Effect of alfalfa supplementary change dietary non-fibrous carbohydrate (NFC) to neutral detergent fiber (NDF) ratio on rumen fermentation and microbial function in Gansu alpine fine wool sheep (Ovis aries).

Bodyweight loss and rumen microbial dysfunction of grazing sheep was a challenge for the sheep production industry during cold season, which were considered to correlated with under-roughage-feeding. Alfalfa is a good roughage supplementary for ruminants, which can improve grazing sheep bodyweight-loss and rumen microbial dysfunction during grass-withering period. This study evaluated the effects of alfalfa hay supplementary change dietary non-fibrous carbohydrate/neutral detergent fiber (NFC/NDF) ratios on rumen fermentation and microbial function of Gansu alpine fine wool sheep during extreme cold season. 120 ewes (3-4 yrs) with an average body weight of 28.71 ± 1.22 kg were allocated randomly into three treatments, and fed NFC/NDF of 1.92 (H group), 1.11 (M group), and 0.68 (L group), respectively. This study was conducted for 107 d, including 7 d of adaption to the diets. The rumen fermentation parameters and microbial characteristics were measured after the end of feeding trials. The results showed that the concentrations of sheep body weight, nitrogen components (Total-N, Soluble protein-N and Ammonia-N), blood biochemical indices (LDH, BUN and CHO) and ruminal volatile fatty acids (TVFA and propionate) significantly increased with an increase in the proportion of NFC/NDF ratios (p < .05), and the acetate and acetate/propionat ratio presented a contrary decreasing trend (p < .05). A total of 1018 OTUs were obtained with 97% consistency. Ruminococcus, Ruminococcaceae and Prevotella were observed as the predominant phyla in ruminal fluid microbiota. Higher NFC/NDF ratios with Alfalfa supplementary increased the richness and diversity of ruminal fluid microbiota, and decreased ruminal fluid microbiota beta-diversity. Using clusters of orthologous groups (COG), the ruminal fluid microbiota of alfalfa supplementary feeding showed low immune pathway and high carbohydrate metabolism pathway. In summary, the study suggested that there was an increasing tendency in dietary NFC/NDF ratio of 1.92 in body weight, ruminal fermentation, microbial community composition and fermentation characteristics through developing alfalfa supplementary system.

Correlation between dynamic contrast-enhanced MRI characteristics and apparent diffusion coefficient with Ki-67-positive expression in non-mass enhancement of breast cancer.

As a remarkably specific characteristic of breast cancer observed on magnetic resonance imaging (MRI), the association between the NME type breast cancer and prognosis, including Ki-67, necessitates comprehensive exploration. To investigate the correlation between dynamic contrast-enhanced MRI (DCE-MRI) characteristics and apparent diffusion coefficient (ADC) values with Ki-67-positive expression in NME type breast cancer. A total of 63 NME type breast cancer patients were retrospectively reviewed. Malignancies were confirmed by surgical pathology. All patients underwent DCE and diffusion-weighted imaging (DWI) before surgery. DCE-MRI characteristics, including tumor distribution, internal enhancement pattern, axillary adenopathy, and time-intensity curve types were observed. ADC values and lesion sizes were also measured. The correlation between these features and Ki-67 expression were assessed using Chi-square test, Fisher's exact test, and Spearman rank analysis. The receiver operating characteristic curve and area under the curve (AUC) was used to evaluate the diagnostic performance of Ki-67-positive expression. Regional distribution, TIC type, and ipsilateral axillary lymph node enlargement were correlated with Ki-67-positive expression (χ2 = 0.397, 0.357, and 0.357, respectively; P < 0.01). ADC value and lesion size were positively correlated with Ki-67-positive expression (rs = 0.295, 0.392; P < 0.05). The optimal threshold values for lesion size and ADC value to assess Ki-67 expression were determined to be 5.05 (AUC = 0.759) cm and 0.403 × 10-3 s/mm2 (AUC = 0.695), respectively. The best diagnosis performance was the ADC combined with lesion size (AUC = 0.791). The ADC value, lesion size, regional distribution, and TIC type in NME type breast cancer were correlated with Ki-67-positive expression. These features will aid diagnosis and treatment of NME type breast cancer.

Assessing the association between overcrowding and human physiological stress response in different urban contexts: a case study in Salzburg, Austria.

