Satellite mapping reveals phytoplankton biomass's spatio-temporal dynamics and responses to environmental factors in a eutrophic inland lake.

Chlorophyll a (Chla) concentration can be used as an indicator of algal biomass, and the accumulation of algal biomass in water column is essential for the emergence of surface blooms. By using Moderate Resolution Imaging Spectrometer (MODIS) data, a machine learning algorithm was previously developed to assess algal biomass within the euphotic depth (Beu). Here, a long-term Beu dataset of Lake Taihu from 2003 to 2020 was generated to examine its spatio-temporal dynamics, sensitivity to environmental factors, and variations in comparison to the surface algal bloom area. During this period, the daily Beu (total Beu within the whole lake) exhibited temporal fluctuations between 40 and 90 t Chla, with an annual average of 63.32 ± 5.23 t Chla. Notably, it reached its highest levels in 2007 (72.34 t Chla) and 2017 (73.57 t Chla). Moreover, it demonstrated a clear increasing trend of 0.197 t Chla/y from 2003 to 2007, followed by a slight decrease of 0.247 t Chla/y after 2017. Seasonal variation showed a bimodal annual cycle, characterized by a minor peak in March âˆ¼ April and a major peak in July âˆ¼ September. Spatially, the average pixel-based Beu (total Beu of a unit water column) ranged from 21.17 to 49.85 mg Chla, with high values predominantly distributed in the northwest region and low values in the central region. The sensitivity of Beu to environmental factors varies depending on regions and time scales. Temperature has a significant impact on monthly variation (65.73%), while the level of nutrient concentrations influences annual variation (55.06%). Wind speed, temperature, and hydrodynamic conditions collectively influence the spatial distribution of Beu throughout the entire lake. Algal bloom biomass can capture trend changes in two mutant years as well as bimodal phenological changes compared to surface algal bloom area. This study can provide a basis for scientific evaluation of water environment and a reference for monitoring algal biomass in other similar eutrophic lakes.

Longitudinal Associations between Metacognition and Spontaneous and Deliberate Mind Wandering During Early Adolescence.

Although metacognition plays a pivotal role in theoretical accounts of mind wandering, their longitudinal relationships have not yet been investigated during the important developmental period of early adolescence. This study aimed to examine the developmental trajectories of spontaneous and deliberate mind wandering and the dynamic associations between metacognition and two types of mind wandering in early adolescence. A sample of 4302 Chinese students beginning in Grade 4 (47.4% female; initial Mage = 9.84, SDage = 0.47) completed questionnaires on five occasions over 2.5 years. The results showed that deliberate mind wandering, but not spontaneous mind wandering, gradually increased from Grade 4 to Grade 6. Metacognition was negatively related to spontaneous mind wandering but positively related to deliberate mind wandering. These findings provide empirical evidence for theoretical viewpoints from both individual differences and developmental perspectives.

Greater habitual resveratrol intakes were associated with lower risk of hip fracture- a 1:1 matched case-control study in Chinese elderly.

The aim of the study was to testify the association of dietary resveratrol (RSV) intakes with hip fracture risk in Chinese elderly. This was a 1:1 age- and gender- matched case-control study. Eligible cases were newly diagnosed patients of hip fracture. Dietary assessment was made by a 79-item validated food frequency questionnaire. Habitual RSV intakes were estimated as the sum of trans- and cis- isomers of resveratrol and piceid according to the available database. Multivariable conditional logistic regression was applied to examine the relationship of dietary RSV and RSV-rich foods with hip fracture risk. A total of 1,070 pairs of hip fracture incident cases and controls were recruited and 1,065 were included for analysis. Compared with the lowest group, total RSV in the highest quartile group had significantly reduced hip fracture risk by 66.3% (OR: 0.337, 0.222 ~ 0.571, ptrend < 0.001). Similar findings were observed for cis- and trans-RSV, cis- and trans-Piceid, as well as RSV-rich foods (grapes, apples and nuts) respectively. Subgroup analysis suggested more evident findings among female and less obese participants. Our findings demonstrated that higher habitual RSV intakes and RSV-rich foods, even in a relatively low amount, were associated with reduced risk of hip fracture in Chinese elderly.

