Stability and Falls Evaluations in AMPutees (SAFE-AMP 2): Reduced functional mobility is associated with a history of injurious falls in lower limb prosthesis users

BACKGROUND

Injurious falls have a high cost and economic impact on an individual and the health system. Several studies have assessed performance-based functional mobility in lower limb prosthesis (LLP) users and fall risk including fall history. However, limited data exist regarding the relationship between functional mobility and a history of injurious falls in individuals who use a LLP. Such information could inform clinical practice and decision making from prosthesis design to policy. The purpose of this study was to identify factors associated with a history of injurious falls among LLP users using a clinical outcomes database.

METHODS

Retrospective (2016-2018) observational study. Logistic regression applied.

RESULTS

A final sample of 12,044 LLP users was included for analysis. Within the sample, 1,529 individuals reported a history of an injurious fall within the previous 6 months. Self-reported functional mobility was stratified into low, middle, and high levels: differences were found between levels for history of an injurious fall. The lowest mobility level was associated with 2.29 higher odds of a history of an injurious fall (95% CI: 1.96-2.69) indicating a potentially greater serious fall risk compared to those with higher mobility levels while controlling for covariates (sex, cause of amputation and level of amputation).

CONCLUSION(S)

Self-reported functional mobility was associated with a history of injurious falls in LLP users. The Prosthetic Limb Users Survey of Mobility is an accessible tool that prosthetists could use to identify individuals with a high risk of falls; this can inform care planning. Rehabilitation plans and prosthesis designs that target LLP users who report low functional mobility may positively impact health outcomes.

Simulating and Forecasting the COVID-19 Spread in a U.S. Metropolitan Region with a Spatial SEIR Model

The global COVID-19 pandemic has taken a heavy toll on health, social, and economic costs since the end of 2019. Predicting the spread of a pandemic is essential to developing effective intervention policies. Since the beginning of this pandemic, many models have been developed to predict its pathways. However, the majority of these models assume homogeneous dynamics over the geographic space, while the pandemic exhibits substantial spatial heterogeneity. In addition, spatial interaction among territorial entities and variations in their magnitude impact the pandemic dynamics. In this study, we used a spatial extension of the SEIR-type epidemiological model to simulate and predict the 4-week number of COVID-19 cases in the Charlotte-Concord-Gastonia Metropolitan Statistical Area (MSA), USA. We incorporated a variety of covariates, including mobility, pharmaceutical, and non-pharmaceutical interventions, demographics, and weather data to improve the model's predictive performance. We predicted the number of COVID-19 cases for up to four weeks in the 10 counties of the studied MSA simultaneously over the time period 29 March 2020 to 13 March 2021, and compared the results with the reported number of cases using the root-mean-squared error (RMSE) metric. Our results highlight the importance of spatial heterogeneity and spatial interactions among locations in COVID-19 pandemic modeling.

Channel-Hopping Sequence and Rendezvous MAC for Cognitive Radio Networks

In cognitive radio networks (CRNs), two secondary users (SUs) need to meet on a channel among multiple channels within a finite time to establish a link, which is called rendezvous. For blind rendezvous, researchers have devised ample well-grounded channel hopping (CH) sequences that guarantee smaller time-to-rendezvous. However, the best part of these works lacks the impact of network factors, particularly channel availability and collision during rendezvous. In this study, a new CH scheme is investigated by jointly considering the medium access control (MAC) protocol for single-hop multi-user CRNs. The analysis of our new variable hopping sequence (V-HS) guarantees rendezvous for the asymmetric channel model within a finite time. Although this mathematical concept guarantees rendezvous between two SUs, opportunities can be overthrown because of the unsuccessful exchange of control packets on that channel. A successful rendezvous also requires the exchange of messages reliably while two users visit the same channel. We propose a MAC protocol, namely ReMAC, that can work with V-HS and CH schemes. This design allows multiple rendezvous opportunities when a certain user visits the channel and modifies the conventional back-off strategy to maintain the channel list. Both simulation and analytical results exhibited improved performance over the previous approaches.

