Logistic regression vs machine learning to predict evacuation decisions in fire alarm situations

In this study we assessed logistic regression and machine learning models to explore their performance in predicting evacuation decisions and to provide readers with insights into the accuracy of these methods. We tested seven machine learning algorithms, including classification and regression tree, Naïve Bayes, K-nearest neighbours, support vector machine, random forest, extreme gradient boosting, and artificial neural network. We used data collected from 1,807 participants through web-based experiments to train and calibrate these models. The performance of each model was evaluated by area under the curve, accuracy, recall, specificity, precision, and F1-score. The results indicate that logistic regression had the highest area under the curve value (0.831), whereas extreme gradient boosting outperformed other machine learning models in terms of accuracy (0.780), specificity (0.810) and precision (0.820). K-nearest neighbours model had the greater recall (0.859) and artificial neural network the highest F1-score (0.785). The models identified that being with a close person was the most influential factor in the response to a fire alarm

Uncovering non-emergency-related factors in threat responses: logistic regression analysis of online experimental data for behaviour patterns

Delving into human behaviour during emergencies, this study investigates the evacuation decisions made by 1.807 individuals across fire alarm, explosion, and shooting scenarios. Through a series of 18 trials, encompassing diverse environmental and social influences, participants faced the decision to evacuate or stay. The impact of 20 influential factors on emergency decisionmaking was explored using logistic regression analyses. Across all threat scenarios, a significant majority of individuals opted to stay rather than evacuate. Our findings revealed a greater influence of factors in explosion trials compared to fire alarm and shooting scenarios. Age emerged as a consistent and significant determinant across all threats, while gender demonstrated significance exclusively within the explosion situations. These results illuminate the impact of nonemergency- related factors in shaping the evacuation decision process, providing with valuable insights for emergency management strategies

Supplementation of xylo-oligosaccharides to suckling piglets promotes the growth of fiber-degrading gut bacterial populations during the lactation and nursery periods

Modulating early-life microbial colonization through xylo-oligosacharides (XOS) supplementation represents an opportunity to accelerate the establishment of fiber-degrading microbial populations and improve intestinal health. Ninety piglets from 15 litters were orally administered once a day from d7 to d27 of lactation with either 5 mL of water (CON) or 5 mL of a solution containing 30 to 60 mg of XOS (XOS). Supplementation ceased at weaning (d28) when all piglets were fed the same commercial pre-starter diet. Growth performance did not differ between treatments during the experimental period (d7 to d40). Piglet's fecal microbiota (n = 30) shifted significantly from the end of lactation (d27) to nursery period (d40) exhibiting an increase in microbial alpha diversity. Animals supplemented with XOS showed higher richness and abundance of fiber-degrading bacteria and short-chain fatty acid (SCFA) production at d27 and d40. Additionally, the predicted abundance of the pyruvate to butanoate fermentation pathway was increased in the XOS group at d40. These results show that supplementation of XOS to lactating piglets promotes fiber-degrading bacterial populations in their hindgut. Moreover, differences observed in the nursery period suggest that XOS can influence the microbiota in the long-term

Screening the ability of natural feed ingredients to interfere with the adherence of enterotoxigenic Escherichia coli (ETEC) K88 to the porcine intestinal mucus

The inhibition of the attachment of bacteria to the intestine by receptor analogues could be a novel approach to prevent enterotoxigenic Escherichia coli (ETEC) K88-induced diarrhoea in piglets. The objective of the present study was to screen the ability of different feed ingredients (FI) to bind to ETEC K88 (adhesion test, AT) and to block its attachment to the porcine intestinal mucus (blocking test, BT) using in vitro microtitration-based models. In the AT, wheat bran (WB), casein glycomacropeptide (CGMP) and exopolysaccharides exhibited the highest adhesion to ETEC K88 (P,0·001). In the BT, WB, CGMP and locust bean (LB) reduced the number of ETEC K88 attached to the intestinal mucus (P,0·001). For WB and LB, fractionation based on their carbohydrate components was subsequently carried out, and each fraction was evaluated individually. None of the WB fractions reduced the adhesion of ETEC K88 to the mucus as did the original extract, suggesting that a protein or glycoprotein could be involved in the recognition process. With regard to the LB fractions, the water-extractable material reduced the adhesion of ETEC K88 (P,0·001) to the mucus similar to the original extract (P,0·001), indicating, in this case, that galactomannans or phenolic compounds could be responsible for the recognition process. In conclusion, among the FI screened, the soluble extracts obtained from WB, LB and CGMP exhibited the highest anti-adhesive properties against ETEC K88 in the BT. These results suggest that they may be good candidates to be included in diets of weaned piglets for the prevention of ETEC K88-induced diarrhoea

Influence of particle size and xylanase in corn-soybean pelleted diets on performance, nutrient utilization, microbiota and short-chain fatty acid production in young broilers