Free-Triiodothyronine to Free-Thyroxine Ratio Mediated the Effect of Prepregnancy Body Mass Index or Maternal Weight Gain During Early Pregnancy on Gestational Diabetes Mellitus.

OBJECTIVE: Maternal overweight or obesity during early pregnancy can increase the subsequent risk of gestational diabetes mellitus (GDM). However, whether these associations are mediated by thyroid hormones and their effect sizes is still unknown. This study aimed to identify the mediating effects of thyroid parameters between prepregnancy body mass index (BMI) or maternal weight gain during early pregnancy on the subsequent risk of GDM. METHODS: This prospective mother-infant cohort study was conducted from 2018 to 2019. A total of 2772 singleton pregnant women were included in the analysis. A questionnaire survey, anthropometric measures, and thyroid function testing were conducted during early pregnancy. Deiodinase activity was evaluated using the free-triiodothyronine-to-free-thyroxine ratio (FT3:FT4). The standard 75-g oral glucose tolerance test was performed during 24 to 28 weeks of gestation to diagnose GDM. A mediation analysis was performed using PROCESS 3.5 to examine the mediating effects of thyroid parameters between prepregnancy BMI or maternal weight gain during early pregnancy on the subsequent risk of GDM. RESULTS: The FT3:FT4 ratio was a significant mediator between prepregnancy BMI or maternal weight gain and GDM, accounting for 16.5% and 18.6% of total effects, respectively. FT3 also mediated the association of prepregnancy BMI with GDM, accounting for 3.3% of the total effects. Thyroid-stimulating hormone suppressed the effects of prepregnancy BMI and maternal weight gain on GDM risk, and the proportion of their total effects was 2.4% and 6.4%, respectively. CONCLUSION: Deiodinase activity, as indicated by the FT3:FT4 ratio, was the strongest mediator among thyroid parameters between prepregnancy BMI or maternal early weight gain and GDM.

A clinical model and nomogram for early prediction of gestational diabetes based on common maternal demographics and routine clinical parameters.

AIM: We aimed to develop a risk prediction model for gestational diabetes mellitus (GDM) based on the common maternal demographics and routine clinical variables in Chinese population. METHODS: Individual information was collected from December 2018 to October 2019 by a pretested questionnaire on demographics, medical and family history, and lifestyle factors. Multivariable logistic regression was performed to establish a predictive model for GDM by variables in pre- and early pregnancy. The consistency and discriminative validity of the model were evaluated by Hosmer-Lemeshow goodness-of-fit testing and ROC curve analysis. Internal validation was appraised by fivefold cross-validation. Clinical utility was assessed by decision curve analysis. RESULTS: Total 3263 pregnant women were included with 17.2% prevalence of GDM. The model equation was: LogitP = -11.432 + 0.065 × maternal age (years) + 0.061 × pre-pregnancy BMI (kg/m2 ) + 0.055 × weight gain in early pregnancy (kg) + 0.872 × history of GDM + 0.336 × first-degree family history of diabetes +0.213 × sex hormone usages during pre- or early pregnancy + 1.089 × fasting glucose (mmol/L) + 0.409 × triglycerides (mmol/L) + 0.082 × white blood cell count (109/L) + 0.669 × positive urinary glucose. Homer-Lemeshow goodness-of-fit testing indicated a good consistency between predictive and actual data (p = 0.586). The area under the ROC curve (AUC) was 0.720 (95% CI: 0.697 ~ 0.744). Cross-validation suggested a good internal validity of the model. A nomogram has been made to establish an easy to use scoring system for clinical practice. CONCLUSIONS: The predictive model of GDM exhibited well acceptable predictive ability, discriminative performance, and clinical utilities. The project was registered in clinicaltrial.gov.com with identifier of NCT03922087.

Anthocyanins regulate serum adipsin and visfatin in patients with prediabetes or newly diagnosed diabetes: a randomized controlled trial.

