.2 [18.2-71.4] months). PROMIS Physical Health and Visual Analog Scale pain scores surveys were available only for patients receiving surgery after November 2019. We aggregated survey data for timepoints between three months and two years post-operatively to assess only patients with meaningful clinical data in regard to their recovery. Patients were divided based on BMI and fracture type. BMI subgroups were classified as: Non-obese (18.5-24.9 kg/m2, n=88), Overweight/Obese I (25-34.9 kg/m2, n=314), Obese II/III (≥35 kg/m2, n=192). Fracture subgroups were divided into two groups: Simple (Unimalleolar types) and complex (Bimalleolar and Trimalleolar variants). Data analysis was performed using Chi-Square and T-Tests with statistical significance set at an alpha (α) of ≤ 0.05. Results: We observed a whole cohort complication rate of (15.3%, n=91/594). Complication rates when stratified by BMI were: Non-obese (12.3%, n=9), Overweight/Obese class I (19.4%, n=61), Obese class II/III (10.3%, n=20). Complication rates for Overweight/Obese I patients were significantly higher when compared to Non-obese patients (p=0.044, OR=2.11). However, there was no significant difference when comparing Non-obese to Class II/III (p=0.972). We observed no significant differences in complications when performing a sub analysis on specific fracture types, regardless of BMI group. Pain scores were significantly higher in both Overweight/Obese I and Obese II/III groups when compared to Non-Obese patients (p= &lt; 0.001, p=0.015). Physical health scores were significantly lower only in the Obese II/III group when compared to Non-Obese patients (p=0.011). Conclusion: Our results indicate that patients who are Overweight/Obese I have a significantly higher risk of complication when compared to patients of normal BMI. Surprisingly, our cohort demonstrated nearly equivalent risk between Obese II/III and Non- obese patient groups. Patient reported outcome data shows different trends with worse pain scores and lower physical health outcomes in the Obese II/III group. These findings add to the growing debate surrounding obesity’s effect on ankle fracture complication rates as well as patient reported outcomes and suggest that increased BMI cannot be viewed purely as a one-to-one relationship with negative outcomes.