Similar Relationship Research Articles

Furofuranoid-Type Lignans and Related Phenolics from Anisacanthus virgularis (Salisb.) Nees with Promising Anticholinesterase and Anti-Ageing Properties: A Study Supported by Molecular Modelling.

Lignan phytomolecules demonstrate promising anti-Alzheimer activity by alleviating dementia and preserving nerve cells. The purpose of this work is to characterize the lignans of Anisacanthus virgularis and explore their potential anti-acetylcholinesterase and anti-ageing effects. Phytochemical investigation of A. virgularis aerial parts afforded a new furofuranoid-type lignan (1), four known structural analogues, namely pinoresinol (2), epipinoresinol (3), phillyrin (4), and pinoresinol 4-O-β-d-glucoside (5), in addition to p-methoxy-trans-methyl cinnamate (6) and 1H-indole-3-carboxaldehyde (7). The structures were established from thorough spectroscopic analyses and comparisons with the literature. Assessment of the anticholinesterase activity of the lignans 1-5 displayed noticeable enzyme inhibition of 1 (IC50 = 85.03 ± 4.26 nM) and 5 (64.47 ± 2.75 nM) but lower activity of compounds 2-4 as compared to the reference drug donepezil. These findings were further emphasized by molecular docking of 1 and 5 with acetylcholinesterase (AChE). Rapid overlay chemical similarity (ROCS) and structure-activity relationships (SAR) analysis highlighted and rationalized the anti-AD capability of these compounds. Telomerase activation testing of the same isolates revealed 1.64-, 1.66-, and 1.72-fold activations in cells treated with compounds 1, 5, and 4, respectively, compared to untreated cells. Our findings may pave the way for further investigations into the development of anti-Alzheimer and/or anti-ageing drugs from furofuranoid-type lignans.

Comparative analysis of organelle genomes provides conflicting evidence between morphological similarity and phylogenetic relationship in diatoms

Diatoms (Bacillariophyta) are abundant phytoplankton groups in marine environments, which contribute approximately 20% of global carbon fixation through photosynthesis. Moreover, diatoms exhibit the highest species diversity (approximately 18,000 diatom species) among marine photosynthetic eukaryotes, which were identified by morphological characteristics. Molecular phylogenetic analyses could shed new insights into the evolutionary relationships of diverse diatom species. Nevertheless, a comprehensive understanding of the phylogenetic relationships of diatom species still remains unclear because the available molecular data are insufficient compared with their high species diversity. Furthermore, several novel diatom species were reported from field samples with no molecular evidence. In particular, the phylogenies of diatom species constructed using organelle genomes revealed that several diatom genera are paraphyletic with high supporting values. We constructed high-resolution phylogenetic trees of diatom species using organelle genomes (plastids and mitochondria) and compared the morphologies in several paraphyletic diatom genera. Especially, the clades Nitzschia and Thalassiosira include several different diatom genera with high phylogenetic supports. Our study demonstrated that some morphological characteristics (e.g., genus characters) of several diatom genera could not represent current genus boundaries. Based on the results, we highlight the necessity for taxonomic reinvestigation. To reestablish this in diatoms, it will be essential to incorporate more genome data from a broader range of taxon samples, along with a comparison of morphological characteristics.

Origin and role of non-skeletal carbonate in coralligenous build-ups: new geobiological perspectives in biomineralization processes

