Identifying interactions among factors related to death occurred at the scene of traffic accidents: Application of "logic regression" method.

Aim: Traffic accidents are caused by several interacting risk factors. This study aimed to investigate the interactions among risk factors associated with death at the accident scene (DATAS) as an indicator of the crash severity, for pedestrians, passengers, and drivers by adopting "Logic Regression" as a novel approach in the traffic field. Method: A case-control study was designed based on the police data from the Road Traffic Injury Registry in northwest of Iran during 2014-2016. For each of the pedestrians, passengers, and drivers' datasets, logic regression with "logit" link function was fitted and interactions were identified using Annealing algorithm. Model selection was performed using the cross-validation and the null model randomization procedure. Results: regarding pedestrians, "The occurrence of the accident outside a city in a situation where there was insufficient light" (OR = 6.87, P-value<0.001) and "the age over 65 years" (OR = 2.97, P-value<0.001) increased the chance of DATAS. "Accidents happening in residential inner-city areas with a light vehicle, and presence of the pedestrians in the safe zone or on the non-separate two-way road" combination lowered the chance of DATAS (OR = 0.14, P-value<0.001). For passengers, "Accidents happening in outside the city or overturn of the vehicle" combination (OR = 8.55, P-value<0.001), and "accidents happening on defective roads" (OR = 2.18, P-value<0.001) increased the odds of DATAS; When "driver was not injured or the vehicle was two-wheeled", chance of DATAS decreased for passengers (OR = 0.25, p-value<0.001). The odds of DATAS were higher for "drivers who had a head-on accident, or drove a two-wheeler vehicle, or overturned the vehicle" (OR = 4.03, P-value<0.001). "Accident on the roads other than runway or the absence of a multi-car accident or an accident in a non-residential area" (OR = 6.04, P-value<0.001), as well "the accident which occurred outside the city or on defective roads, and the drivers were male" had a higher risk of DATAS for drivers (OR = 5.40, P-value<0.001). Conclusion: By focusing on identifying interaction effects among risk factors associated with DATAS through logic regression, this study contributes to the understanding of the complex nature of traffic accidents and the potential for reducing their occurrence rate or severity. According to the results, the simultaneous presence of some risk factors such as the quality of roads, skill of drivers, physical ability of pedestrians, and compliance with traffic rules play an important role in the severity of the accident. The revealed interactions have practical significance and can play a significant role in the problem-solving process and facilitate breaking the chain of combinations among the risk factors. Therefore, practical suggestions of this study are to control at least one of the risk factors present in each of the identified combinations in order to break the combination to reduce the severity of accidents. This may have, in turn, help the policy-makers, road users, and healthcare professionals to promote road safety through prioritizing interventions focusing on effect size of simultaneous coexistence of crash severity determinants and not just the main effects of single risk factors or their simple two-way interactions.

Contrasting carbon cycle responses of semiarid abandoned farmland to simulated warmer-drier and warmer-wetter climates.

Rewilding abandoned farmlands provides a nature-based climate solution via carbon (C) offsetting; however, the C-cycle-climate feedback in such restored ecosystems is poorly understood. Therefore, we conducted a 2-year field experiment in Loess Plateau, China, to determine the impacts of warming (∼1.4 °C) and altered precipitation (±25 %, ±50 %, and ambient), alone or in concert on soil C pools and associated C fluxes. Experimental warming significantly enhanced soil respiration without affecting the ecosystem net C uptake and soil C storage; these variables tended to increase along the manipulated precipitation gradient. Their interactions increased ecosystem net C uptake (synergism) but decreased soil respiration and soil C accumulation (antagonism) compared with a single warming or altered precipitation. Additionally, most variables related to the C cycle tended to be more responsive to increased precipitation, but the ecosystem net C uptake responded intensely to warming and decreased precipitation. Overall, ecosystem net C uptake and soil C storage increased by 94.4 % and 8.2 %, respectively, under the warmer-wetter scenario; however, phosphorus deficiency restricted soil C accumulation under these climatic conditions. By contrast, ecosystem net C uptake and soil C storage decreased by 56.6 % and 13.6 %, respectively, when exposed to the warmer-drier climate, intensifying its tendency toward a C source. Therefore, the C sink function of semiarid abandoned farmland was unsustainable. Our findings emphasize the need for management of post-abandonment regeneration to sustain ecosystem C sequestration in the context of climate change, aiding policymakers in the development of C-neutral routes in abandoned regions.

