Morphology and Anatomy of Foliar Nectaries and Associated Leaves in Mallotus (Euphorbiaceae)

The morphology and anatomy of the foliar nectaries and associated leaves offour species of Mallotus (Euphorbiaceae) were studied. Light microscopic observations of paraffin- and plastic-embedded specimens were complemented with scanning electron micrographs. Leaf anatomy of the four species is typical of large mesophytic plants. Aattened foliar nectaries are shown to be composed of specialized epidermal cells. The nonvascularized nectaries consist of narrow columnar cells each with a large nucleus, numerous vacuoles, and dense cytoplasm. Subglandular parenchyma cells have more pronounced nuclei, more vacuoles and denser cytoplasm than do typical laminar parenchyma. Structurally, these nectaries are similar to those found in other taxa of Euphorbiaceae and in other families of flowering plants. Brief field observations confirmed that ants are readily attracted to the nectar and probably function in a mutualistic relationship with the plants. The actual mechanism of nectar secretion was not studied

A Multiscale Data-Driven Stochastic Method for Elliptic PDEs with Random Coefficients

In this paper, we propose a multiscale data-driven stochastic method (MsDSM) to study stochastic partial differential equations (SPDEs) in the multiquery setting. This method combines the advantages of the recently developed multiscale model reduction method [M. L. Ci, T. Y. Hou, and Z. Shi, ESAIM Math. Model. Numer. Anal., 48 (2014), pp. 449--474] and the data-driven stochastic method (DSM) [M. L. Cheng et al., SIAM/ASA J. Uncertain. Quantif., 1 (2013), pp. 452--493]. Our method consists of offline and online stages. In the offline stage, we decompose the harmonic coordinate into a smooth part and a highly oscillatory part so that the smooth part is invertible and the highly oscillatory part is small. Based on the Karhunen--Loève (KL) expansion of the smooth parts and oscillatory parts of the harmonic coordinates, we can derive an effective stochastic equation that can be well-resolved on a coarse grid. We then apply the DSM to the effective stochastic equation to construct a data-driven stochastic basis under which the stochastic solutions enjoy a compact representation for a broad range of forcing functions. In the online stage, we expand the SPDE solution using the data-driven stochastic basis and solve a small number of coupled deterministic partial differential equations (PDEs) to obtain the expansion coefficients. The MsDSM reduces both the stochastic and the physical dimensions of the solution. We have performed complexity analysis which shows that the MsDSM offers considerable savings over not only traditional methods but also DSM in solving multiscale SPDEs. Numerical results are presented to demonstrate the accuracy and efficiency of the proposed method for several multiscale stochastic problems without scale separation

How Should Physicians in Low- and Middle-Income Countries Regard Electronic Nicotine Delivery Systems to Facilitate Smoking Cessation?

Electronic nicotine delivery systems (ENDS) have been widely referred to as "safer," "healthier," and more "effective" smoking cessation aids, but little evidence supports such claims. New concerns about pulmonary injuries associated with ENDS suggest reasons for concern about these products' health risks and potential for nicotine addiction. Nevertheless, multinational tobacco companies heavily market ENDS to retain customers with nicotine addiction, and global progress against tobacco use might slow as a result. The tobacco industry has managed to divide the tobacco control community by offering hope of harm reduction without actual evidence of ENDS' effectiveness or long-term safety. Low- and middle-income countries need this evidence to assess ENDS' value in mitigating tobacco use

A Multiscale Model Reduction Method for Partial Differential Equations

We propose a multiscale model reduction method for partial differential equations. The main purpose of this method is to derive an effective equation for multiscale problems without scale separation. An essential ingredient of our method is to decompose the harmonic coordinates into a smooth part and a highly oscillatory part so that the smooth part is invertible and the highly oscillatory part is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is in H^2, and can be approximated by a regular coarse mesh. When the multiscale problem has scale separation and a periodic structure, our method recovers the traditional homogenized equation. Furthermore, we provide error analysis for our method and show that the solution to the effective equation is close to the original multiscale solution in the H^1 norm. Numerical results are presented to demonstrate the accuracy and robustness of the proposed method for several multiscale problems without scale separation, including a problem with a high contrast coefficient

A two-stage mechanism of viral RNA compaction revealed by single molecule fluorescence

Long RNAs often exist as multiple conformers in equilibrium. For the genomes of single-stranded RNA viruses, one of these conformers must include a compacted state allowing the RNA to be confined within the virion. We have used single molecule fluorescence correlation spectroscopy to monitor the conformations of viral genomes and sub-fragments in the absence and presence of coat proteins. Cognate RNA-coat protein interactions in two model viruses cause a rapid collapse in the hydrodynamic radii of their respective RNAs. This is caused by protein binding at multiple sites on the RNA that facilitate additional protein-protein contacts. The collapsed species recruit further coat proteins to complete capsid assembly with great efficiency and fidelity. The specificity in RNA-coat protein interactions seen at single-molecule concentrations reflects the packaging selectivity seen for such viruses in vivo. This contrasts with many in vitro reassembly measurements performed at much higher concentrations. RNA compaction by coat protein or polycation binding are distinct processes, implying that defined RNA-coat protein contacts are required for assembly