Garcinia morella extract confers dopaminergic neuroprotection by mitigating mitochondrial dysfunctions and inflammation in mouse model of Parkinson's disease

Dopaminergic neuroprotection is the main interest in designing novel therapeutics against Parkinson's disease (PD). In the process of dopaminergic degeneration, mitochondrial dysfunctions and inflammation are significant. While the existing drugs provide symptomatic relief against PD, a therapy conferring total neuroprotection by targeting multiple degenerative pathways is still lacking. Garcinia morella is a common constituent of Ayurvedic medication and has been used for the treatment of inflammatory disorders. The present study investigates whether administration of G. morella fruit extract (GME) in MPTP mouse model of PD protects against dopaminergic neurodegeneration, including the underlying pathophysiologies, and reverses the motor behavioural abnormalities. Administration of GME prevented the loss of dopaminergic cell bodies in the substantia nigra and its terminals in the corpus striatum of PD mice. Subsequently, reversal of parkinsonian behavioural abnormalities, viz. akinesia, catalepsy, and rearing, was observed along with the recovery of striatal dopamine and its metabolites in the experimental model. Furthermore, reduced activity of the mitochondrial complex II in the nigrostriatal pathway of brain of the mice was restored after the administration of GME. Also, MPTP-induced enhanced activation of Glial fibrillary acidic protein (GFAP) and neuronal nitric oxide synthase (nNOS) in the nigrostriatal pathway, which are the markers of inflammatory stress, were found to be ameliorated on GME treatment. Thus, our study presented a novel mode of dopaminergic neuroprotection by G. morella in PD by targeting the mitochondrial dysfunctions and neuroinflammation, which are considered to be intricately associated with the loss of dopaminergic neurons.

Sepsis Management in Southeast Asia: A Review and Clinical Experience

Sepsis is a life-threatening condition that causes a global health burden associated with high mortality and morbidity. Often life-threatening, sepsis can be caused by bacteria, viruses, parasites or fungi. Sepsis management primarily focuses on source control and early broad-spectrum antibiotics, plus organ function support. Comprehensive changes in the way we manage sepsis patients include early identification, infective focus identification and immediate treatment with antimicrobial therapy, appropriate supportive care and hemodynamic optimization. Despite all efforts of clinical and experimental research over thirty years, the capacity to positively influence the outcome of the disease remains limited. This can be due to limited studies available on sepsis in developing countries, especially in Southeast Asia. This review summarizes the progress made in the diagnosis and time associated with sepsis, colistin resistance and chloramphenicol boon, antibiotic abuse, resource constraints and association of sepsis with COVID-19 in Southeast Asia. A personalized approach and innovative therapeutic alternatives such as CytoSorb® are highlighted as potential options for the treatment of patients with sepsis in Southeast Asia.

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July-December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July-December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July-December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.

Dynamic downscaling and daily nowcasting from influenza surveillance data

Real-time trends from surveillance data are important to assess and develop preparedness for influenza outbreaks. The overwhelming testing demand and limited capacity of testing laboratories for viral positivity render daily confirmed case data inaccurate and delay its availability in preparedness. Using Bayesian dynamic downscaling models, we obtained posterior estimates for daily influenza incidences from weekly estimates of the Centers for Disease Control and Prevention and daily reported constitutional and respiratory complaints during emergency department (ED) visits obtained from the state health departments. Our model provides one-day and seven-day lead forecasts along with 95 % $$ \% $$ prediction intervals. Our hybrid Markov Chain Monte Carlo and Kalman filter algorithms facilitate faster computation and enable us to update our estimates as new data become available. Our method is tested and validated using the State of Michigan data over the years 2009-2013. Reported constitutional and respiratory complaints at the EDs showed strong correlations of 0.81 and 0.68 respectively, with influenza rates. In general, our forecast model can be adapted to track an outbreak with only one respiratory virus as a causative agent.