Strong Bases and beyond: The Prominent Contribution of Neutral Push-Pull Organic Molecules towards Superbases in the Gas Phase.

In this review, the principles of gas-phase proton basicity measurements and theoretical calculations are recalled as a reminder of how the basicity PA/GB scale, based on Brønsted-Lowry theory, was constructed in the gas-phase (PA-proton affinity and/or GB-gas-phase basicity in the enthalpy and Gibbs energy scale, respectively). The origins of exceptionally strong gas-phase basicity of some organic nitrogen bases containing N-sp3 (amines), N-sp2 (imines, amidines, guanidines, polyguanides, phosphazenes), and N-sp (nitriles) are rationalized. In particular, the role of push-pull nitrogen bases in the development of the gas-phase basicity in the superbasicity region is emphasized. Some reasons for the difficulties in measurements for poly-functional nitrogen bases are highlighted. Various structural phenomena being in relation with gas-phase acid-base equilibria that should be considered in quantum-chemical calculations of PA/GB parameters are discussed. The preparation methods for strong organic push-pull bases containing a N-sp2 site of protonation are briefly reviewed. Finally, recent trends in research on neutral organic superbases, leaning toward catalytic and other remarkable applications, are underlined.

A novel insecticide impairs bumblebee memory and sucrose responsiveness across high and low nutrition.

Wild bees are important pollinators of crops and wildflowers but are exposed to a myriad of different anthropogenic stressors, such as pesticides and poor nutrition, as a consequence of intensive agriculture. These stressors do not act in isolation, but interact, and may exacerbate one another. Here, we assessed whether a field-realistic concentration of flupyradifurone, a novel pesticide that has been labelled as 'bee safe' by regulators, influenced bumblebee sucrose responsiveness and long-term memory. In a fully crossed experimental design, we exposed individual bumblebees (Bombus impatiens) to flupyradifurone at high (50% (w/w)) or low (15% (w/w)) sucrose concentrations, replicating diets that are either carbohydrate rich or poor, respectively. We found that flupyradifurone impaired sucrose responsiveness and long-term memory at both sucrose concentrations, indicating that better nutrition did not buffer the negative impact of flupyradifurone. We found no individual impact of sugar deficiency on bee behaviour and no significant interactions between pesticide exposure and poor nutrition. Our results add to a growing body of evidence demonstrating that flupyradifurone has significant negative impacts on pollinators, indicating that this pesticide is not 'bee safe'. This suggests that agrochemical risk assessments are not protecting pollinators from the unintended consequences of pesticide use.

Identifying interactive effects of spatial drivers in soil heavy metal pollutants using interpretable machine learning models.

The accurate identification of spatial drivers is crucial for effectively managing soil heavy metals (SHM). However, understanding the complex and diverse spatial drivers of SHM and their interactive effects remains a significant challenge. In this study, we present a comprehensive analysis framework that integrates Geodetector, CatBoost, and SHapley Additive exPlanations (SHAP) techniques to identify and elucidate the interactive effects of spatial drivers in SHM within the Pearl River Delta (PRD) region of China. Our investigation incorporated fourteen environmental factors and focused on the pollution levels of three prominent heavy metals: Hg, Cd, and Zn. These findings provide several key insights: (1) The distribution of SHM is influenced by the combined effects of various individual factors and interactions within the source-flow-sink process. (2) Compared with the spatial interpretation of individual factors, the interaction between Hg and Cd exhibited enhanced spatial explanatory power. Similarly, interactions involving Zn mainly demonstrated increased spatial explanatory power, but there was one exception in which a weakening was observed. (3) Spatial heterogeneity plays a crucial role in determining the contributions of environmental factors to soil heavy metal concentrations. Although individual factors generally promote metal accumulation, their effects fluctuate when interactions are considered. (4) The SHAP interpretable method effectively addresses the limitations associated with machine-learning models by providing understandable insights into heavy metal pollution. This enables a comparison of the importance of environmental factors and elucidates their directional impacts, thereby aiding in the understanding of interaction mechanisms. The methods and findings presented in this study offer valuable insights into the spatial heterogeneity of heavy metal pollution in soil. By focusing on the effects of interactive factors, we aimed to develop more accurate strategies for managing SHM pollution.

Global untargeted and individual targeted plasma metabolomics of breast cancer recurrence modified by hormone receptors.