Abstract. The coralligenous build-ups located on the Mediterranean shelf in front of Marzamemi (SE Sicily, Italy) represent useful natural examples to use in studying the relationship between skeletal organisms and non-skeletal components in marine bioconstructions. Coralligenous build-ups are formed in open marine systems, and their comparison with coeval bioconstructions (biostalactites) of confined environments, like submarine caves, allows depicting the complex interactions between metazoans and microbial communities in the formations of recent bioconstructions in different Mediterranean settings. In this study, two coralligenous build-ups were characterized in terms of organisms and sediments involved in their formation. The framework mainly consists of coralline algae and subordinate bryozoans and serpulids. Sponges affect the general morphology of the bioconstructions both interacting with skeletonized organisms and through bioerosion activity. The micrite or microcrystalline calcite is present in minor amounts compared to other components that form the build-ups and consists of two types: autochthonous (in situ) and allochthonous (detrital). Fine autochthonous micrite mineralized directly inside the framework cavities and shows aphanitic or peloidal fabric, produced by organomineralization processes of soft sponge tissues and microbial metabolic activity, respectively. The detrital micrite occurring inside cavities derives from external sources or erosion processes of the bioconstructions themselves. This component has been classified as organic or inorganic based on the organic matter contents deduced by UV epifluorescence. A great quantity of sponges live in cavities of the coralligenous build-ups and compete with carbonatogenic bacteria for the same cryptic spaces, limiting the production of microbialites. The sharing of a similar relationship between sponges and microbial communities by coralligenous concretion and biotic crusts of particular submarine caves suggests that this competition is not habitat-specific. On the contrary, it may develop in a range of environmental settings, from open to cryptic systems, and could be used to clarify the role of metazoans vs. microbialites in palaeoecological reconstructions.

Solvent Influence in the Synthesis of Lead(II) Complexes Containing Benzoate Derivatives

A series of lead(II) complexes incorporating benzoate derivative ligands was prepared: [Pb(2MeOBz)2]n (1), [Pb(2MeOBz)2(H2O)]n (2), [Pb2(1,4Bzdiox)4(DMSO)]n (3), [Pb(1,4Bzdiox)2(H2O)]n (4), [Pb(Pip)2(H2O)]n (5), and [Pb(Ac)(Pip)2(MeOH)]n (6) (2MeOBz: 2-methoxybenzoate; 1,4Bzdiox: 1,4-benzodioxan-5-carboxylate; DMSO: dimethylsulfoxide; Ac: acetate; Pip: piperonylate; MeOH: methanol). All compounds were characterized via elemental analysis, ATR-FTIR spectroscopy, and powder XRD. In addition, the crystal structures of some compounds were elucidated. Compounds 1 and 2, involving 2-methoxybenzoate, were closely related, only differing in the presence of one extra aqua ligand found for the latter. However, this implies key changes in the studied properties, e.g., 2 shows solid-state luminescence that displays a different color as a function of the crystal orientation, while 1 does not. The crystal structure of 2 revealed a 1D coordination polymer. A similar relationship was found between compounds 3 and 4, incorporating 1,4-benzodioxan-5-carboxylate. In this pair, only 4, with aqua ligands, displayed a greenish-yellow-color solid-state luminescence. Furthermore, two new lead(II) piperonylate complexes, 5 and 6, were obtained from the reaction between lead(II) acetate and piperonylic acid. In water, all acetate ligands in the metal precursor were displaced and [Pb(Pip)2(H2O)]n (5) was isolated, while in methanol, a mixed acetate–piperonylate complex, [Pb(Ac)(Pip)2(MeOH)]n (6), was precipitated. Considering only conventional Pb-O bonds, the crystal structure of 6 was described as a 1D coordination polymer, although, additionally, the chains were associated via tetrel bonds, defining an extended 2D architecture.

Corporate biodiversity reporting and earnings management: Does a critical mass of female directors have an impact?

This study addresses the relationship between corporate biodiversity reporting (CBR) and earnings management as well as the moderating impact of board gender diversity (BGD). Due to increased regulatory pressure, we relied on a sample of STOXX Europe 600 firms (1,537 firm-year observations) for the business years 2017–2021. In line with the moral licensing hypothesis, we assume that CBR and our two main proxies of earnings management (accruals-based and real earnings management) are positively related, and a critical mass of female directors may weaken this link. Our regression results align with these assumptions and prior research on similar relationships. Moreover, we conduct several endogeneity checks, which support our main results. This study mainly contributes to prior research as it is the first one on the link between CBR and earnings management. We stress major implications for researchers, standard setters, and business practitioners. Biodiversity represents a key sub-pillar of sustainability reporting with an impact on financial reporting, indicating the need for integrated thinking, which should be promoted in future empirical research.

