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Life satisfaction is vital for older adults' well‐being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of life satisfaction among older adults in China using longitudinal data from the China Health and Retirement Longitudinal Study. Latent class growth modeling and growth mixture modeling were employed to identify distinct trajectories of life satisfaction. Machine learning (ML) models were developed to predict different trajectories and identify important predictors of different trajectories. Four distinct trajectories of life satisfaction were identified, showcasing nuanced patterns of life satisfaction that changed over time. ML models, especially random forest, effectively predicted these trajectories. Emotional experiences (particularly the frequency of happiness and loneliness), body mass index, and self‐report health emerged as significant predictors of different life satisfaction trajectories. Our finding revealed the importance of focusing on individuals or groups with consistently low life satisfaction and paying more attention to mental and physical health predictors. Our models might guide future targeted preventative treatments. [ABSTRACT FROM AUTHOR]

Drug-induced sleep endoscopy (DISE) is used for evaluating upper airway anatomy and determining airway obstruction patterns. It is typically performed with the patient in the supine position. Airway collapse severity is influenced by body position and level of consciousness; the resultant dynamic changes may vary across patients. In this study, we evaluated the severity of upper airway collapse through awake endoscopy and DISE and identified factors affecting the pattern of airway collapse severity. This study included 66 patients with obstructive sleep apnea. The patients underwent type 1 polysomnography, tongue strength assessment, awake endoscopy in the sitting and supine positions, and DISE. Group-based trajectory modeling was performed to identify patients with different collapse severity patterns in different body positions and at different levels of consciousness. Patient with similar severity trajectory were assigned to the same group. Two different severity trajectories (group 1 and group 2) were identified at the tongue base level. Tongue depression strength varied significantly between groups 1 and 2 (47.00 vs. 35.00 kPa; P =.047). During awake endoscopy, collapse severity was significantly higher in group 2 than in group 1. Group 1 had lower rapid eye movement/nonrapid eye movement apnea–hypopnea index ratios and higher tongue depression strength than did group 2. In patients with obstructive sleep apnea, tongue strength may vary depending on body position. Our results should be interpreted with caution because of the limited sample size. Future studies should investigate the effect of oropharyngeal rehabilitation on tongue strength and collapse severity. [ABSTRACT FROM AUTHOR]

Background: Although it is well established that obesity is a risk factor for hypertension, the effect of distinct long-term patterns of body mass index (BMI) on blood pressure (BP) in later life is poorly understood. Methods: Based on the China Health and Nutrition Survey, we analyzed 2920 participants aged 3–17 years with initial normal BP at baseline (1991–2011), who were followed up for the development of hypertension (1993–2015). The group-based trajectory model was applied to identify BMI trajectories, and Cox regression was used to assess their associations with hypertension risk. Stratified analyses were conducted to explore differences across subgroups. Results: During an average follow-up time of 11.20 (7.69) years for males and 7.20 (5.21) years for females, 339 males and 212 females were identified with hypertension, respectively. Three BMI trajectories were identified: low-increasing (60.58% of males and 73.03% of females), moderate-increasing (33.08% of males and 24.22% of females), and high-increasing (6.34% of males and 2.76% of females). Our study found a significant positive association between a higher BMI trajectory and hypertension risk in males (all P for trend < 0.05). Specifically, males in the high-increasing BMI group had a higher risk of hypertension compared with those in the low-increasing group (HR = 1.76, 95% CI: 1.04–2.97). Stratified analyses revealed stronger associations among smokers, drinkers, and inactive individuals. Conclusion: Our findings suggest that maintaining a normal BMI and healthy lifestyle from childhood may lower subsequent risk of hypertension. [ABSTRACT FROM AUTHOR]

Background: Trajectories of asthma and allergy in children are heterogeneous and commonly derived from parental report of disease or clinical records. This study combined parental‐reported and register‐based dispensed medication data to characterize childhood trajectories of co‐existing asthma, allergic rhinitis, and eczema. Methods: From a Swedish population‐based birth cohort (N = 5654), survey responses collected at the age of 1, 4.5, 8, and 12 years were linked to dispensed medication register data for the period of 2–13 years. Trajectories were identified with latent class analysis. Statistical metrics and clinical interpretability guided the model selection. Results: Nine distinct trajectories were identified: three asthma‐dominated (early‐onset remitting [n = 189, 3.3%], late‐onset [n = 117, 2.1%], and persistent [n = 149, 2.6%]), two eczema‐dominated (persistent [n = 190, 3.4%] and remitting [n = 432, 7.6%]), one allergic rhinitis‐dominated (late‐onset [n = 259, 4.6%]), two multimorbidity (mid‐childhood asthma and late‐onset allergic rhinitis [n = 144, 2.5%], and persistent eczema and late‐onset allergic rhinitis [n = 90, 1.6%]), and one low‐disease burden trajectory (n = 4084, 72.2%). Differences were seen across the trajectories in the proportion of parental report of disease and dispensed medication as well as by class and quantity of medication dispensed. Conclusion: Combined parental‐reported and dispensed medication data enriches characterization of longitudinal trajectories of asthma and allergy in children by merging subjective experience of disease with healthcare utilization. The identified trajectories were characterized by distinct disease development and prescription patterns suggesting clinically differential morbidity burden. [ABSTRACT FROM AUTHOR]

