Chief complaints and computed tomography results in the emergency department: a three-year retrospective cohort study.

BACKGROUND: Computed tomography (CT) is frequently performed in the patients who admitted to the emergency department (ED), discharged but returned to ED within 72 h. It is unknown whether the main complaints of patients assist physicians to use CT effectively. This study aimed to find the association between chief complaints and the CT results. METHODS: This three-year retrospective cohort study was conducted in the ED of a tertiary medical center. Adult patients who returned to the ED after the index visit were included from 2019 to 2021. Demographics, pre-existing diseases, chief complaints, and CT region were recorded by independent ED physicians. A logistic regression model with an odds ratio (OR) and 95% confidence interval (CI) was used to determine the relationship between chief complaints and positive CT results. RESULTS: In total, 7,699 patients revisited ED after the index visit; 1,202 (15.6%) received CT. The top chief complaints in patients who received CT were abdominal pain, dizziness, and muscle weakness. Patients with abdominal pain or gastrointestinal symptoms had a significantly higher rate of positive abdominopelvic CT than those without it (OR 2.83, 95% CI 1.98-4.05, p < 0.001), while the central nervous system and cardiopulmonary chief complaints were not associated (or negatively associated) with new positive CT findings. CONCLUSION: Chief complaints of patients on revisit to the ED are associated with different yields of new findings when CT scans of the chest, abdomen and head are performed. Physicians should consider these differential likelihoods of new positive findings based on these data.

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach. METHODS: This 3-year retrospective cohort study assessed adult patients between January 2019 and December 2021 from National Taiwan University Hospital Hsin-Chu Branch with high-risk ED revisit, defined as hospital or intensive care unit admission after ED return within 72 hours. A total of 150 features were preliminarily screened, and 79 were used in the prediction model. Deep learning, random forest, extreme gradient boosting (XGBoost) and stacked ensemble algorithm were used. The stacked ensemble model combined multiple ML models and performed model stacking as a meta-level algorithm. Confusion matrix, accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance. RESULTS: Analysis was performed for 6282 eligible adult patients: 5025 (80.0%) in the training set and 1257 (20.0%) in the testing set. High-risk ED revisit occurred for 971 (19.3%) of training set patients vs 252 (20.1%) in the testing set. Leading predictors of high-risk ED revisit were age, systolic blood pressure and heart rate. The stacked ensemble model showed more favourable prediction performance (AUROC 0.82) than the other models: deep learning (0.69), random forest (0.78) and XGBoost (0.79). Also, the stacked ensemble model achieved favourable accuracy and specificity. CONCLUSION: The stacked ensemble algorithm exhibited better prediction performance in which the predictions were generated from different ML algorithms to optimally maximise the final set of results. Patients with older age and abnormal systolic blood pressure and heart rate at the index ED visit were vulnerable to high-risk ED revisit. Further studies should be conducted to externally validate the model.

Exploring the Barriers and Facilitators of Mask-Wearing Behavior During the COVID-19 Pandemic in Taiwan, the United States, the Netherlands, and Haiti: A Qualitative Study.

OBJECTIVE: This study explored the barriers and facilitators of mask-wearing behaviors during the pandemic in Taiwan, the United States, the Netherlands, and Haiti. METHODS: Face-to-face interviews were conducted in Taiwan and online interviews were conducted with participants in the United States, the Netherlands, and Haiti. RESULTS: In general, the habit of wearing a mask before coronavirus disease 2019 (COVID-19) was reported by Taiwanese participants. Additionally, Taiwanese participants perceived that wearing a mask was a social responsibility during the pandemic, suggesting that the collectivistic context might influence mask-wearing behavior. Unlike the Taiwanese population, some people in the United States and the Netherlands were reluctant to wear masks due to perceived restrictions on their freedom. Participants from Haiti mentioned that people who wore masks encountered violence, bullying, and discrimination. The results of this study suggest that political leadership and mask mandates have a strong impact on people's mask-wearing behavior. CONCLUSIONS: These findings have valuable implications for the design of diverse behavioral interventions to enhance mask-wearing as part of infectious disease preparedness. Additionally, the findings from these countries offer valuable insights for the development of effective public health interventions to enhance society's resilience during the current pandemic and future infectious disease outbreaks.

Comparison of on-scene Glasgow Coma Scale with GCS-motor for prediction of 30-day mortality and functional outcomes of patients with trauma in Asia.