Changes in Streamflow Statistics and Catchment Land Uses Across Select USGS Gages in Northwest and West‐central Arkansas

AbstractSince 1901, heavy rainfall events have increased in the United States in both intensity and frequency, and human population in the United States has increased, resulting in significant land use changes. Both trends contribute to an increase in observed flood magnitude and frequency. To determine if a relationship exists between land use/land cover and changing stream flows in northwest Arkansas, this study analyzed temporal changes in various flow statistics for 14 stream gages and compared the rates of change in flow statistics from gages on streams with watersheds that have varying land uses, i.e., urban, agricultural, and undeveloped. Mann‐Kendall analysis was used to determine statistically significant changes in flow statistics, which were then compared to National Land Cover Dataset (NLCD) watershed land uses from 2001 and 2019. All analyzed gages had one or more flow statistics with at least a moderately significant increase, and all analyzed flow statistics showed at least moderately significant streamflow increases at two or more gages (P < 0.100). There were no decreases of any significance in any flow statistic at any gage. In general, urban land development did not happen on native prairies and forests but on previously agricultural land. Significant positive relationships were found between maximum yearly flow and 2019 urban land use, urban land use change from 2001 to 2019, and 2019 Human Development Index (HDI). A similar relationship was found to exist between yearly minimum flow and 2019 HDI. These results highlight the importance of considering the cost of potential stream bank erosion and flooding in future land use planning, permitting, and zoning.

Properties of delay and queue length functions at bus stops

The literature on the relationships between delays and queue lengths as a function of the degree of saturation at road junctions is plentiful. However, little has been written about similar relationships at bus stops. In this article we show delay and queue length functions in bus stops to study their properties by using an ad-hoc simulation model. It was found that delay and queue functions at bus stops differ from that observed at road junctions. The main characteristic is that the functions increase more smoothly at bus stops than at road junctions. Therefore, in the process of designing and operating bus stops, not only the nominal capacity but also a low degree of saturation should be considered to manage congestion in the stop area. In addition, if the bus stop is located upstream of a traffic signal, the green time, and the cycle time play an important role in reducing congestion. This is relevant because on arterial roads most bus stops are close to traffic signals.

A Semi-Supervised Matrixized Graph Embedding Machine for Roller Bearing Fault Diagnosis Under Few-Labeled Samples

Exploring historical measurement data-driven health monitoring schemes for roller bearings is a current research hotspot. In engineering practice, the type of fault data obtained is often unknown and requires expensive costs to be annotated. However, most current intelligent diagnostic methods are based on the assumption that the labeled fault data is sufficient, so as to effectively establish the nonlinear mapping relationship between monitoring signals and health status. For this issue, a newly intelligent diagnosis method based on semi-supervised matrixized graph embedding machine (SMGEM) is proposed. In SMGEM, the geometric similarity relationship of unlabeled and labeled samples is obtained, which is subsequently embedded by incorporating a manifold regularization into SMGEM model, so that SMGEM can use the structure information of unlabeled samples to assist modeling. Meanwhile, a weighted nuclear norm (WNN) is used to highlight the importance of large singular values, so that a more accurate weight matrix can be constructed. The proposed method is verified by several roller bearing fault datasets, and experimental results demonstrate that the proposed semi-supervised diagnosis method can use few labeled samples to obtain a better identification accuracy.

ScCAN: Clustering With Adaptive Neighbor-Based Imputation Method for Single-Cell RNA-Seq Data.