BACKGROUND: Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis. METHODS: We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case-control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model. RESULTS: In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18-0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant. CONCLUSION: Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis.

Clear as a bell? Policy stringency and elderly health during Covid-19.

This paper investigates how restriction policies have impacted elderly self-assessed health (SAH) in Europe during the pandemic, and how the Covid-19 infection interacts with policy stringency to modulate the SAH deterioration. Using the Survey of Health, Aging and Retirement in Europe (SHARE) between October 2019 and August 2021, including 9,034 adults aged 50 years and above, alongside with a stringency index from the Oxford's Coronavirus Government Response Tracker (OxCGRT), we design both an adjusted probit model and a recursive bivariate probit model to test for endogeneity of Covid-19 infection. Estimations results show a bell curve between stringency and SAH degradation: a deleterious effect of restrictions at low levels of stringency up to a tipping point after which more stringent policies become protective. Covid-19 infection moderates this association. Depending on individuals' initial health, the effect of restrictions is uneven: highly stringent policies become damaging for individuals most likely to enter a vulnerabilization path, for whom the bell curve is thus inverted. Overall, this study shows clear patterns of association between policy stringency and perceived health among older Europeans, and highlights the potential trade-off between targeting as many people as possible, those in poor health or those on the edge of vulnerability.

Arbuscular Mycorrhizal Fungi-Mediated Modulation of Physiological, Biochemical, and Secondary Metabolite Responses in Hemp (Cannabis sativa L.) under Salt and Drought Stress.

The increasing impact of global climate change has resulted in adversity stresses, like salt and drought, gradually becoming the main factors that limit crop growth. Hemp, which contains numerous medicinal active components and multiple bioactive functions, is widely used in the agricultural, industrial, and medical fields, hence promoting the rapid development of related industries. Arbuscular mycorrhizal fungi (AMF) can establish a symbiotic relationship with 80% of vascular plants. This symbiosis promotes host plant growth, regulates plant physiology and biochemistry, facilitates secondary metabolite synthesis, and enhances resistance to abiotic stresses. However, the effects of salt stress, drought stress, and AMF interaction in hemp are not well understood. In this study, to investigate this, we performed a study where we cultured hemp that was either inoculated or uninoculated with Funneliformis mosseae and determined changes in effective colonization rate, growth, soluble substances, photosynthesis, fluorescence, ions, and secondary metabolites by cultivating hemp under different concentrations of NaCl (0 mM, 100 mM, and 200 mM) and different soil moisture content (45%, 25%, and 15%). The results showed that salt, drought stress, or salt-drought interaction stress all inhibited colonization rate after stress, plant growth, mainly due to ion toxicity and oxidative damage. Inoculation with F. mosseae effectively alleviated plant growth inhibition under 100 mM NaCl salt stress, drought stress, and salt-drought interaction stress conditions. It also improved osmoregulation, photosynthetic properties, fluorescence properties, and ion homeostasis, and promoted the accumulation of secondary metabolites. However, under 200 mM NaCl salt stress conditions, inoculation with F. mosseae negatively affected plant physiology, biochemistry, and secondary metabolite synthesis, although it did alleviate growth inhibition. The results demonstrate that there are different effects of salt-drought interaction stress versus single stress (salt or drought stress) on plant growth physiology. In addition, we provide new insights about the positive effects of AMF on host plants under such stress conditions and the effects of AMF on plants under high salt stress.

Analysing spatial variability in drought sensitivity of rivers using explainable artificial intelligence.

Hydrological drought can have a severe negative impact on aquatic ecosystems and human living standards. Therefore, being able to predict and gain more insights in the spatial variability in drought sensitivity of rivers is of relevance for water managers. The drought sensitivity of a river is in this study represented by four drought metrics, of which three are relative towards the ecological minimal flow. Statistical and machine learning methods were evaluated to predict these metrics for rivers in the Flanders region of Belgium based on catchment characteristics and data on human interferences. XGBoost had the best performance, with an explained variance of 80 % to 90 %. After applying explaining AI on these models, insights were obtained in the spatial variability of the drought metrics. Irrigation is the most important variable, a high percentage of irrigation leads to a higher drought sensitivity. If there are a lot of human interferences, there is a higher drought sensitivity. Many of the observed dependencies can be explained by the differences in soil infiltration capacity and transferability of water for sandy versus clay soils. No clear dependence with the amount of forest or agriculture was observed, implying that the impact of forest and agriculture on the drought sensitivity of a river is complex.