Background: The relationship between the dynamic changes in insulin resistance (IR) and the prognosis of septic patients remains unclear. This study aims to investigate the correlation between the clinical subphenotype of IR represented by the triglyceride-glucose (TyG) index trajectory and the mortality rate among patients with sepsis. Methods: In this retrospective cohort study, we utilized data from septic patients within the Medical Information Mart for Intensive Care (MIMIC)-IV database version 2.0 to construct trajectories of the TyG index over 72 h. Subsequently, we computed the similarity among various TyG index trajectories with the dynamic time warping (DTW) algorithm and utilized the hierarchical clustering (HC) algorithm to demarcate distinct cluster and identified subphenotypes according to the trajectory trend. Subsequently, we assessed the mortality risk between different subphenotypes using analyses such as survival analysis and validated the robustness of the results through propensity score matching (PSM) and various models. Results: A total of 2350 patients were included in the study. Two trajectory trends: TyG index decreasing (n = 926) and TyG index increasing (n = 1424) were identified, which indicated corresponding to the clinical subphenotype of increased and alleviative IR respectively. The 28-day and in-hospital mortality for the increased IR group was 28.51% and 25.49% respectively. In comparison, patients in the alleviative IR group with a 28-day mortality of 23.54% and an in-hospital mortality of 21.60%. These subphenotypes exhibited distinct prognosis, time dependent Cox model showed the increased IR group with a higher 28-day mortality [hazard ratio (HR): 1.07, 95% confidence interval (CI): 1.02–1.12, P = 0.01] and in-hospital mortality [HR: 1.05, 95% CI: 1.00–1.11, P = 0.045] compared to the alleviative IR group. Sensitivity analyses with various models further validated the robustness of our findings. Conclusion: Dynamic increase in the TyG index trajectory is associated with elevated mortality risk among patients with sepsis, which suggests that dynamic increased IR exacerbates the risk of poor outcomes in patients. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to measure trajectories of craving for methamphetamine during the course of pharmacotherapy trials for methamphetamine use disorder. Design, setting and participants: Craving trajectories were identified using Group‐Based Trajectory Modeling. The association of craving trajectories with drug use trajectories was examined using a dual trajectory model. Association of craving trajectories with other health and social outcomes was also examined. The study used pooled data from five randomized controlled pharmacotherapy trials for methamphetamine use disorder. A total of 866 adults with methamphetamine use disorder participated in randomized controlled pharmacotherapy trials. Measurement: Craving was assessed weekly using the Brief Substance Craving Scale. Drug use was assessed using urine toxicology. Alcohol‐ and drug‐related problems, as well as psychiatric, medical, legal, employment and relationship problems, were measured using the Addiction Severity Index. Findings: A three‐trajectory model with high, medium and low craving trajectories was selected as the most parsimonious model. Craving trajectories were associated with methamphetamine use trajectories in the course of trial; 88.4% of those in the high craving trajectory group had a consistently high frequency of methamphetamine use compared with 18.7% of those in the low craving group. High craving was also associated with less improvement in most other outcomes and higher rate of dropout from treatment. In turn, low craving was associated with a rapidly decreasing frequency of methamphetamine use, greater improvement in most other outcomes and a lower rate of dropout. Participants on modafinil daily and ondansetron 1 mg twice daily were less likely to be in the high craving group compared with those on placebo. Conclusions: Trajectories of methamphetamine craving in the course of clinical trials for methamphetamine use disorder appear to be both highly variable and strongly associated with greater frequency of drug use, other drug‐related outcomes and dropout from trials. Two medications, modafinil daily and ondansetron at a dose of 1 mg two times daily, appear to be associated with greater reduction in craving in the course of treatment compared with placebo. A decrease in methamphetamine craving shows promise as an early indicator of recovery from methamphetamine use disorder. [ABSTRACT FROM AUTHOR]

Ambient PM2.5 samples were collected in Laiwu, a small industrial city in China known for steel production, to measure and evaluate the mass concentrations of PM2.5 and the inorganic water-soluble ions (IWS ions). The highest PM2.5 value recorded was 251.28 μg/m3, which occurred during winter and was lower than other major Chinese cities. The spatial distribution showed that the center of the city, which is connected to the downtown area, was heavily polluted (170 μg/m3 higher) compared to the suburbs. With the exception of winter, the weight of PM2.5 was dominated by IWS ions, with three secondary ions (NO3-, SO42-, and NH4+) accounting for more than 70% of the total ions in mass. This percentage is higher than that of big cities. An increase in sulfur oxidation ratios (SOR), nitrogen oxidation rate (NOR), and anion equivalent/cation equivalent (AE/CE) indicated that the atmosphere in Laiwu was more oxidized than other big cities. The ion analysis revealed that PM2.5 was highly correlated with NO3-, SO42-, and NH4+. The principal component analysis indicated that district heating during winter and industrial output and secondary transformation during summer were the major sources of the water-soluble ions. The backward trajectory study identified the north of Shandong Province as the likely source-area that affected air quality in Laiwu. [ABSTRACT FROM AUTHOR]

Summary: Key predictors of three trajectory group membership of potentially preventable hospitalisations were age, the number of comorbidities, the presence of chronic obstructive pulmonary disease and congestive heart failure, and frailty risk at the occurrence of hip fracture. These predictors of their trajectory group could be used in targeting prevention strategies. Purpose: Although older adults with hip fracture have a higher risk of multiple readmissions after index hospitalisation, little is known about potentially preventable hospitalisations (PPH) after discharge. This study examined group-based trajectories of PPH during a five-year period after a hip fracture among older adults and identified factors predictive of their trajectory group membership. Methods: This retrospective cohort study was conducted using linked hospitalisation and mortality data in New South Wales, Australia, between 2013 and 2021. Patients aged ≥ 65 years who were admitted after a hip fracture and discharged between 2014 and 2016 were identified. Group-based trajectory models were derived based on the number of subsequent PPH following the index hospitalisation. Multinominal logistic regression examined factors predictive of trajectory group membership. Results: Three PPH trajectory groups were revealed among 17,591 patients: no PPH (89.5%), low PPH (10.0%), and high PPH (0.4%). Key predictors of PPH trajectory group membership were age, number of comorbidities, dementia, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), frailty risk, place of incident, surgery, rehabilitation, and length of hospital stay. The high PPH had a higher proportion of patients with ≥ 2 comorbidities (OR: 1.86, 95% confidence interval (CI): 1.04–3.32) and COPD (OR: 2.97, 95%CIs: 1.76–5.04) than the low PPH, and the low and high PPHs were more likely to have CHF and high frailty risk as well as ≥ 2 comorbidities and COPD than the no PPH. Conclusions: Identifying trajectories of PPH after a hip fracture and factors predictive of trajectory group membership could be used to target strategies to reduce multiple readmissions. [ABSTRACT FROM AUTHOR]

Background Frailty is a dynamic syndrome characterized by reduced physiological reserve to maintain homeostasis. Prospective studies have reported frailty worsening in women with breast cancer during chemotherapy, with improvements following treatment. We evaluated whether the Faurot frailty index, a validated claims-based frailty measure, could identify changes in frailty during chemotherapy treatment and identified predictors of trajectory patterns. Methods We included women (65+ years) with stage I-III breast cancer undergoing adjuvant chemotherapy in the SEER-Medicare database (2003-2019). We estimated the Faurot frailty index (range: 0-1; higher scores indicate greater frailty) at chemotherapy initiation, 4 months postinitiation, and 10 months postinitiation. Changes in frailty were compared to a matched noncancer comparator cohort. We identified patterns of frailty trajectories during the year following chemotherapy initiation using K-means clustering. Results Twenty-one thousand five hundred and ninety-nine women initiated adjuvant chemotherapy. Mean claims-based frailty increased from 0.037 at initiation to 0.055 4 months postchemotherapy initiation and fell to 0.049 10 months postinitiation. Noncancer comparators experienced a small increase in claims-based frailty over time (0.055-0.062). We identified 6 trajectory patterns: a robust group (78%), 2 resilient groups (16%), and 3 nonresilient groups (6%). Black women and women with claims for home hospital beds, wheelchairs, and Parkinson's disease were more likely to experience nonresilient trajectories. Conclusions We observed changes in a claims-based frailty index during chemotherapy that are consistent with prior studies using clinical measures of frailty and identified predictors of nonresilient frailty trajectories. Our study demonstrates the feasibility of using claims-based frailty indices to assess changes in frailty during cancer treatment. [ABSTRACT FROM AUTHOR]