Single-cell RNA sequencing (scRNA-seq) is widely used to study cellular heterogeneity in different samples. However, due to technical deficiencies, dropout events often result in zero gene expression values in the gene expression matrix. In this paper, we propose a new imputation method called scCAN, based on adaptive neighborhood clustering, to estimate the zero value of dropouts. Our method continuously updates cell-cell similarity information by simultaneously learning similarity relationships, clustering structures, and imposing new rank constraints on the Laplacian matrix of the similarity matrix, improving the imputation of dropout zero values. To evaluate the performance of this method, we used four simulated and eight real scRNA-seq data for downstream analyses, including cell clustering, recovered gene expression, and reconstructed cell trajectories. Our method improves the performance of the downstream analysis and is better than other imputation methods.

Associations between executive functions assessed in different contexts in a genetically informative sample.

Executive functions (EFs) are cognitive functions that help direct goal-related behavior. EFs are usually measured via behavioral tasks assessed in highly controlled laboratory settings under the supervision of a research assistant. Online versions of EF tasks are an increasingly popular alternative to in-lab testing. However, researchers do not have the same control over the testing environment during online EF assessments. To assess the extent to which EFs assessed in-lab and online are related, we used data from the Colorado Online Twin Study (CoTwins; 887 individual twins aged 13.98-19.05) and constructed an Lab Common EF factor and an Online Common EF factor from four EF tasks assessed in-lab and online. The Lab Common and Online Common EF factors were genetically identical (rA = 1.00) but phenotypically separable (r = .77, 95% confidence interval [0.59, 0.94]) indicating that these EF factors have the same genetic underpinnings but may be differentially influenced by environmental factors. We examined phenotypic, genetic, and environmental correlations between the EF factors and a general cognitive ability factor (g) assessed in the lab and found similar relationships between Lab Common EF and g and Online Common EF and g. Overall, these results suggest that Common EF factors assessed in different contexts are highly related to each other and similarly related to other cognitive outcomes. These findings indicate that online task-based EF assessments could be a viable strategy for increasing sample sizes in large-scale studies, particularly genetically informed studies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Learning Relation-Enhanced Hierarchical Solver for Math Word Problems.

Automatically solving math word problems (MWPs) is a challenging task for artificial intelligence (AI) and machine learning (ML) research, which aims to answer the problem with a mathematical expression. Many existing solutions simply model the MWP as a sequence of words, which is far from precise solving. To this end, we turn to how humans solve MWPs. Humans read the problem part-by-part and capture dependencies between words for a thorough understanding and infer the expression precisely in a goal-driven manner with knowledge. Moreover, humans can associate different MWPs to help solve the target with related experience. In this article, we present a focused study on an MWP solver by imitating such procedure. Specifically, we first propose a novel hierarchical math solver (HMS) to exploit semantics in one MWP. First, to imitate human reading habits, we propose a novel encoder to learn the semantics guided by dependencies between words following a hierarchical "word-clause-problem" paradigm. Next, we develop a goal-driven tree-based decoder with knowledge application to generate the expression. One step further, to imitate human associating different MWPs for related experience in problem-solving, we extend HMS to the Relation-enHanced Math Solver (RHMS) to utilize the relation between MWPs. First, to capture the structural similarity relation, we develop a meta-structure tool to measure the similarity based on the logical structure of MWPs and construct a graph to associate related MWPs. Then, based on the graph, we learn an improved solver to exploit related experience for higher accuracy and robustness. Finally, we conduct extensive experiments on two large datasets, which demonstrates the effectiveness of the two proposed methods and the superiority of RHMS.

Application of improved RBF neural network algorithm in hierarchical management of enterprise

Abstract The grade division of enterprises is conducive to their needs of green development, and the continuous strengthening of computer innovation technology provides an excellent platform for grading the regional management of enterprises. Owing to the differences in energy consumption, labour, land use area, GDP, etc., most of the data collected by the enterprises are unstable, and the data with a small number of samples in categories cannot be ignored. Therefore, based on the related data of basic development in a development area, Guangdong Province within the past 15 years, in this paper, according to the theory of hierarchical management in enterprise, four factors, such as land use, personnel, energy consumption and regional GDP, are used as the relevant attributes, and the grades of enterprises in this region are managed and divided. In addition, the structure of RBF neural network algorithm optimised by similarity relation matrix and the accuracy of enterprise classification under different neural network algorithms are compared. The results show that the hierarchical management of enterprises based on the improved RBF neural network algorithm has high efficiency and accuracy, which is of great significance to the green development of enterprises.

