Elderly Drivers Research Articles

SafeDrive Pro IoT Based Driver Verification System

SafeDrive Pro is an IoT-based Driver Verification System designed to address the rise in vehicular accidents involving underage and unlicensed drivers. By integrating multi-factor authentication, including age verification, facial recognition, and driver license validation, SafeDrive Pro ensures only authorized individuals can operate vehicles. The system aims to improve vehicle security, reduce unauthorized usage, and enhance road safety. The proposed system leverages IoT technology, machine learning for facial recognition, and RFID for license validation. Initial results indicate that the system can effectively prevent unauthorized access, offering a robust approach to reducing road accidents and promoting vehicle security

Amodiaquine ameliorates stress-induced premature cellular senescence via promoting SIRT1-mediated HR repair

DNA damage is considered to be a potentially unifying driver of ageing, and the stalling of DNA damage repair accelerates the cellular senescence. However, augmenting DNA repair has remained a great challenge due to the intricate repair mechanisms specific for multiple types of lesions. Herein, we miniaturized our modified detecting system for homologous recombination (HR) into a 96-well-based platform and performed a high-throughput chemical screen for FDA-approved drugs. We uncovered that amodiaquine could significantly augment HR repair at the noncytotoxic concentration. Further experiments demonstrated that amodiaquine remarkably suppressed stress-induced premature cellular senescence (SIPS), as evidenced by senescence-associated beta-galactosidase (SA-β-gal) staining or senescence‐related markers p21WAF1 and p16ink4a, and the expression of several cytokines. Mechanistic studies revealed that the stimulation of HR repair by amodiaquine might be mostly attributable to the promotion of SIRT1 at the transcriptional level. Additionally, SIRT1 depletion abolished the amodiaquine‐mediated effects on DNA repair and cellular senescence, indicating that amodiaquine delayed the onset of SIPS via a SIRT1-dependent pathway. Taken together, this experimental approach paved the way for the identification of compounds that augment HR activity, which could help to underscore the therapeutic potential of targeting DNA repair for treating aging-related diseases.

Medication Changes Among Older Drivers Involved in Motor Vehicle Crashes

Although older adults may use potentially driver-impairing (PDI) medications that can produce psychomotor impairment, little is known about changes to PDI medication use among older adults from the time before to the time after a motor vehicle crash (MVC). To quantify use of and changes in PDI medications among older adults before and after an MVC. This cohort study used linked Medicare claims and police-reported MVC data on 154 096 person-crashes among 121 846 older drivers. Eligible persons were drivers aged 66 years or older, involved in a police-reported MVC in New Jersey from May 1, 2007, through December 31, 2017, and with continuous enrollment in Medicare fee-for-service Parts A and B for at least 12 months and Part D for at least 120 days prior to the MVC. Data were analyzed from January 2022 to May 2024. Use of benzodiazepines, nonbenzodiazepine hypnotics, opioid analgesics, and other PDI medications in the 120 days before and 120 days after the MVC. Because each person could contribute multiple MVCs during the study period if they met eligibility criteria, the unit of analysis was the number of person-crashes. The proportion of person-crashes after which PDI medications were started, discontinued, or continued was quantified as well. Among 154 096 eligible person-crashes, the mean (SD) age of the drivers was 75.2 (6.7) years at the time of the MVC. Of 121 846 unique persons, 51.6% were women. In 80.0% of the person-crashes, drivers used 1 or more PDI medications before the crash, and in 81.0% of the person-crashes, drivers used 1 or more PDI medications after the crash. Use of benzodiazepines (8.1% before the crash and 8.8% after the crash), nonbenzodiazepine hypnotics (5.9% before the crash and 6.0% after the crash), and opioid analgesics (15.4% before the crash and 17.5% after the crash) was slightly higher after the MVC. After the MVC, drivers in 2.1% of person-crashes started benzodiazepines and 1.4% stopped benzodiazepines, drivers in 1.2% of person-crashes started nonbenzodiazepine hypnotics and 1.2% stopped nonbenzodiazepine hypnotics, and drivers in 8.4% of person-crashes started opioid analgesics and 6.3% stopped opioid analgesics. This cohort study suggests that most older drivers involved in MVCs did not use fewer PDI medications after crashes than before crashes. Qualitative research of perceived risks vs benefits of PDI medications is necessary to understand the reasons why MVCs do not appear to motivate clinicians to deprescribe PDI medications as a strategy to avert potential harms, including additional MVCs.