An assessment of the non-fatal crash risks associated with substance use during rush and non-rush hour periods in the United States

BACKGROUND

Understanding how substance use is associated with severe crash injuries may inform emergency care preparedness.

OBJECTIVES

This study aims to assess the association of substance use and crash injury severity at all times of the day and during rush (6-9 AM; 3-7 PM) and non-rush-hours. Further, this study assesses the probabilities of occurrence of low acuity, emergent, and critical injuries associated with substance use.

METHODS

Crash data were extracted from the 2019 National Emergency Medical Services Information System. The outcome variable was non-fatal crash injury, assessed on an ordinal scale: critical, emergent, low acuity. The predictor variable was the presence of substance use (alcohol or illicit drugs). Age, gender, injured part, revised trauma score, the location of the crash, the road user type, and the geographical region were included as potential confounders. Partially proportional ordinal logistic regression was used to assess the unadjusted and adjusted odds of critical and emergent injuries compared to low acuity injury.

RESULTS

Substance use was associated with approximately two-fold adjusted odds of critical and emergent injuries compared to low acuity injury at all times of the day and during the rush and non-rush hours. Although the proportion of substance use was higher during the non-rush hour period, the interaction effect of rush hour and substance use resulted in higher odds of critical and emergent injuries compared to low acuity injury.

CONCLUSION

Substance use is associated with increased odds of critical and emergent injury severity. Reducing substance use-related crash injuries may reduce adverse crash injuries.

Age of Bottle Cessation and BMI-for-Age Percentile among Children Aged Thirty-Six Months Participating in WIC

Background: Children's age at bottle weaning typically ranges from 12 to 24 months. The recommended age of bottle weaning varies. The American Academy of Pediatrics recommends weaning by 12 months; The American Academy of Pediatric Dentistry recommends 12-15 months; The US Department of Agriculture recommends 18 months. Prolonged bottle use is associated with dental caries, iron-deficiency anemia, and child overweight or obesity. We examined factors associated with age of bottle cessation, and the association between age of bottle cessation and BMI-for-age percentile at age 36 months among Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participants. Methods: Data were from the WIC Infant and Toddler Feeding Practices Study-2 (ITFPS-2). The ITFPS-2, a longitudinal study of WIC participants (mothers and their children) began in 2013. We used Cox proportional hazards models to identify factors associated with bottle cessation and multivariate linear regression to examine the association between age of bottle cessation and BMI. Results: About 34% of children used a bottle longer than 12 months, and 13% longer than 18 months. Bottle cessation at older ages was associated with Hispanic ethnicity, multiparity, low income, low education, higher caregiver weight, and not initiating breastfeeding. The adjusted children's BMI-for-age percentile at age 36 months increased by 0.47 for each additional month of bottle use. Conclusion: Prolonged bottle use was associated with increased children's BMI-for-age percentile. Future research is warranted to determine the optimal age to recommend bottle cessation for WIC participants.

Estimating mortality from coal workers' pneumoconiosis among Medicare beneficiaries with pneumoconiosis using binary regressions for spatially sparse data

Background

Coal workers' pneumoconiosis (CWP) is an occupational lung disease due to inhalation of coal dust. We estimated mortality from CWP and other pneumoconioses among Medicare beneficiaries.

Methods

We used the 5% Medicare Limited Claims Data Set, 2011–2014, to identify patients diagnosed with ICD‐9‐CM 500 (CWP) through 505 (Asbestosis, Pneumoconiosis due to other silica or silicates, Pneumoconiosis due to other inorganic dust, Pneumonopathy due to inhalation of other dust, and Pneumoconiosis, unspecified) codes. We applied binary regression models with spatial random effects to determine the association between CWP and mortality. Our inferences are based on Bayesian spatial hierarchical models, and model fitting was performed using Integrated Nested Laplace Approximation (INLA) algorithm in R/RStudio software.