Effective Value Analysis of Fuzzy Similarity Relation in HQSS for Efficient Granulation.

Hierarchical quotient space structure (HQSS), as a typical description of granular computing (GrC), focuses on hierarchically granulating fuzzy data and mining hidden knowledge. The key step of constructing HQSS is to transform the fuzzy similarity relation into fuzzy equivalence relation. However, on one hand, the transformation process has high time complexity. On the other hand, it is difficult to mine knowledge directly from fuzzy similarity relation due to its information redundancy, i.e., sparsity of effective information. Therefore, this article mainly focuses on proposing an efficient granulation approach for constructing HQSS by quickly extracting the effective value of fuzzy similarity relation. First, the effective value and effective position of fuzzy similarity relation are defined according to whether they could be retained in fuzzy equivalence relation. Second, the number and composition of effective values are presented to confirm that which elements are effective values. Based on these above theories, redundant information and sparse effective information in fuzzy similarity relation could be completely distinguished. Next, both isomorphism and similarity between two fuzzy similarity relations are researched based on the effective value. The isomorphism between two fuzzy equivalence relations is discussed based on the effective value. Then, the algorithm with low time complexity for extracting effective values of fuzzy similarity relation is introduced. On the basis, the algorithm for constructing HQSS is presented to realize efficient granulation of fuzzy data. The proposed algorithms could accurately extract effective information from the fuzzy similarity relation and construct the same HQSS with the fuzzy equivalence relation while greatly reducing the time complexity. Finally, relevant experiments on 15 UCI datasets, 3 UKB datasets, and 5 image datasets are shown and analyzed to verify the effectiveness and efficiency of the proposed algorithm.

Radicle emergence test for cabbage can be assessed using multispectral imaging

The potential of multispectral imaging (MSI, using a VideometerLab©) to achieve automation of the assessment of radicle emergence (RE) in the RE vigour test and thereby increase the throughput of vigour testing, was examined using 12 commercial seed lots from three varieties of cabbage (Brassica oleracea L. var capitata). The RE of the 12 lots was assessed after 48 hours germination at 20°C using both MSI (MSI RE48) and a manual count. The RE counts made using MSI were highly correlated to manual counts taken by eye at the same time (r = 0.97, p < 0.001) and to RE assessments taken using RGB imaging (r = 0.84, p < 0.01). MSI RE48 was significantly related to field emergence after seven days (r = 0.87, p < 0.01) and glasshouse emergence after six days (r = 0.86, p < 0.01); similar relationships with emergence were found for the RE assessments taken using RGB imaging. Our data indicate that an automated count of RE is possible in the RE test using MSI imaging and relates to seed vigour in cabbage.

Correlation between plasma renin concentration and plasma renin activity assays on the Maglumi 800 chemiluminescence immunoassay analyzer

The ratio of plasma aldosterone concentration to plasma renin activity (PAC/PRA) is the most common screening test for primary hyperaldosteronism, but it is not standardized among laboratories. We evaluated the correlation between plasma renin concentration (PRC) and plasma renin activity (PRA), and then PAC/PRC and PAC/PRA ratios on Maglumi 800 immunoassay analyzer. Forty-five plasma samples from volunteers were collected. PRC, PRA and PAC were measured by Maglumi 800 - a fully-auto chemiluminescence immunoassay analyzer. Correlation between plasma renin concentration (PRC) and plasma renin activity (PRA), and then PAC/PRC and PAC/PRA ratios were determined by regression analysis. PRC and PRA showed a good correlation (r = 0.88). The PAC/PRC and PAC/PRA ratios have a similar relationship (r = 0.757). Because of the advantages of the procedure and the independence of PRC from endogenous angiotensinogen levels, PRC may be used preferentially over PRA as high throughput screening tool.