Somatic and mental symptoms associated with dysglycaemia, diabetes-related complications and mental conditions in people with diabetes: Assessments in daily life using continuous glucose monitoring and ecological momentary assessment.

To analyse the potential drivers (glucose level, complications, diabetes type, gender, age and mental health) of diabetes symptoms using continuous glucose monitoring (CGM) and ecological momentary assessment. Participants used a smartphone application to rate 25 diabetes symptoms in their daily lives over 8 days. These symptoms were grouped into four blocks so that each symptom was rated six times on 2 days (noon, afternoon and evening). The symptom ratings were associated with the glucose levels for the previous 2 hours, measured with CGM. Linear mixed-effects models were used, allowing for nested random effects and the conduct of N = 1 analysis of individual associations. In total, 192 individuals with type 1 diabetes and 179 with type 2 diabetes completed 6380 app check-ins. Four symptoms showed a significant negative association with glucose values, indicating higher ratings at lower glucose (speech difficulties, P = .003; coordination problems, P = .00005; confusion, P = .049; and food cravings, P = .0003). Four symptoms showed a significant positive association with glucose values, indicating higher scores at higher glucose (thirst, P = .0001; urination, P = .0003; taste disturbances, P = .021; and itching, P = .0120). There were also significant positive associations between microangiopathy and eight symptoms. Elevated depression and diabetes distress were associated with higher symptom scores. N = 1 analysis showed highly idiosyncratic associations between symptom reports and glucose levels. The N = 1 analysis facilitated the creation of personalized symptom profiles related to glucose levels with consideration of factors such as complications, gender, body mass index, depression and diabetes distress. This approach can enhance precision monitoring for diabetes symptoms in precision medicine.

Targeted apoptosis of senescent cells by valproic acid alleviates therapy-induced cellular senescence and lung aging

BackgroundAccumulation of senescent cells in tissues and their downstream effect programs have emerged as key drivers of aging and age-associated pathologies. Recent progresses in senotherapeutics indicated that either selectively killing senescent cells with senolytics or suppressing the senescence-associated secretory phenotype (SASP) secretion using senomorphics contributes to extending of the healthy lifespan and alleviating numerous age-related disorders in mice. PurposeHowever, the potential side-effects and long-term cytotoxicity of the above novel compounds have not yet been determined. Therefore, it seems to be more efficient to explore new senotherapeutical functions from approved drugs. MethodsThe effects of valproic acid (VPA), a derivative of valine, in cellular senescence were evaluated by senescence-associated β galactosidase (SA-β-Gal) staining, flow cytometry and western blot (WB). The cell viability was tested using CCK-8 kits. Cell apoptosis was detected by Annexin V-EGFP/PI apoptosis detection kit. Cell autophagy was checked using GFP-RFP-LC3 ratiometric plasmid. The roles of VPA in lung aging were investigated by in vivo experiments using H&E and Masson staining, WB, as well as electronic microscope strategies. ResultsHere we identified VPA was able to induce an over-accumulation of reactive oxygen species (ROS) (>1.5 times increasing) and apoptosis (>2 times increasing) of senescent cells. Mechanistically, VPA activated the phospholipid modifying enzyme membrane-bound O-acyltransferase domain-containing protein 1 (MBOAT1), which was repressed during senescence, then promoted mitochondrial autophagy and apoptosis. In addition, VPA was also found to alleviate therapy induced abnormal mitochondria and lung aging phenotype (>1.5 times decreasing of lung fibrosis markers and >2.5 times increasing of naïve/memory CD4+ or CD8+ T cells) in vivo. ConclusionTaken together, our study demonstrated that VPA was able to selectively kill senescent cells both in vitro and in vivo, and thus shedding light on new functions and novel potential application of VPA in anti-aging and anti-age-associated diseases.

Roles of chromatin and genome instability in cellular senescence and their relevance to ageing and related diseases.

Ageing is a complex biological process in which a gradual decline in physiological fitness increases susceptibility to diseases such as neurodegenerative disorders and cancer. Cellular senescence, a state of irreversible cell-growth arrest accompanied by functional deterioration, has emerged as a pivotal driver of ageing. In this Review, we discuss how heterochromatin loss, telomere attrition and DNA damage contribute to cellular senescence, ageing and age-related diseases by eliciting genome instability, innate immunity and inflammation. We also discuss how emerging therapeutic strategies could restore heterochromatin stability, maintain telomere integrity and boost the DNA repair capacity, and thus counteract cellular senescence and ageing-associated pathologies. Finally, we outline current research challenges and future directions aimed at better comprehending and delaying ageing.

