Lammnorman8572

ders under the rear impact of loading, the present set of corridors serve as a fundamental dataset for the validation of female-specific finite element models. Current computational models can also use these corridors for improved validation to add confidence in their outputs.Recent reports provide evidence that contaminated healthcare environments represent major sources for the acquisition and transmission of pathogens. Antimicrobial coatings (AMC) may permanently and autonomously reduce the contamination of such environmental surfaces complementing standard hygiene procedures. This review provides an overview of the current status of AMC and the demands to enable a rational application of AMC in health care settings. find more Firstly, a suitable laboratory test norm is required that adequately quantifies the efficacy of AMC. In particular, the frequently used wet testing (e.g. ISO 22196) must be replaced by testing under realistic, dry surface conditions. Secondly, field studies should be mandatory to provide evidence for antimicrobial efficacy under real-life conditions. The antimicrobial efficacy should be correlated to the rate of nosocomial transmission at least. Thirdly, the respective AMC technology should not add additional bacterial resistance development induced by the biocidal agents and co- or cross-resistance with antibiotic substances. Lastly, the biocidal substances used in AMC should be safe for humans and the environment. These measures should help to achieve a broader acceptance for AMC in healthcare settings and beyond. Technologies like the photodynamic approach already fulfil most of these AMC requirements.

To analyze the association of mast cells found on supraglottic biopsy of pediatric patients with common aerodigestive diseases.

Cross-sectional study.

Tertiary care children's hospital.

A total of 461 pediatric patients undergoing otolaryngology aerodigestive procedures provided consent between 2014 and 2019, and biopsies of the supraglottic larynx were collected at the time of their surgery. Pathologists reviewed biopsies for the presence and number of mast cells per high-power field. The patients' electronic health records were reviewed for relevant demographic data and clinical diagnoses present at the time of biopsy. Multivariate logistic regression was used to assess the relationship of mast cells with odds of aerodigestive disease.

Patients with mast cells in their biopsy had significantly higher odds of asthma (odds ratio [OR], 2.02; 95% CI, 1.17-3.46), gastroesophageal reflux disease (OR, 2.36; 95% CI, 1.47-3.77), laryngomalacia (OR, 2.98; 95% CI, 1.80-4.94), laryngeal anomalies (OR, 2.32; 9 study also showed a nonlinear relationship between number of mast cells and odds of disease diagnosis.Patients with cancer are at significantly greater risk of COVID-19 and its complications than the general population. Since IgG antibodies remain detectable well after infection with the SARS-CoV-2 virus, seroprevalence can be used to estimate the proportion of the cancer population previously infected and potentially immune to SARS-CoV-2. The current study is a multi-center, prospective observational study to assess seroprevalence of SARS-CoV-2 IgG antibody in a cancer population referred for vaccination between April and June 2021. Of a total of 270 adult patients with cancer accrued, 16% reported a history of COVID-19 more than four weeks previously confirmed by PCR. At the same time, serologic positivity for SARSCoV2 IgG was found in 29% of patients prior to vaccination including nearly 20% of patients without a history of confirmed COVID-19. Seropositivity was significantly greater in females consistent with higher rates in patients with breast cancer and gynecologic cancers. A seroconversion rate of 79.5% was observed in cancer patients with a history of PCR confirmed COVID-19, less than observed in the general population. In multivariable analysis, gender and prior history of COVID-19 were both independently associated with seropositivity prior to vaccination. Follow-up is continuing of this cohort of patients with cancer following vaccination to assess antibody and clinical outcomes.In response to the growing numbers of minoritized students (e.g., low-income, first-generation, students of color) transitioning into U.S. systems of higher education, researchers have developed transition-assistance strategies, such as psychologically wise-story interventions. Through a rigorous, theory-driven approach, wise-story interventions use stories to encourage students to develop adaptive meanings about college-transition challenges, subsequently allowing students to persist. Yet there is one critical distinction between existing wise-story interventions. Well-known examples endorse a color-evasive message that all students, regardless of their demographic backgrounds, share similar struggles when adjusting to college. One variation in wise-story interventions ties transition struggles explicitly to students' identities, adopting more of a multicultural perspective. Drawing from diversity frameworks, we offer in this article a comparative analysis of these variations; we outline under what conditions, for whom, and through which processes these varying approaches to identity affect student outcomes. In this discussion, we reflect on both the strengths and challenges of wise-story interventions and offer considerations for extending these approaches. Specifically, we ask whether integrating critical perspectives into wise-story interventions better addresses the experiences of minoritized students as they navigate institutions historically built for dominant groups.

The objective of this study was to reanalyze lateral postmortem human surrogate (PMHS) sled test chestband data to construct updated lateral thoracic injury risk curves (IRCs) using survival analysis.