Deletion of the GABAA α2-subunit does not alter self dministration of cocaine or reinstatement of cocaine seeking

Rationale GABAA receptors containing α2-subunits are highly represented in brain areas that are involved in motivation and reward, and have been associated with addiction to several drugs, including cocaine. We have shown previously that a deletion of the α2-subunit results in an absence of sensitisation to cocaine. Objective We investigated the reinforcing properties of cocaine in GABAA α2-subunit knockout (KO) mice using an intravenous self-administration procedure. Methods α2-subunit wildtype (WT), heterozygous (HT) and KO mice were trained to lever press for a 30 % condensed milk solution. After implantation with a jugular catheter, mice were trained to lever press for cocaine (0.5 mg/kg/infusion) during ten daily sessions. Responding was extinguished and the mice tested for cue- and cocaine-primed reinstatement. Separate groups of mice were trained to respond for decreasing doses of cocaine (0.25, 0.125, 0.06 and 0.03 mg/kg). Results No differences were found in acquisition of lever pressing for milk. All genotypes acquired self-administration of cocaine and did not differ in rates of self-administration, dose dependency or reinstatement. However, whilst WT and HT mice showed a dose-dependent increase in lever pressing during the cue presentation, KO mice did not. Conclusions Despite a reported absence of sensitisation, motivation to obtain cocaine remains unchanged in KO and HT mice. Reinstatement of cocaine seeking by cocaine and cocaine-paired cues is also unaffected. We postulate that whilst not directly involved in reward perception, the α2-subunit may be involved in modulating the “energising” aspect of cocaine’s effects on reward-seeking

Physical Activity and the Menstrual Cycle: A Mixed-Methods Study of Women’s Experiences

The menstrual cycle is an important biological process in women that is associated with a range of physical symptoms, which can shape how women think, feel, and participate in activities of daily life. This study employed a mixed-methods design to investigate adult women’s physical activity throughout the menstrual cycle. One hundred and twenty-eight participants completed an online questionnaire that explored events of the menstrual cycle (e.g., bleeding, pain, fatigue) and physical activity. Semistructured interviews with 21 questionnaire respondents unpacked individual experiences of physical activity throughout the menstrual cycle. From the questionnaire data, 44 participants were categorized as avoiders and 84 as nonavoiders of physical activity due to menstrual events. Avoiders of physical activity reported longer periods, heavier menstrual flow, and higher levels of fatigue and pain compared with nonavoiders. Interviews revealed that avoidance of physical activity ranged from complete avoidance to adaptation (e.g., types of exercise). Reasons for avoidance and adaptation of physical activity included menstrual symptoms, personal thoughts, and concerns about other people’s views of the period. The present study findings emphasize the importance of not only evaluating prevalent physical symptoms, but also unpacking women’s individual perspectives and established societal norms to better understand and normalize physical activity throughout the menstrual cycle

Reply to Comment on Maani Hessari, N.; van Schalkwyk, M.C.; Thomas, S.; Petticrew, M. Alcohol Industry CSR Organisations: What Can Their Twitter Activity Tell Us about Their Independence and Their Priorities? A Comparative Analysis. Int. J. Environ. Res. Public Health 2019, 16, 892.

We are grateful for the opportunity to respond to the letter from the DrinkAware medical advisory panel [...]

Alcohol Industry CSR Organisations: What Can Their Twitter Activity Tell Us about Their Independence and Their Priorities? A Comparative Analysis.

There are concerns about the accuracy of the health information provided by alcohol industry (AI)-funded organisations and about their independence. We conducted a content analysis of the health information disseminated by AI-funded organisations through Twitter, compared with non-AI-funded charities, to assess whether their messages align with industry and/or public health objectives. We compared all tweets from 2016 from Drinkaware (UK); Drinkaware.ie (Ireland); and DrinkWise (Australia), to non-AI-funded charities Alcohol Concern (UK), Alcohol Action Ireland, and FARE (Australia). Industry-funded bodies were significantly less likely to tweet about alcohol marketing, advertising and sponsorship; alcohol pricing; and physical health harms, including cancers, heart disease and pregnancy. They were significantly more likely to tweet about behavioural aspects of drinking and less likely to mention cancer risk; particularly breast cancer. These findings are consistent with previous evidence that the purpose of such bodies is the protection of the alcohol market, and of the alcohol industry's reputation. Their messaging strongly aligns with AI corporate social responsibility goals. The focus away from health harms, particularly cancer, is also consistent with previous evidence. The evidence does not support claims by these alcohol-industry-funded bodies about their independence from industry