Background: The health effects of Life's Essential 8 (LE8) on chronic diseases have been disclosed, but its association with hypertension remains unknown. The current study aimed to explore the potential link between 10-year LE8 trajectory and the incidence of hypertension. Methods: LE8 was constructed from four behaviors and four metabolic factors, ranging from 0 to 100. Latent mixture models were used to identify trajectories of LE8 scores during 2006 to 2016. Incident hypertension was diagnosed based on self-reported clinical diagnoses and physical examinations from 2016 to 2020. Cox models were employed to assess the association of LE8 trajectories with hypertension. In addition to incorporating the mean hs-CRP levels from 2006 to 2016, age, sex, monthly income, educational level, and occupation at recruitment were adjusted for as confounding factors. Results: 7500 participants aged 40.28 ± 10.35 years were included in the study, of whom 2907 (38.76%) were women. Five LE8 trajectory patterns were identified. After around four-year follow-up, 667 hypertension events were observed. Compared to the Low-Stable trajectory, the hazard ratios and 95% confidence intervals for the Moderate-Increasing, Moderate-Decreasing, Moderate-Stable, and High-Stable trajectories were 0.51 (0.40, 0.65), 0.81 (0.64, 1.02), 0.45 (0.36, 0.58), 0.23 (0.16, 0.33), respectively. The risk of incident hypertension decreased as participants improved their LE8 status. The robustness of the primary results was confirmed through several sensitivity analyses. Conclusions: LE8 trajectories were associated with the incident hypertension. People who improved their LE8 scores over time experienced a decreased risk of hypertension, even if they started with lower LE8 scores initially. [ABSTRACT FROM AUTHOR]

Emotional support from family members may have an important effect on adolescent health outcomes, and has been identified as a target for policy to protect against the impacts of poverty and other early life adversities. However, few studies have assessed the extent to which poverty and adversity themselves influence the nature of emotional support that parents can provide to adolescents. We, therefore, aimed to investigate the impact of trajectories of income poverty and family adversities, including parental mental ill health, alcohol misuse and domestic violence across childhood developmental stages on young people's relationships with their families and perceived emotional support received. We analysed longitudinal data on 10,976 children from the nationally representative UK Millennium Cohort study. Exposure trajectories of poverty and family adversities were characterised using group-based multi-trajectory models (age 9 months–14 years). The outcomes were perceived emotional support and quality of family relationships, measured by the three-item Short Social Provisions Scale (SPS-3) and levels of parent–adolescent closeness and conflict, measured at age 14. ORs and 95% CIs were estimated using multivariable logistic regression models, adjusting for potential confounding factors. At age 14, the overall prevalence of low perceived emotional support was 13% (95% CI: 12, 14). Children of mothers with lower socioeconomic status (SES) were more likely to report low emotional support, with a clear social gradient (education—degree plus: 10.3% vs. no qualifications: 15.4%). Compared with children exposed to low levels of poverty and adversity, children in the persistent adversity trajectory groups experienced higher odds of low emotional support and low-quality parent–adolescent relationship; those exposed to both persistent poverty and poor parental mental health were particularly at increased risk of experiencing poor family relationships and low perceived emotional support (adjusted odds ratio 2·2; 95% CI 1·7–2·9). Low perceived emotional support and poor family relationships in adolescence are more prevalent among socially disadvantaged children and adolescents and those experiencing social adversity. Policies to improve levels of family support for UK adolescents should focus on improving modifiable determinants such as child poverty and family mental health. [ABSTRACT FROM AUTHOR]

Autistic adults experience high rates of unemployment, yet research investigating what predicts employment success produces inconsistent results. By utilising longitudinal person-oriented analyses, this study aimed to identify employment trajectories of autistic adults to better understand what may predict stable autistic employment. Participants were 2449 autistic adults (1077 men, 1352 women, 20 non-binary, M = 42.25 years, SD = 14.24), recruited via the Netherlands Autism Register. Latent class analysis utilising employment status across eight annual waves was used to identify longitudinal employment profiles. Fit indices and the interpretability of results indicated a four-class model best fit the data, with profiles reflecting stable unemployment (n = 1189), stable employment (n = 801), early unemployment increasing in probability of employment (n = 183) and high probability of employment reducing across time to low employment (n = 134). Multinominal analyses suggested that compared to the 'stable unemployment' group, membership in the 'stable employment' profile was predicted by fewer autistic traits, lower age, male gender, higher education and diagnosis age, and fewer co-occurring conditions. Higher education predicted both other profiles, with lower age and fewer co-occurring conditions predicting membership in the increasing employment class. Taken together, findings highlight the utility of person-oriented approaches in understanding the longitudinal challenges autistic adults experience maintaining employment and identifies key areas of support. Autistic adults experience difficulties finding and keeping employment. However, research investigating reasons that might explain this difficulty produce mixed results. We gave a survey to 2449 autistic adults and used a statistic method to group them based on their employment status over 8 years. We identified four employment groups that best captured the experiences of autistic adults; this included a group that experienced stable unemployment, a group that experienced stable employment, a group that had high employment that reduced over time, and a group whose employment increased over the 8 years. Further analysis showed that those with fewer autistic traits, younger age, male gender, higher education, later diagnosis age and no co-occurring conditions were more likely to have stable employment. People whose employment changed over time were more likely to have a higher level of education than the stable unemployment group, and those in the increasing employment group were younger age and had no co-occurring conditions. These findings help us better understand that not all autistic adults' experiences of employment are the same, which helps focus where employment programmes and support may be most needed, for example, people who identify as women or have a co-occurring condition. [ABSTRACT FROM AUTHOR]

• Effective degradation and state transition prediction of protein molecular simulation trajectories. • Integrate graph convolutional neural networks and physical constraint optimization. • Provides interpretable results on the importance of protein molecules. Molecular dynamics simulation is a crucial research domain within the life sciences, focusing on comprehending the mechanisms of biomolecular interactions at atomic scales. Protein simulation, as a critical subfield, often utilizes MD for implementation, with trajectory data play a pivotal role in drug discovery. The advancement of high-performance computing and deep learning technology becomes popular and critical to predict protein properties from vast trajectory data, posing challenges regarding data features extraction from the complicated simulation data and dimensionality reduction. Simultaneously, it is essential to provide a meaningful explanation of the biological mechanism behind dimensionality. To tackle this challenge, we propose a new unsupervised model named RevGraphVAMP to intelligently analyze the simulation trajectory. This model is based on the variational approach for Markov processes (VAMP) and integrates graph convolutional neural networks and physical constraint optimization to enhance the learning performance. Additionally, we introduce attention mechanism to assess the importance of key interaction region, facilitating the interpretation of molecular mechanism. In comparison to other VAMPNets models, our model showcases competitive performance, improved accuracy in state transition prediction, as demonstrated through its application to two public datasets and the Shank3-Rap1 complex, which is associated with autism spectrum disorder. Moreover, it enhanced dimensionality reduction discrimination across different substates and provides interpretable results for protein structural characterization. [ABSTRACT FROM AUTHOR]

