TRPM4 is a calcium activated non-selective cation channel, impermeable to Ca2+, in neurons it has been implicated in the regulation of the excitability and in the persistent firing. Cholinergic stimulation is also implicated in changes in excitability that leads neurons to an increased firing frequency, however it is not clear whether TRPM4 is involved in the cholinergic-induced increase in firing frequency. Here using a combination of patch clamp electrophysiology, Ca2+ imaging, immunofluorescence, fluorescence recovery after photobleaching (FRAP) and pharmacological approach, we demonstrate that carbachol (Cch) increases firing frequency, intracellular Ca2+ and that TRPM4 inhibition using 9-Ph and CBA reduces firing frequency and decreases the peak in intracellular Ca2+ induced by Cch in cortical pyramidal neurons in culture. Moreover, we determined that cholinergic stimulation reduces TRPM4 recycling and stabilizes TRPM4 in the plasma membrane. Together our results indicate that cholinergic stimulation increases firing in a TRPM4 dependent manner, and also increases the TRPM4 stability in the membrane, suggesting that TRPM4 is locked in microdomains in the membrane, possibly signaling or cytoskeleton proteins complexes.

Vision-language models are of interest in various domains, including automated driving, where computer vision techniques can accurately detect road users, but where the vehicle sometimes fails to understand context. This study examined the effectiveness of GPT-4V in predicting the level of \'risk\' in traffic images as assessed by humans. We used 210 static images taken from a moving vehicle, each previously rated by approximately 650 people. Based on psychometric construct theory and using insights from the self-consistency prompting method, we formulated three hypotheses: (i) repeating the prompt under effectively identical conditions increases validity, (ii) varying the prompt text and extracting a total score increases validity compared to using a single prompt, and (iii) in a multiple regression analysis, the incorporation of object detection features, alongside the GPT-4V-based risk rating, significantly contributes to improving the model\'s validity. Validity was quantified by the correlation coefficient with human risk scores, across the 210 images. The results confirmed the three hypotheses. The eventual validity coefficient was r = 0.83, indicating that population-level human risk can be predicted using AI with a high degree of accuracy. The findings suggest that GPT-4V must be prompted in a way equivalent to how humans fill out a multi-item questionnaire.

BACKGROUND: Trauma is a significant public health concern in Iran, with high mortality and morbidity rates. This study aimed to assess trauma patients\' profiles in Shahroud, Iran. Study Design: A cross-sectional study.
METHODS: The study involved trauma patients who met specific criteria at Imam Hossein hospital in Shahroud, Iran, between 2016 and 2023, using the National Trauma Registry of Iran (NTRI). The relationship between injury characteristics and the cause of injury was analyzed using chi-square test and post hoc analysis. Quintile regression models assessed the association of demographic and clinical variables with length of stay.
RESULTS: Among 3513 trauma patients, road traffic crashes (RTCs) had a higher percentage of injuries with the Glasgow Coma Scale (GCS) between 9 and 12 (1.7%) compared to falls (0.3%) (P<0.001). Falls caused more moderate cases with injury severity scores (ISS) ranging from 9 to 15 (22.7%) than RTCs (17.1%) (P<0.001). RTC-related injuries required more ventilation (2.7%) and intensive care unit (ICU) admissions (11.1%) than falls (P<0.001). After adjusting for age, GCS, ISS, and body region, fall had a median length of stay nine hours shorter than RTCs (95% CI = -16.2, -1.8).
CONCLUSIONS: Significant injury pattern differences were observed between RTCs and falls. RTCs had higher frequencies of injuries resulting in GCS scores between 9 and 12, while falls had higher frequencies of moderate ISS scores. In addition, patients with RTC-related injuries required more mechanical ventilation and ICU admissions. Moreover, after adjusting for various factors, patients with RTC-related injuries had a significantly longer hospital stay compared to those with fall-related injuries.

BACKGROUND: People living with asthma are disproportionately affected by air pollution, with increased symptoms, medication usage, hospital admissions, and the risk of death. To date, there has been a focus on exhaust emissions, but traffic-related air pollution (TRAP) can also arise from the mechanical abrasion of tyres, brakes, and road surfaces. We therefore created a study with the aim of investigating the acute impacts of non-exhaust emissions (NEEs) on the lung function and airway immune status of asthmatic adults.
METHODS: A randomised three-condition crossover panel design will expose adults with asthma using a 2.5 h intermittent cycling protocol in a random order at three locations in London, selected to provide the greatest contrast in the NEE components within TRAP. Lung function will be monitored using oscillometry, fractional exhaled nitric oxide, and spirometry (the primary outcome is the forced expiratory volume in one second). Biomarkers of inflammation and airborne metal exposure will be measured in the upper airway using nasal lavage. Symptom responses will be monitored using questionnaires. Sources of exhaust and non-exhaust concentrations will be established using source apportionment via the positive matrix factorisation of high-time resolution chemical measures conducted at the exposure sites.
CONCLUSIONS: Collectively, this study will provide us with valuable information on the health effects of NEE components within ambient PM2.5 and PM10, whilst establishing a biological mechanism to help contextualise current epidemiological observations.