Overcrowding in densely populated urban areas is increasingly becoming an issue for mental health disorders. Yet, only few studies have examined the association between overcrowding in cities and physiological stress responses. Thus, this study employed wearable sensors (a wearable camera, an Empatica E4 wristband and a smartphone-based GPS) to assess the association between overcrowding and human physiological stress response in four types of urban contexts (green space, transit space, commercial space, and blue space). A case study with 26 participants was conducted in Salzburg, Austria. We used Mask R-CNN to detect elements related to overcrowding such as human crowds, sitting facilities, vehicles and bikes from first-person video data collected by wearable cameras, and calculated a change score (CS) to assess human physiological stress response based on galvanic skin response (GSR) and skin temperature from the physiological data collected by the wristband, then this study used statistical and spatial analysis to assess the association between the change score and the above elements. The results demonstrate the feasibility of using sensor-based measurement and quantitative analysis to investigate the relationship between human stress and overcrowding in relation to different urban elements. The findings of this study indicate the importance of considering human crowds, sitting facilities, vehicles and bikes to assess the impact of overcrowding on human stress at street level.

Comparison of selected photon shield and organ-based tube current modulation for radiation dose reduction in head computed tomography: A phantom study.

OBJECTIVE: The aim of this study is to investigate the radiation dose and image quality of head CT using SPS and OBTCM techniques. METHODS: Three anthropomorphic head phantoms (1-yr-old, 5-yr-old, and adult) were used. Images were acquired using four modes (Default protocol, OBTCM, SPS, and SPS+OBTCM). Absorbed dose to the lens, anterior brain (brain_A), and posterior brain (brain_P) was measured and compared. Image noise and CNR were assessed in the selected regions of interest (ROIs). RESULTS: Compared with that in the Default protocol, the absorbed dose to the lens reduced by up to 28.33%,71.38%, and 71.12% in OBTCM, SPS, and SPS+OBTCM, respectively. The noise level in OBTCM slightly (≤1.45HU) increased than that in Default protocol, and the SPS or SPS+OBTCM mode resulted in a quantitatively small increase (≤2.58HU) in three phantoms. There was no significant difference in CNR of different phantoms under varies scanning modes (p > 0.05). CONCLUSIONS: During head CT examinations, the SPS mode can reduce the radiation dose while maintaining image quality. SPS+OBTCM couldn't further effectively reduce the absorbed dose to the lens for 1-yr and 5-yr-old phantoms. Thus, SPS mode in pediatric and SPS+OBTCM mode in adult are better than other modes, and should be used in clinical practice.

Assessing the association between urban features and human physiological stress response using wearable sensors in different urban contexts.

Public open space (POS) plays a significant role in fostering human health and wellbeing in cities. A major limitation of current research on POS and health is that there is little attention on the role of various urban features on people's mental health, in different urban context. This study employed wearable sensors (a wearable camera, Empatica 4 wristband and a GPS device) to measure human physiological responses to urban indicators, objectively. To do this, we selected six kinds of public open space (water area, transit area, green area, commercial area, motor traffic area and mixed office and residential area) and recruited 86 participants for an experimental study. Next, we detected urban features by using Microsoft Cognitive Services (MCS) and calculated a change score to assess human physiological stress responses based on galvanic skin response (GSR) and skin temperature from the wristband. Lastly, we applied random effect model and geographically weighted regression analysis to examine the relationship between urban indicators and human physiological stress responses. The findings show that urban flow (vehicles, bikes and people), waterbodies, greenery and places to sit are associated with the changes of human physiological stress response. The findings indicate that the type of urban context may confound the effect of green and blue urban features; i.e., the effect on physiological stress response can be positive or negative depending on the context. The paper highlights the relevance of considering urban context in research on associations between urban features and stress response.

The Modeling of Super Deep Learning Aiming at Knowledge Acquisition in Automatic Driving.

In this paper, we proposed a new theory of solving the multitarget control problem by introducing a machine learning framework in automatic driving and implementing the acquisition of excellent drivers' knowledge. Nowadays, there still exist some core problems that have not been fully realized by the researchers in automatic driving, such as the optimal way to control the multitarget objective functions of energy saving, safe driving, headway distance control, and comfort driving. It is also challenging to resolve the networks that automatic driving is relied on and to improve the performance of GPU chips on complex driving environments. According to these problems, we developed a new theory to map multitarget objective functions in different spaces into the same one and thus introduced a machine learning framework of SDL (super deep learning) for optimal multitarget control based on knowledge acquisition. We will present in this paper the optimal multitarget control by combining the fuzzy relationship of each multitarget objective function and the implementation of excellent drivers' knowledge acquired by machine learning. Theoretically, the impact of this method will exceed that of the fuzzy control method used in the automatic train.

