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The serotonin transporter (SERT) is a member of the Solute Carrier 6 (SLC6) family and is responsible for maintaining the appropriate level of serotonin in the brain. Dysfunction of SERT has been linked to several neuropsychiatric disorders, including depression, anxiety and obsessive-compulsive disorder. Therefore, an in-depth understanding of the mechanism on an atomistic level, coupled with a quantification of transporter dynamics and the associated free energies is required. Here, we constructed Markov state models (MSMs) from extensive unbiased molecular dynamics simulations to quantify the free energy profile of serotonin (5HT) triggered SERT occlusion and explored the driving forces of the mechanism of occlusion. Our results reveal that SERT occludes via multiple intermediate conformations and show that the motion of occlusion is energetically downhill for the 5HT-bound transporter. Force distribution analyses show that the interactions of 5HT with the bundle domain are crucial. During occlusion, attractive forces steadily increase and pull on the bundle domain, which leads to SERT occlusion. Some interactions become repulsive upon full occlusion, suggesting that SERT creates pressure on 5HT to promote its movement towards the cytosol.
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Simulação de Dinâmica Molecular , Proteínas da Membrana Plasmática de Transporte de Serotonina , Serotonina , Proteínas da Membrana Plasmática de Transporte de Serotonina/metabolismo , Humanos , Serotonina/metabolismo , Cadeias de MarkovRESUMO
Extensive studies have demonstrated the restricting effect of past and present drought conditions on vegetation growth over the past three decades. However, the underlying mechanism of the impact of prior drought on vegetation growth - along with the magnitude of its impact over the rest of the 21st century - remains uncertain. Herein, we examined the evolution and characteristics of global vegetation growth and drought for both baseline (1982-2014) and future (2015-2100) periods under four representative pathways using the gross primary productivity (GPP) and the Standardized Precipitation Evapotranspiration Index from the CMIP6. Further, we investigated the time-lagged effects of drought on vegetation growth and the intensity of population and economy exposure to drought by identifying drought-threatened areas under four emission scenarios. The results show that, at the end of the 21st century, the global terrestrial GPP will experience an increasing trend under four scenarios, especially in SSP5-8.5, with a growth rate of 0.032 kg C m-2/decade, which is 10 times higher than that in SSP1-2.6. From the SSP1-2.6 to the SSP5-8.5 scenario, the SPEI change rates are -0.03, -0.01, -0.017, and -0.018/decade, respectively, indicating that the intensity of global drought events will rise with increases in CO2 emissions. 28.3%, 24.7%, 30.4%, and 35% of global land exhibit downward mean time-lagged months in four scenarios, especially in the middle-high latitudes of the northern hemisphere (>45°N), indicating an advanced response of vegetation to drought. Nearly 8, 9.1, 12.9, and 11.5 billion people - valued at 94,138 (SSP1-2.6), 976,020 (SSP2-4.5), 526,595 (SSP3-7.0), and 204,728 (SSP5-8.5) billion US$, respectively - will be threatened by continuous drought. Globally, the population and economy exposure to moderate and extreme drought zones is larger, and the economic risk from extreme droughts is 8 times greater under the high emissions scenario than the low emissions scenario.
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Secas , Ecossistema , Humanos , Mudança ClimáticaRESUMO
Many computational methods have been developed to infer causality among genes using cross-sectional gene expression data, such as single-cell RNA sequencing (scRNA-seq) data. However, due to the limitations of scRNA-seq technologies, time-lagged causal relationships may be missed by existing methods. In this work, we propose a method, called causal inference with time-lagged information (CITL), to infer time-lagged causal relationships from scRNA-seq data by assessing the conditional independence between the changing and current expression levels of genes. CITL estimates the changing expression levels of genes by "RNA velocity". We demonstrate the accuracy and stability of CITL for inferring time-lagged causality on simulation data against other leading approaches. We have applied CITL to real scRNA data and inferred 878 pairs of time-lagged causal relationships. Furthermore, we showed that the number of regulatory relationships identified by CITL was significantly more than that expected by chance. We provide an R package and a command-line tool of CITL for different usage scenarios.
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Redes Reguladoras de Genes , RNA Citoplasmático Pequeno , Algoritmos , Simulação por Computador , Estudos Transversais , Perfilação da Expressão Gênica , Análise de Sequência de RNA , Análise de Célula ÚnicaRESUMO
The signal for climate change effects can be abstruse; consequently, interpretations of evidence must avoid verisimilitude, or else misattribution of causality could compromise policy decisions. Examining climatic effects on wild animal population dynamics requires ability to trap, observe or photograph and to recapture study individuals consistently. In this regard, we use 19 years of data (1994-2012), detailing the life histories on 1179 individual European badgers over 3288 (re-) trapping events, to test whether trapping efficiency was associated with season, weather variables (both contemporaneous and time lagged), body-condition index (BCI) and trapping efficiency (TE). PCA factor loadings demonstrated that TE was affected significantly by temperature and precipitation, as well as time lags in these variables. From multi-model inference, BCI was the principal driver of TE, where badgers in good condition were less likely to be trapped. Our analyses exposed that this was enacted mechanistically via weather variables driving BCI, affecting TE. Notably, the very conditions that militated for poor trapping success have been associated with actual survival and population abundance benefits in badgers. Using these findings to parameterize simulations, projecting best-/worst-case scenario weather conditions and BCI resulted in 8.6% ± 4.9 SD difference in seasonal TE, leading to a potential 55.0% population abundance under-estimation under the worst-case scenario; 38.6% over-estimation under the best case. Interestingly, simulations revealed that while any single trapping session might prove misrepresentative of the true population abundance, due to weather effects, prolonging capture-mark-recapture studies under sub-optimal conditions decreased the accuracy of population estimates significantly. We also use these projection scenarios to explore how weather could impact government-led trapping of badgers in the UK, in relation to TB management. We conclude that population monitoring must be calibrated against the likelihood that weather conditions could be altering trap success directly, and therefore biasing model design.
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Mudança Climática , Mustelidae/fisiologia , Animais , Inglaterra , Comportamento Alimentar , Feminino , Masculino , Modelos Biológicos , Dinâmica Populacional , Estações do Ano , Tempo (Meteorologia)RESUMO
The Brazilian Atlantic Forest hosts one of the world's most diverse and threatened tropical forest biota. In many ways, its history of degradation describes the fate experienced by tropical forests around the world. After five centuries of human expansion, most Atlantic Forest landscapes are archipelagos of small forest fragments surrounded by open-habitat matrices. This 'natural laboratory' has contributed to a better understanding of the evolutionary history and ecology of tropical forests and to determining the extent to which this irreplaceable biota is susceptible to major human disturbances. We share some of the major findings with respect to the responses of tropical forests to human disturbances across multiple biological levels and spatial scales and discuss some of the conservation initiatives adopted in the past decade. First, we provide a short description of the Atlantic Forest biota and its historical degradation. Secondly, we offer conceptual models describing major shifts experienced by tree assemblages at local scales and discuss landscape ecological processes that can help to maintain this biota at larger scales. We also examine potential plant responses to climate change. Finally, we propose a research agenda to improve the conservation value of human-modified landscapes and safeguard the biological heritage of tropical forests.
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Conservação dos Recursos Naturais/métodos , Ecossistema , Florestas , Oceano Atlântico , Brasil , Mudança ClimáticaRESUMO
BACKGROUND: A diagnostic criterion for Major Depressive Disorder (MDD) is difficulty concentrating and increased distractibility. One form of distraction that occurs in everyday life is mind-wandering. The current study aims to test how individuals with MDD and healthy controls differ in their mind-wandering in everyday life. METHODS: Adults diagnosed with MDD (n = 53) and healthy controls (n = 53) completed a week of experience sampling, with prompts administered up to eight times per day. At each prompt, participants reported the occurrence and characteristics of their mind-wandering. They also reported levels of momentary negative affect (NA), positive affect (PA), and rumination. RESULTS: MDD participants reported mind-wandering almost twice as often as healthy control participants. Compared to healthy participants, MDD participants rated their mind-wandering as more negative, but did not differ in terms of temporal orientation. Higher NA and lower PA predicted mind-wandering in the MDD group but not healthy controls, even after controlling for rumination. Time-lagged analyses revealed that current mind-wandering predicted future levels of PA in MDD participants but not in healthy controls; in contrast, current NA and PA did not predict future mind-wandering. LIMITATIONS: Limitations include our examination of specific forms of mind-wandering (i.e., we did not sample the full spectrum of this construct). CONCLUSIONS: Individuals with MDD frequently report engaging in mind-wandering in everyday life, and this appears to be coupled with affect. Mind-wandering may have maladaptive effects in MDD and could serve as a target for intervention.
