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Abstract Background As a currently incurable but preventable disease, the prevention and early diagnosis of Alzheimer’s disease (AD) has long been a research hotspot. Amyloid deposition has been shown to be a major pathological feature of AD. Notably, not all the people with amyloid-beta (Aβ) pathology will have significant cognitive declines and eventually develop AD. Therefore, the aim of this study was to explore the risk factors for cognitive decline in Aβ-positive participants. Methods We included 650 non-demented participants who were Aβ-positive at baseline from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Mixed effects and COX regression models were applied to assess 37 potential risk factors. Mixed effects models were employed to assess the temporal associations between potential risk factors and four cognitive assessment scales. COX regression models were used to assess the impact of potential risk factors on cognitive diagnosis conversion. Univariate and multivariate analyses were applied to the above models. Additionally, we used the Cochran-Armitage trend test to examine whether the incidence of cognitive decline increased with the number concurrent of risk factors. Results Six factors (low diastolic pressure, low body mass index, retired status, a history of drug abuse, Parkinsonism, and depression) were the identified risk factors and four factors (a history of urinary disease, musculoskeletal diseases, no major surgical history, and no prior dermatologic-connective tissue diseases) were found to be suggestive risk factors. The incidence of cognitive decline in the Aβ-positive participants gradually increased as the number of concurrent risk factors increased (p for trend = 0.0005). Conclusions Our study may facilitate the understanding of the potential pathological processes in AD and provide novel targets for the prevention of cognitive decline among participants with Aβ positivity.

IntroductionIncreasing evidence suggests that air pollution has a significant impact on the development of synucleinopathies, but the potential neurobiological mechanisms are unknown. We aimed to explore the associations of air pollution (including ozone [O3], nitrogen dioxide [NO2], and particulate matter [PM2.5]) with CSF α-syn levels in urban older adults.MethodsWe included 933 urban participants from the Chinese Alzheimer’s Biomarker and LifestylE study. The 5-year average levels of air pollution exposure were estimated in the areas of residence. Multivariate linear regression was conducted to detect the correlation of air pollution with CSF α-syn levels. Subgroup analyses by age, gender, season, and history of coronary heart disease (CHD) were performed. Moreover, restricted cubic spline (RCS) models were applied to explore the potential nonlinear relationships.ResultsWe found a significant correlation of CSF α-syn level with PM2.5 in urban participants. Specifically, multiple linear regression showed a significant negative association between PM2.5 and CSF α-syn level (p = 0.029), which was more significant in female, midlife, non-CHD, and cold season subgroups. Besides, RCS models showed that O3 had an inverse J-shaped association with CSF α-syn levels in urban participants (p for nonlinearity = 0.040), and the harmful effect possibly appeared when O3 was above 37.9 ppb.DiscussionLong-term exposure to air pollution was associated with lower CSF α-syn levels, which may offer a new direction for exploring and preventing synucleinopathies.

Abstract Background Cardiometabolic multimorbidity is associated with an increased risk of dementia, but the pathogenic mechanisms linking them remain largely undefined. We aimed to assess the associations of cardiometabolic multimorbidity with cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) pathology to enhance our understanding of the underlying mechanisms linking cardiometabolic multimorbidity and AD. Methods This study included 1464 cognitively intact participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database. Cardiometabolic diseases (CMD) are a group of interrelated disorders such as hypertension, diabetes, heart diseases (HD), and stroke. Based on the CMD status, participants were categorized as CMD-free, single CMD, or CMD multimorbidity. CMD multimorbidity is defined as the coexistence of two or more CMDs. The associations of cardiometabolic multimorbidity and CSF biomarkers were examined using multivariable linear regression models with demographic characteristics, the APOE ε4 allele, and lifestyle factors as covariates. Subgroup analyses stratified by age, sex, and APOE ε4 status were also performed. Results A total of 1464 individuals (mean age, 61.80 years; age range, 40–89 years) were included. The markers of phosphorylated tau-related processes (CSF P-tau181: β = 0.165, P = 0.037) and neuronal injury (CSF T-tau: β = 0.065, P = 0.033) were significantly increased in subjects with CMD multimorbidity (versus CMD-free), but not in those with single CMD. The association between CMD multimorbidity with CSF T-tau levels remained significant after controlling for Aβ42 levels. Additionally, significantly elevated tau-related biomarkers were observed in patients with specific CMD combinations (i.e., hypertension and diabetes, hypertension and HD), especially in long disease courses. Conclusions The presence of cardiometabolic multimorbidity was associated with tau phosphorylation and neuronal injury in cognitively normal populations. CMD multimorbidity might be a potential independent target to alleviate tau-related pathologies that can cause cognitive impairment.