Results

The median age of the sample was 76 years. In a sample of 8531 Medicare beneficiaries, 2568 died. Medicare beneficiaries with CWP had 25% higher odds of death (adjusted OR: 1.25, 95% CI: 1.07, 1.46) than those with other types of pneumoconiosis. The number of comorbid conditions elevated the odds of death by 10% (adjusted OR: 1.10, 95% CI: 1.09, 1.10).

Conclusion

CWP increases the likelihood of death among Medicare beneficiaries. Healthcare professionals should make concerted efforts to monitor patients with CWP to prevent premature mortality.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study

Background

SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains.

Methods

Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches.

Findings

Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts.

Conclusions

Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

A College Fast-Food Environment and Student Food and Beverage Choices: Developing an Integrated Database to Examine Food and Beverage Purchasing Choices among College Students

Universities typically offer residential students a variety of fast-food dining options as part of the student meal plan. When residential students make fast-food purchases on campus there is a digital record of the transaction which can be used to study food purchasing behavior. This study examines the association between student demographic, economic, and behavioral factors and the healthfulness of student fast-food purchases. The 3781 fast-food items sold at the University of North Carolina at Charlotte from fall 2016 to spring 2019 were given a Fast-Food Health Score. Each student participating in the university meal plan was given a Student Average Fast-Food Health Score; calculated by averaging the Fast-Food Health Scores associated with each food and beverage item the student purchased at a fast-food vendor, concession stand, or convenience store over a semester. This analysis included 14,367 students who generated 1,593,235 transactions valued at $10,757,110. Multivariate analyses were used to examine demographic, economic, and behavioral factors associated with Student Average Fast-Food Health Scores. Being of a low income, spending more money on fast-food items, and having a lower GPA were associated with lower Student Average Fast-Food Health Scores. Future research utilizing institutional food transaction data to study healthy food choices is warranted.

Factors that Influence Time to Prosthesis Receipt after Lower Limb Amputation: A Cox Proportional Hazard Model Regression

INTRODUCTION

Early mobility, functional independence, and ambulation are associated benefits after LLA, while an increased risk of clinical complications is associated with no prosthesis.

OBJECTIVE

The aims of this study were to describe time to prosthesis receipt after amputation and to assess the impact of patient demographic and health factors on the rate of prosthesis receipt within 12 months post-LLA.

DESIGN

A retrospective cohort analysis using commercial administrative claims data. Kaplan-Meier and Cox proportional-hazards models were applied to assess time to prosthesis receipt.

SETTING

Watson/Truven administrative database 2014-2016.

PARTICIPANTS

Adults age 18-64 with LLA who maintained their current insurance enrollment for 12 months after amputation.

INTERVENTIONS

Independent variables included diabetes/vascular disease status, amputation level, age, sex, and region.

MAIN OUTCOME MEASURE

Prosthesis receipt was defined based on the presence of codes billed for prosthesis services. Time was measured in days from date of amputation surgery.

RESULTS

Among the sample, 510 individuals maintained enrollment for 12 months post-amputation, of which 443 individuals received a prosthesis within that period (79% BK and 21% AK). The adjusted average rate of time to prosthesis receipt was 138 (95% CI: 113-185) days. Individuals with diabetes/vascular disease were 22% (HR: 1.22 95% CI: 1.02-1.49) more likely to receive a prosthesis earlier than individuals without diabetes/vascular disease and females received a prosthesis later than males at 141 (95% CI: 126-162) days vs 106 (95% CI: 96-119) days, respectively.

CONCLUSION

This study expands the understanding of factors that influence the likelihood of receiving a prosthesis along with the timing of prosthesis receipt after LLA among commercially insured adults. At least half of this sample received a prosthesis within 5 months or less. Disparities in timing and access to a prosthesis based on amputation level and sex were noted, future efforts are needed to address these issues. This article is protected by copyright. All rights reserved.

