Over the past decade, peptide drug discovery has experienced a revival of interest and scientific momentum, as the pharmaceutical industry has come to appreciate the role that peptide therapeutics ...can play in addressing unmet medical needs and how this class of compounds can be an excellent complement or even preferable alternative to small molecule and biological therapeutics. In this Perspective, we give a concise description of the recent progress in peptide drug discovery in a holistic manner, highlighting enabling technological advances affecting nearly every aspect of this field: from lead discovery, to synthesis and optimization, to peptide drug delivery. An emphasis is placed on describing research efforts to overcome the inherent weaknesses of peptide drugs, in particular their poor pharmacokinetic properties, and how these efforts have been critical to the discovery, design, and subsequent development of novel therapeutics.
This review investigated three research questions (i) What is the utility of social cognitive theory (SCT) to explain physical activity (PA)?; (ii) Is the effectiveness of SCT moderated by sample or ...methodological characteristics? and (iii) What is the frequency of significant associations between the core SCT constructs and PA? Ten electronic databases were searched with no date or sample restrictions. Forty‐four studies were retrieved containing 55 SCT models of PA. Methodological quality was assessed using a standardized tool. A random‐effects meta‐analysis revealed that SCT accounted for 31% of the variance in PA. However, methodological quality was mostly poor for these models. Methodological quality and sample age moderated the PA effect size, with increases in both associated with greater variance explained. Although self‐efficacy and goals were consistently associated with PA, outcome expectations and socio‐structural factors were not. This review determined that SCT is a useful framework to explain PA behaviour. Higher quality models explained more PA variance, but overall methodological quality was poor. As such, high‐quality studies examining the utility of SCT to explain PA are warranted.
To assess the potential benefit of digital health interventions (DHIs) on cardiovascular disease (CVD) outcomes (CVD events, all-cause mortality, hospitalizations) and risk factors compared with ...non-DHIs.
We conducted a systematic search of PubMed, MEDLINE, EMBASE, Web of Science, Ovid, CINHAL, ERIC, PsychINFO, Cochrane, and Cochrane Central Register of Controlled Trials for articles published from January 1, 1990, through January 21, 2014. Included studies examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and CVD outcomes or risk factors. Two reviewers independently evaluated study quality utilizing a modified version of the Cochrane Collaboration risk assessment tool. Authors extracted CVD outcomes and risk factors for CVD such as weight, body mass index, blood pressure, and lipid levels from 51 full-text articles that met validity and inclusion criteria.
Digital health interventions significantly reduced CVD outcomes (relative risk, 0.61; 95% CI, 0.46-0.80; P<.001; I(2)=22%). Concomitant reductions in weight (-2.77 lb 95% CI, -4.49 to -1.05 lb; P<.002; I(2)=97%) and body mass index (-0.17 kg/m(2) 95% CI, -0.32 kg/m(2) to -0.01 kg/m(2); P=.03; I(2)=97%) but not blood pressure (-1.18 mm Hg 95% CI, -2.93 mm Hg to 0.57 mm Hg; P=.19; I(2)=100%) were found in these DHI trials compared with usual care. In the 6 studies reporting Framingham risk score, 10-year risk percentages were also significantly improved (-1.24%; 95% CI, -1.73% to -0.76%; P<.001; I(2)=94%). Results were limited by heterogeneity not fully explained by study population (primary or secondary prevention) or DHI modality.
Overall, these aggregations of data provide evidence that DHIs can reduce CVD outcomes and have a positive impact on risk factors for CVD.
Three amigos: Direct oxidative amination of the C2‐position of azoles enables the synthesis of important classes of heterocycle in an efficient and atom‐economic manner (see scheme). Recent research ...has uncovered three distinct approaches to this transformation.
A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2–3day repeat frequency using passive microwave observations from the Soil ...Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037m3m−3, 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026m3m−3, 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.
•Development of SMAP neural network soil moisture retrieval product•Evaluating retrievals and model soil moisture versus core and sparse in situ sites•Comparable skill of SMAP neural network and official SMAP retrieval products•Comparison of global error patterns from triple collocation analysis
A systematic review of randomized controlled trials was conducted to evaluate the effectiveness of eHealth interventions for the prevention and treatment of overweight and obesity in adults. Eight ...databases were searched for studies published in English from 1995 to 17 September 2014. Eighty‐four studies were included, with 183 intervention arms, of which 76% (n = 139) included an eHealth component. Sixty‐one studies had the primary aim of weight loss, 10 weight loss maintenance, eight weight gain prevention, and five weight loss and maintenance. eHealth interventions were predominantly delivered using the Internet, but also email, text messages, monitoring devices, mobile applications, computer programs, podcasts and personal digital assistants. Forty percent (n = 55) of interventions used more than one type of technology, and 43.2% (n = 60) were delivered solely using eHealth technologies. Meta‐analyses demonstrated significantly greater weight loss (kg) in eHealth weight loss interventions compared with control (MD −2.70 −3.33,−2.08, P < 0.001) or minimal interventions (MD −1.40 −1.98,−0.82, P < 0.001), and in eHealth weight loss interventions with extra components or technologies (MD 1.46 0.80, 2.13, P < 0.001) compared with standard eHealth programmes. The findings support the use of eHealth interventions as a treatment option for obesity, but there is insufficient evidence for the effectiveness of eHealth interventions for weight loss maintenance or weight gain prevention.