Coupled effect of load weights and belt use on male shoulder pressure redistribution.

Shoulder pressure redistribution is jointly affected by backpack loads and belt support. However, the combined effect of both factors has rarely been fully evaluated. Here, we studied the coupled effect of backpack loads and belt support on shoulder pressure redistribution. All twenty-eight healthy male subjects underwent eight loading conditions with both chest and hip belts fastened (CH) and unfastened (CON) in four conditions where the backpack weighed 7.5, 15, 22.5, and 30% of body weight (BW). Shoulder pressure distribution was quantified through a pressure-sensing vest mat. The results showed that using the hip belt and chest belt was effective in relieving the high pressure in the lateral clavicle and medial trapezius region and strengthening the load-bearing capacity of shoulder. However, the assistance in pressure relief of using belt was weakened when load increased to 30% BW. This study also showed that the belt use can be effective in improving pressure asymmetry on both sides.

Compression caused by loads may result in shoulder injuries. An in-depth analysis of shoulder pressure distribution is necessary. This study showed that the hip-belt and chest-belt use was effective in relieving the high pressure in the lateral clavicle region and medial trapezius region and strengthening the load-bearing capacity of shoulder.

Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China.

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies. In this study, we comprehensively investigated the combined effects of multiple large-scale atmospheric circulation patterns on precipitation changes in China. Specifically, Pearson correlation analysis and Partial Wavelet Coherence (PWC) were used to identify the primary teleconnection factors influencing precipitation dynamics. Furthermore, we used the cross-wavelet method to elucidate the temporal lag and periodic relationships between multiple teleconnection factors and their interactions. Finally, the multiple wavelet coherence analysis method was used to identify the dominant two-factor and three-factor combinations shaping precipitation dynamics. This analysis facilitated the quantification and determination of interaction types and influencing pathways of teleconnection factors on precipitation dynamics, respectively. The results showed that: (1) the Atlantic Multidecadal Oscillation (AMO), EI Niño-Southern Oscillation (ENSO), East Asia Summer Monsoon (EASM), and Indian Ocean Dipole (IOD) were dominant teleconnection factors influencing Standardized Precipitation Index (SPI) dynamics; (2) significant correlation and leading or lagging relationships at different timescales generally existed for various teleconnection factors, where AMO was mainly leading the other factors with positive correlation, while ENSO and Southern Oscillation (SO) were mainly lagging behind other factors with prolonged correlations; and (3) the interactions between teleconnection factors were quantified into three types: enhancing, independent and offsetting effects. Specifically, the enhancing effect of two-factor combinations was stronger than the offsetting effect, where AMO + NAO (North Atlantic Oscillation) and AMO + AO (Atlantic Oscillation) had a larger distribution area in southern China. Conversely, the offsetting effect of three-factor combinations was more significant than that of the two-factor combinations, which was mainly distributed in northeast and northwest regions of China. This study sheds new light on the mechanisms of modulation and pathways of influencing various large-scale factors on seasonal precipitation dynamics.

Improving hospital quality risk-adjustment models using interactions identified by hierarchical group lasso regularisation.

BACKGROUND: Risk-adjustment (RA) models are used to account for severity of illness in comparing patient outcomes across hospitals. Researchers specify covariates as main effects, but they often ignore interactions or use stratification to account for effect modification, despite limitations due to rare events and sparse data. Three Agency for Healthcare Research and Quality (AHRQ) hospital-level Quality Indicators currently use stratified models, but their variable performance and limited interpretability motivated the design of better models. METHODS: We analysed patient discharge de-identified data from 14 State Inpatient Databases, AHRQ Healthcare Cost and Utilization Project, California Department of Health Care Access and Information, and New York State Department of Health. We used hierarchical group lasso regularisation (HGLR) to identify first-order interactions in several AHRQ inpatient quality indicators (IQI) - IQI 09 (Pancreatic Resection Mortality Rate), IQI 11 (Abdominal Aortic Aneurysm Repair Mortality Rate), and Patient Safety Indicator 14 (Postoperative Wound Dehiscence Rate). These models were compared with stratum-specific and composite main effects models with covariates selected by least absolute shrinkage and selection operator (LASSO). RESULTS: HGLR identified clinically meaningful interactions for all models. Synergistic IQI 11 interactions, such as between hypertension and respiratory failure, suggest patients who merit special attention in perioperative care. Antagonistic IQI 11 interactions, such as between shock and chronic comorbidities, illustrate that naïve main effects models overestimate risk in key subpopulations. Interactions for PSI 14 suggest key subpopulations for whom the risk of wound dehiscence is similar between open and laparoscopic approaches, whereas laparoscopic approach is safer for other groups. Model performance was similar or superior for composite models with HGLR-selected features, compared to those with LASSO-selected features. CONCLUSIONS: In this application to high-profile, high-stakes risk-adjustment models, HGLR selected interactions that maintained or improved model performance in populations with heterogeneous risk, while identifying clinically important interactions. The HGLR package is scalable to handle a large number of covariates and their interactions and is customisable to use multiple CPU cores to reduce analysis time. The HGLR method will allow scholars to avoid creating stratified models on sparse data, improve model calibration, and reduce bias. Future work involves testing using other combinations of risk factors, such as vital signs and laboratory values. Our study focuses on a real-world problem of considerable importance to hospitals and policy-makers who must use RA models for statutorily mandated public reporting and payment programmes.