BACKGROUND AND IMPORTANCE: This study compared the on-scene Glasgow Coma Scale (GCS) and the GCS-motor (GCS-M) for predictive accuracy of mortality and severe disability using a large, multicenter population of trauma patients in Asian countries. OBJECTIVE: To compare the ability of the prehospital GCS and GCS-M to predict 30-day mortality and severe disability in trauma patients. DESIGN: We used the Pan-Asia Trauma Outcomes Study registry to enroll all trauma patients >18 years of age who presented to hospitals via emergency medical services from 1 January 2016 to November 30, 2018. SETTINGS AND PARTICIPANTS: A total of 16,218 patients were included in the analysis of 30-day mortality and 11 653 patients in the analysis of functional outcomes. OUTCOME MEASURES AND ANALYSIS: The primary outcome was 30-day mortality after injury, and the secondary outcome was severe disability at discharge defined as a Modified Rankin Scale (MRS) score ≥4. Areas under the receiver operating characteristic curve (AUROCs) were compared between GCS and GCS-M for these outcomes. Patients with and without traumatic brain injury (TBI) were analyzed separately. The predictive discrimination ability of logistic regression models for outcomes (30-day mortality and MRS) between GCS and GCS-M is illustrated using AUROCs. MAIN RESULTS: The primary outcome for 30-day mortality was 1.04% and the AUROCs and 95% confidence intervals for prediction were GCS: 0.917 (0.887-0.946) vs. GCS-M:0.907 (0.875-0.938), P  = 0.155. The secondary outcome for poor functional outcome (MRS ≥ 4) was 12.4% and the AUROCs and 95% confidence intervals for prediction were GCS: 0.617 (0.597-0.637) vs. GCS-M: 0.613 (0.593-0.633), P  = 0.616. The subgroup analyses of patients with and without TBI demonstrated consistent discrimination ability between the GCS and GCS-M. The AUROC values of the GCS vs. GCS-M models for 30-day mortality and poor functional outcome were 0.92 (0.821-1.0) vs. 0.92 (0.824-1.0) ( P  = 0.64) and 0.75 (0.72-0.78) vs. 0.74 (0.717-0.758) ( P  = 0.21), respectively. CONCLUSION: In the prehospital setting, on-scene GCS-M was comparable to GCS in predicting 30-day mortality and poor functional outcomes among patients with trauma, whether or not there was a TBI.

Updated trends in the outcomes of out-of-hospital cardiac arrest from 2017-2021: Prior to and during the coronavirus disease (COVID-19) pandemic.

Objective: This study aims to describe out-of-hospital cardiac arrest (OHCA) characteristics and trends before and during the coronavirus disease-2019 (COVID-19) pandemic in Taiwan. Methods: We conducted a retrospective cohort study using a 5-year interrupted time series analysis. Eligible adults with non-traumatic OHCAs from January 2017 to December 2021 in 3 hospitals (university medical center, urban second-tier hospital, and rural second-tier hospital) were retrospectively enrolled. Variables were extracted from the emergency medical service reports and medical records. The years 2020 and 2021 were defined as the COVID-19 pandemic period. Outcomes included survival to admission after a sustained return of spontaneous circulation, survival to hospital discharge, and good neurological outcomes (cerebral performance category score 1 or 2). Results: We analyzed 2819 OHCA, including 1227 from a university medical center, 617 from an urban second-tier hospital, and 975 from a rural second-tier hospital. The mean age was 71 years old, and 60% of patients were males. During the COVID-19 pandemic period, video-assisted endotracheal tube intubation replaced the traditional direct laryngoscopy intubation. The trends of outcomes in the pre-pandemic and pandemic periods varied among different hospitals. Compared with the pre-pandemic period, the outcomes at the university medical center during the COVID-19 pandemic were significantly poorer in several respects. The survival rate on admission dropped from 44.6% to 39.4% (P = 0.037), and the survival rate to hospital discharge fell from 17.5% to 14.9% (P = 0.042). Additionally, there was a notable decrease in patients' good neurological outcomes, declining from 13.2% to 9.7% (P = 0.048). In contrast, the outcomes in urban and rural second-tier hospitals during the COVID-19 pandemic did not significantly differ from those in the pre-pandemic period. Conclusions: COVID-19 may alter some resuscitation management in OHCAs. There were no overall significant differences in outcomes before and during COVID-19 pandemic, but there were significant differences in outcomes when stratified by hospital types.

Risk stratification of patients with chest pain who have an unscheduled revisit to the emergency department.