Assessment of Mitochondrial Complex II and III Activity in Brain Sections: A Histoenzymological Technique

Mitochondrial impairment stands to be a major factor which contributes to the onset and pathogenesis of several neurodegenerative disorders, of which Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD) are among the notable ones. Extensive researches suggest the probable role of mitochondrial complex II and III dysfunction as underlying players in the pathogenesis of AD, PD, and HD. Present scenario of the world in occurrence of neurodegenerative disorders demands more research and development in this field. The development of enzyme histochemistry as an analytical technique has eased the assessment of mitochondrial complex activity at both qualitative and quantitative levels. Based on the principle of redox reactions of chromogenic substrates catalyzed by the enzymes in question, this histochemical analysis has been applied by researchers worldwide and has proved to be reliable. The present chapter hereby discusses the methods followed in performing histoenzymology of mitochondrial complex II and III activity. The chapter also puts light on the precautions which should be followed while performing histoenzymology in order to yield significant results.

The association of crash response times and deaths at the crash scene: A cross-sectional analysis using the 2019 National Emergency Medical Service Information System

BACKGROUND

Deaths at the crash scene (DAS) are crash deaths that occur within minutes after a crash. Rapid crash responses may reduce the occurrence of DAS.

OBJECTIVES

This study aims to assess the association of crash response time and DAS during the rush and nonrush hour periods by rurality/urbanicity.

METHOD

This single-year cross-sectional study used the 2019 National Emergency Medical Services (EMS) Information System. The outcome variable was DAS. The predictor variables were crash response measures: EMS Chute Initiation Time (ECIT) and EMS Travel Time (ETT). Age, gender, substance use, region of the body injured, and the revised trauma score were used as potential confounders. Logistic regression was used to assess the unadjusted and adjusted odds of DAS.

RESULTS

A total of 654,675 persons were involved in EMS-activated road crash events, with 49.6% of the population exposed to crash events during the rush hour period. A total of 2,051 persons died at the crash scene. Compared to the baseline of less than 1 minute, ECIT ranging from 1 to 5 minutes was significantly associated with 58% (95% CI: 1.45-1.73) increased odds of DAS. Also, when compared to the baseline of less than 9 minutes, ETT ranging between 9 and 18 minutes was associated with 34% (95% CI: 1.22-1.47) increased odds of DAS. These patterns were consistent during the rush and nonrush hour periods and across rural and urban regions.

CONCLUSION

Reducing crash response times may reduce the occurrence of DAS.

Computation offloading technique for energy efficiency of smart devices

The substantial number of wearable devices in the healthcare industry and the continuous growth of the market procreates the demand for computational offloading. Despite major development of wearable devices and offloading techniques, there are several concerns such as latency, battery power, and computation capability that requires significant development. In this paper, we focus on the fact that most smart wearable devices have Bluetooth pairing with smartphones, and Bluetooth communication is significantly energy-efficient compare to 3G/LTE or Wi-Fi. We propose a computation offloading technique that offloads from the smartphone to the cloud server considering the decision model of both wearable devices and smartphones. Mobile cloud computing can elevate the capacity of smartphones considering the battery state and efficient communications with the cloud. In our model, we increase the energy efficiency of smart devices. To accomplish this, a Dhrystone Millions of Instructions per Second (DMIPS)-based workload measurement model along with a computation offloading decision model were created. According to the performance evaluation, offloading from wearable devices to smartphones and offloading once to cloud server can reduce energy consumption significantly.

Evaluating the association of self-reported psychological distress and self-rated health on survival times among women with breast cancer in the U.S

BACKGROUND

Psychological distress and self-rated health status may create additional complexities in patients already diagnosed with breast cancer. This study aims to assess the association of self-report-based assessment of psychological distress and self-rated health on survival times among women with breast cancer diagnoses.

METHODS

Seventeen-year data from the Integrated Public Use Microdata Series-National Health Interview Survey (IPUMS-NHIS) were pooled and analyzed. Women who were aged 30 to 64 years old, with breast cancer diagnosis were selected (n = 2,819). The outcome variable was time to death. The independent variables were self-reported assessment of psychological distress and self-rated health. Psychological distress was defined using the Kessler-6 scale while self-rated health was measured on a 3-point Likert scale: Poor, Fair, and Good-to-Excellent (referred to as good for brevity). We computed unadjusted and adjusted hazard ratios (HR) using Cox-Proportional Hazard regression models with sociodemographic characteristics and measures of health care access used as potential confounders. Significance was set at alpha = 0.05.

