Determining the Extent of Market and Extent of Resource for Stated Preference Survey Design Using Mapping Methods

Determining the appropriate survey population and the commodity to be valued are among the most fundamental design decisions for stated preference (SP) surveys. However, often little information is available about who in the population holds measurable value for the resource (the extent of the market) and their perceptions regarding the scope of the resource to be valued (the extent of the resource). In this paper, we present a novel approach using cognitive mapping interview techniques to shed light on these design questions. The method also provides ancillary information that assists in the interpretation of information collected during focus groups and through SP survey administration. The approach was developed and tested as part of an ongoing study on environmental degradation associated with acidification in the Southern Appalachian Mountain region. Although damage from acidification in the study region is broad, it is not clear whether residents of this region care, in both a use and nonuse sense, about resources in their states of residence, in neighboring states, on public lands, or more broadly across the region. From a pilot study, we found that participants show a significant home-state preference in the number and size of natural areas that they value within the larger Southern Appalachian Mountain region. However, this preference is not strong enough to suggest that the market for improving these resources is solely constrained to residents of the state in which the resource is located.stated preference, cognitive mapping, extent of market, extent of resource, definition of commodity

The menin inhibitor revumenib in KMT2A-rearranged or NPM1-mutant leukaemia

Targeting critical epigenetic regulators reverses aberrant transcription in cancer, thereby restoring normal tissue functio

Comparison of various decalcifying agents to evaluate their efficacy

Background: Bone is a biological complex structure primarily comprising collagen and minerals. It is important to demineralize these mineralized tissues to remove their calcium apatite crystals for analysing the sub-cellular, cellular, and fibrillar architecture. Six demineralizing agents’ efficacy was examined by assessing their duration, ease of handling tissue, staining, and histological criteria. The present study aimed to evaluate six commonly used demineralizing agents to identify the best decalcifying agent. Methods: Twenty resected hard tissue specimens (1 cm × 1 cm x 1 cm) from the archives were used in the study. These segments were decalcified by solutions namely 10% nitric acid, 10% formic acid, 14% ethylene di amine tetra acetic acid (EDTA), a mixture of formic acid and hydrochloric acid (formic + HCL) 4% each, and a mixture of formic acid and nitric acid 4% each (formic + HNO3), 10% formal nitric acid further subjected to radiographic endpoint test. Results: The present study confirmed the fact that samples treated with EDTA showed the best overall impression in terms of tissue integrity and histology followed by 10% formal nitric acid which gave fairly good cellular details and was also rapid in the action. Conclusions: Based on the present study findings, we suggest that 10% formal nitric acid is the better decalcifying agent available, considering time and tissue integrity as two main factors

Parents\u27 Perception of their Children\u27s Asthma, 2002-2008: A Community-Based Study

Childhood asthma is a chronic health condition that is one of the leading causes of hospitalizations and missed school days for children. It also affects the lives of both asthmatic children and their families

Online Learning Engagement Factors of Undergraduate Students’ Learning Outcomes: Effects on Learning Satisfaction and Performance

This study aimed to explore the factors influencing the learning experience, using the community of inquiry (CoI) framework, that contribute to students’ satisfaction with online learning and academic performance during the pandemic. Data were collected from 609 undergraduate students at four private universities in Malaysia through an online questionnaire. The questionnaire was derived from the community inquiry survey and the satisfaction with the online learning questionnaire. The empirical results indicated that the primary factors influencing students’ satisfaction with online learning were cognitive presence, social presence, and teaching presence, in that order of importance. The model was further tested with specific measures of online learning satisfaction, including online course interaction, instruction, course management, instructor quality, and satisfaction with the technology used in the course. Factor reduction analysis groups satisfaction into three categories: “interaction, instruction, and course management” were combined into one category, which includes the course instructor and the technology. Stepwise correlation analysis indicated that all the CoI areas had a significant influence on the satisfaction of all three groups, except for the impact of social presence on the satisfaction of online instructors. Among the predictors, cognitive presence consistently played a significant role in all aspects of satisfaction and performance

Electro-deposited nano-webbed structures based on polyaniline/multi walled carbon nanotubes for enzymatic detection of organophosphates

We report the development of an ultrasensitive electrochemical sensor using polyaniline (PANi) and carboxyl functionalized multi-walled carbon nanotubes (fMWCNT) for the detection of organophosphates (OPs) in real samples. The sensor was tested in the linear concentration range of 10 ng/L to 120 ng/L. The limit of detection (LoD) was found to be 8.8 ng/L with sensitivity 0.41 mA/ng/L/cm2 for chlorpyrifos (CPF); and 10.2 ng/L with sensitivity 0.58 mA/ng/L/cm2 for methyl parathion (MP). The vegetable samples (cucumber) were also tested. The average % recovery for CPF and MP were found to be 98.05% and 96.63% respectively. The developed sensor showed stability for a period of 30 days. The interference of the sensor was studied with heavy metals (cadmium (Cd), chromium (Cr), lead (Pb), arsenic (As)) which was found to be < 10%. The developed sensor will play a major role in real-time monitoring of food products, leading to food safety

3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC50) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors

Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors

<p>Abstract</p> <p>Background</p> <p>Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study.</p> <p>Methods</p> <p>Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features.</p> <p>Results</p> <p>The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors.</p> <p>Conclusion</p> <p>A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.</p

Dendronized fluorosurfactant for highly stable water-in-fluorinated oil emulsions with minimal inter-droplet transfer of small molecules

Fluorosurfactant-stabilized microfluidic droplets are widely used as pico- to nanoliter volume reactors in chemistry and biology. However, current surfactants cannot completely prevent inter-droplet transfer of small organic molecules encapsulated or produced inside the droplets. In addition, the microdroplets typically coalesce at temperatures higher than 80 °C. Therefore, the use of droplet-based platforms for ultrahigh-throughput combination drug screening and polymerase chain reaction (PCR)-based rare mutation detection has been limited. Here, we provide insights into designing surfactants that form robust microdroplets with improved stability and resistance to inter-droplet transfer. We used a panel of dendritic oligo-glycerol-based surfactants to demonstrate that a high degree of inter- and intramolecular hydrogen bonding, as well as the dendritic architecture, contribute to high droplet stability in PCR thermal cycling and minimize inter-droplet transfer of the water-soluble fluorescent dye sodium fluorescein salt and the drug doxycycline