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Afeto , Atenção , Transtorno Depressivo Maior , Avaliação Momentânea Ecológica , Humanos , Transtorno Depressivo Maior/psicologia , Feminino , Masculino , Adulto , Pessoa de Meia-Idade , Ruminação Cognitiva/fisiologia , Adulto Jovem , Pensamento/fisiologia , Estudos de Casos e ControlesRESUMO
As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies.
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BACKGROUND: Dengue fever is a tropical disease and a major public health concern, and almost half of the world's population lives in areas at risk of contracting this disease. Climate change is identified by WHO and other international health authorities as one of the primary factors that contribute to the rapid spread of dengue fever. METHODS: We evaluated the effect of sanitation on the cross-correlation between rainfall and the first symptoms of dengue in the city of Mato Grosso do Sul, which is in a state in the Midwest region of Brazil, and employed the time-lagged detrended cross-correlation analysis (DCCAC) method. RESULTS: Co-movements were obtained through the time-phased DCCAC to analyze the effects of climatic variables on arboviruses. The use of a time-lag analysis was more robust than DCCAC without lag to present the behavior of dengue cases in relation to accumulated precipitation. Our results show that the cross-correlation between rain and dengue increased as the city implemented actions to improve basic sanitation in the city. CONCLUSION: With climate change and the increase in the global average temperature, mosquitoes are advancing beyond the tropics, and our results show that cities with improved sanitation have a high correlation between dengue and annual precipitation. Public prevention and control policies can be targeted according to the period of time and the degree of correlation calculated to structure vector control and prevention work in places where sanitation conditions are adequate.
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Dengue , Animais , Humanos , Dengue/epidemiologia , Saneamento , Mosquitos Vetores , Chuva , Temperatura , IncidênciaRESUMO
Background: Food craving relates to unhealthy eating behaviors such as overeating or binge eating and is thus a promising target for digital interventions. Yet, craving varies strongly across the day and is more likely in some contexts (external, internal) than in others. Prediction of food cravings ahead of time would enable preventive interventions. Objective: The objective of this study was to investigate whether upcoming food cravings could be detected and predicted from passive smartphone sensor data (excluding geolocation information) without the need for repeated questionnaires. Methods: Momentary food craving ratings, given six times a day for 14â days by 56 participants, served as the dependent variable. Predictor variables were environmental noise, light, device movement, screen activity, notifications, and time of the day recorded from 150 to 30â min prior to these ratings. Results: Individual high vs. low craving ratings could be predicted on the test set with a mean area under the curve (AUC) of 0.78. This outperformed a baseline model trained on past craving values in 85% of participants by 14%. Yet, this AUC value is likely the upper bound and needs to be independently validated with longer data sets that allow a split into training, validation, and test sets. Conclusions: Craving states can be forecast from external and internal circumstances as these can be measured through smartphone sensors or usage patterns in most participants. This would allow for just-in-time adaptive interventions based on passive data collection and hence with minimal participant burden.
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Research on environmental exposure and its impacts on people's mood has attracted increasing attention. Most studies focus on the spatiality of geographic contexts, but they neglect the influence of temporality in the relationships between environments and mood. To this end, a survey was conducted in January 2019 in Guangzhou, China, and measured data (micro-environments, built environments, EMA records, GPS trajectories, and activity logs) covering a weekday were collected from 125 participants. Then, multiple linear regression models are employed to examine and compare the associations between environments and mood based on three possible types of temporal responses (cumulative response, momentary response, and time-lagged response). The results indicate that there are great differences in environmental mood effects based on different types of temporal responses. Specifically, (i) for three types of temporal responses, exposure to PM2.5 and noise have mood-blunting effects, whereas exposure to green spaces has mood-augmenting effects. (ii) For two types of temporal responses, higher temperature (in winter) may positively influence individual mood based on cumulative and time-lagged response, and higher POI density can positively affect mood based on cumulative and momentary response. (iii) Relative humidity may not have time-related effects on mood. Although all three types of temporal responses are observed in this study, the most significant manifestation is momentary response. These findings not only enrich theoretical research on environmental mood effects and temporality, but also inform the practice of more refined and humanistic urban planning, environmental governance, and public services.