Tree-based approaches to understanding factors influencing crash severity across roadway classes: A Thailand case study

Existing studies often overlook the nuanced differences between various road classifications and their respective crash dynamics, hindering the development of targeted interventions to mitigate crash severity. To address this gap, this study investigates factors influencing the likelihood of fatality in road crashes across highways, collector roads, and local roads in Thailand using crash data from 2015 to 2021. Highways connect regions with high-speed traffic and large volumes, collector roads link smaller communities with lower traffic density but allow higher speeds, and local roads primarily pass through villages, with narrow pathways, two traffic lanes, and frequent motorcycle use. The study employs machine learning methodologies utilizing tree-based algorithms, including Decision Trees, Random Forest, Gradient Boosting, AdaBoost, Extra Trees, XGBoost, LightGBM, and CatBoost. The XGBoost model delivered superior performance for highways, while Gradient Boosting slightly outperformed XGBoost for local and collector roads. Both models consistently achieved a test accuracy of 0.70, with precision between 0.66 and 0.67, recall ranging from 0.59 to 0.61, and F1-scores from 0.58 to 0.61. The AUC values also consistently ranged from 0.59 to 0.61. SHAP values reveal key factors influencing fatality risk across road types, including speeding, gender disparities, driving under the influence of alcohol, inadequate lighting, and elderly drivers. Specific concerns include reversing on highways, collisions in poorly lit areas on collector roads, and helmet non-use on local roads. The findings support policy recommendations to address speeding, target male and older drivers, prevent reversing incidents, enhance lighting, and promote helmet use. This research deepens our understanding of factors affecting road crash severity and offers valuable insights for improving road safety across various environments.

Protection of the genome and the central exome by peripheral non-coding DNA against DNA damage in health, ageing and age-related diseases.

DNA in eukaryotic genomes is under constant assault from both exogenous and endogenous sources, leading to DNA damage, which is considered a major molecular driver of ageing. Fortunately, the genome and the central exome are safeguarded against these attacks by abundant peripheral non-coding DNA. Non-coding DNA codes for small non-coding RNAs that inactivate foreign nucleic acids in the cytoplasm and physically blocks these attacks in the nucleus. Damage to non-coding DNA produced during such blockage is removed in the form of extrachromosomal circular DNA (eccDNA) through nucleic pore complexes. Consequently, non-coding DNA serves as a line of defence for the exome against DNA damage. The total amount of non-coding DNA/heterochromatin declines with age, resulting in a decrease in both physical blockage and eccDNA exclusion, and thus an increase in the accumulation of DNA damage in the nucleus during ageing and in age-related diseases. Here, we summarize recent evidence supporting a protective role of non-coding DNA in healthy and pathological states and argue that DNA damage is the proximate cause of ageing and age-related genetic diseases. Strategies aimed at strengthening the protective role of non-coding DNA/heterochromatin could potentially offer better systematic protection for the dynamic genome and the exome against diverse assaults, reduce the burden of DNA damage to the exome, and thus slow ageing, counteract age-related genetic diseases and promote a healthier life for individuals.

Exploration of the Characteristics of Elderly-Driver-Involved Single-Vehicle Hit-Fixed-Object Crashes in Pennsylvania, USA

With the acceleration of population aging, the elderly driving safety issue is increasingly prominent. Method: With the crash data of Pennsylvania from 2010 to 2019, this study exclusively discusses features of single-vehicle hit-fixed-object crashes (SVHFOCs), one of the most common and deadliest crash types for elderly drivers. Results: Firstly, we demonstrate that elderly drivers are much more likely to be injured and killed than young drivers in SVHFOCs by checking crash consequences. The descriptive analysis indicates that elderly drivers have very different crash features from young drivers. They are found to drive with more caution in many aspects, such as more low-speed local travels, fewer illegal behaviors, fewer nighttime travels, etc. Then, a logistic regression model is built to find the factors significantly influencing the severity of SVHFOCs from driver, vehicle, roadway, and environment. The estimation results indicate that female sex, not wearing a seatbelt, DUI, rural area, and SUV involvement tend to be associated with more severe SVHFOCs. Additionally, illumination, weather, and road type could also significantly affect crash severity. Especially, SVHFOCs in adverse weather, in dark conditions, and at intersections are found to be less severe, which implies that elderly drivers might drive more carefully in complex environments. Practical Applications: These findings are expected to provide new insights for agencies in formulating customized measures to prevent elderly drivers from being involved in SVHFOCs.