Wind Energy Harvesting with Vertically Aligned Piezoelectric Inverted Flags.

Wind-energy-harvesting generators based on inverted flag architecture are an attractive option to replace batteries in low-power wireless electronic devices and deploy-and-forget distributed sensors. This study examines two important aspects that have been overlooked in previous research: the interaction between an inverted flag and a neighboring solid boundary and the interaction among multiple contiguous inverted flags arranged in a vertical row. Systematic tests have been carried out with metal-only 'baseline' flags as well as a 'harvester' variant, i.e., the baseline metal flag covered with PVDF (polyvinylidene difluoride) piezoelectric polymer elements. In each case, dynamic response and power generation were measured and assessed. For baseline metal flags, the same qualitative trend is observed when the flag approaches an obstacle, whether this is a wall or another flag. As the gap distance reduces, the wind speed range at which flapping occurs gradually shrinks and shifts towards lower velocities. The increased damping introduced by attaching PVDF elements to the baseline metal flags led to a considerable narrowing of the flapping wind speed range, and the wall-to-flag or flag-to-flag interaction led to a power reduction of up to one order of magnitude compared to single flags. The present findings highlight the strong dependence of the power output on the flapping frequency, which decreases when the flag approaches a wall or other flags mounted onto the same pole. Minimum flag-to-flag and flag-to-wall spacing values are suggested for practical applications to avoid power reduction in multi-flag arrangements (2-3H and 1-2H respectively, where H is flag height).

Interactive effects of sleep and physical activity on depression among rural university students in China.

Background: Decreased sleep quality and physical activity among university students have become important concerns, while depressive symptoms are on the rise, especially in rural areas. Previous studies have confirmed the association between sleep quality and physical activity and depressive symptoms, but the effect of their interaction on depressive symptoms has been less studied. For this reason, the present study analyzed the interaction between sleep quality and physical activity on depressive symptoms to provide reference and assistance for mental health promotion and intervention for university students in rural areas of China. Methods: In this study, we investigated sleep quality, physical activity, and depressive symptoms in 11,423 university students in rural areas of China. The association of sleep quality and physical activity with depressive symptoms was analyzed by using univariate analysis and logistic regression analysis. And further analyzed the association between the interaction effect of sleep quality and physical activity and depressive symptoms. Results: The proportion of university students with depressive symptoms in rural China was 33.3%, with a higher proportion of girls students (36.7%) having depressive symptoms than boys students (28.8%). Logistic regression analysis of the interaction between sleep quality and physical activity and depressive symptoms in university students showed that university students with poor sleep quality and MVPA>60 min/d (OR = 4.40,95% CI: 3.75-5.05) had the highest risk of depressive symptoms (p < 0.001). University students with moderate sleep quality and MVPA of 30-60 min/d (OR = 1.18, 95% CI: 0.75-1.61) had the lowest risk of depressive symptoms (p < 0.001). Moreover, there was no gender difference in this result. Conclusion: The prevalence of depressive symptoms was higher among university students in rural areas of China. There was an interaction between sleep quality and MVPA on depressive symptoms, maintaining a good quality of sleep and an appropriate length of MVPA has a contributory effect on mental health, and the same trend was found for both boys and girls students. It is recommended that university students in rural areas of China should first maintain proper sleep quality while maintaining 30-60 min of MVPA per day, which may reduce the risk of depressive symptoms.