AIMS: Acute cardiovascular (CV) emergencies are critical conditions that require urgent attention in the emergency department (ED). Failure to make a timely diagnosis may result in unscheduled ED revisits and severe outcomes. Therefore, this study aimed to investigate the risk factors associated with potentially missed acute CV emergencies. METHODS AND RESULTS: This retrospective study enrolled adult patients who presented with chest pain and returned to the ED within 72 h. Demographic information, pre-existing medical conditions, chief complaints, triage level and vital signs, electrocardiography (ECG) reports, and laboratory data were collected from medical charts by independent physicians. The primary outcome was the diagnosis of acute CV diseases, including ACS, pulmonary embolism, unstable arrhythmia, acute decompensated heart failure, and aortic dissection. Multivariable logistic regression was used to analyze the association between variables and acute CV emergencies. A total of 453 eligible patients were included, with 60 (13.2%) patients diagnosed as acute CV emergencies at the ED revisit. Risk factors for acute CV emergencies included male gender (adjusted odds ratio [aOR] = 2.71, 95% confidence interval [CI] = 1.17-6.25), abnormal ECG rhythm (aOR = 10.33, 95% CI = 4.68-22.83), and abnormal changes in high sensitivity Troponin-T (hs-cTnT) during sequential follow-up (aOR = 6.52, 95% CI = 2.19-19.45). CONCLUSIONS: Male gender, abnormal ECG rhythm, and a significant increase in sequential follow-up hs-cTnT levels were identified as significant risk factors for acute CV emergencies. ED physicians should recognize these high-risk patients with chest pain to prevent misdiagnosis and potential severe complications.

A simplified scoring model for predicting bacteremia in the unscheduled emergency department revisits: The SADFUL score.

BACKGROUND: Bacteremia is a severe complication of infectious disease. Patients with a high bacteremia risk in the emergency department (ED) but misidentified would lead to the unscheduled revisits. This study aimed to develop a simplified scoring model to predict bacteremia in patients with unscheduled ED revisits. METHODS: Adult patients with unscheduled ED revisits within 72 h with a final diagnosis of infectious disease were retrospectively included. The development cohort included patients visiting the ED from January 1, 2019 to December 31, 2021. Internal validation was performed in patients visiting the ED from January 1, 2022 to March 31, 2022. Variables including demographics, pre-comorbidities, triage levels, vital signs, chief complaints, and laboratory data in the index visit were analyzed. Bacteremia was the primary outcome determined by blood culture in either index visits or revisits. RESULTS: The SADFUL score for predicting bacteremia comprised the following predictors: "S"egmented neutrophil percentage (+3 points), "A"ge > 55 years (+1 point), "D"iabetes mellitus (+1 point), "F"ever (+2 points), "U"pper respiratory tract symptoms (-2 points), and "L"eukopenia (2 points). The area under receiver operating characteristic curve with 95% confidence interval in the development (1802 patients, 190 [11%] with bacteremia) and the validation cohort (134 patients, 17 [13%] with bacteremia) were 0.78 (0.74-0.81) and 0.79 (0.71-0.88), respectively. CONCLUSIONS: The SADFUL score is a simplified useful tool for predicting bacteremia in patients with unscheduled ED revisits. The scoring model could help ED physicians decrease misidentification of patients at a high risk for bacteremia and potential complications.

Differences in the characteristics and patterns of adult emergency department return visits before and after the coronavirus disease 2019 outbreak.

BACKGROUND: Data about changes in the characteristics of ED return visits before and after the COVID-19 outbreak are limited. This study aimed to report the differences on utility in ED return visits after the COVID-19 outbreak. METHODS: This retrospective cohort study was conducted from 2019 to 2020. Adult patients with ED return visits were included in the analysis. Variables including demographic characteristics, pre-comorbidities, triage levels, vital signs, chief complaints, management, and diagnosis were recorded and confirmed via a manual assessment. RESULTS: The proportion of patients with ED visits decreased by 23%. Hence, that of patients with ED return visits also reduced from 2580 to 2020 patients (22%) after the COVID-19 outbreak. The average age (60-57.8 years) of patients with return visits was significantly younger, and the proportion of female patients decreased remarkably. Further, the proportion of patients with chronic pre-existing diseases at the return visit significantly differed after the COVID-19 outbreak. The proportion of patients with chief complaints including dizziness, dyspnea, cough, vomiting, diarrhea, and chills during the return visits significantly differed before and after the COVID-19 pandemic. In the multivariable logistic regression model, age, high triage level were significantly associated with unfavorable outcome return visit. CONCLUSION: The use of services in the ED has changed since the COVID-19 outbreak. Hence, the proportion of patients with unplanned return visits within 72 h decreased. After the COVID-19 outbreak, people are now cautious whether they should return to the ED, as in the pre-pandemic situation, or just treat conservatively at home.