DeepRCI: Predicting ATP-Binding Proteins Using the Residue-Residue Contact Information.

Adenine-5'-triphosphate (ATP) is a direct energy source for various activities of tissues and cells in the body. The release of ATP energies requires the assistance of ATP-binding proteins. Therefore, the identification of ATP-binding proteins is of great significance for the research on organisms. So far, there are several methods for predicting ATP-binding proteins. However, the accuracies of these methods are so low that the predicted proteins are inaccurate. Here, we designed a novel method, called as DeepRCI (based on Deep convolutional neural network and Residue-residue Contact Information), for predicting ATP-binding proteins. In order to maximize the performance of our method, we experimented with different hyperparameters and finally chose a 12-depth-512-filters deep convolutional neural network with an input size of 448*448. By using this model, DeepRCI achieved an accuracy of 93.61% on the test set which means a significant improvement of 11.78% over the state-of-the-art methods. We also compared the performance of residue-residue contact information datasets with different noise levels which are mainly due to gaps in the multiple sequence alignment. Compared with the low-noise dataset, the prediction accuracy on the high-noise dataset is reduced by 6.78%, which affects the performance of DeepRCI to a certain extent. We believe that with the increase of sequence data, this problem will eventually be solved. Finally, we provide a web service of DeepRCI which link can be obtained in Data Availability.

Association of Total Thyroidectomy or Thyroid Lobectomy With the Quality of Life in Patients With Differentiated Thyroid Cancer With Low to Intermediate Risk of Recurrence.

IMPORTANCE: Owing to the good prognosis of differentiated thyroid cancer (DTC), guidelines recommend total thyroidectomy (TT) or thyroid lobectomy (TL) as surgical treatment for DTC with low to intermediate risk of recurrence. However, the association of these surgeries with the health-related quality of life (HRQOL) of patients with DTC with low to intermediate risk of recurrence is unclear. OBJECTIVE: To longitudinally compare the HRQOL of patients with DTC undergoing different surgeries. DESIGN, SETTING, AND PARTICIPANTS: This prospective observational longitudinal cohort study enrolled patients diagnosed with DTC with low to intermediate risk of recurrence at the First Affiliated Hospital, Sun Yat-sen University, China, from October 1, 2018, to September 31, 2019. Eligible patients were categorized into TL and TT groups according to the surgery they underwent. They were evaluated preoperatively and followed up at 1, 3, 6, and 12 months postoperatively using 3 HRQOL-related questionnaires (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, version 3.0; Hospital Anxiety and Depression Scale; and Thyroid Cancer-Specific Quality of Life Questionnaire); serum thyrotropin levels, complications, and patient satisfaction were also monitored. Data were analyzed to compare the HRQOL of patients undergoing different surgeries at different time points. EXPOSURES: Total thyroidectomy or TL. MAIN OUTCOMES AND MEASURES: The primary end point was HRQOL (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, version 3.0; Hospital Anxiety and Depression Scale; and Thyroid Cancer-Specific Quality of Life Questionnaire) at different time points, and the secondary end points were postoperative complications, thyrotropin level, and patient satisfaction. RESULTS: Of the 1060 eligible patients, 563 underwent TL (438 women [77.8%]; median [IQR] age, 38 [31-45] years), and 497 underwent TT (390 women [78.5%]; median [IQR] age, 38 [32-48] years). Compared with the TL group, including the 1- to 4-cm tumor subgroup, the TT group experienced more postoperative HRQOL problems at 1 and 3 months postoperatively. However, nearly all the differences disappeared at 6 and 12 months postoperatively. CONCLUSIONS AND RELEVANCE: Results of this study suggest that HRQOL of patients with DTC with low to intermediate risk of recurrence is not associated with the extent of surgery, and HRQOL may not be an important consideration when making surgical decisions. If better HRQOL is requested in the short term, TL may be preferred.

Association between leisure-time physical activity and the built environment in China: Empirical evidence from an accelerometer and GPS-based fitness app.