BACKGROUND: The beet webworm, Loxostege sticticalis, a worldwide pest of many crops, performs a seasonal migration, causing periodic outbreaks in Asia, Europe and North America. Although long‐distance migration is well documented in China, patterns of transboundary migration among China, Russia and Mongolia are largely unknown. We performed a phase analysis of L. sticticalis periodic outbreaks among three countries based on 30 years of historical population data, analyzed the wind systems during migration over boundary regions, and traced the migratory routes in a case study of outbreaks in 2008 by trajectory simulation. RESULTS: Highly synchronized outbreak years of L. sticticalis were observed between China and Mongolia, China and eastern Siberia, China and western Siberia, Mongolia and eastern Siberia, eastern Siberia and western Siberia from 1978 to 2008, indicating possible transboundary migration between these regions. Winds at 300–600 m altitude, where adult migration usually occurs, also showed a high probability of northwestern winds in Haila'er (China), Chita (Russia) and Choybalsan (Mongolia), favoring successful adult migration from these areas to northern and northeastern China. Back trajectory analysis further showed that the first‐generation adults that caused the severe outbreak of second‐generation larvae in 2008 originated from eastern Siberia, eastern Mongolia, and the boundary regions of China–Russia and China–Mongolia. CONCLUSION: Our findings demonstrated that the source of L. sticticalis outbreaks in northern China was closely related to the outbreaks in Siberia and Mongolia via long‐distance transboundary windborne migration. This information will help guide international monitoring and management strategies against this notorious pest. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

JianJiang Pan,1,&ast; XiXuan Cai,1,&ast; JieRu Chen,1 MingYing Xu,1 JingYu Hu,1 YueChun Mao,1 Tao Chen,2 LuSha Li,1 MengQi Jin,1 LiYing Chen1 1Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People’s Republic of China; 2Department of General Practice, Jianqiao Community Health Service Center, Hangzhou, Zhejiang, 310021, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: LiYing Chen, Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China, Email 3197020@zju.edu.cnPurpose: Understanding the role of systemic inflammation in the development of Metabolic Syndrome (MetS) is crucial for identifying individuals at a higher risk of this cluster of conditions that increase the risk of heart disease, stroke, and diabetes.Patients and Methods: A retrospective cohort study was conducted with 4,312 participants who were free from MetS at the study’s onset and had high-sensitivity C-reactive protein (hsCRP) levels measured. Latent class trajectory modeling was utilized to identify distinct hsCRP trajectory patterns. Multivariable regression and proportional hazards analyses were employed to evaluate the predictive value of hsCRP trajectories for the development of MetS.Results: During the 1.63-year follow-up period, 1,308 participants developed metabolic syndrome (MetS). Individuals with high hsCRP levels exhibited a significantly increased risk of developing MetS compared to those with low hsCRP levels (HR = 1.062, 95% CI 1.103– 1.113). The hsCRP trajectory analysis identified three distinct groups: low-stable, increasing, and decreasing. The decreasing and increasing hsCRP trajectory groups demonstrated a 1.408-fold (95% CI 1.115– 1.779) and a 1.618-fold (95% CI 1.288– 2.033) increased risk of MetS, respectively.Conclusion: This study suggests that participants with higher baseline hsCRP levels and increasing hsCRP trajectories are associated with a progression toward MetS. Long-term hsCRP trajectories may serve as useful tools for identifying individuals at higher risk of MetS who could benefit from targeted preventive and therapeutic interventions.Keywords: high-sensitivity C-reactive protein, metabolic syndrome, trajectory analysis, retrospective cohort study, risk prediction

Abstract Background Although it is well established that obesity is a risk factor for hypertension, the effect of distinct long-term patterns of body mass index (BMI) on blood pressure (BP) in later life is poorly understood. Methods Based on the China Health and Nutrition Survey, we analyzed 2920 participants aged 3–17 years with initial normal BP at baseline (1991–2011), who were followed up for the development of hypertension (1993–2015). The group-based trajectory model was applied to identify BMI trajectories, and Cox regression was used to assess their associations with hypertension risk. Stratified analyses were conducted to explore differences across subgroups. Results During an average follow-up time of 11.20 (7.69) years for males and 7.20 (5.21) years for females, 339 males and 212 females were identified with hypertension, respectively. Three BMI trajectories were identified: low-increasing (60.58% of males and 73.03% of females), moderate-increasing (33.08% of males and 24.22% of females), and high-increasing (6.34% of males and 2.76% of females). Our study found a significant positive association between a higher BMI trajectory and hypertension risk in males (all P for trend

Abstract Background The relationship between the dynamic changes in insulin resistance (IR) and the prognosis of septic patients remains unclear. This study aims to investigate the correlation between the clinical subphenotype of IR represented by the triglyceride-glucose (TyG) index trajectory and the mortality rate among patients with sepsis. Methods In this retrospective cohort study, we utilized data from septic patients within the Medical Information Mart for Intensive Care (MIMIC)-IV database version 2.0 to construct trajectories of the TyG index over 72 h. Subsequently, we computed the similarity among various TyG index trajectories with the dynamic time warping (DTW) algorithm and utilized the hierarchical clustering (HC) algorithm to demarcate distinct cluster and identified subphenotypes according to the trajectory trend. Subsequently, we assessed the mortality risk between different subphenotypes using analyses such as survival analysis and validated the robustness of the results through propensity score matching (PSM) and various models. Results A total of 2350 patients were included in the study. Two trajectory trends: TyG index decreasing (n = 926) and TyG index increasing (n = 1424) were identified, which indicated corresponding to the clinical subphenotype of increased and alleviative IR respectively. The 28-day and in-hospital mortality for the increased IR group was 28.51% and 25.49% respectively. In comparison, patients in the alleviative IR group with a 28-day mortality of 23.54% and an in-hospital mortality of 21.60%. These subphenotypes exhibited distinct prognosis, time dependent Cox model showed the increased IR group with a higher 28-day mortality [hazard ratio (HR): 1.07, 95% confidence interval (CI): 1.02–1.12, P = 0.01] and in-hospital mortality [HR: 1.05, 95% CI: 1.00–1.11, P = 0.045] compared to the alleviative IR group. Sensitivity analyses with various models further validated the robustness of our findings. Conclusion Dynamic increase in the TyG index trajectory is associated with elevated mortality risk among patients with sepsis, which suggests that dynamic increased IR exacerbates the risk of poor outcomes in patients.

Abstract Background The health effects of Life’s Essential 8 (LE8) on chronic diseases have been disclosed, but its association with hypertension remains unknown. The current study aimed to explore the potential link between 10-year LE8 trajectory and the incidence of hypertension. Methods LE8 was constructed from four behaviors and four metabolic factors, ranging from 0 to 100. Latent mixture models were used to identify trajectories of LE8 scores during 2006 to 2016. Incident hypertension was diagnosed based on self-reported clinical diagnoses and physical examinations from 2016 to 2020. Cox models were employed to assess the association of LE8 trajectories with hypertension. In addition to incorporating the mean hs-CRP levels from 2006 to 2016, age, sex, monthly income, educational level, and occupation at recruitment were adjusted for as confounding factors. Results 7500 participants aged 40.28 ± 10.35 years were included in the study, of whom 2907 (38.76%) were women. Five LE8 trajectory patterns were identified. After around four-year follow-up, 667 hypertension events were observed. Compared to the Low-Stable trajectory, the hazard ratios and 95% confidence intervals for the Moderate-Increasing, Moderate-Decreasing, Moderate-Stable, and High-Stable trajectories were 0.51 (0.40, 0.65), 0.81 (0.64, 1.02), 0.45 (0.36, 0.58), 0.23 (0.16, 0.33), respectively. The risk of incident hypertension decreased as participants improved their LE8 status. The robustness of the primary results was confirmed through several sensitivity analyses. Conclusions LE8 trajectories were associated with the incident hypertension. People who improved their LE8 scores over time experienced a decreased risk of hypertension, even if they started with lower LE8 scores initially.

Shichao Liang,1 Tengfei Yang2 1Department of Emergency Medicine, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China; 2Department of Health Management, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of ChinaCorrespondence: Tengfei Yang, Department of Health Management, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Heping District, Shenyang, 110004, People’s Republic of China, Email yangtf@sj-hospital.orgObjective: Longitudinal cohort analysis was performed to identify the association between changes in the gamma-glutamyl transferase (GGT)/high-density lipoprotein cholesterol (HDL-C) ratio trajectory and the risk of developing diabetes mellitus.Methods: This was a retrospective cohort study. We analyzed the latent trajectory classes of changes in the GGT/HDL-C ratio by applying a latent class mixture model with healthy individuals who underwent medical checkups from January 2017 to December 2021 as the study subjects. To analyze the effect of the GGT/HDL-C ratio trajectory classes on new-onset diabetes mellitus, we then applied a multivariate Cox proportional risk regression model. Statistical analysis was performed using the R-software with the LCMM package.Results: The study cohort comprised 3410 participants. All participants were followed up for 5 years, and 95 developed diabetes (4-year incidence of 2.78%). By applying the latent class mixed model, we categorized participants into three trajectory groups: low-stability group (n = 2253), medium-increase group (n = 941), and high-increase group (n = 216). The Cox proportional risk regression model analysis showed that the hazard ratio (95% confidence interval) for the incidence of diabetes mellitus was 1.73 (1.04– 2.87) in the medium-increase group and 3.96 (2.11– 7.44) in the high-increase group. Moreover, we calculated the estimated model-based levels and linear slopes of the GGT/HDL-C ratios for each age group between 26 and 85 years at 10-year intervals, respectively. The results indicated the strongest correlation between the GGT/HDL-C ratio slope and diabetes in the 46– 55 year age group, with an odds ratio of 1.51 (1.25– 1.83).Conclusion: A large increase in the GGT/HDL-C ratio was highly associated with the risk of developing diabetes mellitus. This result suggests that vigilance for changes in the GGT/HDL-C ratio trajectory during community health screening can help identify potential patients with diabetes, enabling early intervention and treatment.Keywords: GGT/HDL-C ratio, trajectory analysis, diabetes mellitus, cohort study, health management

Abstract Background The binary diagnosis of Metabolic Syndrome(MetS) fails to accurately evaluate its severity, and the association between MetS severity and frailty progression remains inadequately elucidated. This study aims to clarify the relationship between the severity of MetS and the progression of frailty among the middle-aged and elderly population in China. Method Participants from the 2011–2018 China Health and Retirement Longitudinal Study(CHARLS) were included for a longitudinal analysis. The study employs a frailty index(FI) based on 32 health deficits to diagnose frailty and to assess FI trajectories. An age-sex-ethnicity-specific MetS scoring model (MetS score) was used to assess metabolic syndrome severity in Chinese adults. The Cumulative MetS score from 2012 to 2015 was calculated using the formula: (MetS score in wave 1 + MetS score in wave 3) / 2 × time(2015 - 2012). The association between MetS score, Cumulative MetS score, and the risk and trajectory of frailty were evaluated using Cox regression/logistic regression, and linear mixed models. Restricted Cubic Splines(RCS) models were utilized to detect potential non-linear associations. Results A higher MetS score was significantly associated with an increased risk of frailty(HR per 1 SD increase = 1.205; 95%CI: 1.14 to 1.273) and an accelerated FI trajectory(β per 1 SD increase = 0.113 per year; 95%CI: 0.075 to 0.15 per year). Evaluating changes in MetS score using a Cumulative MetS score indicated that each 1 SD increase in the Cumulative MetS score increased the risk of frailty by 22.2%(OR = 1.222; 95%CI: 1.133 to 1.319) and accelerated the rate of increase in FI(β = 0.098 per year; 95%CI: 0.058 to 0.138 per year). RCS model results demonstrated a dose-response curve relationship between MetS score and Cumulative MetS score with frailty risk. Stratified analysis showed consistency across subgroups. The interaction results indicate that in males and individuals under aged 60, MetS score may accelerate the increase in FI, a finding consistent across both models. Conclusions Our findings underscore the positive correlation between the severity of MetS and frailty progression in the middle-aged and elderly, highlighting the urgent need for early identification of MetS and targeted interventions to reduce the risk of frailty.

Aiming at the lack of effective analysis and identification of operational area in the traditional battlefield situation awareness process, a method of aerial battlefield target trajectory analysis method for operational area extraction is proposed. Firstly, based on the improved Douglas-Peucker algorithm, the featured trajectory is extracted based on the original target trajectory, thus reducing the trajectory redundant information. Secondly, the clustering by fast search and find of density peaks (CFSFDP) algorithm is used to cluster the featured trajectory, which obtains multiple featured points clusters. Finally, each featured points cluster is scanned based on Graham's convex hull algorithm to obtain closed polygons to characterize the combat areas. The feasibility and effectiveness of the algorithm model are verified by several case simulations.

Background: The binary diagnosis of Metabolic Syndrome(MetS) fails to accurately evaluate its severity, and the association between MetS severity and frailty progression remains inadequately elucidated. This study aims to clarify the relationship between the severity of MetS and the progression of frailty among the middle-aged and elderly population in China. Method: Participants from the 2011–2018 China Health and Retirement Longitudinal Study(CHARLS) were included for a longitudinal analysis. The study employs a frailty index(FI) based on 32 health deficits to diagnose frailty and to assess FI trajectories. An age-sex-ethnicity-specific MetS scoring model (MetS score) was used to assess metabolic syndrome severity in Chinese adults. The Cumulative MetS score from 2012 to 2015 was calculated using the formula: (MetS score in wave 1 + MetS score in wave 3) / 2 × time(2015 - 2012). The association between MetS score, Cumulative MetS score, and the risk and trajectory of frailty were evaluated using Cox regression/logistic regression, and linear mixed models. Restricted Cubic Splines(RCS) models were utilized to detect potential non-linear associations. Results: A higher MetS score was significantly associated with an increased risk of frailty(HR per 1 SD increase = 1.205; 95%CI: 1.14 to 1.273) and an accelerated FI trajectory(β per 1 SD increase = 0.113 per year; 95%CI: 0.075 to 0.15 per year). Evaluating changes in MetS score using a Cumulative MetS score indicated that each 1 SD increase in the Cumulative MetS score increased the risk of frailty by 22.2%(OR = 1.222; 95%CI: 1.133 to 1.319) and accelerated the rate of increase in FI(β = 0.098 per year; 95%CI: 0.058 to 0.138 per year). RCS model results demonstrated a dose-response curve relationship between MetS score and Cumulative MetS score with frailty risk. Stratified analysis showed consistency across subgroups. The interaction results indicate that in males and individuals under aged 60, MetS score may accelerate the increase in FI, a finding consistent across both models. Conclusions: Our findings underscore the positive correlation between the severity of MetS and frailty progression in the middle-aged and elderly, highlighting the urgent need for early identification of MetS and targeted interventions to reduce the risk of frailty. [ABSTRACT FROM AUTHOR]

