Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations.

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.e. sequence pre-training-based graph neural network (SPGNN), that combines pre-training and fine-tuning stages to predict lncRNA-miRNA associations from RNA sequences and the existing interactions represented as a graph. First, we utilize a sequence-to-vector technique to generate pre-trained embeddings based on the sequences of all RNAs during the pre-training stage. In the fine-tuning stage, we use Graph Neural Network to learn node representations from the heterogeneous graph constructed using lncRNA-miRNA association information. We evaluate our proposed scheme SPGNN on our newly collected animal lncRNA-miRNA association dataset and demonstrate that combining the $k$-mer technique and Doc2vec model for pre-training with the Simple Graph Convolution Network for fine-tuning is effective in predicting lncRNA-miRNA associations. Our approach outperforms state-of-the-art baselines across various evaluation metrics. We also conduct an ablation study and hyperparameter analysis to verify the effectiveness of each component and parameter of our scheme. The complete code and dataset are available on GitHub: https://github.com/zixwang/SPGNN.

Brain structure, amyloid, and behavioral features for predicting clinical progression in subjective cognitive decline.

As a potential preclinical stage of Alzheimer's dementia, subjective cognitive decline (SCD) reveals a higher risk of future cognitive decline and conversion to dementia. However, it has not been clear whether SCD status increases the clinical progression of older adults in the context of amyloid deposition, cerebrovascular disease (CeVD), and psychiatric symptoms. We identified 99 normal controls (NC), 15 SCD individuals who developed mild cognitive impairment in the next 2 years (P-SCD), and 54 SCD individuals who did not (S-SCD) from ADNI database with both baseline and 2-year follow-up data. Total white matter hyperintensity (WMH), WMH in deep (DWMH) and periventricular (PWMH) regions, and voxel-wise grey matter volumes were compared among groups. Furthermore, using structural equation modelling method, we constructed path models to explore SCD-related brain changes longitudinally and to determine whether baseline SCD status, age, and depressive symptoms affect participants' clinical outcomes. Both SCD groups showed higher baseline amyloid PET SUVR, baseline PWMH volumes, and larger increase of PWMH volumes over time than NC. In contrast, only P-SCD had higher baseline DWMH volumes and larger increase of DWMH volumes over time than NC. No longitudinal differences in grey matter volume and amyloid was observed among NC, S-SCD, and P-SCD. Our path models demonstrated that SCD status contributed to future WMH progression. Further, baseline SCD status increases the risk of future cognitive decline, mediated by PWMH; baseline depressive symptoms directly contribute to clinical outcomes. In conclusion, both S-SCD and P-SCD exhibited more severe CeVD than NC. The CeVD burden increase was more pronounced in P-SCD. In contrast with the direct association of depressive symptoms with dementia severity progression, the effects of SCD status on future cognitive decline may manifest via CeVD pathologies. Our work highlights the importance of multi-modal longitudinal designs in understanding the SCD trajectory heterogeneity, paving the way for stratification and early intervention in the preclinical stage. PRACTITIONER POINTS: Both S-SCD and P-SCD exhibited more severe CeVD at baseline and a larger increase of CeVD burden compared to NC, while the burden was more pronounced in P-SCD. Baseline SCD status increases the risk of future PWMH and DWMH volume accumulation, mediated by baseline PWMH and DWMH volumes, respectively. Baseline SCD status increases the risk of future cognitive decline, mediated by baseline PWMH, while baseline depression status directly contributes to clinical outcome.

Ultra-compact and fabrication-tolerant multimode photonic jumpers based on dual Bezier curves.

Compact routing of multimode bus waveguides is of great significance for on-chip mode-division multiplexing (MDM) systems to realize high integration density and flexible layout. In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, multimode photonic jumper (MPJ) on a standard silicon-on-insulator (SOI) platform. It enables an ultra-compact connection between two parallel multimode waveguides (MWGs) with an arbitrary displacement. As a proof of concept, we describe two MPJs with displacements of 5.9 µm and 0.6 µm, each supporting three modes and featuring a longitudinal distance of around 14 µm. For both MPJs, the experimental results show insertion losses (ILs) below 0.086 dB and inter-modal cross talk (CT) below -17.6 dB over the wide wavelength range of 1525-1600 nm for all three modes.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis.

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

Improving the ferroelectric properties of Lu doped Hf0.5Zr0.5O2thin films by capping a CeOxlayer.