To reexamine the relationship between leisure-time physical activity (LTPA) and the built environment (BE), this paper takes advantage of the massive amount of data collected by an accelerometer and GPS-based fitness mobile app. Massive LTPA data from more than 3 million users were recorded by Codoon in 500m by 500m grid cells and aggregated to 742 natural cities in mainland China. Six BE indicators were quantified using GIS at the city scale. Robust regression analysis was used to estimate the correlation between LTPA and BE. Five of six BE indicators-connectivity, road density, land use mix, points of interest density, and density of parks and squares-were significantly, positively, independently, and linearly related to LTPA in the regression analysis. The study obtains findings that are consistent with the previous literature but also provides novel insights into the important role of POI density in encouraging LTPA, as well as how the relationship between LTPA and BE varies by time of day. The study also sheds light on the embrace of new technology and new data in public health and urban studies.

Assessing the Current Integration of Multiple Personalised Wearable Sensors for Environment and Health Monitoring.

The ever-growing development of sensor technology brings new opportunities to investigate impacts of the outdoor environment on human health at the individual level. However, there is limited literature on the use of multiple personalized sensors in urban environments. This review paper focuses on examining how multiple personalized sensors have been integrated to enhance the monitoring of co-exposures and health effects in the city. Following PRISMA guidelines, two reviewers screened 4898 studies from Scopus, Web of Science, ProQuest, Embase, and PubMed databases published from January 2010 to April 2021. In this case, 39 articles met the eligibility criteria. The review begins by examining the characteristics of the reviewed papers to assess the current situation of integrating multiple sensors for health and environment monitoring. Two main challenges were identified from the quality assessment: choosing sensors and integrating data. Lastly, we propose a checklist with feasible measures to improve the integration of multiple sensors for future studies.

A specialized myodural bridge named occipital-dural muscle in the narrow-ridged finless porpoise (Neophocaena asiaeorientalis).

A dense bridge-like tissue named the myodural bridge (MDB) connecting the suboccipital muscles to the spinal dura mater was originally discovered in humans. However, recent animal studies have revealed that the MDB appears to be an evolutionarily conserved anatomic structure which may have significant physiological functions. Our previous investigations have confirmed the existence of the MDB in finless porpoises. The present authors conducted research to expound on the specificity of the MDB in the porpoise Neophocana asiaeorientalis (N.asiaeorientalis). Five carcasses of N.asiaeorientalis, with formalin fixation, were used for the present study. Two of the carcasses were used for head and neck CT scanning, three-dimensional reconstructions, and gross dissection of the suboccipital region. Another carcass was used for a P45 plastination study. Also, a carcass was used for a histological analysis of the suboccipital region and also one was used for a Scanning Electron Microscopy study. The results revealed that the MDB of the N.asiaeorientalis is actually an independent muscle originating from the caudal border of the occiput, passing through the posterior atlanto-occipital interspace, and then attaches to the cervical spinal dura mater. Thus the so called MDB of the N.asiaeorientalis is actually an independent and uniquely specialized muscle. Based on the origin and insertion of this muscle, the present authors name it the 'Occipital-Dural Muscle'. It appears that the direct pull of this muscle on the cervical spinal dura mater may affect the circulation of the cerebrospinal fluid by altering the volume of the subarachnoid space via a pumping action.

Reproducibility of radiomics features derived from intravoxel incoherent motion diffusion-weighted MRI of cervical cancer.

BACKGROUND: The reproducibility of intravoxel incoherent motion (IVIM)-based radiomics studies in humans has not been reported. PURPOSE: To determine the inter- and intra-observer variability on the reproducibility of IVIM-based radiomics features in cervical cancer (CC). MATERIAL AND METHODS: The IVIM images of 25 patients with CC were retrospectively collected. Based on the high-resolution T2-weighted images, the regions of interest (ROIs) were independently delineated twice in diffusion-weighted images at a b value of 1000 s/mm2 (interval time was one month) by two radiologists. This was done at the largest transversal cross-sections of the tumors. The ROI was subsequently used in apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps derived from IVIM images. In total, 105 radiomics features were then finally extracted from the IVIM-derived maps. The inter- and intra-observer reproducibility of IVIM-derived features was then evaluated using the intraclass correlation coefficient. RESULTS: Inter- and intra-observer variability affected the reproducibility of radiomics features. D* map had 100% and 95% reproducible features, ADC map had 89% and 93%, D map had 97% and 86%, while f map had 54% and 62% reproducible features with good to excellent reliability in the intra-observer analysis. Similarly, D* map had 90% and 94%, ADC map had 85% and 70%, D map had 81% and 78%, while f map had 41% and 93% reproducible features with good to excellent reliability in the inter-observer analysis. CONCLUSION: Inter- and intra-observer variability can affect radiomics analysis. Cognizant to this, multicenter studies should pay more attention to intra- and inter-observer variability.

