Abstract The endocannabinoid system (ECS) is a widespread neuromodulatory system that plays important roles in central nervous system development, synaptic plasticity, and the response to endogenous ...and environmental insults. The ECS comprises cannabinoid receptors, endogenous cannabinoids (endocannabinoids), and the enzymes responsible for the synthesis and degradation of the endocannabinoids. The most abundant cannabinoid receptors are the CB1 cannabinoid receptors; however, CB2 cannabinoid receptors, transient receptor potential channels, and peroxisome proliferator activated receptors are also engaged by some cannabinoids. Exogenous cannabinoids, such as tetrahydrocannabinol, produce their biological effects through their interactions with cannabinoid receptors. The best-studied endogenous cannabinoids are 2-arachidonoyl glycerol and arachidonoyl ethanolamide (anandamide). Despite similarities in chemical structure, 2-arachidonoyl glycerol and anandamide are synthesized and degraded by distinct enzymatic pathways, which impart fundamentally different physiologic and pathophysiologic roles to these two endocannabinoids. As a result of the pervasive social use of cannabis and the involvement of endocannabinoids in a multitude of biological processes, much has been learned about the physiologic and pathophysiologic roles of the ECS. This review provides an introduction to the ECS with an emphasis on its role in synaptic plasticity and how the ECS is perturbed in schizophrenia.
In vivo fluorescence imaging can perform real‐time, noninvasive, and high spatiotemporal resolution imaging to accurately obtain the dynamic biological information in vivo, which plays significant ...roles in the early diagnosis and treatment of cancer. However, traditional in vivo fluorescence imaging usually operates in the visible and near‐infrared (NIR)‐I windows, which are severely interfered by the strong tissue absorption, tissue scattering, and autofluorescence. The emergence of NIR‐II imaging at 1000–1700 nm significantly breaks through the imaging limitations in deep tissues, due to less tissue scattering and absorption. Benefiting from the outstanding optical properties of NIR‐II quantum dots (QDs), such as high brightness and good photostability, in vivo fluorescence imaging exhibits excellent temporal‐spatial resolution and large penetration depth, and QDs have become a kind of promising fluorescent biomarkers in the field of in vivo fluorescence imaging. Herein, the authors review NIR‐II QDs from preparation to modification, and summarize recent applications of NIR‐II QDs, including in vivo imaging and imaging‐guided therapies. Finally, they discuss the special concerns when NIR‐II QDs are shifted from in vivo imaging applications to further in‐depth applications.
Near‐infrared‐II quantum dots exhibit outstanding optical properties including tunable emission, excellent fluorescence stability, large Stokes shift, high temporal‐spatial resolution imaging, and large penetration depth, making them overcome the autofluorescence and scattering problems in deep tissue imaging and become promising candidates in the field of fluorescence imaging and therapy in vivo.
Incidence of hepatocellular carcinoma (HCC) is on the rise due to the prevalence of chronic hepatitis and cirrhosis. Although there are surgical and chemotherapy treatment avenues the mortality rate ...of HCC remains high. Immunotherapy is currently the new frontier of cancer treatment and the immunobiology of HCC is emerging as an area for further exploration. The tumor microenvironment coexists and interacts with various immune cells to sustain the growth of HCC. Thus, immunosuppressive cells play an important role in the anti-tumor immune response. This review will discuss the current concepts of immunosuppressive cells, including tumor-associated macrophages, marrow-derived suppressor cells, tumor-associated neutrophils, cancer-associated fibroblasts, and regulatory T cell interactions to actively promote tumorigenesis. It further elaborates on current treatment modalities and future areas of exploration.
Certification is an essential stage in disease eradication efforts, encompassing epidemiological, managerial, and political complexities. The certification of smallpox eradication in the People's ...Republic of China (PRC, or China) exemplifies the multifaceted nature of the certification. Despite eradicating smallpox in the early 1960s, before the Global Smallpox Eradication Programme (SEP) intensified in 1967, China was one of the last countries certified as smallpox-free by the World Health Organization (WHO) in 1979. The WHO encountered notable resistance during the certification of smallpox eradication in China. This article examines the underlying motivations propelling China's resistance, the factors that contributed to the shifts in its stance, the challenges navigated by the WHO, and the ultimate achievement of certification despite controversies surrounding its transparency and credibility. Through the case of the certification of smallpox eradication, the article provides a historical context of China's selective engagement in global health governance, emphasising the critical importance of building a trusting relationship between the WHO and its member states. It offers insights for fostering effective collaboration among diverse stakeholders driven by varied political agendas in addressing shared global health challenges such as the coronavirus disease (COVID-19) pandemic.