An Intelligent System for Determining Driver Anxiety Level: A Comparison Study of Two Fuzzy-Based Models

While driving, stress and frustration can affect safe driving and pose the risk of causing traffic accidents. Therefore, it is important to control the driver’s anxiety level in order to improve the driving experience. In this paper, we propose and implement an intelligent system based on fuzzy logic (FL) for deciding the driver’s anxiety level (DAL). In order to investigate the effects of the considered parameters and compare the evaluation results, we implement two models: DAL Model 1 (DALM1) and DAL Model 2 (DALM2). The input parameters of DALM1 include driving experience (DE), in-car environment conditions (IECs), and driver age (DA), while for DALM2, we add a new parameter called the accident anxiety state (AAS). For both models, the output parameter is DAL. We carried out many simulations and compared the results of DALM1 and DALM2. The evaluation results show that the DAL is very good for drivers’ ages between 30 to 50 years old. However, when the driver’s age is below 30 or above 50, DAL tends to decline. With an increase in DE and IECs, the DAL value is decreased. But when the AAS is increased, the DAL is increased. DALM2 is more complex because the rule base is larger than DALM1, but it makes a better decision of DAL value.

Identifying the reciprocal causation between hit-and-run behavior and crash injury severity

Objective Hit-and-run behavior is believed to exacerbate the injury severity of traffic crashes due to the delayed emergency response for the victims. However, several previous studies indicated the opposite finding that hit-and-run crashes were associated with less severe injuries. The relevant studies mainly identified the statistical associations between hit-and-run behavior and injury severity without revealing causation between them. To this end, the study aims to explore the reciprocal causation between the two variables. Method The two-stage probit model with endogenous regressors is employed to identify the reciprocal causation between hit-and-run behavior and crash injury severity for single- and two-vehicle crashes, respectively, with the use of crash data extracted from the Crash Report Sampling System and Fatality Analysis Reporting System (2016-2019). Results The results indicate that 1) for both single- and two-vehicle crashes, the fleeing behavior can significantly increase the injury severity of the victims in the crashes while the severe injury of the victims has a negative impact on the propensity of such behavior, 2) the propensity of hit-and-run behavior is influenced by various instrumental variables such as driver age, gender, alcohol involvement, weekday, area type, and light condition, and 3) crash injury severity is significantly related to the victim age, gender, and vehicle damage. Conclusions There is a reciprocal causation between hit-and-run behavior and injury severity in traffic crashes. The analytical results can provide a reasonable explanation for the counterintuitive finding on hit-an-run crashes and help mitigate the injury severity.

Investigating factors affecting injury severity of single-vehicle run-off-road crashes

This study aimed to identify and investigate the contributing factors influencing injury severity in single-vehicle run-off-road (ROR) crashes, which are known for their high severity. The primary objective was to analyze and compare the impact of these factors across three distinct vehicle classes: passenger cars, sport utility vehicles (SUVs), and pickups. A mixed logit model with heterogeneity in mean and variance was developed to analyze the injury severity outcomes in ROR crashes for the three vehicle classes. The model accounted for the potential variations in the impact of contributing factors across different vehicle types. The study revealed several significant variables consistently influencing injury severity across all three vehicle classes. These included driver age, alcohol or drug usage, seatbelt utilization, airbag deployment, higher travel speeds, and the vehicle model year post-2010. Notably, as driver age increased, the impact on changes in injury severity outcomes was more pronounced for pickup drivers compared to those operating passenger cars and SUVs. Among the common findings was the highly effective role of seatbelt usage in mitigating injury severity in ROR crashes. Additionally, passenger cars were associated with increased injury severity, particularly at relatively higher travel speeds exceeding 75 mph when contrasted with SUVs and pickups traveling between 61 and 75 mph. The study highlights the importance of considering vehicle class-specific factors in analyzing injury severity in ROR crashes. Recommendations include further in-depth investigations into distinct factors contributing to injury severity within each vehicle class and utilizing more extensive crash datasets to gain additional insights for enhancing road safety.