Multilevel and spatial analyses of childhood malnutrition in Uganda: examining individual and contextual factors.

In this study, we examine the concepts of spatial dependence and spatial heterogeneity in the effect of macro-level and micro-level factors on stunting among children aged under five in Uganda. We conducted a cross-sectional analysis of 3624 Ugandan children aged under five, using data from the 2016 Ugandan Demographic and Health Survey. Multilevel mixed-effect analysis, spatial regression methods and multi-scale geographically weight regression (MGWR) analysis were employed to examine the association between our predictors and stunting as well as to analyse spatial dependence and variability in the association. Approximately 28% of children were stunted. In the multilevel analysis, the effect of drought, diurnal temperature and livestock per km2 on stunting was modified by child, parent and household factors. Likewise, the contextual factors had a modifiable effect on the association between child's sex, mother's education and stunting. The results of the spatial regression models indicate a significant spatial error dependence in the residuals. The MGWR suggests rainfall and diurnal temperature had spatial varying associations with stunting. The spatial heterogeneity of rainfall and diurnal temperature as predictors of stunting suggest some areas in Uganda might be more sensitive to variability in these climatic conditions in relation to stunting than others.

An optimal posttreatment surveillance strategy for cancer survivors based on an individualized risk-based approach.

The optimal post-treatment surveillance strategy that can detect early recurrence of a cancer within limited visits remains unexplored. Here we adopt nasopharyngeal carcinoma as the study model to establish an approach to surveillance that balances the effectiveness of disease detection versus costs. A total of 7,043 newly-diagnosed patients are grouped according to a clinic-molecular risk grouping system. We use a random survival forest model to simulate the monthly probability of disease recurrence, and thereby establish risk-based surveillance arrangements that can maximize the efficacy of recurrence detection per visit. Markov decision-analytic models further validate that the risk-based surveillance outperforms the control strategies and is the most cost-effective. These results are confirmed in an external validation cohort. Finally, we recommend the risk-based surveillance arrangement which requires 10, 11, 13 and 14 visits for group I to IV. Our surveillance strategies might pave the way for individualized and economic surveillance for cancer survivors.

DeepRTCP: Predicting ATP-Binding Cassette Transporters Based on 1-Dimensional Convolutional Network.

ATP-binding cassette (ABC) transporters can promote cells to absorb nutrients and excrete harmful substances. It plays a vital role in the transmembrane transport of macromolecules. Therefore, the identification of ABC transporters is of great significance for the biological research. This paper will introduce a novel method called DeepRTCP. DeepRTCP uses the deep convolutional neural network and a feature combined of reduced amino acid alphabet based tripeptide composition and PSSM to recognize ABC transporters. We constructed a dataset named ABC_2020. It contains the latest ABC transporters downloaded from Uniprot. We performed 10-fold cross-validation on DeepRTCP, and the average accuracy of DeepRTCP was 95.96%. Compared with the start-of-the-art method for predicting ABC transporters, DeepRTCP improved the accuracy by 9.29%. It is anticipated that DeepRTCP can be used as an effective ABC transporter classifier which provides a reliable guidance for the research of ABC transporters.

Lobar location of lesions in computed tomography-guided lung biopsy is correlated with major pneumothorax: A STROBE-compliant retrospective study with 1452 cases.