Utility of carotid ultrasound on prediction of 1-year mortality in emergency department patients with neurological deficits: A 10-year population-based cohort study.

BACKGROUND: This study aimed to investigate the association between the carotid ultrasound results and 1-yr mortality of patients with neurological deficits in the emergency department (ED). METHODS: This study included patients with neurological symptoms who presented to the ED between January 1, 2009 and December 31, 2018, and underwent sonographic imaging of the bilateral carotid bulb, common carotid artery (CCA), internal carotid artery (ICA), and external carotid arteries. A stenosis degree of >50% was defined as significant carotid stenosis. Carotid plaque score (CPS) was calculated by adding the score of stenosis severity of all segments. The association between carotid ultrasound results and 1-yr mortality was investigated using the Cox regression model. RESULTS: The analysis included 7,961 patients (median age: 69 yr; men: 58.7%). Among them, 247 (3.1%) passed away from cardiovascular (CV)-related causes, and 746 (9.4%) died within a year. The mortality group presented with more significant carotid stenosis of the carotid bulb, CCA, or ICA and had a higher median CPS. A higher CPS was associated with a greater 1-yr all-cause mortality (adjusted hazard ratio [aHR] = 1.08; 95% confidence interval [CI] = 1.03-1.13; p = 0.001; log-rank p < 0.001) and CV-related mortality (aHR = 1.13; 95% CI = 1.04-1.22; p = 0.002, log-rank p < 0.001). Significant stenosis of either carotid artery segment did not result in a higher risk of 1-yr mortality. CONCLUSIONS: We comprehensively investigated the utility of carotid ultrasound parameters on predicting mortality in this 10-yr population-based cohort, which included over 7,000 patients with acute neurological deficits presented to the ED. The result showed that CPS could be used as risk stratification tools for 1-yr all-cause and CV mortality.

Assessment of the Functional Capacity and Preparedness of the Haitian Healthcare System to Fight against the COVID-19 Pandemic: A Narrative Review.

Low-income countries, such as Haiti, are facing challenges in fighting the COVID-19 pandemic due to resource shortages and fragile healthcare systems. This study assessed the functional capacity and preparedness of the Haitian healthcare system regarding the COVID-19 pandemic. It employed a narrative review approach to analyze secondary data and used the Donabedian model and the global health security index as the theoretical frameworks to evaluate preparedness. The findings reveal that Haiti faces challenges in tackling the COVID-19 pandemic due to a lack of biosafety and biosecurity regulations, inadequate laboratory systems for COVID-19 testing, and shortages of human resources and personal protective equipment. Moreover, poverty remains widespread, and people lack access to clean water and sanitation services, resulting in a high risk of COVID-19 infection. Furthermore, a lack of communication, rumors, the circulation of fake news regarding COVID-19, and stigmatization cause distrust and reduce the number of people seeking healthcare services. Haiti faces challenges with respect to tackling the pandemic. The Haitian government can strengthen and improve the capacity of the healthcare system to fight against the COVID-19 pandemic and infectious diseases emerging in the future.

Building lexical networks: Preschoolers extract different types of information in cross-situational learning.

Children's everyday learning environment is semantically structured. For example, semantically related things (e.g., fork and spoon) usually co-occur in the same contexts. The current study examines the effects of semantically structured contexts on preschool-age children's (N = 65, 33 girls, age range: 52-68 months) use of statistical information to learn novel word-object mappings. Children were assigned into one of two conditions, in which objects from the same semantic category repeatedly co-occurred in the same trials (Same-category condition) or objects from different categories repeatedly co-occurred in the same trials (Different-categories condition). Children's word learning performance in the two conditions were comparable. However, their errors at test suggested that information extracted by children in the two conditions differed. Importantly, children in the Same-category condition extracted both statistical and semantic relationships from the stimuli.

A matter of trust: a qualitative comparison of the determinants of COVID-19 vaccine hesitancy in Taiwan, the United States, the Netherlands, and Haiti.