Cloud and cloud shadow segmentation is one of the most important issues in remote sensing image processing. Most of the remote sensing images are very complicated. In this work, a dual-branch model ...composed of transformer and convolution network is proposed to extract semantic and spatial detail information of the image, respectively, to solve the problems of false detection and missed detection. To improve the model's feature extraction, a mutual guidance module (MGM) is introduced, so that the transformer branch and the convolution branch can guide each other for feature mining. Finally, in view of the problem of rough segmentation boundary, this work uses different features extracted by the transformer branch and the convolution branch for decoding and repairs the rough segmentation boundary in the decoding part to make the segmentation boundary clearer. Experimental results on the Landsat-8, Sentinel-2 data, the public dataset high-resolution cloud cover validation dataset created by researchers at Wuhan University (HRC_WHU), and the public dataset Spatial Procedures for Automated Removal of Cloud and Shadow (SPARCS) demonstrate the effectiveness of our method and its superiority to the existing state-of-the-art cloud and cloud shadow segmentation approaches.
•GB reduced the CI symptoms of banana fruit.•GB enhanced the contents of antioxidant substances.•GB elevated enzyme activities and gene expression of antioxidant enzymes.•GB increased total ...antioxidant capacity.
Chilling injury (CI) represents a physiological disorder caused by improper low temperature management, which affects the postharvest quality and marketing potential of banana fruit. In this study, postharvest application of glycine betaine (GB) can significantly reduce the CI incidence of banana fruit during cold storage, as observed by lower CI index, electrolyte leakage, malondialdehyde (MDA) contents, and higher values of lightness, chlorophyll, soluble sugar contents. Moreover, GB not only increased the antioxidant substances such as total phenolics, glutathione and ascorbic acids (AsA), but also elevated the enzyme activities and gene expression of the antioxidant enzymes including ascorbate peroxidase (APX), catalase (CAT), superoxide dismutase (SOD) and peroxidase (POD). In addition, GB could obviously enhance the total antioxidant capacity of banana fruit under refrigerated storage. Collectively, these findings suggest that GB-attenuated CI incidence in banana fruit during cold storage might be, at least partially, ascribed to the enhancement of antioxidant system involving antioxidant substances, as well as enzyme activities and gene expression of antioxidant enzymes.
The Keap1–Nrf2–ARE ((Kelch‐like ECH‐Associating protein 1) nuclear factor erythroid 2 related factor 2‐antioxidant response element) pathway is one of the most important defense mechanisms against ...oxidative and/or electrophilic stresses, and it is closely associated with inflammatory diseases, including cancer, neurodegenerative diseases, cardiovascular diseases, and aging. In recent years, progress has been made in strategies aimed at modulating the Keap1–Nrf2–ARE pathway. The Nrf2 activator DMF (Dimethylfumarates) has been approved by the FDA as a new first‐line oral drug to treat patients with relapsing forms of multiple sclerosis, while a phase 3 study of another promising candidate, CDDO‐Me, was terminated for safety reasons. Directly inhibiting Keap1–Nrf2 protein–protein interactions as a novel Nrf2‐modulating strategy has many advantages over using electrophilic Nrf2 activators. The development of Keap1–Nrf2 protein–protein interaction inhibitors has become a topic of intense research, and potent inhibitors of this target have been identified. In addition, inhibiting Nrf2 activity has attracted an increasing amount of attention because it may provide an alternative cancer therapy. This review summarizes the molecular mechanisms and biological functions of the Keap1–Nrf2–ARE system. The main focus of this review is on recent progress in studies of agents that target the Keap1–Nrf2–ARE pathway and the therapeutic applications of such agents.
•This study five generalized distributions were used for hydrometeorological frequency analysis.•The entropy theory were proposed to estimate parameters of those distributions.•The five generalized ...distributions generally fitted the extreme rainfall data well.•The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.
Frequency analysis of hydrometeorological and hydrological extremes is needed for the design of hydraulic and civil infrastructure facilities as well as water resources management. A multitude of distributions have been employed for frequency analysis of these extremes. However, no single distribution has been accepted as a global standard. Employing the entropy theory, this study derived five generalized distributions for frequency analysis that used different kinds of information encoded as constraints. These distributions were the generalized gamma (GG), the generalized beta distribution of the second kind (GB2), and the Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B) and Halphen type inverse B distribution (Hal-IB), among which the GG and GB2 distribution were previously derived by Papalexiou and Koutsoyiannis (2012) and the Halphen family was first derived using entropy theory in this paper. The entropy theory allowed to estimate parameters of the distributions in terms of the constraints used for their derivation. The distributions were tested using extreme daily and hourly rainfall data. Results show that the root mean square error (RMSE) values were very small, which indicated that the five generalized distributions fitted the extreme rainfall data well. Among them, according to the Akaike information criterion (AIC) values, generally the GB2 and Halphen family gave a better fit. Therefore, those general distributions are one of the best choices for frequency analysis. The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.
As an effective tool to show the fuzziness of qualitative information, the interval-valued T-spherical fuzzy set can utilize three kinds of information, namely, membership, abstinence, and ...non-membership, to show the opinions of decision-maker. Given this advantage, many interval-valued T-spherical fuzzy multi-criteria decision-making (IVTSF-MCDM) methods have been designed. However, most of the existing IVTSF-MCDM methods have a common limitation that the inability to effectively show the impacts of extreme data. To address this limitation, this study develops a novel MCDM method based on interval-valued T-spherical fuzzy extended power aggregation operator. First, interval-valued T-spherical fuzzy cross-entropy (CE) and interval-valued T-spherical fuzzy symmetrical CE are defined to measure the difference between two interval-valued T-spherical fuzzy numbers, which are used to determine criteria weights in MCDM. Second, interval-valued T-spherical fuzzy extended power average operator and interval-valued T-spherical fuzzy extended power geometric operator are proposed, and their properties are investigated. Moreover, in view of that criteria may be assigned to different weights, this study defines interval-valued T-spherical fuzzy extended power weighted average operator and interval-valued T-spherical fuzzy extended power weighted geometric operator to derive the order of alternatives. Finally, the applicability of the proposed method is validated by the case about investment country selection, while the sensitivity and comparison analyses are also conducted to further prove its advantages and effectiveness.
Potassium‐ion hybrid capacitors (KICs) reconciling the advantages of batteries and supercapacitors have stimulated growing attention for practical energy storage because of the high abundance and low ...cost of potassium sources. Nevertheless, daunting challenge remains for developing high‐performance potassium accommodation materials due to the large radius of potassium ions. Molybdenum diselenide (MoSe2) has recently been recognized as a promising anode material for potassium‐ion batteries, achieving high capacity and favorable cycling stability. However, KICs based on MoSe2 are scarcely demonstrated by far. Herein, a diatomite‐templated synthetic strategy is devised to fabricate nitrogen‐doped MoSe2/graphene (N‐MoSe2/G) composites with favorable pseudocapacitive potassium storage targeting a superior anode material for KICs. Benefiting from the unique biomorphic structure, high electron/K‐ion conductivity, enriched active sites, and the conspicuous pseudocapacitive effect of N‐MoSe2/G, thus‐derived KIC full‐cell manifests high energy/power densities (maximum 119 Wh kg−1/7212 W kg−1), outperforming those of recently reported KIC counterparts. Furthermore, the potassium storage mechanism of N‐MoSe2/G composite is systematically explored with the aid of first‐principles calculations in combination of in situ X‐ray diffraction and ex situ Raman spectroscopy/transmission electron microscopy/X‐ray photoelectron spectroscopy.
Nitrogen‐doped MoSe2/graphene composites prepared via a biotemplated strategy are employed as highly effective anodes for potassium‐ion hybrid capacitors, manifesting high energy/power density (119 Wh kg−1/7212 W kg−1) and long lifespan.
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