The effect of different levels of vitamin C and chromium on growth performance, carcass characteristics, digestive organs, immunity, blood constituents, liver enzymes, cecal microflora, meat sensory taste and fatty acid profile of breast meat in broilers.

BACKGROUND: Antioxidants such as vitamin C (VC) and chromium (Cr), which effectively scavenge free radicals, may improve functional characteristics of the intestine and may reduce intestinal diseases. Cr absorption increases in the presence of VC. In poultry, VC is mainly derived from glucose; hence, Cr is an important component for glucose tolerance. We evaluated the synergistic effects of these two antioxidants together. OBJECTIVES: This study aims to investigate two levels of VC and two levels of Cr and their interaction on growth performance, carcass characteristics, digestive organs, immunity, blood constituents, liver enzymes, cecal microflora, meat sensory taste and fatty acid profile of breast meat in broilers. METHODS: Two levels of VC (250 and 500 mg/kg dry matter [DM]) and two levels of Cr (700 and 1400 µg/kg DM) were added to a basic diet for 42 days in five treatments. The 2 × 2 plus 1 (control group) factorial experiment was performed in a completely randomised design for 42 days using 360 one-day-old male chicks. RESULTS: Very low-density lipoprotein, high-density lipoprotein, low-density lipoprotein, total cholesterol and triglyceride level, liver enzymes, antibody titer against sheep red blood cells, fat content, odour, chewing ability, elasticity and oral sensation traits were affected by combination of VC and Cr. CONCLUSIONS: Combination of VC and Cr can increase unsaturated fatty acids and decrease saturated fatty acids, as well as improve cecal microbial flora, and may be useful as antioxidant compounds and non-antimicrobial stimulants for economic growth. The use of 250 mg/kg of VC and 700 µg/kg of Cr is recommended in broiler diets.

Comparative assessment of the performance of one- and two-liquid phase biotrickling filters for the simultaneous abatement of gaseous mixture of methanol, α-pinene, and hydrogen sulfide.

A gaseous mixture of methanol (M), α-pinene (P), and hydrogen sulfide (H) was treated in one/two-liquid phase biotrickling filters (OLP/TLP-BTFs) at varying inlet concentrations and at an empty bed residence time (EBRT) of 57 s. The performance of TLP-BTF [BTF (A)] improved significantly in terms of M and P removal due to the presence of silicone oil at 5% v/v. The maximum elimination capacities (ECs) of M, P, and H in BTF (A) were obtained as 309, 73, and 56 g m-3 h-1, respectively. While, the maximum ECs achieved in the BTF operated without silicone oil [BTF (B)] were 172, 28, and 21 g m-3 h-1 for M, P, and H removal, respectively. Increasing the inlet concentration of H from 32 to 337 ppm inhibited P removal in both the BTFs. The presence of silicone oil enhanced gas-liquid mass transfer, prevented the BTF from experiencing substrate inhibition effects and allowed reaching high ECs for M and P. The experiments showed promising results for the long-term operation of removal of M, P, and H mixture in a one-stage TLP-BTF with the decreasing negative effects of M and H on P degradation.

Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

The Interaction of Dietary Patterns and Genetic Variants on the Risk of Cardiovascular Diseases in Chinese Patients with Type 2 Diabetes.

SCOPE: Diabetes is an important risk factor for cardiovascular disease (CVD), which in turn is the most common and serious complication of diabetes. This study analyzes dietary patterns and single nucleotide polymorphisms (SNPs) in 543 diabetes patients with new-onset cardiovascular events and 461 diabetic patients without. METHODS AND RESULTS: SNPs are determined and analyzed using real time PCR and gene chip method. Factor analysis and logistic regression are used to determine dietary patterns and evaluate the level of associations and interaction effects, respectively. The legumes and edible fungi pattern and vegetable pattern show a significant negative correlation with complication risk. ADIPOQ rs37563 and legumes and edible fungi pattern have a significant interactive effect on disease, and patients with a high score of C polymorphism genotype (GC + CC) have a lower risk of disease. 5-10-Methylenetetrahydrofolate reductase (MTHFR) rs1801131 and vegetable pattern have a borderline interaction effect on disease, and those patients with TT genotype have a lower risk of disease. CONCLUSION: These findings provide new insights into the role of the interactive protection of dietary patterns and SNPs. And participants with specific alleles show a lower risk of cardiovascular complications.