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Conservação dos Recursos Naturais , Política Ambiental , Humanos , Afeto , Exposição Ambiental/efeitos adversos , Inquéritos e QuestionáriosRESUMO
BACKGROUND: Impulsivity is a prominent feature of bipolar disorder associated with various negative sequelae; moreover, it may be a precursor to shifts in affect or mood, but little is known about its association with affect on a day-to-day timescale. Ecological momentary assessments (a method that captures moment-to-moment ratings of psychological states by repeatedly sampling the same individual) of impulsivity and affect using mobile surveys allow for more nuanced examination of mechanisms of mood and behavior dysregulation. However, few existing studies have validated an ecological momentary assessment of impulsivity in bipolar disorder and examined its time-lagged associations with positive and negative affect. 70 participants with bipolar disorder and 102 healthy comparisons participated in an intensive longitudinal study: they underwent 14 days of ecological momentary assessment data collection annually for 1-4 years. Multiple measures of impulsivity and affect were collected using self-report, behavioral, and ecological momentary assessment modalities; these measures were compared, and levels of impulsivity were compared between bipolar disorder and healthy comparison groups. Time-lagged analyses using daily means explored the next-day predictive relationship of impulsivity on positive/negative affect, and vice versa. RESULTS: The ecological momentary measure of impulsivity was moderately correlated with the self-report but not behavioral impulsivity measure. Bipolar disorder participants evinced higher self-report, behavioral, and daily impulsivity than healthy comparison participants. Time-lagged analyses revealed a bi-directional association between high impulsivity and high next-day negative (but not positive) affect. Post hoc analyses showed that impulsivity specifically predicted next-day anger and anxiety. CONCLUSIONS: Our multimodal assessment of impulsivity allowed for an examination of the day-to-day course of impulsivity and affect, crucial steps toward understanding the mechanisms of mood symptom and episode onset in bipolar disorder.
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OBJECTIVES: There is limited evidence of a temporal relationship between periodontal diseases and self-perceived general health. To plug this knowledge gap, we aimed to assess how periodontal health affects future self-rated health (SRH). METHODS: We collected data from five waves of an annual nationwide Japanese survey of dental patients from 2015 to 2019. The analysis of repeated measurements included 9306 observations from 4242 patients aged 20 years or older. The clinical periodontitis measurements were bleeding on probing, deepest periodontal pocket depth and most severe clinical attachment loss (CAL). We used a self-administered questionnaire to collect data on sociodemographic characteristics, diabetes history, health behaviour, SRH and self-reported periodontitis. We applied 2-level ordered logistic regression models for repeated measurements to examine the relationships between SRH (time t) and 1-year-lagged periodontal health (time t-1) after adjusting for covariates. RESULTS: The percentage of SRH responses recorded at time t as 'good', 'moderate' and 'poor' were 36.9%, 52.4% and 10.7%, respectively. Multivariate analyses showed that the risk of poorer SRH at time t increased in patients with CAL ≥7 mm (odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.02-1.30), those who reported bleeding gums (OR = 1.33, 95% CI = 1.21-1.46) and those who perceived swollen gums (OR = 1.40, 95% CI = 1.26-1.56) at time t-1. Sensitivity analyses using the 4-year follow-up model and 3-year-lagged cohort model also showed consistent results. CONCLUSION: Periodontitis shows a gradual contribution to future SRH in dental patients, even after adjusting for sociodemographic characteristics, general health and health-related behaviours.
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Nível de Saúde , Estudos de Coortes , Humanos , Modelos Logísticos , Razão de Chances , Autorrelato , Inquéritos e QuestionáriosRESUMO
OBJECTIVES: Prior research has linked subjective features of social situations with short-term changes in affect (e.g., across days, hours), but little is known about the directionality of such links. Our study examined the concurrent and lead-lag relationships between social contact satisfaction and affect in the flow of daily life. METHOD: Using ecological momentary assessment (EMA), wherein 78 late-middle-aged and older adults reported on 2,739 social contacts (average 5.02 per day, SD = 2.95) across seven consecutive days, we examined how the level of social contact satisfaction was concurrently and prospectively associated with affect (high-arousal and low-arousal positive affect [PA], high-arousal and low-arousal negative affect [NA]). RESULTS: Higher contact satisfaction was concurrently associated with more high- and low-arousal PA and less high- and low-arousal NA. The influence of contact satisfaction remains for predicting greater low-arousal PA (quietness, calmness) during the next social contact. NA (either high- or low-arousal) predicted lower satisfaction during the next social contact, but such sustainable influence was not observed for PA. DISCUSSION: The study reveals a cycle in which elevated NA may trigger unsatisfactory social contact, which subsequently predicted less low-arousal PA such as quietness and calmness. Our study provided a more nuanced and differentiated picture of the temporal sequencing of everyday social contact and momentary affect. Practitioners may gain insights from our study into the development of just-in-time adaptive interventions that aim for the betterment of affective well-being in old age.