Chestband and injury data were gathered from 16 previously conducted PMHS sled tests. Briefly, 2 chestbands were wrapped around the thorax's circumference at the levels of ribs 4 and 8. Tests were conducted at 6.7 m/s on a rigid and padded load wall fixed to the top of a rebound sled. The injuries were reclassified using the Abbreviated Injury Scale (AIS) 2015 coding scheme. Chestband signals were combined with pretest specimen measurements to calculate the chest deflection contour time history. Deflections were determined using updated processing techniques calculating the change in length of every point on the contour from the impacted side using the thorax's midpoint as the origin. Four candidate metrics were selected the deflection from rib 4, the deflection from rib 8, the greater of the deflections frof the peak deflections was found to best represent the thoracic chest deflection response. Mass-based side impact IRCs were calculated for occupants representing the WorldSID 5th percentile female and 50th percentile male anthropomorphic test device.

IRCs were developed using survival analysis, and the average of the peak deflections was found to best represent the thoracic chest deflection response. Mass-based side impact IRCs were calculated for occupants representing the WorldSID 5th percentile female and 50th percentile male anthropomorphic test device.Objective Risky driving behaviors, such as texting while driving, are common among young adults and increase risk of traffic accidents and injuries. We examine the relationship between poor sleep and risky driving behaviors among college students as potential targets for traffic injury prevention.Methods Data for this study were obtained from a cross-sectional survey administered to a college student sample in the United States Midwest (n = 1,305). Sleep was measured using the Pittsburgh Sleep Quality Index (PSQI). Risky driving behaviors were measured, including sending texts/emails; reading texts/emails while driving; talking on the phone while driving; falling asleep while driving; and driving under the influence. Risky driving behavior was defined as a response of "just once," "rarely," "sometimes," "fairly often" or "regularly" (reference = "never"). Logistic regression was used to examine the relationship between sleep and risky driving, after adjusting for confounders.Results Among participants, 75% reported sending texts/emails while driving, 82% reported reading texts/emails while driving, and 84% reported phone talking while driving; 20% reported falling asleep while driving; 8% reported driving under the influence; and 62% reported 3 or more risky behaviors. Compared to those reporting no sleep disturbance, those with sleep disturbance "once or twice a week" were more likely to report sending a text/email while driving (aOR 2.9, 95%CI1.7-4.9), reading a text/email while driving (aOR3.1,95%CI1.5-5.5), talking on the phone while driving (aOR1.9, 95%CI1.0-3.4), and falling asleep while driving (aOR3.4,95%CI1.5-7.4). Compared to those reporting no daytime dysfunction, those reporting issues "once or twice a week" were more likely to report talking on the phone while driving (aOR1.7, 95%CI1.1-2.7) and falling asleep while driving (aOR3.6,95%CI2.3-5.6).Conclusions Future research may consider designing behavioral interventions that aim to improve sleep, reduce drowsy driving among young adults.

The SARS-CoV-2 pandemic abruptly switched the healthcare service for patients with inflammatory bowel disease (IBD) towards a telemedicine dominated approach. The aim of this study was to investigate the impact of this switch on monitoring of patients and on disease activity.

The pre-pandemic year included 868 patients and the first year of the pandemic included 891 patients. Medical records were retrospectively checked for contacts, changes in medical treatment, performed fecal calprotectin (FC) tests and colonoscopies.

The scheduled follow-up visits to a doctor for patients with IBD shifted from mostly face-to-face pre-pandemic (from 389 to 118 appointments) to mostly telephone-based during the pandemic (from 13 to 423 appointments). There was a 21.3% increase in mean overall scheduled health contacts (

 < .001) and a 20.0% increase for the mean number of FC tests (

 < .001) in the year of the pandemic compared to the pre-pandemic year. The proportion of patients who had a surveillance colonosd surveillance colonoscopies. Between the two periods observed, the patients showed no difference in medical treatment or in disease activity.

The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.

A series of parametric studies was carried out using a family car finite element model and MADYMO pedestrian models (AM50, AF05, 6YO). The car model was developed and tuned by 11 impact tests. The initial gaits for the pedestrian models were obtained from volunteer experiments to reproduce 420 pre-crash reactions. Furthermore, by factoring the pedestrian models (3 types), pedestrian directions (2 each), impact positions (3 each), and car velocities (6 levels) with the pre-crash parameters, a total of 45,360 car-to-pedestrian impact simulations were performed. After the simulations, image datasets were created by labeling the pedestrian collision images with head injury criteria of 15 ms (HIC) and dividing the images into training and test data based on model type. Next, deep learning was conducted using the training dataset to obtain trained models.