Global urban planning has promoted green infrastructure (GI) such as street trees, shrubs or other greenspace in order to mitigate air pollution. Although considerable attention has been paid to ...understanding particulate matter (PM) deposition on GI, there has been little focus on identifying which leaf traits might maximise airborne PM removal. This paper examines existing literature to synthesize the state of knowledge on leaf traits most relevant to PM removal. We systematically reviewed measurement studies that evaluated particulate matter accumulated on leaves on street trees, shrubs green roofs, and green walls, for a variety of leaf traits. Our final selection included 62 papers, most from field studies and a handful from wind tunnel studies. The following were variously promoted as useful traits: coniferous needle leaves; small, rough and textured broadleaves; lanceolate and ovate shapes; waxy coatings, and high-density trichomes. Consideration of these leaf traits, many of which are also associated with drought tolerance, may help to maximise PM capture. Although effective leaf traits were identified, there is no strong or consistent evidence to identify which is the most influential leaf trait in capturing PM. The diversity in sampling methods, wide comparison groups and lack of background PM concentration measures in many studies limited our ability to synthesize results. We found that several ancillary factors contribute to variations in the accumulation of PM on leaves, thus cannot recommend that selection of urban planting species be based primarily on leaf traits. Further research into the vegetation structural features and standardization of the method to measure PM on leaves is needed.
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•Texture, wax or high-density trichomes are considered effective leaf traits for PM capture.•Comparative studies among plant species reveal substantial variation in PM capture.•The most efficient species for PM removal differs among research contexts.•Botanical features and local weather should be part of planning urban plantings.
There is some consensus that coniferous needle leaves; small, rough and textured broadleaves; extended oval shapes; waxy coatings and high-density trichomes are traits considered to be effective in retaining particulate matter.
Skeletal muscle weakness occurs with aging and in females this is compounded by the loss of estrogen with ovarian failure. Estrogen deficiency mediates decrements in muscle strength from both ...inadequate preservation of skeletal muscle mass and decrements in the quality of the remaining skeletal muscle. Processes and components of skeletal muscle that are affected by estrogens are beginning to be identified. This review focuses on mechanisms that contribute to the loss of muscle force generation when estrogen is low in females, and conversely the maintenance of strength by estrogen. Evidence is accumulating that estrogen deficiency induces apoptosis in skeletal muscle contributing to loss of mass and thus strength. Estrogen sensitive processes that affect quality, i.e., force generating capacity of muscle, include myosin phosphorylation and satellite cell function. Further detailing these mechanisms and identifying additional mechanisms that underlie estrogenic effects on skeletal muscle is important foundation for the design of therapeutic strategies to minimize skeletal muscle pathologies, such as sarcopenia and dynapenia.
•Estrogen deficiency results in loss of muscle mass through apoptotic mechanisms.•Inconclusive evidence that loss of estrogen affects muscle protein turnover.•Dynapenia due to estrogen deficiency in females is related to myosin dysfunction.•Lack of estrogen impairs muscle regeneration ultimately impacting force generation.
The field of quantum computing has grown from concept to demonstration devices over the past 20 years. Universal quantum computing offers efficiency in approaching problems of scientific and ...commercial interest, such as factoring large numbers, searching databases, simulating intractable models from quantum physics, and optimizing complex cost functions. Here, we present an 11-qubit fully-connected, programmable quantum computer in a trapped ion system composed of 13
Yb
ions. We demonstrate average single-qubit gate fidelities of 99.5Formula: see text, average two-qubit-gate fidelities of 97.5Formula: see text, and SPAM errors of 0.7Formula: see text. To illustrate the capabilities of this universal platform and provide a basis for comparison with similarly-sized devices, we compile the Bernstein-Vazirani and Hidden Shift algorithms into our native gates and execute them on the hardware with average success rates of 78Formula: see text and 35Formula: see text, respectively. These algorithms serve as excellent benchmarks for any type of quantum hardware, and show that our system outperforms all other currently available hardware.
Circadian rhythms play a critical role in the physiological processes involved in energy metabolism and energy balance (EB). A large array of metabolic processes, including the expression of many ...energy‐regulating endocrine hormones, display temporal rhythms that are driven by both the circadian clock and food intake. Mealtime has been shown to be a compelling zeitgeber in peripheral tissue rhythms. Inconsistent signalling to the periphery, because of mismatched input from the central clock vs time of eating, results in circadian disruption in which central and/or peripheral rhythms are asynchronously time shifted or their amplitudes reduced. A growing body of evidence supports the negative health effects of circadian disruption, with strong evidence in murine models that mealtime‐induced circadian disruption results in various metabolic consequences, including energy imbalance and weight gain. Increased weight gain has been reported to occur even without differences in energy intake, indicating an effect of circadian disruption on energy expenditure. However, the translation of these findings to humans is not well established because the ability to undertake rigorously controlled dietary studies that explore the chronic effects on energy regulation is challenging. Establishing the neuroendocrine changes in response to both acute and chronic variations in mealtime, along with observations in populations with routinely abnormal mealtimes, may provide greater insight into underlying mechanisms that influence long‐term weight management under different meal patterns. Human studies should explore mechanisms through relevant biomarkers; for example, cortisol, leptin, ghrelin and other energy‐regulating neuroendocrine factors. Mistiming between aggregate hormonal signals, or between hormones with their receptors, may cause reduced signalling intensity and hormonal resistance. Understanding how mealtimes may impact on the coordination of endocrine factors is essential for untangling the complex regulation of EB. Here a review is provided on current evidence of the impacts of mealtime on energy metabolism and the underlying neuroendocrine mechanisms, with a specific focus on human research.
Circadian disruption from altered meal timing may contribute to energy imbalance through modifying neuroendocrine pathways involved in the regulation of energy intake and energy metabolism. Here, we review current evidence regarding the impact of circadian disruption on energy balance, focusing specifically on mealtime and its effects on energy expenditure in human studies. We discuss changes in neuroendocrine signals and their rhythms in response to circadian disruption, aiming to understand how diverse meal patterns may differentially influence energy balance.
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