PREDICTING THE CHARACTERISTICS OF DRIVER’S LICENSE APPLICANTS AT SATPAS POLRESTA MANOKWARI USING HIERARCHICAL MULTIPLE REGRESSION

This research aims to predict the characteristics of driver's license (SIM) applicants at the SATPAS (Driver’s License Issuance Unit) Polresta Manokwari using Hierarchical Multiple Regression analysis. The study explores six key variables: gender, age, occupation, city, type of driver's license, and type of application, as predictors of applicant characteristics. The analysis was conducted using SPSS version 29, with data collected from the population of driver's license applicants since 2023. Three models were tested, with Model 3 being identified as the best predictor, explaining 7% of the variance in applicant characteristics (R² = 0.070). This model incorporates the variables of age, occupation, city, and type of application, while gender and driver's license class were found to have no significant individual impact. The partial t-test results show that age, occupation, city, and type of application significantly influence applicant characteristics, with negative regression coefficients indicating that an increase in these variables leads to a decrease in the predicted characteristics of SIM applicants. The study highlights practical implications for SATPAS, suggesting that service processes could be improved by considering demographic factors such as age and occupation in order to optimize resource allocation and reduce service complexity. However, the study has several limitations. The use of secondary data limits the completeness and accuracy of the analysis, and the limited number of variables results in a narrow interpretation of the factors influencing SIM applicants. Additionally, the model explains only a small portion of the variance in applicant characteristics, suggesting that other unmeasured factors, such as education level or driving experience, may play a more significant role. Furthermore, the findings are not generalizable to other regions, as local conditions may impact license application patterns. Future research should address these limitations by collecting primary data, expanding the range of variables, employing more sophisticated analytical methods, and exploring other regions. This would provide a more comprehensive understanding of the factors affecting driver's license applicants and contribute to enhancing the quality of SIM issuance services in Indonesia. Keywords: Driver's License, Prediction, Hierarchical Multiple Regression, Applicant Characteristics

Mangrove forest regeneration age map and drivers of restoration success in Gulf Cooperation Council countries from satellite imagery

Mangrove forests are found across the Gulf Cooperation Council (GCC) region despite challenging environmental extremes, including highly variable temperatures and hypersalinity. Understanding the biophysical and anthropogenic factors that influence mangrove forest growth is key to locate suitable areas for regeneration and afforestation activities. The main objectives of this study were to develop a mangrove forest regeneration age map that represents the age of all the existing secondary mangroves in the past 37 years (1986–2023). Long-term Landsat satellite imagery, the random forest classification algorithm, and logistic regression analyses were used to identify the existing secondary mangroves and determine the underlying drivers that contribute to the successful afforestation of mangroves in the region. Our results showed that only around 8.5% of secondary mangrove forests in the GCC region were older than 30 years, with mangroves younger than 5 years being the most abundant age class (41.3%). Saudi Arabia and Oman have the highest percentages of young mangroves, while relatively older secondary mangrove forests were most common in Bahrain, Qatar, and UAE. The current trends in overall mangrove area show that the UAE and Saudi Arabia have the largest total mangrove area among the GCC countries, followed by Qatar, Oman, Bahrain, and Kuwait. The results of the stepwise logistic regression show that the main drivers that influence mangrove regeneration are lower elevation, lower slope, higher available soil moisture, lower average temperatures, higher precipitation, greater proximity to freshwater sources, lower population density and greater distance from agricultural and urban areas. Our results aim to offer support to decision-making in selecting optimal areas for new planting initiatives in the region.

FANS Unfixed: Isolation and Proteomic Analysis of Mouse Cell Type-Specific Brain Nuclei.

Epigenetic-mediated gene regulation orchestrates brain cell-type gene expression programs, and epigenetic dysregulation is a major driver of aging and disease-associated changes. Proteins that mediate gene regulation are mostly localized to the nucleus; however, nuclear-localized proteins are often underrepresented in gene expression studies and have been understudied in the context of the brain. To address this challenge, we have optimized an approach for nuclei isolation that is compatible with proteomic analysis. This was coupled to a mass spectrometry protocol for detecting proteins in low-concentration samples. We have generated nuclear proteomes for neurons, microglia, and oligodendrocytes from the mouse brain cortex and identified cell-type nuclear proteins associated with chromatin structure and organization, chromatin modifiers such as transcription factors, and RNA-binding proteins, among others. Our nuclear proteomics platform paves the way for assessing brain cell type changes in the nuclear proteome across health and disease, such as neurodevelopmental, aging, neurodegenerative, and neuroinflammatory conditions. Data are available via ProteomeXchange with the identifier PXD053515.