Interoception, the sense of the physiological condition of our body, is impaired in individuals with autism spectrum disorders. Evidence suggests that subclinical autistic traits are mild manifestations of autistic symptoms, present in the general population. We examined the resting-state functional connectivity (rsFC) associating with interoception and autistic traits in 62 healthy young adults. Autistic traits correlated negatively with the rsFC between the lateral ventral anterior insula and anterior cingulate cortex. Interoceptive accuracy and sensibility correlated positively with the rsFC between interoceptive brain networks and the cerebellum, supplementary motor area, and visual regions. The results suggest that a negative relationship between interoception and autistic traits is largely accounted for by both self-report measures and decreased rsFC amongst the interoceptive brain network.

Abstract Background Metabolic acidosis is a major complication of critical illness. However, its current epidemiology and its treatment with sodium bicarbonate given to correct metabolic acidosis in the ICU are poorly understood. Method This was an international retrospective observational study in 18 ICUs in Australia, Japan, and Taiwan. Adult patients were consecutively screened, and those with early metabolic acidosis (pH

Background: Vitamin D deficiency is common in the general population worldwide, and the prevalence and severity of vitamin D deficiency increase in critically ill patients. The prevalence of vitamin D deficiency in a community-based cohort in Northern Taiwan was 22.4%. This multicenter cohort study investigated the prevalence of vitamin D deficiency and associated factors in critically ill patients in Northern Taiwan.Methods: Critically ill patients were enrolled and divided into five groups according to their length of stay at intensive care units (ICUs) during enrolment as follows: group 1,

Background: Investigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on identifying the crucial difference in emotion sequence patterns among different interaction groups remains in its infancy. Objectives: This research utilizes deep learning and sequential pattern mining to investigate whether there are differences in emotion sequence patterns across different groups of learners who exhibit various types of interactions in online discussion forums. Methods: Data from a comprehensive array of sources, including log files, discussion texts and scores from 498 learners in online discussion forums, were collected for this study. The agglomerative hierarchical algorithm is used to classify learners into groups with different levels of interactions. Additionally, we implement and evaluate multiple deep learning models for detecting different emotions from online discussions. Relevant emotion sequence patterns were identified using sequence pattern analysis and the identified emotion sequence patterns were compared across different groups with different levels of interactions. Results and Conclusions: Using an agglomerative hierarchical algorithm, we classified learners into three distinct groups characterized by different levels of interactions: high, average and low level. Leveraging the bi-directional long short-term memory model for emotion detection yielded the highest predictive performance, with an impressive F-measure of 94.01%, a recall rate of 93.83% and an accuracy score of 95.01%. The results also revealed that learners in the low-level interaction group experienced more emotion transition from boredom to frustration than the other two groups. Therefore, the aggregation of students into groups and the utilization of their MOOC log data offer educators the capability to provide adaptive emotional feedback, customize assessments and offer more personalized attention as needed.

Background: Appropriate utilization of intensive care unit (ICU) beds are essential. Patients with critical illness who have do not resuscitate (DNR) have a reduced priority of intensive care. However, the possibility of recovery/survival is ambiguous and multifactorial. Objective: To deliberate the characteristics and outcomes of critical illness in patients with prior DNR who were admitted to the emergency department (ED)-ICU. Method: This was a retrospective cohort study conducted between April 2015 and November 2015 in a university-based hospital. Non-traumatic patients with DNR admitted to ED-ICU from ED were included. Results: Seventy-eight non-trauma patients with prior DNR status were included in the final analysis. 51.3% (40/78) patients were male with median age 83 (IQR: 75–89) years. The median APACHE II score was 24.5 (IQR: 20–30). 50% (39/78) of the DNR patients survived to discharge. Patients who survived to discharge had lower APACHE II score (23 (IQR: 20–28) vs. 28 (18–38), p = 0.028). There was no significant difference in age, gender, and Charlson index. ROC curves were constructed, generating a cut-off of the APACHE II score at 29.5 for determining survival to discharge (AUC = 0.644, p = 0.028). In multivariate Cox proportional model, APACHE II score above 29.5 was an independent predictor for mortality. (Hazard ratio = 2.46; 95% confidence interval: 1.04–5.83, p = 0.042). Conclusion: Our study found that 50% of patients with prior DNR on ICU admission survived to discharge, indicating that aggressive care is not definitely futile. Further prospective studies are required to evaluate the cost-effectiveness and patients' and/or families' satisfaction of the ICU admission of DNR patients. Keywords: Do not resuscitate, Futility, Intensive care units