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Afeto , Satisfação Pessoal , Interação Social , Sintomas Afetivos , Idoso , Nível de Alerta , Controle Comportamental , Avaliação Momentânea Ecológica , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Otimismo , Ajustamento Social , Habilidades SociaisRESUMO
Impact of direct heat stress (HS) on genetic parameter estimates, i.e., HS close to the trait recording date, was verified in several previous studies conducted in dairy and beef cattle populations. The aim of the present study was to analyze the impact of time-lagged HS at different recording periods during late pregnancy (a.p.) and postpartum (p.p.) on genetic parameter estimates for birth weight (BWT) and weight gain traits (200 d- and 365 d-weight gain (200dg, 365dg)) in offspring of the dual-purpose cattle breed "Rotes Höhenvieh" (RHV). Furthermore, we estimated genetic correlations within traits across time-lagged climatic indicators, in order to proof possible genotype by environment interactions (G×E). Trait recording included 5,434 observations for BWT, 3,679 observations for 200dg and 2,998 observations for 365dg. Time-lagged climatic descriptors were classes for the mean temperature humidity index (mTHI) and number of HS days (nHS) from the following periods: 7 d-period a.p. (BWT), 56 d-period a.p., and 56 d-period p.p. (200dg and 365dg). Genetic parameters were estimated via 2-trait animal models, i.e., defining the same trait in different climatic environments as different traits. Genetic variances and heritabilities for all traits increased with increasing mTHI- and nHS-classes for all recording periods, indicating pronounced genetic differentiation with regard to time-lagged in utero HS and HS directly after birth. Similarly, in low mTHI- and nHS-classes indicating cold stress, genetic variances, and heritabilities were larger than for temperate climates. Genetic correlations substantially smaller than 0.80 indicating G × E were observed when considering same traits from mTHI- and nHS-classes in greater distance. Estimated breeding values (EBV) of the 10 most influential sires with the largest number of offspring records fluctuated across mTHI- and nHS-classes. Correlations between sire EBV for same traits from distant climatic classes confirmed the genetic correlation estimates. Sires displaying stable EBV with climatic alterations were also identified. Selection of those sires might contribute to improved robustness in the RHV outdoor population genetically.
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Lactação , Leite , Animais , Peso ao Nascer , Bovinos/genética , Feminino , Resposta ao Choque Térmico , Modelos Genéticos , Fenótipo , Período Pós-Parto , Gravidez , Aumento de Peso/genéticaRESUMO
Hurricanes are devastating natural disasters which dramatically modify the physical landscape and alter the socio-physical and biochemical characteristics of the environment, thus exposing the affected communities to new environmental stressors, which persist for weeks to months after the hurricane. This paper has three aims. First, it conceptualizes potential direct and indirect health effects of hurricanes and provides an overview of factors that exacerbate the health effects of hurricanes. Second, it summarizes the literature on the health impact of hurricanes. Finally, it examines the time lag between the hurricane (landfall) and the occurrence of diseases. Two major findings emerge from this paper. Hurricanes are shown to cause and exacerbate multiple diseases, and most adverse health impacts peak within six months following hurricanes. However, chronic diseases, including cardiovascular disease and mental disorders, continue to occur for years following the hurricane impact.
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Tempestades Ciclônicas , Desastres , HumanosRESUMO
Molecular dynamics simulations can now routinely access the microsecond timescale, making feasible direct sampling of ligand association events. While Markov State Model (MSM) approaches offer a useful framework for analyzing such trajectory data to gain insight into binding mechanisms, accurate modeling of ligand association pathways and kinetics must be done carefully. We describe methods and good practices for constructing MSMs of ligand binding from unbiased trajectory data and discuss how to use time-lagged independent component analysis (tICA) to build informative models, using as an example recent simulation work to model the binding of phenylalanine to the regulatory ACT domain dimer of phenylalanine hydroxylase. We describe a variety of methods for estimating association rates from MSMs and discuss how to distinguish between conformational selection and induced-fit mechanisms using MSMs. In addition, we review some examples of MSMs constructed to elucidate the mechanisms by which p53 transactivation domain (TAD) and related peptides bind the oncoprotein MDM2.