Background: The postpartum period is a critical phase in which postpartum women experience dynamic changes in their physiology, psychology, and family status. Objective: This study investigated the changes in women's quality of life (QoL) during the first, third, and sixth months of the postpartum period and their associated factors. Methods: A single-group repeated-measure design was used to collect data from 282 postpartum women recruited from a regional hospital in Taiwan. We used the brief World Health Organization Quality of Life scale, Social Support Scale, and Edinburgh Postnatal Depression Scale to assess postpartum women's quality of life, social support, and postpartum depressive symptoms, respectively. The data were analyzed using trajectory analysis and generalized estimating equations. Results: The trajectory analysis indicated that postpartum women could be categorized into low, medium, and high QoL groups. Although the medium and high QoL groups maintained stable QoL levels, the low QoL group experienced a linear decrease in QoL over time. Moreover, the determinants of postpartum women's QoL were immigrant status, employment status, family type, social support, and postpartum depression. Conclusions: Health care providers should assess these determinants of postpartum QoL in perinatal women to identify those at risk of low postpartum quality of life. Early assessment and intervention by health care providers could significantly improve the health status of women after childbirth. [ABSTRACT FROM AUTHOR]

The first single-cell penile cancer atlas identified 83 682 single cells within 14 major cell types and 65 cell subpopulations, offering unprecedented insights into penile cancer biology. TP53 mutations might be a driver of worse prognosis, irrespective of human papillomavirus (HPV) status, challenging the currently used stratification by HPV only. Our work reveals key molecular pathways underlying poor prognosis and therapy resistance. These insights might facilitate patient selection for clinical trials and enable development of personalized therapies, sparing patients from the currently used highly toxic chemotherapies. TP53 loss-of-function (TP53LOF) mutations might be a driver of poor prognosis and chemoresistance in both human papillomavirus (HPV)-independent (HPV–) and HPV-associated (HPV+) penile squamous cell carcinoma (PSCC). Here, we aim to describe transcriptomic differences in the PSCC microenvironment stratified by TP53LOF and HPV status. We used single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing to obtain a comprehensive atlas of the cellular architecture of PSCC. TP53LOF and HPV status were determined by targeted next-generation sequencing and sequencing HPV-DNA reads. Six HPV+ TP53 wild type (WT), six HPV– TP53WT, and four TP53LOF PSCC samples and six controls were included. Immunohistochemistry and hematoxylin-eosin confirmed the morphological context of the observed signatures. Prognostic differences between patient groups were validated in 541 PSCC patients using Kaplan-Meier survival estimates. Patients with aberrant p53 staining fare much worse than patients with either HPV– or HPV+ tumors and WT p53 expression. Using scRNA-seq, we revealed 65 cell subtypes within 83 682 cells. TP53LOF tumors exhibit a partial epithelial-to-mesenchymal transition, immune-excluded, angiogenic, and morphologically invasive environment, underlying their aggressive phenotype. HPV– TP53WT tumors show stemness and immune exhaustion. HPV+ TP53WT tumors mirror normal epithelial maturation with upregulation of antibody-drug-conjugate targets and activation of innate immunity. Inherent to the scRNA-seq analysis, low sample size is a limitation and validation of signatures in large PSCC cohorts is needed. This first scRNA-seq atlas offers unprecedented in-depth insights into PSCC biology underlying prognostic differences based on TP53 and HPV status. Our findings provide clues for testing novel biomarker-driven therapies in PSCC. Here, we analyzed tissues of penile cancer at the level of individual cells, which helps us understand why patients who harbor a deactivating mutation in the TP53 gene do much worse than patients lacking such a mutation. Such an analysis may help us tailor future therapies based on TP53 gene mutations and human papillomavirus status of these tumors. [ABSTRACT FROM AUTHOR]

The prognosis of clear cell renal cell carcinoma (ccRCC) is typically based on clinical stage, but it can vary for some patients. Transcriptomic analysis is vital for understanding ccRCC progression, though its correlation with the clinical stage in predicting prognosis is uncertain. We aim to employ trajectory inference to study ccRCC's molecular progression and identify potential new markers for judging disease progression and prognosis. Using a trajectory inference approach, we characterize the molecular progression profile of ccRCC based on transcriptome profiling. Additional pathway activity, immune response, and miRNA profiling scoring were integrated to identify possible drivers of trajectory progression. Scoring based on the trajectory demonstrates a significant improvement in patient prognosis prediction and identifies 10 risk factors in patients with low-grade tumors, and nine protective factors in patients with high-grade tumors. Mechanistically, we demonstrate an association between solute light carrier transporters are associated with ccRCC progression, with SLC7A5 expression being validated through immunohistochemistry to increase in metastatic patients. Trajectory analysis of ccRCC transcriptomes can be used to model the molecular progression of disease and may assist in ccRCC prognosis. SLC7A5 is aberrantly expressed in ccRCC and may be a risk factor for poor prognosis. [ABSTRACT FROM AUTHOR]

Unsupervised feature selection is a critical step for efficient and accurate analysis of single-cell RNA-seq data. Previous benchmarks used two different criteria to compare feature selection methods: (i) proportion of ground-truth marker genes included in the selected features and (ii) accuracy of cell clustering using ground-truth cell types. Here, we systematically compare the performance of 11 feature selection methods for both criteria. We first demonstrate the discordance between these criteria and suggest using the latter. We then compare the distribution of selected genes in their means between feature selection methods. We show that lowly expressed genes exhibit seriously high coefficients of variation and are mostly excluded by high-performance methods. In particular, high-deviation- and high-expression-based methods outperform the widely used in Seurat package in clustering cells and data visualization. We further show they also enable a clear separation of the same cell type from different tissues as well as accurate estimation of cell trajectories. [ABSTRACT FROM AUTHOR]