THE INFLUENCE OF EVENING TWILIGHT ON THE ATTENTION OF DRIVERS OF DIFFERENT AGES IN CITY CONDITIONS

The article examines the issue of driver safety in cities in the evening twilight. A group of drivers aged 20 to 40 years with a total driving experience of 3 to 16 years was studied. Drivers with 3-5 years of driving experience had an average age of 25 years, and drivers with 10-16 years of driving experience had an average age of 34 years. Drivers drove along known routes at dusk and after dark. We measured drivers’ attention with a Pupil Labs headset, as well as functional state shifts with a respiratory rate monitor. The "Neulog Respiration Monitor Belt" device was used to determine the parameters of external breathing of drivers. Previously, we measured breathing parameters when the driver was in a calm state. Since the morning, the drivers’ breathing rate has been 10-12 breathing cycles. The results of the research indicate a significant difference in the shifts in the functional state during the movement along the routes for both groups. When the lighting changes from the beginning of the evening twilight, the energy consumption by drivers increases by 40%. At the same time, the maximum rate of energy consumption for the driver is 12.6 kJ/min, i.e. 2.9 kcal/min. Also, drivers with less driving experience were less attentive and more emotionally stressed. At the same time, the drivers of both groups experienced significant difficulties in reducing the lighting in the event of conflicting situations while driving. At the same time, energy expenditure significantly exceeded the limit indicators, and attention indicators worsened. This fact was observed after 15-20 minutes of driving in the evening twilight. The experimentally obtained data on changes in the driver’s attention index in the conditions of evening twilight can be used to build multifactorial models taking into account traffic parameters on different categories of streets. In the conditions of the evening twilight, the driver’s attention is significantly reduced. When the illumination changes from 50 lux (driving time 15-20 min.) and less, the driver experiences visual fatigue from constantly searching for objects on the road. At the same time, the number of fixations is significantly reduced, as the driver spends more time recognizing and searching for the necessary elements of the road environment, pedestrians, etc. Danger in the driver causes a state of stress, which is reflected in an increase in the driver’s breathing rate and, as a consequence, a change in the functional state. The main factor affecting the amount of energy spent in such conditions is the interaction of the driver with the road conditions. These factors require the driver to take certain actions when driving a car: acceleration, braking, maintaining speed and certain reactions in the event of a traffic hazard. The results of the analysis of parameters of the functional state of drivers with different years of work showed significant differences between electrophysiological indicators, both when moving in conditions of evening twilight and in background conditions. In the background conditions, lower values of electrophysiological indicators are primarily related to the different age of the drivers. Drivers with 3-5 years of driving experience had an average age of 25 years, and drivers with 10-16 years of driving experience had an average age of 34 years. Keywords: driver attention, traffic flow, human factor.

What would affect drivers’ stop-and-go decisions at yellow dilemma zones? A driving simulator study in Hong Kong

Yellow dilemma, at which a driver can neither stop nor go safely after the onset of yellow signals, is one of the major crash contributory factors at the signal junctions. Studies have visited the yellow dilemma problem using observation surveys. Factors including road environment, traffic conditions, and driver characteristics that affect the driver behaviours are revealed. However, it is rare that the joint effects of situational and attitudinal factors on the driver behaviours at the yellow dilemma zone are considered. In this study, drivers’ propensity to stop after the onset of yellow signals is examined using the driving simulator approach. For instances, the association between driver propensity, socio-demographics, safety perception, traffic signals, and traffic and weather conditions are measured using a binary logit model. Additionally, variations in the effect of influencing factors on driver behaviours are accommodated by adding the interaction terms for driver characteristics, traffic flow characteristics, traffic signals, and weather conditions. Results indicate that weather conditions, traffic volume, position of yellow dilemma in the sequence, driver age and safety perception significantly affect the drivers’ propensity to stop after the onset of yellow signals. Furthermore, there are remarkable interactions for the effects of driver gender and location of yellow dilemma.

A Pragmatic Approach to Introducing Translational Geroscience Into the Clinic: A Paradigm Based on the Incremental Progression of Aging-Related Clinical Research.