BACKGROUND: Epidemiological studies have suggested that adipsin and visfatin are associated with the development of type 2 diabetes. This is the first study to investigate the effects of supplementation with purified anthocyanins on serum adipsin and visfatin in patients with prediabetes or newly diagnosed diabetes. METHODS: A total of 160 participants with prediabetes or newly diagnosed diabetes (40-75 years old) were given 320 mg anthocyanins or placebo daily for 12 weeks in a randomized trial. Serum adipsin, serum visfatin, lipids and glycated hemoglobin A1c (HbA1c) were measured. The areas under the curve (AUCs) for glucose, insulin and C-peptide were determined before-and after-treatment by a standard 3-h 75 g oral glucose tolerance test (OGTT). RESULTS: Relatively significant increases in serum adipsin (net change 0.15 µg/mL [0.03, 0.27], p = 0.018) and decreases in visfatin (-3.5 ng/mL [-6.69, -0.31], p = 0.032) were observed between the anthocyanins and placebo groups. We also observed significant improvements in HbA1c (-0.11% [-0.22, -0.11], p = 0.033), apolipoprotein A-1 (apo A-1) (0.12 g/L [0.03, 0.21], p = 0.012) and apolipoprotein B (apo B) (-0.07 g/L [-0.14, -0.01], p = 0.033) in response to the anthocyanins intervention. CONCLUSION: Purified anthocyanins supplementation for 12 weeks increased serum adipsin and decreased serum visfatin in patients with prediabetes or newly diagnosed diabetes. Trial registration ClinicalTrials.gov, identifier: NCT02689765.

Trends and determinants of catastrophic health expenditure in China 2010-2018: a national panel data analysis.

BACKGROUND: Catastrophic health expenditures (CHE) are out-of-pocket payments (OOP) that exceed a predefined percentage or threshold of a household's resources, usually 40 %, that can push households into poverty in China. We analyzed the trends in the incidence and intensity, and explored the determinants, of CHE, and proposed policy recommendation to address CHE. METHODS: A unique 5-year national urban-rural panel database was constructed from the China Family Panel Studies (CFPS) surveys. CHE incidence was measured by calculating headcount (percentage of households incurring CHE to the total household sample) and intensity was measured by overshoot (degree by which an average out of pocket health expenditure exceeds the threshold of the total sample). A linear probability model was employed to assess the trend in the net effect of the determinants of CHE incidence and a random effect logit model was used to analyse the role of the characteristics of the household head, the household and household health utilization on CHE incidence. RESULTS: CHE determinants vary across time and geographical location. From 2010 to 2018, the total, urban and rural CHE incidence all showed a decreasing tend, falling from 14.7 to 8.7 % for total households, 12.5-6.6 % in urban and 16.8-10.9 % in rural areas. CHE intensity decreased in rural (24.50-20.51 %) and urban (22.31-19.57 %) areas and for all households (23.61-20.15 %). Inpatient services were the most important determinant of the incidence of CHE. For urban households, the random effect logit model identified household head (age, education, self-rated health); household characteristics (members 65 + years, chronic diseases, family size and income status); and healthcare utilization (inpatient and outpatient usage) as determinants of CHE. For rural areas, the same variables were significant with the addition of household head's sex and health insurance. CONCLUSIONS: The incidence and intensity of CHE in China displayed a downward trend, but was higher in rural than urban areas. Costs of inpatient service usage should be a key intervention strategy to address CHE. The policy implications include improving the economic level of poor households, reforming health insurance and reinforcing pre-payment hospital insurance methods.

The 6-month effect of whole soy and purified isoflavones daidzein on thyroid function-A double-blind, randomized, placebo controlled trial among Chinese equol-producing postmenopausal women.

The aim of this study was to examine the effect of whole soy and purified daidzein on markers of thyroid function in Chinese postmenopausal women who were equol-producers. Total 270 eligible women were randomized to either one of the three isocaloric supplements: 40 g soy flour (whole soy group), 40 g low-fat milk powder +63 mg daidzein (daidzein group) or 40 g low-fat milk powder (placebo) daily for 6 months. Serum thyroid markers were tested at baseline and 6 months for thyroid stimulating hormone, free triiodothyronine, reverse triiodothyronine and free thyroxine (FT4). There was no significant difference in the 6-month changes of thyroid markers among the three groups. Subgroup analysis among women with lowered thyroid function suggested a modest decrease of FT4. This randomized controlled trial among Chinese equol-producing postmenopausal women indicates the consumption of whole soy and purified daidzein at the provided dosages are safe and have no detrimental effect on thyroid function.