Neurofilament-light chain (NF-L) and phosphorylated neurofilament-heavy chain (pNF-H) are axonal proteins that have been reported as potential diagnostic and prognostic biomarkers in traumatic brain injury (TBI). However, detailed temporal profiles for these proteins in blood, and interrelationships in the acute and chronic time periods post-TBI have not been established. Our objectives were: 1) to characterize acute-to-chronic serum NF-L and pNF-H profiles after moderate-severe TBI, as well as acute cerebrospinal fluid (CSF) levels; 2) to evaluate CSF and serum NF-L and pNF-H associations with each other; and 3) to assess biomarker associations with global patient outcome using both the Glasgow Outcome Scale-Extended (GOS-E) and Disability Rating Scale (DRS). In this multi-cohort study, we measured serum and CSF NF-L and pNF-H levels in samples collected from two clinical cohorts (University of Pittsburgh [UPITT] and Baylor College of Medicine [BCM]) of individuals with moderate-severe TBI. The UPITT cohort includes 279 subjects from an observational cohort study; we obtained serum (n = 277 unique subjects) and CSF (n = 95 unique subjects) daily for 1 week, and serum every 2 weeks for 6 months. The BCM cohort included 103 subjects from a previous randomized clinical trial of erythropoietin and blood transfusion threshold after severe TBI, which showed no effect on neurological outcome between treatment arms; serum (n = 99 unique subjects) and CSF (n = 54 unique subjects) NF-L and pNF-H levels were measured at least daily during Days (D) 0-10 post-injury. GOS-E and DRS were assessed at 6 months (both cohorts) and 12 months (UPITT cohort only). Results show serum NF-L and pNF-H gradually rise during the first 10 days and peak at D20-30 post-injury. In the UPITT cohort, acute (D0-6) NF-L and pNF-H levels correlate within CSF and serum (Spearman r = 0.44-0.48; p < 0.05). In the UPITT cohort, acute NF-L CSF and serum levels, as well as chronic (Months [M]2-6) serum NF-L levels, were higher among individuals with unfavorable GOS-E and worse DRS at 12 months (p < 0.05, all comparisons). In the BCM cohort, higher acute serum NF-L levels were also associated with unfavorable GOS-E. Higher pNF-H serum concentrations (D0-6 and M2-6), but not CSF pNF-H, were associated with unfavorable GOS-E and worse DRS (p < 0.05, all comparisons) in the UPITT cohort. Relationships between biomarker levels and favorable outcome persisted after controlling for age, sex, and Glasgow Coma Scale. This study shows for the first time that serum levels of NF-L and pNF-H peak at D20-30 post-TBI. Serum NF-L levels, and to a lesser extent pNF-H levels, are robustly associated with global patient outcomes and disability after moderate-severe TBI. Further studies on clinical utility as prognosis and treatment-response indicators are needed. [ABSTRACT FROM AUTHOR]

Helicoverpa armigera (Hübner) is a destructive agricultural pest. Facultative migration usually causes regional catastrophes; therefore, developing a simple and easy new technology for the monitoring and early warning of immigrant populations is urgent. Between 2021 and 2023, we conducted a population-monitoring study on H. armigera immigrants in Xundian County, Yunnan Province, where the migration pathway for pests from southeast Asia extends to southwest China. Based on the differences in the reproductive organ development parameters of H. armigera at different ages, we established an adult age discrimination model. The monitoring results of field populations with semiochemical attractants and sex pheromones between 2021 and 2023 showed that the daily average age of the adult population of H. armigera fluctuated above 6 days, and the trapping dynamics with semiochemical attractants and sex pheromones were the same. Both trapping methods yielded H. armigera males of different ages and had identical age structures, indicating that the H. armigera population primarily migrated from other regions. The trajectory analysis showed that the H. armigera population that migrated to Xundian between May and September was primarily from South Kunming, and after October, it was primarily the southward-migrating population north of Qujing City, Yunnan Province. Based on the relationship between the daily average fecundity and the age of H. armigera, a dynamic prediction model for the fecundity of the immigrant population was established. In this study, the prediction models and methods based on semiochemical attractants could potentially be used in the surveillance and population alerting of H. armigera. [ABSTRACT FROM AUTHOR]

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

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion. [ABSTRACT FROM AUTHOR]

Objective: White blood cells (WBC) play an important role in the inflammatory response of the body. Elevated WBC counts on admission in patients with subarachnoid hemorrhage (SAH) correlate with a poor prognosis. However, the role of longitudinal WBC trajectories based on repeated WBC measurements during hospitalization remains unclear. We explored the association between different WBC trajectory patterns and in-hospital mortality. Methods: We analyzed a cohort of consecutive patients with SAH between 2012 and 2020. Group-based trajectory modeling (GBTM) was used to group the patients according to their white blood cell patterns over the first 4 days. Stabilized inverse probability treatment weighting (sIPTW) was used to balance baseline demographic and clinical characteristics. We analyzed the association between the WBC trajectory groups and in-hospital mortality using a Cox proportional hazards model. Results: In total, 506 patients with SAH were included in this retrospective cohort. The final model identified two distinct longitudinal WBC trajectories. After adjusting for confounding factors, multivariate regression analysis suggested that an elevated longitudinal WBC trajectory increased the risk of in-hospital mortality (hazard ratio [HR], 2.476; 95% confidence interval [CI] 1.081–5.227; P = 0.024) before sIPTW, and (HR, 2.472; 95%CI 1.489–4.977; P = 0.018) after sIPTW. Conclusion: In patients with SAH, different clinically relevant groups could be identified using WBC trajectory analysis. The WBC count trajectory—initially elevated and then decreased— may lead to an increased risk of in-hospital mortality following SAH. [ABSTRACT FROM AUTHOR]

In recent years, the construction industry worldwide has shown significant interest in Building Information Modeling (BIM). This study aims to analyze the dissemination of knowledge about BIM in construction engineering applications using Main Path Analysis (MPA). The research sample comprises 3,761 papers related to BIM's application in the construction industry, sourced from the ISI Web of Science database. Initially, we investigate trends in paper publications, conduct country and journal analyses, and examine author statistics. Subsequently, we calculate traversal counts along the search path links to reveal the development trajectory of BIM. The trajectory of BIM's evolution in the construction industry can be divided into four stages as identified through the global key-route main path analysis: 1) BIM standardization; 2) Integration of completed building projects using BIM; 3) BIM applications in precast construction projects; and 4) BIM applications in land management. These findings provide a clear understanding of how BIM has been applied and evolved within the construction industry. [ABSTRACT FROM AUTHOR]

Aiming at the lack of effective analysis and identification of operational area in the traditional battlefield situation awareness process, a method of aerial battlefield target trajectory analysis method for operational area extraction is proposed. Firstly, based on the improved Douglas-Peucker algorithm, the featured trajectory is extracted based on the original target trajectory, thus reducing the trajectory redundant information. Secondly, the clustering by fast search and find of density peaks (CFSFDP) algorithm is used to cluster the featured trajectory, which obtains multiple featured points clusters. Finally, each featured points cluster is scanned based on Graham's convex hull algorithm to obtain closed polygons to characterize the combat areas. The feasibility and effectiveness of the algorithm model are verified by several case simulations. [ABSTRACT FROM AUTHOR]

Objectives: Heart rate variability (HRV) is becoming more prevalent as a measurable parameter in wearable sleep-monitoring devices, which are simple and effective instruments for illness evaluation. Currently, most studies on investigating OSA severity and HRV have measured heart rates during wakefulness or sleep. Therefore, the objective of this study was to investigate the circadian rhythm of HRV in male patients with OSA and its value for the estimation of OSA severity using group-based trajectory modeling. Methods: Patients with complaints of snoring were enrolled from the Sleep Center of Shandong Qianfoshan Hospital. Patients were divided into 3 groups according to apnea hypopnea index (AHI in events/h), as follows: (<15, 15≤AHI<30, and ≥30). HRV parameters were calculated using 24 h Holter monitoring, which included time-domain and frequency-domain indices. Circadian differences in the standard deviation of normal to normal (SDNN) were evaluated for OSA severity using analysis of variance, trajectory analysis, and multinomial logistic regression. Results: A total of 228 patients were enrolled, 47 with mild OSA, 48 moderate, and 133 severe. Patients with severe OSA exhibited reduced triangular index and higher very low frequency than those in the other groups. Circadian HRV showed that nocturnal SDNN was considerably higher than daytime SDNN in patients with severe OSA. The difference among the OSA groups was significant at 23, 24, 2, and 3 o'clock sharp between the severe and moderate OSA groups (all P<0.05). The heterogeneity of circadian HRV trajectories in OSA was strongly associated with OSA severity, including sleep structure and hypoxia-related parameters. Among the low-to-low, low-to-high, high-to-low, and high-to-high groups, OSA severity in the low-to-high group was the most severe, especially compared with the low-to-low and high-to-low SDNN groups, respectively. Conclusions: Circadian HRV in patients with OSA emerged as low daytime and high nocturnal in SDNN, particularly in men with severe OSA. The heterogeneity of circadian HRV revealed that trajectories with low daytime and significantly high nighttime were more strongly associated with severe OSA. Thus, circadian HRV trajectories may be useful to identify the severity of OSA. [ABSTRACT FROM AUTHOR]