Geroscience posits that molecular drivers underlie the aging process. Gerotherapeutics entail strategies to counter molecular drivers of aging to reduce the chronic diseases and geriatric syndromes they trigger. Although the concept of gerotherapeutics for prevention has generated much excitement, the implications of prescribing potentially harmful medications to older adults who are "healthy" have been associated with many delays. Concerns regarding safety and valid endpoints have contributed to holdups. In contrast, it has been relatively easier to implement trials of medications with gerotherapeutic properties as novel approaches to remedy disease. In these applications, the risks of the medications are easier to justify when therapeutic benefits are perceived as outweighing the harms of the disease. Likewise, metrics of effective disease treatments are often seen as more reliable and quantifiable than metrics of health prolongation. Overall, clarifying geroscience mechanisms in disease therapeutic applications provides key opportunities to advance translational geroscience, especially as preventive geroscience trials are often encumbered. In this review, gerotherapeutic benefits of canakinumab, cholchicine, and zoledronic acid as parts of disease management are considered. Longevity Clinics and other opportunities to advance translational geroscience as parts of contemporary care are also discussed.

Biogenic and Anthropogenic Secondary Organic Aerosols Become Fluorescent after Highly Acidic Aging.

Primary biological aerosol particles (PBAPs) and secondary organic aerosol (SOA) both contain organic compounds that share similar chemical and optical properties. Fluorescence is often used to characterize PBAPs; however, this may be hindered due to interferences from fluorophores in SOA. Despite extensive efforts to understand the aging of SOA under elevated particle acidity conditions, little is known about how these processes affect the fluorescence of SOA and thereby their interference with the measurements of PBAPs. The objective of this study is to investigate the fluorescence of SOA and understand the influence of acidity on the optical properties of organic aerosols and potential interference for the analysis of bioaerosols. The SOA was generated by O3- or OH-initiated oxidation of d-limonene or α-pinene, as well as by OH-initiated oxidation of toluene or xylene. The SOA compounds were then aged by exposure to varying concentrations of aqueous H2SO4 for 2 days. Absorption and fluorescence spectrophotometry were used to examine the changes in the optical properties before and after aging. The key observation was the appearance of strongly light-absorbing and fluorescent compounds at pH = ∼-1, suggesting that acidity is a major driver of SOA aging. The aged SOA from biogenic precursors (d-limonene and α-pinene) resulted in stronger fluorescence than the aged SOA from toluene and xylene. The absorption spectra of the aged SOA changed drastically in shape upon dilution, whereas the shapes of the fluorescence spectra remained the same, suggesting that the fluorophores and chromophores in SOA are separate sets of species. The fluorescence spectra of aged SOA overlapped with the fluorescence spectra of PBAPs, suggesting that SOA exposed to highly acidic conditions can be confused with PBAPs detected by fluorescence-based methods. These processes are likely to play a role in the atmospheric regions where high concentrations of H2SO4 persist, such as the upper troposphere and lower stratosphere.

Gerotherapeutics: Aging Mechanism-based Pharmaceutical and Behavioral Interventions to Reduce Cancer Racial and Ethnic Disparities.

The central premise of this article is that a portion of the established relationships between social determinants of health and racial/ethnic disparities in cancer morbidity and mortality are mediated through differences in rates of biological aging processes. We further posit that using knowledge about aging could enable discovery and testing of new mechanism-based pharmaceutical and behavioral interventions ("gerotherapeutics") to differentially improve the health of minoritized cancer survivors and reduce cancer disparities. These hypotheses are based on evidence that lifelong differences in adverse social determinants of health contribute to disparities in rates of biological aging ("social determinants of aging"), with minoritized groups having accelerated aging (ie, a steeper slope or trajectory of biological aging over time relative to chronological age) more often than non-minoritized groups. Acceleration of biological aging can increase the risk, age of onset, aggressivity and/or stage of many adult cancers. There are also documented negative feedback loops whereby the cellular damage caused by cancer and its therapies act as drivers of additional biological aging. Together, these dynamic intersectional forces can contribute to differences in cancer outcomes between minoritized vs non-minoritized survivor populations. We highlight key targetable biological aging mechanisms with potential applications to reducing cancer disparities and discuss methodological considerations for pre-clinical and clinical testing of the impact of gerotherapeutics on cancer outcomes in minoritized populations. Ultimately, the promise of reducing cancer disparities will require broad societal policy changes that address the structural causes of accelerated biological aging and ensure equitable access to all new cancer control paradigms.