Adaptive instance similarity embedding for online continual learning

We study the online continual learning (CL) paradigm, where the learner must continually learn a sequence of tasks. In this setting, improving the learning ability of the model and mitigating catastrophic forgetting are two pivotal factors. Note that most existing approaches for online continual learning are based on the experience replay strategy. In this type of method, a memory buffer is applied to store a subset of previous tasks to prevent catastrophic forgetting. The samples from between the current task and the memory buffer are jointly trained to update the network parameters. Consider that most methods only generate the feature embeddings via a shared feature extractor and then train the network via cross-entropy loss. We argue that such methods fail to explore the feature embedding in its entirety and neglect the similar relations between samples, thus leading to lower discriminant performance, especially in an online learning setting. To this end, we propose the Adaptive Instance Similarity Embedding for Online Continual Learning (AISEOCL) framework, which further takes all the sample relations in a given batch into account. In detail, firstly, the experience replay strategy is used to avoid catastrophic forgetting. Then, during training, we apply the adaptive similar embedding to obtain additional valuable similar information from the current training samples composed of the current and previous tasks. Since not all samples are equally important to make a prediction, we further weigh the importance of each instance accordingly resorting to the attention mechanism. Importantly, we further impose a similarity distillation loss on the distributions of the similarity relationship between current and previous models. Such operation can transfer the similarity relationship between different samples from the old model to the current model to alleviate catastrophic forgetting. With this strategy, AISEOCL can further improve the learning ability of the model while enhancing the discriminant power, which is also beneficial to stably resist forgetting. The experiments on several existing benchmarks validate the effectiveness of our proposed approach.

Impact of ICT Sector Research and De velopment Expenditure on the Market Capitalization in the US, the EU and China

Purpose: Due to the growing global role of enterprises from the information and communication technology sector from the leading regions of the USA, EU and China in the industry, the author’s research goal was to try to identify factors influencing the value of listed enterprises understood as its stock exchange capitalization. For the purpose, research was carried out on the impact of a group of twenty-six variables on the company’s market capitalization, among which the most important conclusions concern the impact of seven variables, i.e. revenues, research and development expenses, earnings before interest, taxes, depreciation and amortization (EBITDA), earnings before interest and taxes (EBIT), total equity, total assets, total revenues and dividend rate. Design/Methodology/Approach: The study used research methods in the form of a random effects model and a fixed effects model, and then used the Hausmann test to verify which of the models is better suited to establishing the relationship between the selected independent variables and the dependent variable in the form of the stock market capitalization of companies from the ICT sector. Findings: It was found that the impact of equity or the level of revenues on market capitalization is much smaller than in the case of research and development expenses and that the issue of depreciation of assets is an important factor in the market valuation of enterprises from the ICT sector. Additionally, the level of assets and equity has, although limited, impact on the market valuation of the company, regardless of the region in which an entity operates. Revenues are important from a regionalization perspective – company’s market capitalization is the largest in the case of the ICT services subsector in China. There is no similar relationship among manufacturers of ICT devices operating in all three regions. Research limitations/Implications: Due to the fact that the COVID-19 pandemic and the global economic slowdown are important factors affecting the ICT sector, further research on the value of ICT enterprises should take the aspects into account.

Characterization of the Complete Mitochondrial Genome of Agelas nakamurai from the South China Sea.