A hybrid approach of random forest and random parameters logit model of injury severity modeling of vulnerable road users involved crashes.

Vulnerable road users (VRUs) involved crashes are a major road safety concern due to the high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity models separately have limitations in crash data analysis. This study develops a hybrid approach of Random Forest based SHAP algorithm (RF-SHAP) and random parameters logit modeling framework to explore significant factors and identify the underlying interaction effects on injury severity of VRUs-involved crashes in Shenyang (China) from 2015 to 2017. The results show that the hybrid approach can uncover more underlying causality, which not only quantifies the impact of individual factors on injury severity, but also finds the interaction effects between the factors with random parameters and fixed parameters. Seven factors are found to have significant effect on crash injury severity. Two factors, including primary roads and rural areas produce random parameters. The interaction effects reveal interesting combination features. For example, even though rural areas and primary roads increase the likelihood of fatal crash occurrence individually, the interaction effect of the two factors decreases the likelihood of being fatal. The findings form the foundation for developing safety countermeasures targeted at specific crash groups for reducing fatalities in future crashes.

Association of insulin signaling pathway-related gene polymorphisms and gene-gene interactions with MAFLD in obese children. / èƒ°å²›ç´ ä¿¡å·é€šè·¯ç›¸å ³åŸºå› å¤šæ€æ€§å’ŒåŸºå› -åŸºå› äº¤äº’ä½œç”¨ä¸Žè‚¥èƒ–å„¿ç«¥MAFLDçš„å ³è”.

OBJECTIVES: Insulin signaling pathway plays an important role in metabolic associated fatty liver disease (MAFLD), however, the association between polymorphisms of genes related to insulin signaling pathway and MAFLD remains unclear. This study aims to investigate the association between insulin signaling pathway-related gene polymorphisms and gene-gene interactions with MAFLD susceptibility in obese children so as to provide scientific basis for further study of genetic mechanism. METHODS: A total of 502 obese children with MAFLD who admitted to Hunan Provincial Children's Hospital from September 2019 to October 2021, were recruited as a case group, and 421 obese children with non-MAFLD admitted during the same period were recruited as a control group. Socio-demographic information, preterm birth history, eating habits, and exercise status of the subjects were collected by inquiry survey, and anthropometric information was collected by physical measurement. At the same time, 2 mL of venous blood was collected to extract DNA, and the polymorphism of insulin signaling pathway-related genes (5 representative candidate genes, 12 variants) was detected. Multivariate Logistic regression analysis was used to investigate the association between insulin signaling pathway-related gene polymorphisms and MAFLD in obese children. RESULTS: After adjusting for confounder factors, INS rs3842748 was significantly associated with the risk of MAFLD in obese children in allele, heterozygous, and dominant models [OR and 95% CI 1.749 (1.053 to 2.905), 1.909 (1.115 to 3.267), 1.862 (1.098 to 3.157), all P<0.05]; INS rs3842752 was significantly associated with the risk of MAFLD in obese children in heterozygous and dominant models [OR and 95% CI 1.736 (1.028 to 2.932), 1.700 (1.015 to 2.846), all P<0.05]. NR1H3 rs3758674 was significantly correlated with the risk of MAFLD in obese children in allele model [OR and 95% CI 0.716 (0.514 to 0.997), P<0.05]. SREBP-1c rs2297508 was significantly associated with the risk of MAFLD in obese children in allele and dominant models [OR and 95% CI 0.772 (0.602 to 0.991) and 0.743 (0.557 to 0.991), all P<0.05]. SREBP-1c rs8066560 was significantly associated with the risk of MAFLD in obese children in allele, heterozygous, and dominant models [OR and 95% CI 0.759 (0.589 to 0.980), 0.733 (0.541 to 0.992), 0.727 (0.543 to 0.974), all P<0.05]. NR1H3 rs3758674 mutant C and SREBP-1c rs2297508 mutant G had interaction in the development of MAFLD in obese children [OR and 95% CI 0.407 (0.173 to 0.954), P<0.05]. CONCLUSIONS: The INS, NR1H3, and SREBP-1c gene polymorphisms in the insulin signaling pathway are associated with the susceptibility of MAFLD in obese children, but the functions and mechanisms of these genes need to be further studied.