Lu doped Hf0.5Zr0.5O2 (HZO) ferroelectric films were prepared on Pt/TiN/SiO2/Si substrate by chemical solution deposition (CSD) method, and an interfacial engineering strategy for improving the ferroelectric property was explored by capping the Lu doped HZO films with a cerium oxide layer. Compared with the Lu doped HZO film without the CeOx coating layer, the Lu doped HZO film with the CeOx coating layer has a larger remanent polarization (2Pr=34.72 µC/cm2) and presents weaker wake-up behavior, which result from the higher orthogonal phase ratio and the lower oxygen vacancy of the CeOx coated Lu doped HZO film. In addition, the CeOx coating can remarkably improve the fatigue resistance and retention performance of the Lu doped HZO films. It is hoped that the results can provide an effective approach for the realization of high-performance and highly reliable hafnium oxide based ferroelectric thin films.

Family risk, parental cortisol contagion, and parenting: A process-oriented approach to spillover.

This multi-method longitudinal study sought to investigate linkage in parental neuroendocrine functioning - indicated by cortisol - over two measurement occasions. In addition, we examined how parental cortisol linkage may operate as an intermediate factor in the cascade of contextual risks and parenting. Participants were 235 families with a young child (Mage = 33.56, 36.00 years for mothers and fathers respectively), who were followed for two annual measurement occasions. Parental cortisol linkage was measured around a laboratory conflict discussion task at both measurement occasions (i.e., pre-discussion, 20- and 40-minute post-discussion for each measurement occasion). Maternal and paternal parenting behavior was observed during a parent-child discipline discussion task. Findings indicated similar levels of cortisol linkage between parents over the two measurement occasions. Furthermore, cortisol linkage between parents operated as an intermediate factor between contextual risks and more compromised parenting behavior. That is, greater contextual risks, indicated by greater neighborhood risk and interparental conflict, were linked to greater cortisol linkage between parents over time, which was in turn linked to greater authoritarian parenting during parent-child interaction. Findings highlighted the importance of understanding physiological-linkage processes with respect to the impact of contextual risks on family functioning and may have crucial implications for clinical work.

Interparental Conflict and Early Adolescent Depressive Symptoms: Parent-Child Triangulation as the Mediator and Grandparent Support as the Moderator.

A notable ambiguity persists concerning whether distinct forms of parent-child triangulation (unstable coercive coalition, stable coalition, detouring-attacking, detouring supportive, parentification) might mediate the association between interparental conflict and early adolescent depressive symptoms similarly within the context of Chinese Confucianism. Filling this research gap, this study aimed to examine the mediating role of the five dimensions of parent-child triangulation in the association between interparental conflict and early adolescent depressive symptoms, as well as the moderating effect of grandparent support on this mediating pathway. Data were drawn from a sample of 761 Chinese adolescents (M age = 12.82 ± 0.47, 49.1% girls). Structural equation model analyses indicated that unstable coercive coalition, stable coalition, and detouring-attacking behaviors partially mediated the association between interparental conflict and adolescent depressive symptoms, while detouring-supportive behaviors and parentification did not demonstrate such mediating effects. Unlike Western societies, a negative correlation was observed between interparental conflict and parentification in the context of China. Grandparent support mitigated the adverse effects of both interparental conflict and the unstable coercive coalition on early adolescent depressive symptoms.

Achieving Record External Quantum Efficiency of 11.5 % in Solution-Processable Deep-Blue Organic Light-Emitting Diodes Utilizing Hot Exciton Mechanism.

High performance solution-processable deep-blue emitters with a Commission International de l'Eclairage (CIE) coordinate of CIEy≤0.08 are highly desired in ultrahigh-definition display. Although, deep-blue materials with hybridized local and charge-transfer (HLCT) excited-state feature are promising candidates, their rigidity and planar molecular structures limit their application in solution-processing technique. Herein, four novel deep-blue solution-processable HLCT emitters were first proposed by attaching rigid imide aliphatic rings as functional units onto the HLCT emitting core. The functional units not only improve solubility, enhance thermal properties and morphological stability of the emitting core, but also promote photoluminescence efficiency, balance charge carrier transport, and inhibit aggregation-caused quenching effect due to the weak electron-withdrawing property as well as steric hindrance. The corresponding solution-processable organic light-emitting diodes (OLEDs) substantiate an unprecedented maximum external quantum efficiency (EQEmax) of 11.5 % with an emission peak at 456 nm and excellent colour purity (full width at half maximum=56 nm and CIEy=0.09). These efficiencies represent the state-of-the-art device performance among the solution-processable blue OLEDs based on the "hot exciton" mechanism. This simple strategy opens up a new avenue for designing highly efficient solution-processable deep-blue organic luminescent materials.

HMCDA: a novel method based on the heterogeneous graph neural network and metapath for circRNA-disease associations prediction.

Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease associations identification are labor-intensive. In this work, we propose a novel method based on the heterogeneous graph neural network and metapaths for circRNA-disease associations prediction termed as HMCDA. First, a heterogeneous graph consisting of circRNA-disease associations, circRNA-miRNA associations, miRNA-disease associations and disease-disease associations are constructed. Then, six metapaths are defined and generated according to the biomedical pathways. Afterwards, the entity content transformation, intra-metapath and inter-metapath aggregation are implemented to learn the embeddings of circRNA and disease entities. Finally, the learned embeddings are used to predict novel circRNA-disase associations. In particular, the result of extensive experiments demonstrates that HMCDA outperforms four state-of-the-art models in fivefold cross validation. In addition, our case study indicates that HMCDA has the ability to identify novel circRNA-disease associations.

An artificial-intelligence-based age-specific template construction framework for brain structural analysis using magnetic resonance images.

It is an essential task to construct brain templates and analyze their anatomical structures in neurological and cognitive science. Generally, templates constructed from magnetic resonance imaging (MRI) of a group of subjects can provide a standard reference space for analyzing the structural and functional characteristics of the group. With recent development of artificial intelligence (AI) techniques, it is desirable to explore AI registration methods for quantifying age-specific brain variations and tendencies across different ages. In this article, we present an AI-based age-specific template construction (called ASTC) framework for longitudinal structural brain analysis using T1-weighted MRIs of 646 subjects from 18 to 82 years old collected from four medical centers. Altogether, 13 longitudinal templates were constructed at a 5-year age interval using ASTC, and tissue segmentation and substructure parcellation were performed for analysis across different age groups. The results indicated consistent changes in brain structures along with aging and demonstrated the capability of ASTC for longitudinal neuroimaging study.

Active polarization controller based on micro-ring resonators.

On-chip polarization handling is of great significance for optical interconnects to overcome polarization sensitivity. In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, on-chip polarization controller (PC) on a 220 nm silicon-on-insulator (SOI) platform. It is the first demonstration of a PC based on micro-ring resonators. Any input polarization states can be actively converted to the standard transverse-electric (TE) mode under the phase manipulation. Experimental results show that the insertion loss is less than 0.8 dB and the polarization dependent loss (PDL) is around 0.5 dB. The proposed device also exhibits excellent performances in wavelength tunability over the C band and 35 Gbps data transmission.

Homogeneity Assumptions in the Analysis of Dynamic Processes.

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples.

Safety of different surgical modalities for recurrent respiratory papillomatosis resection: A systematic review and meta-analysis.

BACKGROUND: Currently, the most common surgical modalities used for recurrent respiratory papillomatosis (RRP) resection are microdebrider, carbon dioxide (CO2 ) laser and potassium-titanyl-phosphate (KTP) laser. However, complication rates vary among different surgical modalities and have been controversial in different studies. OBJECTIVE OF REVIEW: This study systematically reviews the available studies which reported intra-operative and post-operative complications, aiming to compare the safety of microdebrider, CO2 laser and KTP laser. TYPE OF REVIEW: Meta-analysis. SEARCH STRATEGY: Seven electronic databases (PubMed/MEDLINE, EMBASE[Ovid], Scopus, Cochrane Library and Web of Science) were searched from inception through 28 April 2022. Randomised controlled, prospective or retrospective observational studies that recorded the complications of three different surgical modalities for RRP resection were included in the meta-analysis. EVALUATION METHOD: Outcomes of interest were intra-operative and post-operative complications, and complication rate was calculated to evaluate the safety of surgical methods. RESULTS: Twenty different studies were included in quantitative synthesis. Only one study compared outcomes of those three kinds of treatment modalities simultaneously, two studies compared microdebrider and CO2 laser, and the remaining studies focussed on only one of three treatments. The weighted average complication rate for microdebrider was 0.03 (95% confidence interval [CI] 0.00-0.21), n = 6, for CO2 laser treatment was 0.16 (95% CI 0.09-0.25), n = 14 and for KTP laser treatment was 0.04 (95% CI 0.00-0.14), n = 4. CONCLUSION: The limited evidence demonstrated that CO2 lasers in the surgical treatment of RRP may lead to more surgical complications, and microdebrider and KTP lasers may be safer. However, the heterogeneous data limit any strong comparison of outcomes of different treatment of laryngeal papillomas. Future randomised controlled trials that directly compare the safety of different surgical modalities are needed.

Testing the empirical integration of threat-deprivation and harshness-unpredictability dimensional models of adversity.