Use of Extended-Hückel Descriptors for Rapid and Accurate Predictions of Conjugated Torsional Energy Barriers.

Over the past few decades, virtual high-throughput screening (vHTS) and molecular dynamics simulations have become effective and widely used tools in the initial stages of drug discovery efforts. These methods allow a great number of druglike molecules to be screened quickly and inexpensively. Unfortunately, however, the accuracies of both these methods rely on the quality of the underlying molecular mechanics force fields (FFs), which are often poor. This major weakness originates from the reliance of FFs on a finite list of specific parameters, called atom types, which have low transferability between molecules. In particular, the torsional energy barriers of druglike molecules are notoriously difficult to predict. Continuing our endeavor to understand factors affecting the torsional energy barriers of small molecules and quantify them, we showed that descriptors calculated using the extended-Hückel method could be used to rapidly assign accurate torsion parameters for conjugated molecules. This method, called H-TEQ 4.5, was developed using a set of 684 conjugated molecules. It was subsequently validated on a test set of 200 diverse molecules and produced an average root-mean-square error (rmse) of 1.01 kcal·mol-1, with respect to the reference quantum mechanic torsional profiles. For comparison, GAFF2, MMFF94, and MAB produced average rmse's of 3.49, 1.50, and 1.77 kcal·mol-1, respectively. H-TEQ 4.5 is also computationally inexpensive, running just under 0.25 ms for a biphenyl molecule on a home computer, allowing it to be used for vHTS of large libraries of compounds. Overall, H-TEQ 4.5 solved the problems associated with the transferability of torsion parameters for conjugated molecules. This method was incorporated into the Molecular Operating Environment and will be available for a wide variety of applications.

Effect of whole soy and purified daidzein on androgenic hormones in chinese equol-producing post-menopausal women: a six-month randomised, double-blinded and Placebo-Controlled trial.

A randomised, double-blind and placebo-controlled trial was performed to examine the effects of whole soy and isoflavone daidzein on serum androgenic hormones in Chinese equol-producing post-menopausal women. A total of 270 eligible women aged 45-70 years were randomised to either one of the three iso-caloric supplements: 40 g soy flour (whole soy group), 40 g low-fat milk powder +63 mg daidzein (daidzein group) or 40 g low-fat milk powder (placebo group) daily for 6 months. Fasting venous samples were tested for serum androstenedione (AD), testosterone (T), prolactin, sex hormone binding globulin and dehydroepiandrosterone sulphate. Intention-to-treat analysis indicated that serum T (p = .022) and AD (p = .05) levels modestly but significantly decreased after 6-month daidzein treatment in comparison with placebo, with a mean difference of -0.057 nmol/L (95%CI: -0.185 to 0.070, p = .018) and -0.118 ng/mL (95%CI: -0.240-0.004, p = .045), respectively. This 6-month trial suggested that purified daidzein may exhibit less androgenic effect.Trial registration: The trial was registered in ClinicalTrials.gov with identifier of NCT01270737. (URL: http://clinicaltrials.gov/ct2/show/NCT01270737.).

Asymmetric α-alkylation of cyclic ß-keto esters and ß-keto amides by phase-transfer catalysis.

Without employing any transition metal, a highly enantioselective α-alkylation of cyclic ß-keto esters and ß-keto amides has been realized by phase-transfer catalysis. This improved procedure is applicable to different kinds of halides with cinchona derivatives and gives the corresponding products in excellent enantiopurities (up to 98% ee) and good yields (up to 98%). Moreover, the reaction was scalable and the phase-transfer catalyst was recyclable. This provided an alternative and competitive method to the asymmetric α-alkylation of ß-dicarbonyl compounds.

Atom Type Independent Modeling of the Conformational Energy of Benzylic, Allylic, and Other Bonds Adjacent to Conjugated Systems.

Applications of computational methods to predict binding affinities for protein/drug complexes are routinely used in structure-based drug discovery. Applications of these methods often rely on empirical force fields (FFs) and their associated parameter sets and atom types. However, it is widely accepted that FFs cannot accurately cover the entire chemical space of drug-like molecules, due to the restrictive cost of parametrization and the poor transferability of existing parameters. To address these limitations, initiatives have been carried out to develop more transferable methods, in order to allow for more rigorous descriptions of any drug-like molecule. We have previously reported H-TEQ, a method which does not rely on atom types and incorporates well established chemical principles to assign parameters to organic molecules. The previous implementation of H-TEQ (a torsional barrier prediction method) only covered saturated and lone pair containing molecules; here, we report our efforts to incorporate conjugated systems into our model. The next step was the evaluation of the introduction of unsaturations. The developed model (H-TEQ3.0) has been validated on a wide variety of molecules containing heteroaromatic groups, alkyls, and fused ring systems. Our method performs on par with one of the most commonly used FFs (GAFF2), without relying on atom types or any prior parametrization.

Torsional Energy Barriers of Biaryls Could Be Predicted by Electron Richness/Deficiency of Aromatic Rings; Advancement of Molecular Mechanics toward Atom-Type Independence.

Biaryl molecules are ubiquitous pharmacophores found in natural products and pharmaceuticals. In spite of this, existing molecular mechanics force fields are unable to accurately reproduce their torsional energy profiles, except for a few well-parametrized cases. This effectively limits the ability of structure-based drug design methods to correctly identify hits involving biaryls with confidence (e.g., during virtual screening, employing docking and/or molecular dynamics simulations). Continuing in our endeavor to quantify organic chemistry principles, we showed that the torsional energy profile of biaryl compounds could be computed on-the-fly based on the electron richness/deficiency of the aromatic rings. This method, called H-TEQ 4.0, was developed using a set of 131 biaryls. It was subsequently validated on a separate set of 100 diverse biaryls, including multisubstituted, bicyclic and tricyclic druglike molecules, and produced an average root-mean-square error (RMSE) of 0.95 kcal·mol-1. For comparison, GAFF2 produced an RMSE of 3.88 kcal·mol-1, owing to problems associated with the transferability of torsion parameters. The success of H-TEQ 4.0 provided further evidence that force fields could transition to become atom-type independent, providing that the correct chemical principles are used. Overall, this method solved the problem of transferability of biaryl torsion parameters, while simultaneously improving the overall accuracy of the force field.

Prevalence of sleep disturbances in Chinese university students: a comprehensive meta-analysis.

This is a meta-analysis of the pooled prevalence of sleep disturbances and its associated factors in Chinese university students. English (PubMed, PsycINFO, Embase) and Chinese (SinoMed, Wan Fang Database and Chinese National Knowledge Infrastructure) databases were systematically and independently searched from inception until 16 August 2016. The prevalence of sleep disturbances was pooled using random-effects model. Altogether 76 studies involving 112 939 university students were included. The overall pooled prevalence of sleep disturbances was 25.7% (95% CI: 22.5-28.9%). When using the screening scales Pittsburgh Sleep Quality Index, Athens Insomnia Scale and Self-Rating Sleeping State Scale, and the diagnostic criteria of the Chinese Classification of Mental Disorders (Second Edition), the pooled prevalence of sleep disturbances was 24.1% (95% CI: 21.0-27.5%) and 18.1% (95% CI: 16.4-20.0%), respectively. The percentages of students dissatisfied with sleep quality and those suffering from insomnia symptoms were 20.3% (95% CI: 13.0-30.3%) and 23.6% (95% CI: 18.9-29.0%), respectively. Subgroup analyses revealed that medical students were more vulnerable to sleep disturbances than other student groups. There was no significant difference between males and females, and across geographic locations. Sleep disturbances are common in Chinese university students. Appropriate strategies for prevention and treatment of sleep disturbances in this population need greater attention.

Enantioselective α-Benzoyloxylation of ß-Keto Esters by N-Oxide Phase-Transfer Catalysts.

An efficient and enantioselective α-benzoyloxylation of ß-keto esters has been achieved by phase-transfer catalysis. This simple catalytic procedure is applicable to a range of ß-keto esters with cinchona-derived N-oxide asymmetric phase-transfer catalysts and gives the corresponding products in good enantiopurity (up to 95% ee) and yield (up to 99%). This simple and effective oxyfunctionalization is a useful synthetic strategy for introducing an oxygen-containing functional group at the α position of ß-dicarbonyl compounds.

I2-Triggered N-O cleavage of ketoxime acetates for the synthesis of 3-(4-pyridyl)indoles.

A facile and complementary [3 + 2 + 1] annulation of aryl ketoxime acetates and 3-formylindoles to give pyridine derivatives is reported. The condensation reaction demonstrated that I2 was capable of triggering N-O bond cleavage of ketoxime acetates to generate iminyl radicals via a single electron transfer pathway. This direct and operationally simple protocol provides a fundamental platform to synthesize 3-(4-pyridyl)indoles with high functional group compatibility and high regioselectivity.

Atom Types Independent Molecular Mechanics Method for Predicting the Conformational Energy of Small Molecules.

We previously implemented a well-known qualitative chemical principle into an accurate quantitative model computing relative potential energies of conformers. According to this principle, hyperconjugation strength correlates with electronegativity of donors and acceptors. While this earlier version of our model applies to σ bonds, lone pairs, disregarded in this earlier version, also have a major impact on the conformational preferences of molecules. Among the well-established principles used by organic chemists to rationalize some organic chemical behaviors are the anomeric effect, the alpha effect, basicity, and nucleophilicity. These effects are directly related to the presence of lone pairs. We report herein our effort to incorporate lone pairs into our model to extend its applicability domain to any saturated small molecules. The developed model H-TEQ 2 has been validated on a wide variety of molecules from polyaromatic molecules to carbohydrates and molecules with high heteroatoms/carbon ratios. Interestingly, this method, in contrast to common force field-based methods, does not rely on atom types and is virtually applicable to any organic molecules.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

The influence of visual mental imagery size on metamemory accuracy in judgment of learning.

Many studies have found the font size of to-be-remembered words has a significant influence on judgments of learning (JOLs). However, few studies have investigated whether JOLs are affected by the mental imagery size of to-be-remembered words, even when the font sizes themselves are kept identical in study materials. This study investigated whether the visual mental imagery size influences the participants' JOLs and what the underlying mechanisms are. In Experiments 1 and 2, participants learned words with identical font sizes, mentally generated large or small imageries and then made JOLs. We found that JOLs under the large imagery condition were significantly higher than those under the small imagery condition, but actual recall performance exhibited no significant difference. In Experiment 3, participants pressed a button immediately after mental imagery generation and showed that it took significantly longer to generate large imageries than to generate small imageries, and the difference in JOLs between two conditions was no longer significant. In Experiment 4, we used a questionnaire to investigate the contribution of beliefs and found that participants believed large imageries were easier to remember. These findings indicate that imagery size has a significant impact on JOLs, in which beliefs may play a leading role.

Elucidating Hyperconjugation from Electronegativity to Predict Drug Conformational Energy in a High Throughput Manner.

Computational chemists use structure-based drug design and molecular dynamics of drug/protein complexes which require an accurate description of the conformational space of drugs. Organic chemists use qualitative chemical principles such as the effect of electronegativity on hyperconjugation, the impact of steric clashes on stereochemical outcome of reactions, and the consequence of resonance on the shape of molecules to rationalize experimental observations. While computational chemists speak about electron densities and molecular orbitals, organic chemists speak about partial charges and localized molecular orbitals. Attempts to reconcile these two parallel approaches such as programs for natural bond orbitals and intrinsic atomic orbitals computing Lewis structures-like orbitals and reaction mechanism have appeared. In the past, we have shown that encoding and quantifying chemistry knowledge and qualitative principles can lead to predictive methods. In the same vein, we thought to understand the conformational behaviors of molecules and to encode this knowledge back into a molecular mechanics tool computing conformational potential energy and to develop an alternative to atom types and training of force fields on large sets of molecules. Herein, we describe a conceptually new approach to model torsion energies based on fundamental chemistry principles. To demonstrate our approach, torsional energy parameters were derived on-the-fly from atomic properties. When the torsional energy terms implemented in GAFF, Parm@Frosst, and MMFF94 were substituted by our method, the accuracy of these force fields to reproduce MP2-derived torsional energy profiles and their transferability to a variety of functional groups and drug fragments were overall improved. In addition, our method did not rely on atom types and consequently did not suffer from poor automated atom type assignments.