The Agelas genus sponges are widely distributed and provide shelter for organisms that inhabit reefs. However, there is a lack of research on the genetic diversity of the Agelas sponges. Additionally, only one Agelas mitochondrial genome has been documented, leaving the characteristics of the Agelas genus's mitogenome in need of further clarification. To address this research gap, we utilized Illumina HiSeq4000 sequencing and de novo assembly to ascertain the complete mitochondrial genome of Agelas sp. specimens, sourced from the South China Sea. Our analysis of the cox1 barcoding similarity and phylogenetic relationship reveals that taxonomically, the Agelas sp. corresponds to Agelas nakamurai. The mitogenome of Agelas nakamurai is 20,885 bp in length, encoding 14 protein-coding genes, 24 transfer RNA genes, and 2 ribosomal RNA genes. Through a comparison of the mitochondrial genes, we discovered that both Agelas nakamurai and Agelas schmidti have an identical gene arrangement. Furthermore, we observed a deletion in the trnD gene and duplication and remodeling of the trnL gene in the Agelas nakamurai's mitogenome. Our evolutionary analysis also identified lineage-specific positive selection sites in the nad3 and nad5 genes of the Agelas sponges' mitogenome. These findings shed light on the gene rearrangement events and positive selection sites in the mitogenome of Agelas nakamurai, providing valuable molecular insights into the evolutionary processes of this genus.

THE RELATIONSHIP BETWEEN MOOD OF CAREGIVERS AND CARE RECIPIENTS WITH DEMENTIA

Abstract Anxiety and depression are common behavioral and psychological symptoms of dementia. Although there are many individual level factors related to their anxiety and depression, it is unknown whether caregivers’ mood influence anxiety and depression of their care recipients with dementia. Therefore, this study was conducted to examine the relationship between anxiety and depression of caregivers and that of care recipients with dementia. This study was a secondary data analysis using the National Health and Aging Trends Study (NHATS) Round 7 data and National Study of Caregiving (NSOC) III. This study used 553 dyads of older adults aged 65 years and older who had probable dementia at the time of the interview and their family caregivers. Anxiety and depression of both the caregivers and care recipients of dementia were measured with the Generalized Anxiety Disorder-2 (GAD-2) and Patient Health Questionnaire-2 (PHQ-2) respectively. Descriptive statistical analyses, chi-square tests, and logistic regression analyses were used. There were significant relationships between the caregivers’ anxiety and the care recipients’ anxiety presentation (Chi2=10.06, p< 0.01). Similar relationships were also found for depression (Chi2=5.22, p=0.02). Logistic regression analyses showed that when caregivers had anxiety or depression, it was more likely that their care recipients show anxiety (OR=2.25, p=0.002, 95% CI=1.35-3.74) or depression (OR=1.78, p=0.023, 95% CI=1.08-2.94). Because dementia caregivers’ negative mood can influence their care recipients’ mood, health care professionals should conduct early interventions for caregivers with negative moods.

APPLYING TIME-VARYING EFFECT MODELING TO EXAMINE DAILY VARIATION IN SUICIDAL IDEATION AMONG DEMENTIA CAREGIVERS

Abstract Emerging evidence suggests that caregivers may experience high rates of suicidal ideation. However, relatively little is known about daily contextual factors, including day-to-day depression and anxiety-related symptoms, that increase the severity of suicidal ideation over time. The purpose of this study was to apply time-varying effect modeling (TVEM) to examine daily depression and anxiety symptoms leading up to an individual’s highest suicidal ideation score within a span of 14 days in a sample of community-dwelling ADRD caregivers. The intercept-only model revealed an increase in the mean scores of daily suicidal ideation four days leading up to an individual’s highest score. Additionally, there was a significant decrease four days after the highest suicidal ideation point. The relationship between depression and daily suicidal ideation was significant 1-day leading up to the highest suicidal ideation score. Similar relationships were observed with daily anxiety as a time-varying predictor in a separate model. The results from this study suggest that suicidal ideation can vary between days, with depression and anxiety influencing the intensity of the slope leading to and following an individual’s highest suicidal ideation score. Examining suicidal ideation trajectories over time and factors associated with varying severity can help inform targeted interventions to support dementia caregivers and mitigate the risk of severe psychological distress associated with dementia caregiving.