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In astrodynamics, orbit cranking is usually referred to as an interplanetary transfer strategy that exploits multiple gravity-assist maneuvers to change both the inclination and eccentricity of the spacecraft osculating orbit without changing the specific mechanical energy, that is, the semimajor axis. In the context of a solar sail-based mission, however, the concept of orbit cranking is typically referred to as a suitable guidance law that is able to (optimally) change the orbital inclination of a circular orbit of an assigned radius in a general heliocentric three-dimensional scenario. In fact, varying the orbital inclination is a challenging maneuver from the point of view of the velocity change, so orbit cranking is an interesting mission application for a propellantless propulsion system. The aim of this paper is to analyze the performance of a spacecraft equipped with an Electric Solar Wind Sail in a cranking maneuver of a heliocentric circular orbit. The maneuver performance is calculated in an optimal framework considering spacecraft dynamics described by modified equinoctial orbital elements. In this context, the paper presents an analytical version of the three-dimensional optimal guidance laws obtained by using the classical Pontryagin's maximum principle. The set of (analytical) optimal control laws is a new contribution to the Electric Solar Wind Sail-related literature. [ABSTRACT FROM AUTHOR]

Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes. Mice leaving from a stable entrance learned to efficiently navigate to the food without the need for landmarks. We developed a quantitative framework to reveal how the mice estimate the food location based on analyses of trajectories and active hole checks. After learning, the computed ‘target estimation vector’ (TEV) closely approximated the mice’s route and its hole check distribution. The TEV required learning both the direction and distance of the start to food vector, and our data suggests that different learning dynamics underlie these estimates. We propose that the TEV can be precisely connected to the properties of hippocampal place cells. Finally, we provide the first demonstration that, after learning the location of two food sites, the mice took a shortcut between the sites, demonstrating that they had generated a cognitive map.

ObjectiveWe aimed to characterize quality of life (QOL) trajectories among patients with intermediate and advanced hepatocellular carcinoma patients treated with immunotherapy.MethodsBarcelona Clinic Liver Cancer (BCLC) stage B-C HCC patients receiving immunotherapy at Guangxi Medical University Cancer Hospital were included. Trajectories of QOL, assessed using the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) questionnaire, were identified through iterative estimations of group-based trajectory models. Associations with trajectory group membership were analyzed using multivariable multinomial logistic regression.ResultsThree trajectory groups were identified (n=156): excellent (35.3%), poor (43.6%), and deteriorating (21.1%) QOL. The deteriorating trajectory group reported a mean QOL score of 124.79 (95% CI, 116.58–133.00), but then declined significantly at month-2 (estimated QOL score 98.67 [95% CI, 84.33–113.00]), and the lowest mean score is reached at month-6 (estimated QOL score 16.58 [95% CI, 0–46.07]). Factors associated with membership to the deteriorating group included no drinking (odds ratio [OR] vs yes [95% CI], 3.70 [1.28–11.11]), no received radiotherapy (OR vs yes [95% CI], 8.33 [1.41–50.00]), diabetes (OR vs no [95% CI], 6.83 [1.57–29.73]), and extrahepatic metastasis (OR vs no [95% CI], 3.08 [1.07–8.87]). Factors associated with membership to the poor group also included body mass index ≤24.0 kg/m2 (OR vs no [95% CI], 4.49 [1.65–12.22]).ConclusionsThis latent-class analysis identified a high-risk cluster of patients with severe, persistent post-immunotherapy QOL deterioration. Screening relevant patient-level characteristics may inform tailored interventions to mitigate the detrimental impact of immunotherapy and preserve QOL.

Abstract Background No study has concentrated on the association of LE8 with cancer risk and death. We aim to examine the association of LE8 with death and cancer. Methods A total of 94733 adults aged 51.42 ± 12.46 years and 77551 participants aged 54.09±12.06 years were enrolled in longitudinal and trajectory analysis respectively. Baseline LE8 was divided into three groups based on the American Heart Association criteria and three trajectory patterns by latent mixture models. We reviewed medical records and clinical examinations to confirm incident cancer during the period from 2006 to 2020. Death information was collected from provincial vital statistics offices. Cox models were used. Results 12807 all-cause deaths and 5060 cancers were documented during a 14-year follow-up. Relative to participants with high LE8 at baseline, participants with lower levels of LE8 have a significantly increased risk of mortality and incident cancer. All these risks have an increasing trend with LE8 level decreasing. Meanwhile, the trajectory analysis recorded 7483 all-cause deaths and 3037 incident cancers after approximately 10 years. The associations of LE8 with death and cancer were identical to the longitudinal study. In the subtype cancer analysis, LE8 has a strong effect on colorectal cancer risk. Moreover, the cut point is 56.67 in the association between LE8 and death, while the cut point altered to 64.79 in the association between LE8 and incident cancers. These associations were enhanced among younger adults. Conclusions There was a significant association of LE8 with death and cancer risk, especially for the young population.

Background: No study has concentrated on the association of LE8 with cancer risk and death. We aim to examine the association of LE8 with death and cancer. Methods: A total of 94733 adults aged 51.42 ± 12.46 years and 77551 participants aged 54.09±12.06 years were enrolled in longitudinal and trajectory analysis respectively. Baseline LE8 was divided into three groups based on the American Heart Association criteria and three trajectory patterns by latent mixture models. We reviewed medical records and clinical examinations to confirm incident cancer during the period from 2006 to 2020. Death information was collected from provincial vital statistics offices. Cox models were used. Results: 12807 all-cause deaths and 5060 cancers were documented during a 14-year follow-up. Relative to participants with high LE8 at baseline, participants with lower levels of LE8 have a significantly increased risk of mortality and incident cancer. All these risks have an increasing trend with LE8 level decreasing. Meanwhile, the trajectory analysis recorded 7483 all-cause deaths and 3037 incident cancers after approximately 10 years. The associations of LE8 with death and cancer were identical to the longitudinal study. In the subtype cancer analysis, LE8 has a strong effect on colorectal cancer risk. Moreover, the cut point is 56.67 in the association between LE8 and death, while the cut point altered to 64.79 in the association between LE8 and incident cancers. These associations were enhanced among younger adults. Conclusions: There was a significant association of LE8 with death and cancer risk, especially for the young population. [ABSTRACT FROM AUTHOR]