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Cadeias de Markov , Simulação de Dinâmica Molecular , Fenilalanina Hidroxilase/química , Fenilalanina/química , Proteínas Proto-Oncogênicas c-mdm2/química , Software , Proteína Supressora de Tumor p53/química , Cinética , Ligantes , Ligação Proteica , Domínios Proteicos , Estrutura Terciária de ProteínaRESUMO
Molecular simulation trajectories represent high-dimensional data. Such data can be visualized by methods of dimensionality reduction. Non-linear dimensionality reduction methods are likely to be more efficient than linear ones due to the fact that motions of atoms are non-linear. Here we test a popular non-linear t-distributed Stochastic Neighbor Embedding (t-SNE) method on analysis of trajectories of 200 ns alanine dipeptide dynamics and 208 µs Trp-cage folding and unfolding. Furthermore, we introduce a time-lagged variant of t-SNE in order to focus on rarely occurring transitions in the molecular system. This time-lagged t-SNE efficiently separates states according to distance in time. Using this method it is possible to visualize key states of studied systems (e.g., unfolded and folded protein) as well as possible kinetic traps using a two-dimensional plot. Time-lagged t-SNE is a visualization method and other applications, such as clustering and free energy modeling, must be done with caution.
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We review the TD-WGcluster (time delayed weighted edge clustering) software integrating static interaction networks with time series data in order to detect modules of nodes between which the information flows at similar time delays and intensities. The software has represented an advancement of the state of the art in the software for the identification of connected components due to its peculiarity of dealing with direct and weighted graphs, where the attributes of the physical entities represented by nodes vary over time. This chapter aims to deepen those theoretical aspects of the clustering model implemented by TD-WGcluster that may be of greater interest to the user. We show the instructions necessary to run the software through some exploratory cases and comment on the results obtained.
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Análise por Conglomerados , Algoritmos , SoftwareRESUMO
Background: Previous research has paid less attention to examine the mechanisms through which positive feedback affects employees' organizational citizenship behavior (OCB). Moreover, the use of cross-sectional data in most previous research has prevented researchers to make accurate inferences about the mediating processes between feedback and OCB. Given that, more research is required to understand the ways feedback enhances OCB. Purpose: This study sought to explain how positive feedback may affect employees' OCB. Specifically, a mediating role of organization-based self-esteem (OBSE) in linking positive feedback and OCB was examined in a three-wave time-lagged model. Method: Data were gathered from full-time employees and their supervisors from private banks in two districts of Southern Punjab (N=264). A three-wave time-lagged autoregressive mediation model was tested by using partial least squares structural equation modeling. Results: The results of time-lagged multiple linear regression analyses indicate that positive feedback predicts OBSE, which in turn partially mediates the feedback-OCB relationship. Conclusion: This study concludes that positive feedback itself is less explicative in describing its effect on employees' OCB. Other mechanisms such as OBSE can explain why positive feedback enhances OCB.
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Background: This time-lagged study delves into the impact of digitalization on job stress. Digitalization is defined as the incorporation of digital technologies into various aspects of work life, fundamentally transforming processes, interactions, and decision-making. Aim: The present research focuses on the mediating roles of job-related risk and personal risk, and the moderating effect of gender. We hypothesized that employees' aversion to risks, both in their professional and personal facets, mediates the relationship between the rapid digitalization of their work environment and the resultant job stress. Regarding gender as a moderator, recent research suggests that gender can influence the experience of workplace stress, with women often experiencing higher levels of stress than men in certain situations. This indicates that gender might also moderate the relationship between digital living, risk perception, and job-related stress. This approach allows for an examination of the ways in which digital technology adoption influences workplace stress, considering the temporally spaced data. Methods: Conducted over three waves of data collection among 795 Chinese employees, the research utilizes Hayes's Model 8, adept at revealing the dynamics of digitalization's influence in the workplace and its effects on individual well-being. Results: The study corroborates Hypothesis 1 by establishing a significant, albeit less pronounced, relationship between digital living and job stress. The findings also support Hypothesis 2 by demonstrating that both job risk and personal risk mediate this relationship. The study's results also validate Hypothesis 3, indicating that gender moderates the relationship between digital living, job risk, personal risk, and job stress. Finally, the significant interaction effects found in the study, particularly the stronger conditional negative effect of digital living on perceptions of job and personal risks for males, despite the absence of statistical significance failed to support Hypothesis 4. Implications: This study sheds light on the dynamics of job stress in the context of a digitalizing work environment. The results have important implications for designing workplace strategies and interventions that are sensitive to risk perceptions and gender differences in the digital era.