We aim to evaluate the accuracy of the new prehospital notification criteria for patients with potential acute stroke in the prehospital setting. Methods: We conducted a retrospective observational study from March 2011 to February 2013 of potential acute stroke patients prenotified using the new criteria which were: (1) positive Cincinnati Prehospital Stroke Scale (CPSS); (2) symptom onset within 3 hours; and (3) blood glucose level > 60 mg/dL. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the new criteria were calculated and outcomes of acute stroke patients were reported. Data of all patients with stroke or transient ischemic attack (TIA) transported to the destination hospital were also obtained to evaluate the compliance of emergency medical technicians. Results: There were 2888 patients suspected of stroke by emergency medical technicians and 221 patients prenotified due to meeting the criteria. The PPV, NPV, sensitivity, and specificity of the new criteria were 76.9%, 96.6%, 64.9%, and 98.1%, respectively. Onset time > 3 hours (24/51, 47.1%) and seizure (27.5%) were the two most common conditions leading to false prenotification. Of all prenotified patients, 23.1% (51/221) received thrombolytic therapy. Hemorrhagic stroke or ischemic stroke with hemorrhagic transformation (53.8%) and minor symptoms or rapid recovery (26.9%) were the most common reasons excluding correctly prenotified patients from thrombolytic therapy. Conclusion: The accuracy of the new prehospital stroke criteria has higher PPV and specificity compared to previous CPSS validation studies.

The Modified Early Warning Score (MEWS) reflects the physiological changes of cardiac arrest and has been used in identifying patient deterioration. Physiological reserve capacity is an important outcome predictor, but is seldom reported due to recording limitations in cardiac arrest patients. The aim of the study was to evaluate whether periarrest MEWS could be a further prognostic factor in in-hospital cardiac arrest. Methods: This was a retrospective cohort study of nontrauma adult patients who had experienced in-hospital cardiac arrest during emergency department stays at an urban, 2600-bed tertiary medical center in Taiwan from February 2011 to July 2013. Data regarding patients' characteristics, Charlson Comorbidity Score, MEWS score before events, mode of arrest, and outcome details were extracted following the Utstein guidelines for uniform reporting of cardiac arrest. Results: During the 30-month period, 234 patients suffered in-hospital cardiac arrest during emergency department stays, and 99 patients with periarrest MEWS were included in the final analysis. The MEWS at triage did not differ significantly between survival-to-discharge and mortality groups (3.42 ± 2.2 vs. 4.02 ± 2.65, p = 0.811). Periarrest MEWS was lower in the survival-to-discharge group (4.41 ± 2.28 vs. 5.82 ± 2.84, p = 0.053). In multivariate logistic regression analysis, periarrest MEWS was an independent predictors for survival to discharge. A rise in periarrest MEWS reduced the chance of survival to discharge by 0.77-fold (95% confidence interval: 0.60–0.97, p = 0.028). Conclusion: The simplest MEWS system not only can be used as a prevention measure, but the periarrest MEWS could also be considered as an independent predictor of mortality after in-hospital cardiac arrest.

As student bodies on college campuses in the United States (U.S.) continue to diversify, university counseling centers have begun to recognize the importance of hiring multilingual therapists and trainees to meet the needs of 66 million U.S. residents who speak languages other than English. The study used a qualitative approach to better understand the experiences of multilingual therapists and trainees working at university counseling centers in the U.S. Thirty-one participants (three men and 28 women; 27 senior staff and four trainees) completed an online survey with six open-ended questions. The following themes were identified: rewards and benefits of providing multilingual therapy, supervision experiences given, and organizational support provided to multilingual therapists. Senior staff participants also make suggestions for trainees who would like to practice multilingual therapy as well as support that agencies can offer to their multilingual therapists. Limitations, practical implications, and future research directions are discussed.

The authors of this study utilized data from the Community College Survey of Student Engagement to conduct a critical examination of perceptions of institutional support among transfer-seeking community college students in North Carolina. We adopted an intersectional quantitative approach by centering racial and ethnic identity, and examining the influence of other social and institutional identities, integration, and institutional conditions on support perceptions among Black/African American, Hispanic/Latine, and White students. Multiple regression models affirmed the importance of interaction with institutional agents via socioacademic integration and transfer advising across racial and ethnic identity groups, with some within-group differences in intersectionality of identities and significant institutional conditions. Findings suggest the need for additional research on structural barriers to transfer, use of asset-based frameworks to understand student experiences pre- and post-transfer, and implementation of student-centered advising as the foundation of organizational cultures that promote equitable transfer.