COVID-19 vaccination is an effective intervention preventing individuals from contracting SARS-CoV-2 or transmitting the virus to others. However, in many countries, vaccine hesitancy has impeded the progress of mass vaccination to reach herd immunity. This study aimed to understand the similarities and differences in the determinants of COVID-19 vaccine hesitancy in Taiwan, the United States, the Netherlands, and Haiti. A qualitative study was conducted by face-to-face interviews with participants in Taiwan and remote online interviews with participants in the United States, the Netherlands, and Haiti. In total, 47 interviews were conducted. A reflective thematic analysis was employed to analyze the collected data. Distrust of COVID-19 vaccines was reported by the participants in all countries. A perception of a lack of necessity or urgency to be vaccinated was reported by the Taiwanese and Haitian participants. Lack of knowledge regarding COVID-19 vaccines was reported by the Taiwanese, U.S. and Haitian participants, contributing to hesitation or refusal to vaccination. Regarding misinformation and rumors, misinformation was found among a few Taiwanese and Dutch participants. Additionally, rumors concerning COVID-19 vaccines were mentioned by the Dutch and Haitian participants. Furthermore, a lack of verified information was reported by the participants in all four countries. Overall, the current study suggests that vaccine hesitancy exists among participants in Taiwan, the United States, the Netherlands, and Haiti. Building trust in the COVID-19 vaccine, cultivating vaccine literacy, clarifying misinformation and rumors concerning COVID-19 vaccines, and providing verified information are critical for increasing public acceptance of the COVID-19 vaccine.

Intravenous antibiotics at the index emergency department visit as an independent risk factor for hospital admission at the return visit within 72 hours.

INTRODUCTION: Although infection was the most common symptom in patients returning to the ED, whether intravenous antibiotic administration at the index visit could serve as an indicator of patients with infectious diseases at high risk for hospital admission after returning to the ED within a short period of time remains unclear. The study aimed to investigate the potential risk factors for hospital admission in patients returning to the ED within 72 hours with a final diagnosis of infectious diseases. MATERIAL AND METHODS: This retrospective cohort study analyzed return visits to the ED from January to December 2019. Adult patients aged >20 years who had a return visit to the ED within 72 hours with an infectious disease were included herein. In total, 715 eligible patients were classified into the intravenous antibiotics and non-intravenous antibiotics group (reference group). The outcome studied was hospital admission to general ward and intensive care unit (ICU) at the return visits. RESULTS: Patients receiving intravenous antibiotics at index visits had significantly higher risk-approximately two times-for hospital admission at the return visits than those did not (adjusted odds ratio = 2.47, 95% CI = 1.34-4.57, p = 0.004). For every 10 years increase in age, the likelihood for hospital admission increased by 38%. Other factors included abnormal respiratory rate and high C-reactive protein levels. CONCLUSIONS: Intravenous antibiotic administration at the index visit was an independent risk factor for hospital admission at return visits in patients with an infection disease. Physicians should consider carefully before discharging patients receiving intravenous antibiotics.

Governmental public health in Taiwan.

A healthy and safe public health environment is a fundamental responsibility of government; achieving it requires collaboration across multiple sectors. Public health services include, for example, vaccination and quarantine for infectious diseases; health promotion, such as anti-smoking campaigns for noncommunicable diseases; and health insurance for universal health coverage. All these services require intersectoral actions in which the government must play a fundamental role, either partially or totally. The Taiwanese outlook on governmental public health infrastructure and professionalization of public health is given in this paper. It also describes the national governmental public health measures that were employed during the Covid-19 pandemic and discusses the challenges ahead for the country's governmental public health. Governmental public health is essential and should not be affected by changes in political forms or socioeconomic development. Instead, effective governmental public health will promote these developments while protecting citizens' right to health.

Parent-Child Joint Behaviors in Novel Object Play Create High-Quality Data for Word Learning.

This research takes a dyadic approach to study early word learning and focuses on toddlers' (N = 20, age: 17-23 months) information seeking and parents' information providing behaviors and the ways the two are coupled in real-time parent-child interactions. Using head-mounted eye tracking, this study provides the first detailed comparison of children's and their parents' behavioral and attentional patterns in two free-play contexts: one with novel objects with to-be-learned names (Learning condition) and the other with familiar objects with known names (Play condition). Children and parents in the Learning condition modified their individual and joint behaviors when encountering novel objects with to-be-learned names, which created clearer signals that reduced referential ambiguity and potentially facilitated word learning.

