Bibliometric analysis in motorcycle accident research: a global overview

770 million motorcycles are estimated on the roads. Motorcyclists represent more than 380,000 annual deaths worldwide. 28% of the global fatalities in the roads in 2016. With the increase of the accident rate, studies have been developed within the scientific literature. Bibliometric analysis is applied in the field of motorcycle safety in order to identify relevant publications on risk factors of road crashes and their implications. The information in this research was extracted from Web of Science and Scopus databases between 1947 and May 31, 2018. The study identified the key bibliometric indicators such as publications, authors, journals, countries, institutions, citation and co-citation analysis, subject categories, and co-occurrence of terms. EndNote, Microsoft Excel, Statgraphics Centurion and VOS-viewer software were used for the analysis. In total, 1813 articles were considered. The publications from 2000 to 2017 exhibits an average growth of 9%. The journal “Accident Analysis and Prevention” was the key issue in the publication and citation. The top institutions were the University of California, Universiti Putra Malaysia, and Monash University. The average citation of the top 10 articles was 134. A network visualization map showed that ‘vehicle’, ‘model’, ‘system’, ‘road’, ‘safety’, and ‘behavior’ were the most commons key terms. Bibliometric analysis demonstrates a high collaboration between authors and institutions. Two growing trends were identified. First, studies on the protection of the motorcyclist and the safe design considering the performance. Second, studies in analysis, characterization, and prevention of accidents. These studies are more related to the generation of strategies for the protection of road safety for motorcyclists

Extraction of decision rules using genetic algorithms and simulated annealing for prediction of severity of traffic accidents by motorcyclists

The objective of this study is to analysis of accident of motorcyclists on Bogotá roads in Colombia. For detection of conditions related to crashes and their severity, the proposed model develops the strategies to enhance road safety. In this context, data mining and machine learning techniques are used to investigate 34,232 accidents by motorcyclists during January 2013 to February 2018. Both the Genetic algorithm and simulated annealing are applied in conjunction with mining rules (support, confidence, lift, and comprehensibility) as per objectives of the problem. The application of a hybrid algorithm allows for the creation and definition of optimal hierarchical decision rules for the prediction of the severity of motorcycle traffic accidents. The proposed method yields good results in the metrics of recall (90.07%), precision (89.87%), and accuracy (90.06%) on the data set. The results increase the prediction by 20–21% in comparisons with the following methods: Decision Trees (CART, ID3, and C4.5), Support Vector Machines (SVMs), K-Nearest Neighbor (KNN), Naive Bayes, Neural Networks, Random Forest, and Random Tree. The proposed method defines 11 rules for the prediction of accidents with material damage, 24 rules with injuries, and 12 rules with fatalities. The variables with the most recurrence in the definition of rules are time, weather and road conditions, and the number of victims involved in the accidents. Finally, the interactions of the conditions and characteristics presented in motorcycle accidents are analyzed which contribute to the definition of countermeasures for road safety. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature

Total and high molecular weight adiponectin have similar utility for the identification of insulin resistance

<p>Abstract</p> <p>Background</p> <p>Insulin resistance (IR) and related metabolic disturbances are characterized by low levels of adiponectin. High molecular weight adiponectin (HMWA) is considered the active form of adiponectin and a better marker of IR than total adiponectin. The objective of this study is to compare the utility of total adiponectin, HMWA and the HMWA/total adiponectin index (S_Aindex) for the identification of IR and related metabolic conditions.</p> <p>Methods</p> <p>A cross-sectional analysis was performed in a group of ambulatory subjects, aged 20 to 70 years, in Mexico City. Areas under the receiver operator characteristic (ROC) curve for total, HMWA and the S_Aindex were plotted for the identification of metabolic disturbances. Sensitivity and specificity, positive and negative predictive values, and accuracy for the identification of IR were calculated.</p> <p>Results</p> <p>The study included 101 men and 168 women. The areas under the ROC curve for total and HMWA for the identification of IR (0.664 <it>vs</it>. 0.669, <it>P </it>= 0.74), obesity (0.592 <it>vs</it>. 0.610, <it>P </it>= 0.32), hypertriglyceridemia (0.661 <it>vs</it>. 0.671, <it>P </it>= 0.50) and hypoalphalipoproteinemia (0.624 <it>vs</it>. 0.633, <it>P </it>= 0.58) were similar. A total adiponectin level of 8.03 μg/ml was associated with a sensitivity of 57.6%, a specificity of 65.9%, a positive predictive value of 50.0%, a negative predictive value of 72.4%, and an accuracy of 62.7% for the diagnosis of IR. The corresponding figures for a HMWA value of 4.25 μg/dl were 59.6%, 67.1%, 51.8%, 73.7% and 64.2%.</p> <p>The area under the ROC curve of the S_Aindex for the identification of IR was 0.622 [95% CI 0.554-0.691], obesity 0.613 [95% CI 0.536-0.689], hypertriglyceridemia 0.616 [95% CI 0.549-0.683], and hypoalphalipoproteinemia 0.606 [95% CI 0.535-0.677].</p> <p>Conclusions</p> <p>Total adiponectin, HMWA and the S_Aindex had similar utility for the identification of IR and metabolic disturbances.</p

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements