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Chitosan is a cationic polysaccharide that is usually obtained by alkaline deacetylation of chitin poly(N-acetylglucosamine). It is biocompatible, biodegradable, mucoadhesive, and non-toxic. These excellent biological properties make chitosan a good candidate for a platform in developing drug delivery systems having improved biodistribution, increased specificity and sensitivity, and reduced pharmacological toxicity. In particular, chitosan nanoparticles are found to be appropriate for non-invasive routes of drug administration: oral, nasal, pulmonary and ocular routes. These applications are facilitated by the absorption-enhancing effect of chitosan. Many procedures for obtaining chitosan nanoparticles have been proposed. Particularly, the introduction of hydrophobic moieties into chitosan molecules by grafting to generate a hydrophobic-hydrophilic balance promoting self-assembly is a current and appealing approach. The grafting agent can be a hydrophobic moiety forming micelles that can entrap lipophilic drugs or it can be the drug itself. Another suitable way to generate self-assembled chitosan nanoparticles is through the formation of polyelectrolyte complexes with polyanions. This paper reviews the main approaches for preparing chitosan nanoparticles by self-assembly through both procedures, and illustrates the state of the art of their application in drug delivery.

In 2008 a deep economic crisis started in the US and rapidly spread around the world. The crisis severely affected the labor market and employees' well-being. Hence, the aim of this work is to implement a systematic review of the principal studies that analyze the impact of the economic crisis on the health of workers. We conducted our search on the PubMed database, and a total of 19 articles were selected for review. All studies showed that the economic crisis was an important stressor that had a negative impact on workers' mental health. Most of the studies documented that a rise in unemployment, increased workload, staff reduction, and wages reduction were linked to an increased rate of mood disorders, anxiety, depression, dysthymia, and suicide. Some studies showed that problems related to the crisis may have also affected the general health of workers by increasing the risk of such health problems as cardiovascular and respiratory diseases. Finally, some studies looked at the impact of the crisis on health care services. These studies demonstrated that the reduction in public expenditure on health care services, and the reduction of public hospital budgets due to the recession, led to organizational problems (eg, medical supply shortages).

Controlling the hybridization of single atoms in suitable host materials opens unique opportunities for catalyst design, but equally faces many challenges. Here, we highlight emerging directions from the last, highly productive, decade in single-atom catalysis and identify frontiers for future research.

We provide additional evidence on the relationship between uncertainty and economic activity. For this purpose, we gather and construct a wide range of proxy indicators of economic and economic policy uncertainty from Spain. We distinguish between the relative merits of different types of measures based on (i) the volatility of financial markets; (ii) economic analysts’ disagreement; and (iii) economic policy uncertainty. We show that the first and the third block of measures are the most relevant to grasp the negative effects of unexpected changes in uncertainty on aggregate economic developments, as measured by real GDP. In addition, we find that economic policy uncertainty and financial uncertainty shocks produce visible negative effects on private consumption. The negative responses on capital goods investments are initially bigger in magnitude but vanish more quickly.

Nanostructured materials of diverse architecture are ubiquitous in industrial catalysis. They offer exciting prospects to tackle various sustainability challenges faced by society. Since the introduction of the concept a century ago, researchers aspire to control the chemical identity, local environment and electronic properties of active sites on catalytic surfaces to optimize their reactivity in given applications. Nowadays, numerous strategies exist to tailor these characteristics with varying levels of atomic precision. Making headway relies upon the existence of analytical approaches able to resolve relevant structural features and remains challenging due to the inherent complexity even of the simplest heterogeneous catalysts, and to dynamic effects often occurring under reaction conditions. Computational methods play a complementary and ever-increasing role in pushing forward the design. Here, we examine how nanoscale engineering can enhance the selectivity and stability of catalysts. We highlight breakthroughs towards their commercialization and identify directions to guide future research and innovation. This Review summarizes how distinct approaches to nanostructural engineering enhance features that determine the selectivity and stability of catalysts.

Night shift work, exposure to light at night (ALAN) and circadian disruption may increase the risk of hormone-dependent cancers. We evaluated the association of exposure to ALAN during sleeping time with breast and prostate cancer in a population based multicase-control study (MCC-Spain), among subjects who had never worked at night. We evaluated chronotype, a characteristic that may relate to adaptation to light at night. We enrolled 1,219 breast cancer cases, 1,385 female controls, 623 prostate cancer cases, and 879 male controls from 11 Spanish regions in 2008-2013. Indoor ALAN information was obtained through questionnaires. Outdoor ALAN was analyzed using images from the International Space Station (ISS) available for Barcelona and Madrid for 2012-2013, including data of remotely sensed upward light intensity and blue light spectrum information for each geocoded longest residence of each MCC-Spain subject. Among Barcelona and Madrid participants with information on both indoor and outdoor ALAN, exposure to outdoor ALAN in the blue light spectrum was associated with breast cancer [adjusted odds ratio (OR) for highest vs. lowest tertile, OR=1.47; 95% CI: 1.00, 2.17] and prostate cancer (OR=2.05; 95% CI: 1.38, 3.03). In contrast, those exposed to the highest versus lowest intensity of outdoor ALAN were more likely to be controls than cases, particularly for prostate cancer. Compared with those who reported sleeping in total darkness, men who slept in \"quite illuminated\" bedrooms had a higher risk of prostate cancer (OR=2.79; 95% CI: 1.55, 5.04), whereas women had a slightly lower risk of breast cancer (OR=0.77; 95% CI: 0.39, 1.51). Both prostate and breast cancer were associated with high estimated exposure to outdoor ALAN in the blue-enriched light spectrum. https://doi.org/10.1289/EHP1837.

Since the inception of the current pandemic, COVID-19 related misinformation has played a role in defaulting control of the situation. It has become evident that the internet, social media, and other communication outlets with readily available data have contributed to the dissemination and availability of misleading information. It has perpetuated beliefs that led to vaccine avoidance, mask refusal, and utilization of medications with insignificant scientific data, ultimately contributing to increased morbidity. Undoubtedly, misinformation has become a challenge and a burden to individual health, public health, and governments globally. Our review article aims at providing an overview and summary regarding the role of media, other information outlets, and their impact on the pandemic. The goal of this article is to increase awareness of the negative impact of misinformation on the pandemic. In addition, we discuss a few recommendations that could aid in decreasing this burden, as preventing the conception and dissemination of misinformation is essential.

Smart grids are able to forecast customers’ consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand. To face today’s demand forecasting challenges, where the data generated by smart grids is huge, modern data-driven techniques need to be used. In this scenario, Deep Learning models are a good alternative to learn patterns from customer data and then forecast demand for different forecasting horizons. Among the commonly used Artificial Neural Networks, Long Short-Term Memory networks—based on Recurrent Neural Networks—are playing a prominent role. This paper provides an insight into the importance of the demand forecasting issue, and other related factors, in the context of smart grids, and collects some experiences of the use of Deep Learning techniques, for demand forecasting purposes. To have an efficient power system, a balance between supply and demand is necessary. Therefore, industry stakeholders and researchers should make a special effort in load forecasting, especially in the short term, which is critical for demand response.

Rice (Oryza sativa) stands among the world's most important crop species. Rice is salt sensitive, and the undue accumulation of sodium ions (Na⁺) in shoots has the strongest negative correlation with rice productivity under long-term salinity. The plasma membrane Na⁺/H⁺ exchanger protein Salt Overly Sensitive 1 (SOS1) is the sole Na⁺ efflux transporter that has been genetically characterized to date. Here, the importance of SOS1-facilitated Na⁺ flux in the salt tolerance of rice was analyzed in a reverse-genetics approach. A sos1 loss-of-function mutant displayed exceptional salt sensitivity that was correlated with excessive Na⁺ intake and impaired Na⁺ loading into the xylem, thus indicating that SOS1 controls net root Na⁺ uptake and long-distance Na⁺ transport to shoots. The acute Na⁺ sensitivity of sos1 plants at low NaCl concentrations allowed analysis of the transcriptional response to sodicity stress without effects of the osmotic stress intrinsic to high-salinity treatments. In contrast with that in the wild type, sos1 mutant roots displayed preferential down-regulation of stress-related genes in response to salt treatment, despite the greater intensity of stress experienced by the mutant. These results suggest there is impaired stress detection or an inability to mount a comprehensive response to salinity in sos1. In summary, the plasma membrane Na⁺/H⁺ exchanger SOS1 plays a major role in the salt tolerance of rice by controlling Na⁺ homeostasis and possibly contributing to the sensing of sodicity stress.

Regimes do not change consistently across territorial levels. There has been progress in understanding national democratic erosions and subnational regimes, but barring a few exceptions, these research strands have not engaged in a thorough dialogue. To bridge this gap, I contend that when democracy advances in one territorial level, but erodes in another, we observe multilevel regime decoupling (MRD). Using global data from the Varieties of Democracy project, I examine the 1990–2022 period, showing that the proportion of decoupled cases increased from 20% in the 1990s, to 43% in the first decade of the twenty-first century. Preliminary regression analyses and a descriptive exploration of Italy, South Africa, India, and the United States indicate the non-deterministic influence of structural factors and the potentially pivotal role of courts in facilitating decoupled change. Considering these findings, renewed data collection efforts and an actor-centred approach are needed to strengthen our understanding of the varieties of (de)coupled regime change that have become common over the last decade. Given that regimes across territorial levels increasingly move in separate directions, future assessments of autocratization and democratic change need to embed territorial considerations in their analysis to remain informative about citizens’ real-world experiences on the ground.