The objective of this study was to investigate the effects of particle size and xylanase supplementation in corn-based pellet diets on the performance and digestive traits in young broilers. A total of 512 male Ross 308 broilers were used in a 21-day study. The treatments were designed in a 4 × 2 factorial arrangement with four levels of geometric mean diameter (Dgw) of corn (540, 660, 1390, and 1700 µm), and two levels of xylanase (0 or 16,000 BXU/kg diet). Feeding coarse corn diets (1390 and 1700 µm Dgw) and xylanase supplementation showed an inferior coefficient of variation of body weight. Higher gizzard weight, microbiome alpha-diversity, and clustered separately beta-diversity (p < 0.05) were observed in birds fed coarse diets. The addition of xylanase promoted changes in relative bacteria abundance, increasing Lachnospiraceae, Defluviitaleaceae, Bacteroidaceae, Bacillaceae, Eggerthellaceae, and Streptococcaceae families in the 1700 µm group, and Christensenellaceae and Lachnospiraceae families in the 540 µm Dgw group. In conclusion, xylanase supplementation and particle size of corn interact in the intestinal environment, showing changes in microbial composition. Coarse diets and xylanase supplementation showed improved body weight homogeneity, which might be related to a better gut development and microbiota modulation

Dietary xylanase and live yeast supplementation influence intestinal bacterial populations and growth performance of piglets fed a sorghum-based diet

This study was to evaluate the effect of xylanase supplementation and the addition of live yeast, Saccharomyces cerevisiae, on growth performance and intestinal microbiota in piglets. One hundred and eighty commercial crossbred 23-d-old piglets (PIC 417) were sorted by initial BW and allocated to 3 treatments: control (CTR) diet, CTR diet supplemented with xylanase at 16,000 birch xylan units/kg (XYL) and XYL diet supplemented with live yeast (2 × 10 10 CFU/g) at 1 kg/t (XYL + LY). Each treatment had 10 replicates, with 6 animals each. A sorghum-based diet and water were available ad libitum for 42 d of the study. Average daily gain (ADG) and average daily feed intake (ADFI) were measured from 0 to 42 d (23- to 65-d-old) and feed conversion ratio (FCR) calculated. At the end of the study, bacterial identification through 16S rRNA (V3 to V4) sequencing of the ileal and caecal digesta from one piglet per replicate was performed. No treatment effects were observed on ADFI. Pigs offered the live yeast in addition to the xylanase had increased ADG compared with those supplemented with xylanase alone (XYL + LY vs. XYL; P = 0.655). FCR was improved with XYL and XYL + LY compared with CTR (P = 0.018). Clostridiaceae counts in the ileum tended to reduce by 10% with XYL and 14% with XYL + LY compared to CTR (P = 0.07). XYL and XYL + LY increased the counts of Lactobacillaceae in the caecum compared with CTR (P < 0.0001). Dietary supplementation of live yeast combined with xylanase improved growth performance and microbial balance of piglets during the nursery phase

Longitudinal changes in gambling, buying and materialism in adolescents: A population-based study

Gambling disorder, gambling-related cognitive biases, compulsive buying, and materialistic values lead to impaired functioning in important areas of life. The aims of the present longitudinal study are (1) to evaluate the change produced after one year in those mentioned variables and (2) to examine the gender role in these changes and to analyze the mediational mechanisms among the variables of the study. The sample was composed of 182 adolescents (103 females and 79 males) from secondary education Spanish institutions who completed self-administered questionnaires. Structural equation modeling has been used to explore associations between the different variables. Our results show significant decreases in compulsive buying, materialism, and cognitive biases related to gambling after one year. Gambling disorder severity was directly related to cognitive distortions of gambling and being a man. Compulsive buying was associated with older age and the female gender. Materialism was associated with compulsive buying and the male gender. In conclusion, gambling disorder, gambling-related cognitive biases, compulsive buying, and materialistic values change over time in different ways, according to gender. The understanding of gambling disorder and compulsive buying in adolescents could potentially lead to early prevention and treatment programs for the specific needs of gender and age

Plasma p-tau231 and p-tau217 as state markers of amyloid-β pathology in preclinical Alzheimer’s disease

Blood biomarkers indicating elevated amyloid-β (Aβ) pathology in preclinical Alzheimer's disease are needed to facilitate the initial screening process of participants in disease-modifying trials. Previous biofluid data suggest that phosphorylated tau231 (p-tau231) could indicate incipient Aβ pathology, but a comprehensive comparison with other putative blood biomarkers is lacking. In the ALFA+ cohort, all tested plasma biomarkers (p-tau181, p-tau217, p-tau231, GFAP, NfL and Aβ42/40) were significantly changed in preclinical Alzheimer's disease. However, plasma p-tau231 reached abnormal levels with the lowest Aβ burden. Plasma p-tau231 and p-tau217 had the strongest association with Aβ positron emission tomography (PET) retention in early accumulating regions and associated with longitudinal increases in Aβ PET uptake in individuals without overt Aβ pathology at baseline. In summary, plasma p-tau231 and p-tau217 better capture the earliest cerebral Aβ changes, before overt Aβ plaque pathology is present, and are promising blood biomarkers to enrich a preclinical population for Alzheimer's disease clinical trials

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis