Social Media Data Mining of Antitobacco Campaign Messages: Machine Learning Analysis of Facebook Posts.

BACKGROUND: Social media platforms provide a valuable source of public health information, as one-third of US adults seek specific health information online. Many antitobacco campaigns have recognized such trends among youth and have shifted their advertising time and effort toward digital platforms. Timely evidence is needed to inform the adaptation of antitobacco campaigns to changing social media platforms. OBJECTIVE: In this study, we conducted a content analysis of major antitobacco campaigns on Facebook using machine learning and natural language processing (NLP) methods, as well as a traditional approach, to investigate the factors that may influence effective antismoking information dissemination and user engagement. METHODS: We collected 3515 posts and 28,125 associated comments from 7 large national and local antitobacco campaigns on Facebook between 2018 and 2021, including the Real Cost, Truth, CDC Tobacco Free (formally known as Tips from Former Smokers, where "CDC" refers to the Centers for Disease Control and Prevention), the Tobacco Prevention Toolkit, Behind the Haze VA, the Campaign for Tobacco-Free Kids, and Smoke Free US campaigns. NLP methods were used for content analysis, including parsimonious rule-based models for sentiment analysis and topic modeling. Logistic regression models were fitted to examine the relationship of antismoking message-framing strategies and viewer responses and engagement. RESULTS: We found that large campaigns from government and nonprofit organizations had more user engagements compared to local and smaller campaigns. Facebook users were more likely to engage in negatively framed campaign posts. Negative posts tended to receive more negative comments (odds ratio [OR] 1.40, 95% CI 1.20-1.65). Positively framed posts generated more negative comments (OR 1.41, 95% CI 1.19-1.66) as well as positive comments (OR 1.29, 95% CI 1.13-1.48). Our content analysis and topic modeling uncovered that the most popular campaign posts tended to be informational (ie, providing new information), where the key phrases included talking about harmful chemicals (n=43, 43%) as well as the risk to pets (n=17, 17%). CONCLUSIONS: Facebook users tend to engage more in antitobacco educational campaigns that are framed negatively. The most popular campaign posts are those providing new information, with key phrases and topics discussing harmful chemicals and risks of secondhand smoke for pets. Educational campaign designers can use such insights to increase the reach of antismoking campaigns and promote behavioral changes.

Associations between use of specific social media sites and electronic cigarette use among college students.

OBJECTIVE: To examine dose-response associations between use of specific social media sites and the use of electronic cigarettes (e-cigarettes) and traditional cigarettes. METHODS: This was a cross-sectional study of 298 first-year college students enrolled in the fall 2019 semester at a large state university. Heckman selection and Probit model were used to estimate associations between use of specific social media sites and e-cigarette/traditional cigarette use. RESULTS: Each additional hour per day spent on Snapchat was associated with a 4.61% increase in the probability of lifetime e-cigarette use. In addition, among current e-cigarette users, more time spent on Snapchat was associated with more frequent e-cigarette use (marginal effects: 0.13, p = 0.001). Facebook, Twitter, Snapchat and Instagram were not associated with traditional cigarette smoking. CONCLUSION: Snapchat was the only major social media platform associated with both lifetime and current e-cigarette use.

The allosteric mechanism leading to an open-groove lipid conductive state of the TMEM16F scramblase.

TMEM16F is a Ca2+-activated phospholipid scramblase in the TMEM16 family of membrane proteins. Unlike other TMEM16s exhibiting a membrane-exposed hydrophilic groove that serves as a translocation pathway for lipids, the experimentally determined structures of TMEM16F shows the groove in a closed conformation even under conditions of maximal scramblase activity. It is currently unknown if/how TMEM16F groove can open for lipid scrambling. Here we describe the analysis of ~400 µs all-atom molecular dynamics (MD) simulations of the TMEM16F revealing an allosteric mechanism leading to an open-groove, lipid scrambling competent state of the protein. The groove opens into a continuous hydrophilic conduit that is highly similar in structure to that seen in other activated scramblases. The allosteric pathway connects this opening to an observed destabilization of the Ca2+ ion bound at the distal site near the dimer interface, to the dynamics of specific protein regions that produces the open-groove state to scramble phospholipids.

The permeation of potassium ions through the lipid scrambling path of the membrane protein nhTMEM16.

The TMEM16 family of transmembrane proteins includes Ca2+-activated phospholipid scramblases (PLS) that can also function as non-selective ion channels. Extensive structural and functional studies have established that a membrane-exposed hydrophilic groove in TMEM16 PLS can serve as a translocation pathway for lipids. However, it is still unclear how the TMEM16 PLS conduct ions. A "protein-delimited pore" model suggests that ions are translocated through a narrow opening of the groove region, which is not sufficiently wide to allow lipid movement, whereas a "proteolipidic pore" model envisions ions and lipids translocating through an open conformation of the groove. We investigated the dynamic path of potassium ion (K+) translocation that occurs when an open groove state of nhTMEM16 is obtained from long atomistic molecular dynamics (MD) simulations, and calculated the free energy profile of the ion movement through the groove with umbrella sampling methodology. The free energy profile identifies effects of specific interactions along the K+ permeation path. The same calculations were performed to investigate ion permeation through a groove closed to lipid permeation in the nhTMEM16 L302A mutant which exhibits a stable conformation of the groove that does not permit lipid scrambling. Our results identify structural and energy parameters that enable K+ permeation, and suggest that the presence of lipids in the nhTMEM16 groove observed in the simulations during scrambling or in/out diffusion, affect the efficiency of K+ permeation to various extents.

TMEM16 scramblases thin the membrane to enable lipid scrambling.

TMEM16 scramblases dissipate the plasma membrane lipid asymmetry to activate multiple eukaryotic cellular pathways. Scrambling was proposed to occur with lipid headgroups moving between leaflets through a membrane-spanning hydrophilic groove. Direct information on lipid-groove interactions is lacking. We report the 2.3 Å resolution cryogenic electron microscopy structure of the nanodisc-reconstituted Ca2+-bound afTMEM16 scramblase showing how rearrangement of individual lipids at the open pathway results in pronounced membrane thinning. Only the groove's intracellular vestibule contacts lipids, and mutagenesis suggests scrambling does not require specific protein-lipid interactions with the extracellular vestibule. We find scrambling can occur outside a closed groove in thinner membranes and is inhibited in thicker membranes, despite an open pathway. Our results show afTMEM16 thins the membrane to enable scrambling and that an open hydrophilic pathway is not a structural requirement to allow rapid transbilayer movement of lipids. This mechanism could be extended to other scramblases lacking a hydrophilic groove.

Does Physical Activity Predict Obesity-A Machine Learning and Statistical Method-Based Analysis.

BACKGROUND: Obesity prevalence has become one of the most prominent issues in global public health. Physical activity has been recognized as a key player in the obesity epidemic. OBJECTIVES: The objectives of this study are to (1) examine the relationship between physical activity and weight status and (2) assess the performance and predictive power of a set of popular machine learning and traditional statistical methods. METHODS: National Health and Nutrition Examination Survey (NHANES, 2003 to 2006) data were used. A total of 7162 participants met our inclusion criteria (3682 males and 3480 females), with average age ranging from 48.6 (normal weight) to 52.1 years old (overweight). Eleven classifying algorithms-including logistic regression, naïve Bayes, Radial Basis Function (RBF), local k-nearest neighbors (k-NN), classification via regression (CVR), random subspace, decision table, multiobjective evolutionary fuzzy classifier, random tree, J48, and multilayer perceptron-were implemented and evaluated, and they were compared with traditional logistic regression model estimates. RESULTS: With physical activity and basic demographic status, of all methods analyzed, the random subspace classifier algorithm achieved the highest overall accuracy and area under the receiver operating characteristic (ROC) curve (AUC). The duration of vigorous-intensity activity in one week and the duration of moderate-intensity activity in one week were important attributes. In general, most algorithms showed similar performance. Logistic regression was middle-ranking in terms of overall accuracy, sensitivity, specificity, and AUC among all methods. CONCLUSIONS: Physical activity was an important factor in predicting weight status, with gender, age, and race/ethnicity being less but still essential factors associated with weight outcomes. Tailored intervention policies and programs should target the differences rooted in these demographic factors to curb the increase in the prevalence of obesity and reduce disparities among sub-demographic populations.

Healthfulness Assessment of Recipes Shared on Pinterest: Natural Language Processing and Content Analysis.

BACKGROUND: Although Pinterest has become a popular platform for distributing influential information that shapes users' behaviors, the role of recipes pinned on Pinterest in these behaviors is not well understood. OBJECTIVE: This study aims to explore the patterns of food ingredients and the nutritional content of recipes posted on Pinterest and to examine the factors associated with recipes that engage more users. METHODS: Data were collected from Pinterest between June 28 and July 12, 2020 (207 recipes and 2818 comments). All samples were collected via 2 new user accounts with no search history. A codebook was developed with a raw agreement rate of 0.97 across all variables. Content analysis and natural language processing sentiment analysis techniques were employed. RESULTS: Recipes using seafood or vegetables as the main ingredient had, on average, fewer calories and less sodium, sugar, and cholesterol than meat- or poultry-based recipes. For recipes using meat as the main ingredient, more than half of the energy was obtained from fat (277/490, 56.6%). Although the most followed pinners tended to post recipes containing more poultry or seafood and less meat, recipes with higher fat content or providing more calories per serving were more popular, having more shared photos or videos and comments. The natural language processing-based sentiment analysis suggested that Pinterest users weighted taste more heavily than complexity (225/2818, 8.0%) and health (84/2828, 2.9%). CONCLUSIONS: Although popular pinners tended to post recipes with more seafood or poultry or vegetables and less meat, recipes with higher fat and sugar content were more user-engaging, with more photo or video shares and comments. Data on Pinterest behaviors can inform the development and implementation of nutrition health interventions to promote healthy recipe sharing on social media platforms.

Membrane lipids are both the substrates and a mechanistically responsive environment of TMEM16 scramblase proteins.

Recent discoveries about functional mechanisms of proteins in the TMEM16 family of phospholipid scramblases have illuminated the dual role of the membrane as both the substrate and a mechanistically responsive environment in the wide range of physiological processes and genetic disorders in which they are implicated. This is highlighted in the review of recent findings from our collaborative investigations of molecular mechanisms of TMEM16 scramblases that emerged from iterative functional, structural, and computational experimentation. In the context of this review, we present new MD simulations and trajectory analyses motivated by the fact that new structural information about the TMEM16 scramblases is emerging from cryo-EM determinations in lipid nanodiscs. Because the functional environment of these proteins in in vivo and in in vitro is closer to flat membranes, we studied comparatively the responses of the membrane to the TMEM16 proteins in flat membranes and nanodiscs. We find that bilayer shapes in the nanodiscs are very different from those observed in the flat membrane systems, but the function-related slanting of the membrane observed at the nhTMEM16 boundary with the protein is similar in the nanodiscs and in the flat bilayers. This changes, however, in the bilayer composed of longer-tail lipids, which is thicker near the phospholipid translocation pathway, which may reflect an enhanced tendency of the long tails to penetrate the pathway and create, as shown previously, a nonconductive environment. These findings support the correspondence between the mechanistic involvement of the lipid environment in the flat membranes, and the nanodiscs. © 2019 Wiley Periodicals, Inc.

Dynamic modulation of the lipid translocation groove generates a conductive ion channel in Ca2+-bound nhTMEM16.

Both lipid and ion translocation by Ca2+-regulated TMEM16 transmembrane proteins utilizes a membrane-exposed hydrophilic groove. Several conformations of the groove are observed in TMEM16 protein structures, but how these conformations form, and what functions they support, remains unknown. From analyses of atomistic molecular dynamics simulations of Ca2+-bound nhTMEM16 we find that the mechanism of a conformational transition of the groove from membrane-exposed to occluded from the membrane involves the repositioning of transmembrane helix 4 (TM4) following its disengagement from a TM3/TM4 interaction interface. Residue L302 is a key element in the hydrophobic TM3/TM4 interaction patch that braces the open-groove conformation, which should be changed by an L302A mutation. The structure of the L302A mutant determined by cryogenic electron microscopy (cryo-EM) reveals a partially closed groove that could translocate ions, but not lipids. This is corroborated with functional assays showing severely impaired lipid scrambling, but robust channel activity by L302A.

FeP/C Composites as an Anode Material for K-Ion Batteries.

Owing to their natural abundance, the low potential, and the low cost of potassium, potassium-ion batteries are regarded as one of the alternatives to lithium-ion batteries. In this work, we successfully fabricated a FeP/C composite, a novel electrode material for PIBs, through a simple and productive high-energy ball-milling method. The electrode delivers a reversible capacity of 288.9 mA·h·g-1 (2nd) at a discharge rate of 50 mA g-1, which can meet the future energy storage requirements. Density functional theory calculations suggest a lower diffusion barrier energy of K+ than Na+, which allows faster K+ diffusion in FeP.

A Cobalt-Free Li(Li0.17 Ni0.17 Fe0.17 Mn0.49 )O2 Cathode with More Oxygen-Involving Charge Compensation for Lithium-Ion Batteries.

High-energy-density and low-cost lithium-ion batteries are sought to meet increasing demand for portable electronics. In this study, a cobalt-free Li(Li0.17 Ni0.17 Fe0.17 Mn0.49 )O2 (LNFMO) cathode material is chosen, owing to the reversible anionic redox couple O2- /O- . The aim is to elucidate the Fe-substitution function and oxygen redox mechanism of experimentally synthesized Li(Li0.16 Ni0.19 Fe0.18 Mn0.46 )O2 by DFT. The redox processes of cobalt-containing Li(Li0.17 Ni0.17 Co0.17 Mn0.49 )O2 (LNCMO) are compared with those of LNFMO. Redox couples including Ni2+ /Ni3+ /Ni4+ , Fe3+ /Fe4+ or Co3+ /Co4+ , and O2- /O- are found, confirmed by a X-ray photoelectron spectroscopy, and explained by redox competition between O and transition metals. In LNFMO and LNCMO, O ions with an Li-O-Li configuration readily participate in oxidation, and the most active O ions are coordinated to Mn4+ and Li+ . Oxidation of O in LNCMO is triggered earlier, along with that of Co. Fe substitution activates O ions, contributes additional oxygen redox charge compensation of 0.44 e per formula unit, avoids concentrated accumulation of oxygen oxidation, and improves structural stability. This work provides new scope for designing cobalt-free, low-cost, and higher-energy-density cathode materials for Li-ion batteries.

A Cobalt-Free Li(Li0.16 Ni0.19 Fe0.18 Mn0.46 )O2 Cathode for Lithium-Ion Batteries with Anionic Redox Reactions.

Lithium-rich, Mn-based layered oxides Li2 MnO3 -LiMO2 (M=Ni, Co) have been considered as promising cathode candidates owing to their high capacity. However, the resources shortage and high price of cobalt make it imperious to substitute cobalt with other high-abundance elements. Here, we synthesized a low-cost, cobalt-free, Fe-substituted oxide material, Li(Li0.16 Ni0.19 Fe0.18 Mn0.46 )O2 . It exhibited a high reversible capacity of 169.2 mAh g-1 after 100 cycles and maintained an extraordinarily high discharge potential during cycling. X-ray photoelectron spectroscopy and DFT calculations revealed that super iron FeIV exists in the delithiated state, and oxygen participates in the redox reaction in addition to the Ni2+ /Ni4+ and Fe3+ /Fe4+ redox couples. The anionic oxidation preferentially occurred on oxygen with a Li-O-Li configuration and with oxidized Fe and Ni coordination.

Lithiation Behavior of Coaxial Hollow Nanocables of Carbon-Silicon Composite.

A design of coaxial hollow nanocables of carbon nanotubes and silicon composite (CNTs@Silicon) was presented, and the lithiation/delithiation behavior was investigated. The FIB-SEM studies demonstrated hollow structured silicon tends to expand inward and shrink outward during lithiation/delithiation, which reveal the mechanism of inhibitive effect of the excessive growth of solid-electrolyte interface by hollow structured silicon. The as-prepared coaxial hollow nanocables demonstrate an impressive reversible specific capacity of 1150 mAh g-1 over 500 cycles, giving an average Coulombic efficiency of >99.9%. The electrochemical impedance spectroscopy and differential scanning calorimetry confirmed the SEI film excessive growth is prevented.

High Volumetric Capacity of Hollow Structured SnO2@Si Nanospheres for Lithium-Ion Batteries.

A novel design of hollow structured SnO2@Si nanospheres was presented, which not only demonstrates high volumetric capacity as anode of LIBs, but also prevents aggregation of Sn and confines solid electrolyte interphase thickening. An impressive volumetric specific capacity of 1030 mAh cm-3 was maintained after 500 cycles. The electrochemical impedance spectroscopy and differential scanning calorimetry indicated that solid electrolyte interphase can be confined in pores of as-prepared hollow structured SnO2@Si.

Monitoring Water Clusters "Melt" Through Vibrational Spectroscopy.

Characterizing structural and phase transformations of water at the molecular level is key to understanding a variety of multiphase processes ranging from ice nucleation in the atmosphere to hydration of biomolecules and wetting of solid surfaces. In this study, state-of-the-art quantum simulations with a many-body water potential energy surface, which exhibits chemical and spectroscopic accuracy, are carried out to monitor the microscopic melting of the water hexamer through the analysis of vibrational spectra and appropriate structural order parameters as a function of temperature. The water hexamer is specifically chosen as a case study due to the central role of this cluster in the molecular-level understanding of hydrogen bonding in water. Besides being in agreement with the experimental data available for selected isomers at very low temperature, the present results provide quantitative insights into the interplay between energetic, entropic, and nuclear quantum effects on the evolution of water clusters from "solid-like" to "liquid-like" structures. This study thus demonstrates that computer simulations can now bridge the gap between measurements currently possible for individual isomers at very low temperature and observations of isomer mixtures at ambient conditions.

Confined Solid Electrolyte Interphase Growth Space with Solid Polymer Electrolyte in Hollow Structured Silicon Anode for Li-Ion Batteries.

Silicon anodes for lithium-ion batteries are of much interest owing to their extremely high specific capacity but still face some challenges, especially the tremendous volume change which occurs in cycling and further leads to the disintegration of electrode structure and excessive growth of solid electrolyte interphase (SEI). Here, we designed a novel approach to confine the inward growth of SEI by filling solid polymer electrolyte (SPE) into pores of hollow silicon spheres. The as-prepared composite delivers a high specific capacity of more than 2100 mAh g-1 and a long-term cycle stability with a reversible capacity of 1350 mAh g-1 over 500 cycles. The growing behavior of SEI was investigated by electrochemical impedance spectroscopy and differential scanning calorimetry, and the results revealed that SPE occupies the major space of SEI growth and thus confines its excessive growth, which significantly improves cycle performance and Coulombic efficiency of cells embracing hollow silicon spheres.

Tuning vibrational mode localization with frequency windowing.

Local-mode coordinates have previously been shown to be an effective starting point for anharmonic vibrational spectroscopy calculations. This general approach borrows techniques from localized-orbital machinery in electronic structure theory and generates a new set of spatially localized vibrational modes. These modes exhibit a well-behaved spatial decay of anharmonic mode couplings, which, in turn, allows for a systematic, a priori truncation of couplings and increased computational efficiency. Fully localized modes, however, have been found to lead to unintuitive mixtures of characteristic motions, such as stretches and bends, and accordingly large bilinear couplings. In this work, a very simple, tunable localization frequency window is introduced, in order to realize the transition from normal modes to fully localized modes. Partial localization can be achieved by localizing only pairs of modes within this traveling frequency window, which allows for intuitive interpretation of modes. The optimal window size is suggested to be a few hundreds of wave numbers, based on small- to medium-sized test systems, including water clusters and polypeptides. The new sets of partially localized coordinates retain their spatial coupling decay behavior while providing a reduced number of potential energy evaluations for convergence of anharmonic spectra.

Vibrational Signatures of Conformer-Specific Intramolecular Interactions in Protonated Tryptophan.

Because of both experimental and computational challenges, protonated tryptophan has remained the last aromatic amino acid for which the intrinsic structures of low-energy conformers have not been unambiguously solved. The IR-IR-UV hole-burning spectroscopy technique has been applied to overcome the limitations of the commonly used IR-UV double resonance technique and to measure conformer-specific vibrational spectra of TrpH(+), cooled to T = 10 K. Anharmonic ab initio vibrational spectroscopy simulations unambiguously assign the dominant conformers to the two lowest-energy geometries from benchmark coupled-cluster structure computations. The match between experimental and ab initio spectra provides an unbiased validation of the calculated structures of the two experimentally observed conformers of this benchmark ion. Furthermore, the vibrational spectra provide conformer-specific signatures of the stabilizing interactions, including hydrogen bonding and an intramolecular cation-π interaction.

Accelerating Ab Initio Path Integral Simulations via Imaginary Multiple-Timestepping.

This work investigates the use of multiple-timestep schemes in imaginary time for computationally efficient ab initio equilibrium path integral simulations of quantum molecular motion. In the simplest formulation, only every n(th) path integral replica is computed at the target level of electronic structure theory, whereas the remaining low-level replicas still account for nuclear motion quantum effects with a more computationally economical theory. Motivated by recent developments for multiple-timestep techniques in real-time classical molecular dynamics, both 1-electron (atomic-orbital basis set) and 2-electron (electron correlation) truncations are shown to be effective. Structural distributions and thermodynamic averages are tested for representative analytic potentials and ab initio molecular examples. Target quantum chemistry methods include density functional theory and second-order Møller-Plesset perturbation theory, although any level of theory is formally amenable to this framework. For a standard two-level splitting, computational speedups of 1.6-4.0x are observed when using a 4-fold reduction in time slices; an 8-fold reduction is feasible in some cases. Multitiered options further reduce computational requirements and suggest that quantum mechanical motion could potentially be obtained at a cost not significantly different from the cost of classical simulations.