The aim of the study was an assessment of the pollution level and identification of the antimony sources in soils in areas subjected to industrial anthropopressure from: transport, metallurgy and electrical waste recycling. The combination of soil magnetometry, chemical analyzes using atomic spectrometry (ICP-OES and ICP-MS), Sb fractionation analysis, statistical analysis (Pearson\'s correlation matrix, factor analysis) as well as Geoaccumulation Index, Pollution Load Index, and Sb/As factor allowed not only the assessment of soil contamination degree, but also comprehensive identification of different Sb sources. The results indicate that the soil in the vicinity of the studied objects was characterized by high values of magnetic susceptibility and thus, high contents of potentially toxic elements. The most polluted area was in the vicinity of electrical waste processing plants. Research has shown that the impact of road traffic and wearing off brake blocks, i.e. traffic anthropopression in general, has little effect on the surrounding soil in terms of antimony content. Large amounts of Pb, Zn, As and Cd were found in the soil collected in the vicinity of the heap after the processing of zinc-lead ores, the average antimony (11.31 mg kg-1) content was lower in the vicinity of the heap than in the area around the electrical and electronic waste processing plant, but still very high. Antimony in the studied soils was demobilized and associated mainly with the residual fraction.

The one of the leading causes of adolescent morbidity and mortality worldwide is motor vehicle accidents (MVA). The use of seat belts significantly lowers MVA fatalities and injuries. The aim of this study is to investigate adolescent seat belt usage patterns and relation with risky behaviors. The study conducted at two medical institutions with non-immigrant and literate adolescents aged 12-18. Demographics, seat belt use, and risk-taking behavior were collected through questionnaires. 726 teenagers (422 girls and 304 boys) with an average age of 176.7 ± 23.37 months participated in the study. Parents\' educational levels and front-seat belt use have been found to be correlated. Comparatively to non-users, seat belt users demonstrated lower risk scores (total, traffic, substance, and social). The use of seat belts was significantly predicted by traffic risk, according to logistic regression. The frequency of seatbelt use was higher among participants from cities with higher socioeconomic status. As a result, it was found that adolescents who exhibited more risky behaviors had a lower frequency of seat belt use and seat belt use was associated with socioeconomic level and parental education level. It is thought that population-based studies to be conducted on this subject are important.

New particle formation (NPF) is a major source of atmospheric aerosol particles, including cloud condensation nuclei (CCN), by number globally. Previous research has highlighted that NPF is less frequent but more intense at roadsides compared to urban background. Here, we closely examine NPF at both background and roadside sites in urban Central Europe. We show that the concentration of oxygenated organic molecules (OOMs) is greater at the roadside, and the condensation of OOMs along with sulfuric acid onto new particles is sufficient to explain the growth at both sites. We identify a hitherto unreported traffic-related OOM source contributing 29% and 16% to total OOMs at the roadside and background, respectively. Critically, this hitherto undiscovered OOM source is an essential component of urban NPF. Without their contribution to growth rates and the subsequent enhancements to particle survival, the number of >50 nm particles produced by NPF would be reduced by a factor of 21 at the roadside site. Reductions to hydrocarbon emissions from road traffic may thereby reduce particle numbers and CCN counts.

UNASSIGNED: Road traffic injuries (RTIs) are one of the major health problems in developed and developing countries. In Iran, RTIs are the first leading cause of years of life lost (YLL). So, the present study investigated the 11-year trend of RTI- related mortalities in Iran.
UNASSIGNED: This study was a population-based cross-sectional study. All-cause deaths as well as RTI-related mortalities\' data were collected from the Civil Registration Organization (CRO) and Legal medical organization (LMO) of Isfahan during 2011-2021. The mid-year population, number of deaths due to RTIs, the crude and age-standardized mortality (per 100,000) of RTIs, and the percentage of proportional mortality by sex and year of accident during the study period were calculated and reported. Also, trend analysis was done using join point regression program.
UNASSIGNED: During the study period, 11,248 deaths occurred due to RTIs in Isfahan province. 8,894 cases were male (79.03%), the highest number of deaths in both male and female cases was reported in those aged 15-39 years. Among the males, trend of standardized mortality in 2011-2015 was decreasing (annual percentage changes = -6.76(CI 95%: -2.53, -15.03)), while in 2015-2021 it was increasing (annual percentage changes = 3.00 (CI 95%: 0.63, 9.87)). However, no significant trend was observed among females.
UNASSIGNED: The findings of the present study showed that the number and standardized mortality rate of RTIs decreased during the 11-year period. It seems that applying stricter policies, improving the quality of the roads of the province, improving the quality of cars, and increasing the number of hospital and pre-hospital medical facilities can play an effective role in reducing RTIs.

OBJECTIVE: Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs.
METHODS: This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages.
RESULTS: Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively.
CONCLUSIONS: The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers.

[This corrects the article DOI: 10.3389/fimmu.2023.1332943.].