Mental health crisis in healthcare providers in the COVID-19 pandemic: a cross-sectional facility-based survey.

OBJECTIVES: During a pandemic, healthcare providers experience increased mental and physical burden. Burnout can lead to treatment errors, patient mortality, increased suicidal ideation and substance abuse as well as medical malpractice suits among medical staff. This study aimed to investigate the occurrence of burnout, acute stress disorder, anxiety disorder and depressive disorder among healthcare providers at the third month of the COVID-19 pandemic. DESIGN: A cross-sectional facility-based survey. SETTING: Hospitals around the country with different levels of care. PARTICIPANTS: A total of 1795 respondents, including 360 men and 1435 women who participated in the survey. PRIMARY OUTCOME MEASURES: Burnout was assessed using the Physician Work Life Study. A score of ≥3 implied burnout. RESULTS: Of the 1795 respondents, 723 (40.3%) reported burnout, and 669 (37.3%) cared for patients with COVID-19. Anxiety levels were mild in 185 (10.3%) respondents, moderate in 209 (11.6%) and severe in 1401 (78.1%). The mean Center for Epidemiologic Studies Depression Scale-10 score was 9.5±6.3, and 817 (45.5%) respondents were classified as having depression. Factors associated with burnout were working in acute and critical care (ACC) divisions (adjusted OR (aOR)=1.84, 95% CI 1.20 to 3.39, p=0.019), caring for patients with COVID-19 (aOR=3.90, 95% CI 1.14 to 13.37, p=0.031) and having depressive disorder (aOR=9.44, 95% CI 7.44 to 11.97, p<0.001). CONCLUSIONS: Physicians and nurses are vulnerable to burnout during a pandemic, especially those working in ACC divisions. Anxiety disorder, depressive disorder and care of patients with COVID-19 may be factors that influence the occurrence of burnout among healthcare providers.

Lipidomics of children and adolescents exposed to multiple industrial pollutants.

BACKGROUND: There are limited studies on the lipidomics of children and adolescents exposed to multiple industrial pollutants. OBJECTIVES: In this study, we aimed to investigate lipid profile perturbations in 99 children and adolescents (aged 9-15) who lived in a polluted area surrounding the largest petrochemical complex in Taiwan. Previous studies have reported increased risks of acute and chronic diseases including liver dysfunctions and chronic kidney disease (CKD) in residents living in this area. METHODS: We measured urinary concentrations of 11 metals and metalloids and polycyclic aromatic hydrocarbons (PAHs) metabolite 1-hydroxypyrene (1-OHP) as exposure biomarkers, and urinary oxidative stress biomarkers and serum acylcarnitines as early health effect biomarkers. The association between individual exposure biomarkers and early health effect biomarkers were analyzed using linear regression, while association of combined exposure biomarkers with four oxidative stress biomarkers and acylcarnitines were analyzed using weighted quantile sum (WQS) regression. Lipid profiles were analyzed using an untargeted liquid chromatography mass spectrometry-based technique. "Meet-in-the-middle" approach was applied to identify potential lipid features that linked multiple industrial pollutants exposure with early health effects. RESULTS: We identified 15 potential lipid features that linked elevated multiple industrial pollutants exposure with three increased oxidative stress biomarkers and eight deregulated serum acylcarnitines, including one lysophosphatidylcholines (LPCs), four phosphatidylcholines (PCs), and two sphingomyelins (SMs) that were up-regulated in high exposure group compared to low exposure group, and two LPCs, four PCs, and two phosphatidylinositols (PIs) down-regulated in high exposure group compared to low exposure group. CONCLUSION: Our findings could provide information for understanding the health effects, including early indicators and biological mechanism identification, of children and adolescents exposed to multiple industrial pollutants during critical stages of development.

The distributional properties of exemplars affect category learning and generalization.

What we learn about the world is affected by the input we receive. Many extant category learning studies use uniform distributions as input in which each exemplar in a category is presented the same number of times. Another common assumption on input used in previous studies is that exemplars from the same category form a roughly normal distribution. However, recent corpus studies suggest that real-world category input tends to be organized around skewed distributions. We conducted three experiments to examine the distributional properties of the input on category learning and generalization. Across all studies, skewed input distributions resulted in broader generalization than normal input distributions. Uniform distributions also resulted in broader generalization than normal input distributions. Our results not only suggest that current category learning theories may underestimate category generalization but also challenge current theories to explain category learning in the real world with skewed, instead of the normal or uniform distributions often used in experimental studies.