Recent dimensional models of adversity informed by a neurobiological deficit framework highlights threat and deprivation as core dimensions, whereas models informed by an evolutionary, adaptational and functional framework calls attention to harshness and unpredictability. This report seeks to evaluate an integrative model of threat, deprivation, and unpredictability, drawing on the Fragile Families Study. Confirmatory factor analysis of presumed multiple indicators of each construct reveals an adequate three-factor structure of adversity. Theory-based targeted predictions of the developmental sequelae of each dimension also received empirical support, with deprivation linked to health problems and cognitive ability; threat linked to aggression; and unpredictability to substance use and sexual risk-taking. These findings lend credibility to utility of the three-dimensional integrative framework of adversity. It could thus inform development of dimensional measures of risk assessment and exploration of multidimensional adversity profiles, sensitive to individual differences in lived experiences, supporting patient-centered, strength-based approaches to services.

COVID-19 pandemic impacts on the elderly: the relationship between PPPD and prefrontal alpha rhythm.

BACKGROUND: In the COVID-19 epidemic more patients presented with persistent postural-perceptual dizziness (PPPD), but it has received little attention by the doctors in China and many patients reject psychological measurements or scales. Therefore, there is an urgent need for an objective method to diagnose and evaluate PPPD. OBJECTIVE: To investigate the effect of the COVID-19 epidemic on elderly PPPD patients and define the relationship between prefrontal alpha rhythm asymmetry (FAA) by Electroencephalography (EEG) and PPPD. METHODS: This case-control study was conducted to discuss the differences of elderly outpatients (>60 years) with PPPD during the peak period of COVID-19 in 2020 and the corresponding period in 2019, and collect the prefrontal FAA value in PPPD during COVID-19 outbreak, which were compared to its FAA in healthy control. RESULTS: Compared with the same period in 2019, the number of elderly PPPD patients during the epidemic period in 2020 increased significantly (16.4%, p = 0.000, x2 =31.802) . The left alpha wave signal power (F3) was significantly higher than the right alpha wave signal power (F4) (Z= -3.073, p = 0.002). In PPPD patients FAA were significantly lower in patients compared to control group (Z = -11.535, p = 0.000). There was a negative correlation between FAA and HAMA scores (R2 =0.906, p < 0.05) and a negative correlation between FAA and HAMD scores (R2 =0.859, p < 0.05), too. CONCLUSIONS: The increase in cases of elderly PPPD patients is most likely attributed to the mental health in older adults during the COVID-19 pandemic. Less left frontal brain activity in EEG may be related to elderly PPPD.

Idiographic and nomothetic relationships between momentary interpersonal behaviors, interpersonal complementarity, and alliance ruptures in psychotherapy.

In this study, we aimed to examine how moment-to-moment interpersonal behaviors of warmth and dominance in patients and therapists, as well as interpersonal complementarity, are related to withdrawal and confrontation ruptures as sessions unfold. Sixteen psychotherapy sessions from eight independent therapeutic dyads were sampled for the highest level of alliance ruptures from a naturalistic psychotherapy data set featuring evidence-based psychodynamic psychotherapy for patients with interpersonal problems and personality pathology. Interpersonal behaviors, complementarity, and alliance ruptures were generated every 30 s within each session. Subgrouping within group iterative multiple model estimation (S-GIMME) was used to identify an idiographic network structure for each session and examine generalizability at the nomothetic and subgroup levels. Nomothetically, patients' dominance negatively predicted therapists' dominance concurrently, but positively predicted therapists' dominance with a 30-s lag; additionally, therapists' dominance predicted their own concurrent warmth. At the subgroup level, therapists being less dominant than typical predicted more concurrent withdrawal ruptures. Idiographic modeling revealed a high degree of heterogeneity in how interpersonal behaviors are associated with ruptures. More confrontation ruptures concurrently predicted higher dominance complementarity in one subgroup. This study demonstrated the interconnection between patients' and therapists' in-session behaviors as well as the role of therapists' behaviors in momentary rupture development. This study highlights the importance of attuning and responding to individualized, momentary therapeutic contexts in navigating ruptures, and emphasizes the value of idiographic relational network approaches to aid in psychotherapy research and case conceptualization. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Experiment-Based Interventions to Diabetic Retinopathy: Present and Advances.

Diabetic retinopathy is the major blinding disease among working-age populations, which is becoming more significant due to the growth of diabetes. The metabolic-induced oxidative and inflammatory stress leads to the insult of neovascular unit, resulting in the core pathophysiology of diabetic retinopathy. Existing therapies focus on the inflammation, oxidation, and angiogenesis phenomena of diabetic retinopathy, without effect to radically cure the disease. This review also summarizes novel therapeutic attempts for diabetic retinopathy along with their advantages and disadvantages, mainly focusing on those using cellular and genetic techniques to achieve remission on a fundamental level of disease.