Pneumothorax is a common complication in computed tomography (CT)-guided percutaneous lung biopsy (CPLB). Whether the lobar location of lesions contributes to the incidence of pneumothorax should be further clarified.A total of 1452 consecutive patients who underwent CPLB between January 2010 and March 2018 were retrospectively analyzed. The incidence of pneumothorax was compared among 5 different lobe biopsies. Minor pneumothorax was defined as pneumothorax without chest tube placement and major pneumothorax was defined as pneumothorax with chest tube placement.The positive diagnosis rate of pathology for this cohort was approximately 84%, with 22.5% (326/1452) of the patients experiencing pneumothorax. The rates of pneumothorax were 19.5%, 24.5%, 33.9%, 21.4%, and 23.9% for the right upper lobe, right lower lobe, right middle lobe, left upper lobe, and left lower lobe, respectively (P = .09). Chest tube placement was necessary in 19.0% (62/326) of the patients with pneumothorax. The rates of major pneumothorax were 5.3%, 2.6%, 10.2%, 4.7%, and 2.6% for the right upper lobe, right lower lobe, right middle lobe, left upper lobe, and left lower lobe biopsies, respectively (P = .02). This result was further confirmed by the propensity score-matching method. Moreover, 8.7% (127/1452) of the patients experienced puncture of fissure, the rates of which were 13.5%, 5%, 10.2%, 9.1%, and 4.3% for the right upper lobe, right lower lobe, right middle lobe, left upper lobe, and left lower lobe, respectively (P < .001). Within the pneumothorax patient group, the rate of lobe fissure puncture (15.2%) was significantly lower in patients with minor pneumothorax than (51.6%) in those with major pneumothorax (P < .001).Upper and middle lobe lesion biopsies show a significantly high rate of major pneumothorax, which may be due to more puncture of fissure. It is crucial to carefully distinguish the fissure around lesions and bypass it to avoid major pneumothorax.

Diminished inhibitory impact of ZnO nanoparticles on anaerobic fermentation by the presence of TiO2 nanoparticles: Phenomenon and mechanism.

Engineered nanoparticle materials (ENMs) are widely and increasingly produced and employed in many sectors. The use of diverse ENMs potentially leads to the release of multiple ENMs into the environment. These ENMs after discharge will be end in wastewater treatment plant and present in sludge. This work investigated the effect of multi-ENMs systems of ZnO and TiO2 on sludge anaerobic fermentation and the related toxicity mechanism. Results revealed that the toxicity of ZnO ENMs on anaerobic fermentation was reduced in the presence of TiO2 ENMs. Investigation on the change of free Zn2+ and reactive oxygen species (OH and H2O2) suggested that both of free Zn2+ and ROS contributed to the toxicity mechanism. Zn2+ decrease was the main reason for the reduced toxicity in multi-ENMs systems. ROS mainly led to the reduction of cell viability in anaerobic fermentation systems. The presence of TiO2 in the multi-ENMs systems promoted the recovery of enzyme activity, cell viability and bacteria abundance.

MetaPGN: a pipeline for construction and graphical visualization of annotated pangenome networks.

Pangenome analyses facilitate the interpretation of genetic diversity and evolutionary history of a taxon. However, there is an urgent and unmet need to develop new tools for advanced pangenome construction and visualization, especially for metagenomic data. Here, we present an integrated pipeline, named MetaPGN, for construction and graphical visualization of pangenome networks from either microbial genomes or metagenomes. Given either isolated genomes or metagenomic assemblies coupled with a reference genome of the targeted taxon, MetaPGN generates a pangenome in a topological network, consisting of genes (nodes) and gene-gene genomic adjacencies (edges) of which biological information can be easily updated and retrieved. MetaPGN also includes a self-developed Cytoscape plugin for layout of and interaction with the resulting pangenome network, providing an intuitive and interactive interface for full exploration of genetic diversity. We demonstrate the utility of MetaPGN by constructing Escherichia coli pangenome networks from five E. coli pathogenic strains and 760 human gut microbiomes,revealing extensive genetic diversity of E. coli within both isolates and gut microbial populations. With the ability to extract and visualize gene contents and gene-gene physical adjacencies of a specific taxon from large-scale metagenomic data, MetaPGN provides advantages in expanding pangenome analysis to uncultured microbial taxa.

Hydrogen bonds between methanol and the light liquid olefins 1-pentene and 1-hexene: from application to fundamental science.

We have recently developed a new extraction process for significantly reducing the olefin content in commercial FCC gasoline. To gain insights into the origins of this process, we have investigated the dissolution of the light liquid olefins 1-pentene and 1-hexene in methanol through computer modelling together with NMR spectroscopy. We find two important hydrogen bonding modes for methanol olefin interactions - namely, O-Hπ and C-HO.