RESULTS

Women with breast cancer assessed as having psychological distress had 46% (Adjusted HR: 1.46; 95% CI: 1.02-2.09) increased risks of mortality. Also, women who rated their health as poor or fair had a significantly elevated mortality risk (Poor Health: Adjusted HR: 3.05; 95% CI: 2.61-4.69; Fair Health: Adjusted HR: 1.83; 95% CI: 1.43-2.35) as compared to women with good health status.

CONCLUSIONS

Self-reported psychological distress and fair and poor self-rated health are associated with reduced survival times among women with breast cancer diagnoses.

Exploring the relationship of rush hour period and fatal and non-fatal crash injuries in the U.S.: A systematic review and meta-analysis

Road crashes are preventable causes of morbidity and mortality. In the U.S., substantial crashes occur during the rush hour period. The rush hour represents the period of the day during which the density of humans and vehicles in the road environment is highest. In the U.S., the rush hour period is bi-modal, occurring in the morning and the afternoon, at times that vary by state and urban-rural status. This systematic review and meta-analysis aimed to evaluate the association between the rush hour period and fatal and non-fatal crash injuries. Selected articles were limited to peer-reviewed full-text articles that measured crash injury as an outcome and rush hour as either a predictor, covariate, stratification, or a control variable. A total of 17 articles were identified for systematic review and nine articles were included in the meta-analysis. Across the selected studies, the rush-hour period signified the period of "peak traffic flow." During the rush hour period, aggressive driving behavior, truck driving, bicycle riding, and precipitation were associated with increased crash events or crash injuries. Across the nine studies included in the meta-analysis, the effective sample size was 236,433. The rush-hour period was associated with a 28% increased risk of fatal crash injury (Pooled RR: 1.28; 95% CI: 1.11-1.45) and the morning rush hour period was associated with 36% increased crash injury risk (Pooled RR: 1.36; 95% CI: 1.13-1.59). The rush hour period, though less commonly studied as a predictor of fatal and non-fatal crash injuries, represents an important domain in need of crash injury prevention attention. The knowledge of the pattern of crash injuries, as it varies across countries, states, regions, and county can inform policy and intervention, in the presence of competing public health needs.

Carbon-based metal-free electrocatalysts: from oxygen reduction to multifunctional electrocatalysis

Since the discovery of N-doped carbon nanotubes as the first carbon-based metal-free electrocatalyst (C-MFEC) for oxygen reduction reaction (ORR) in 2009, C-MFECs have shown multifunctional electrocatalytic activities for many reactions beyond ORR, such as oxygen evolution reaction (OER), hydrogen evolution reaction (HER), carbon dioxide reduction reaction (CO₂RR), nitrogen reduction reaction (NRR), and hydrogen peroxide production reaction (H₂O₂PR). Consequently, C-MFECs have attracted a great deal of interest for various applications, including metal-air batteries, water splitting devices, regenerative fuel cells, solar cells, fuel and chemical production, water purification, to mention a few. By altering the electronic configuration and/or modulating their spin angular momentum, both heteroatom(s) doping and structural defects (e.g., atomic vacancy, edge) have been demonstrated to create catalytic active sites in the skeleton of graphitic carbon materials. Although certain C-MFECs have been made to be comparable to or even better than their counterparts based on noble metals, transition metals and/or their hybrids, further research and development are necessary in order to translate C-MFECs for practical applications. In this article, we present a timely and comprehensive, but critical, review on recent advancements in the field of C-MFECs within the past five years or so by discussing various types of electrocatalytic reactions catalyzed by C-MFECs. An emphasis is given to potential applications of C-MFECs for energy conversion and storage. The structure-property relationship for and mechanistic understanding of C-MFECs will also be discussed, along with the current challenges and future perspectives.