Temperature-Resistant Intrinsic High Dielectric Constant Polyimides: More Flexibility of the Dipoles, Larger Permittivity of the Materials.

High dielectric constant polymers have been widely studied and concerned in modern industry, and the induction of polar groups has been confirmed to be effective for high permittivity. However, the way of connection of polar groups with the polymer backbone and the mechanism of their effect on the dielectric properties are unclear and rarely reported. In this study, three polyimides (C0-SPI, C1-SPI, and C2-SPI) with the same rigid backbone and different linking groups to the dipoles were designed and synthesized. With their rigid structure, all of the polyimides show excellent thermal stability. With the increase in the flexibility of linking groups, the dielectric constant of C0-SPI, C1-SPI, and C2-SPI enhanced in turn, showing values of 5.6, 6.0, and 6.5 at 100 Hz, respectively. Further studies have shown that the flexibility of polar groups affected the dipole polarization, which was positively related to the dielectric constant. Based on their high permittivity and high temperature resistance, the polyimides exhibited outstanding energy storage capacity even at 200 °C. This discovery reveals the behavior of the dipoles in polymers, providing an effective strategy for the design of high dielectric constant materials.

Dosimetric feasibility of stereotactic ablative radiotherapy in pulmonary vein isolation for atrial fibrillation using intensity-modulated proton therapy.

PURPOSE: To evaluate dosimetric properties of intensity-modulated proton therapy (IMPT) for simulated treatment planning in patients with atrial fibrillation (AF) targeting left atrial-pulmonary vein junction (LA-PVJ), in comparison with volumetric-modulated arc therapy (VMAT) and helical tomotherapy (TOMO). METHODS: Ten thoracic 4D-CT scans with respiratory motion and one with cardiac motion were used for the study. Ten respiratory 4D-CTs were planned with VMAT, TOMO, and IMPT for simulated AF. Targets at the LA-PVJ were defined as wide-area circumferential ablation line. A single fraction of 25 Gy was prescribed to all plans. The interplay effects from cardiac motion were evaluated based on the cardiac 4D-CT scan. Dose-volume histograms (DVHs) of the ITV and normal tissues were compared. Statistical analysis was evaluated via one-way Repeated-Measures ANOVA and Friedman's test with Bonferroni's multiple comparisons test. RESULTS: The median volume of ITV was 8.72cc. All plans had adequate target coverage (V23.75Gy  ≥ 99%). Compared with VMAT and TOMO, IMPT resulted in significantly lower dose of most normal tissues. For VMAT, TOMO, and IMPT plans, Dmean of the whole heart was 5.52 ± 0.90 Gy, 5.89 ± 0.78 Gy, and 3.01 ± 0.57 Gy (P < 0.001), mean dose of pericardium was 4.74 ± 0.76 Gy, 4.98 ± 0.62 Gy, and 2.59 ± 0.44 Gy (P < 0.001), and D0.03cc of left circumflex artery (LCX) was 13.96 ± 5.45 Gy, 14.34 ± 5.91 Gy, and 8.43 ± 7.24 Gy (P < 0.001), respectively. However, no significant advantage for one technique over the others was observed when examining the D0.03cc of esophagus and main bronchi. CONCLUSIONS: IMPT targeting LA-PVJ for patients with AF has high potential to reduce dose to surrounding tissues compared to VMAT or TOMO. Motion mitigation techniques are critical for a particle-therapy approach.

Use of Composites in Analysis of Individual Time Series: Implications for Person-Specific Dynamic Parameters.

Psychology has seen an increase in the study of intra-individual processes through time series. Although timely and relevant, modeling variance from unique sources in time series may lead to model non-convergence, making it tempting to reduce the number of parameters in the model. The purpose of this paper was to investigate use of composite scores in analysis of individual time series. To meet this goal, we compared the dynamic factor analysis (DFA) model using multiple indicators with the autoregressive (AR) and autoregressive + white noise (AR + WN) models using composites. We conducted a Monte Carlo study in which a DFA(1,1) model was used to generate the data with varying conditions of size of factor loadings, number of indicators, size of AR parameters, and time series length. We also conducted analysis of empirical data from six individuals' daily self-reports of mood. Findings indicated that the DFA(1,1) and AR(1) + WN models performed comparably in their recovery of AR parameters, while the AR(1) model underestimated the parameter under nearly all conditions. However, variability of estimates may make the AR(1) + WN model less viable for researchers conducting individual-level analyses when the true data-generating mechanism is the DFA(1, 1) model.