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This book figures out that network security and informatization have entered a development stage of greater permeation and deeper integration into all aspects of the economy and society. In particular since the 2008 financial crisis, the world's major economies have placed a strategic focus on network security and informatization in order to seek out new growth points, alleviate energy and ecological pressures, improve living standards, and improve social governance through new technological transformations in fields such as cloud computing, the Internet of Things, mobile internet, big data, smart cities, and a wave of applications. The effects on the economy and society have emerged and will continue to make significant progress. Based on China's stage of new urbanization, industrialization, informatization, and agricultural modernization and major characteristics, as well as the intrinsic need for synchronized development, this book encourages society to accelerate the pace of development, expand the scope of work and promote informatization and the comprehensive, coordinated, effective linking and deep integration of informatization with all areas of the economy and society.-- Provided by publisher.

Taxol®, an antitumor drug with significant activity, is the first microtubule stabilizing agent described in the literature. This short review of the mechanism of action of Taxol® emphasizes the research done in the Horwitz’ laboratory. It discusses the contribution of photoaffinity labeled analogues of Taxol® toward our understanding of the binding site of the drug on the microtubule. The importance of hydrogen/deuterium exchange experiments to further our insights into the stabilization of microtubules by Taxol® is addressed. The development of drug resistance, a major problem that arises in the clinic, is discussed. Studies describing differential drug binding to distinct β-tubulin isotypes are presented. Looking forward, it is suggested that the β-tubulin isotype content of a tumor may influence its responses to Taxol®.

Climate change has the potential to change the distribution of pests globally and their resistance to pesticides, thereby threatening global food security in the 21st century. However, predicting where these changes occur and how they will influence current pest control efforts is a challenge. Using experimentally parameterised and field-tested models, we show that climate change over the past 50 years increased the overwintering range of a global agricultural insect pest, the diamondback moth ( Plutella xylostella ), by ~2.4 million km 2 worldwide. Our analysis of global data sets revealed that pesticide resistance levels are linked to the species’ overwintering range: mean pesticide resistance was 158 times higher in overwintering sites compared to sites with only seasonal occurrence. By facilitating local persistence all year round, climate change can promote and expand pesticide resistance of this destructive species globally. These ecological and evolutionary changes would severely impede effectiveness of current pest control efforts and potentially cause large economic losses. Climate-driven range shifts may affect pesticide resistance. Here, the authors analyse experimentally parameterised and field-tested models to show that a cosmopolitan insect pest, the diamondback moth, is acquiring resistance against local pesticides through expanding overwintering range.

Interleukin-7 (IL-7), a molecule known for its growth-promoting effects on progenitors of B cells, remains one of the most extensively studied cytokines. It plays a vital role in health maintenance and disease prevention, and the congenital deficiency of IL-7 signaling leads to profound immunodeficiency. IL-7 contributes to host defense by regulating the development and homeostasis of immune cells, including T lymphocytes, B lymphocytes, and natural killer (NK) cells. Clinical trials of recombinant IL-7 have demonstrated safety and potent immune reconstitution effects. In this article, we discuss IL-7 and its functions in immune cell development, drawing on a substantial body of knowledge regarding the biology of IL-7. We aim to answer some remaining questions about IL-7, providing insights essential for designing new strategies of immune intervention.

COVID-19 has spread globally. Epidemiological susceptibility to COVID-19 has been reported in patients with cancer. We aimed to systematically characterise clinical features and determine risk factors of COVID-19 disease severity for patients with cancer and COVID-19. In this multicentre, retrospective, cohort study, we included all adult patients (aged ≥18 years) with any type of malignant solid tumours and haematological malignancy who were admitted to nine hospitals in Wuhan, China, with laboratory-confirmed COVID-19 between Jan 13 and March 18, 2020. Enrolled patients were statistically matched (2:1) with patients admitted with COVID-19 who did not have cancer with propensity score on the basis of age, sex, and comorbidities. Demographic characteristics, laboratory examinations, illness severity, and clinical interventions were compared between patients with COVID-19 with or without cancer as well as between patients with cancer with non-severe or severe COVID-19. COVID-19 disease severity was defined on admission on the basis of the WHO guidelines. Univariable and multivariable logistic regression, adjusted for age, sex, comorbidities, cancer type, tumour stage, and antitumour treatments, were used to explore risk factors associated with COVID-19 disease severity. This study was registered in the Chinese Clinical Trial Register, ChiCTR2000030807. Between Jan 13 and March 18, 2020, 13 077 patients with COVID-19 were admitted to the nine hospitals in Wuhan and 232 patients with cancer and 519 statistically matched patients without cancer were enrolled. Median follow-up was 29 days (IQR 22–38) in patients with cancer and 27 days (20–35) in patients without cancer. Patients with cancer were more likely to have severe COVID-19 than patients without cancer (148 [64%] of 232 vs 166 [32%] of 519; odds ratio [OR] 3·61 [95% CI 2·59–5·04]; p<0·0001). Risk factors previously reported in patients without cancer, such as older age; elevated interleukin 6, procalcitonin, and D-dimer; and reduced lymphocytes were validated in patients with cancer. We also identified advanced tumour stage (OR 2·60, 95% CI 1·05–6·43; p=0·039), elevated tumour necrosis factor α (1·22, 1·01–1·47; p=0·037), elevated N-terminal pro-B-type natriuretic peptide (1·65, 1·03–2·78; p=0·032), reduced CD4+ T cells (0·84, 0·71–0·98; p=0·031), and reduced albumin–globulin ratio (0·12, 0·02–0·77; p=0·024) as risk factors of COVID-19 severity in patients with cancer. Patients with cancer and COVID-19 were more likely to deteriorate into severe illness than those without cancer. The risk factors identified here could be helpful for early clinical surveillance of disease progression in patients with cancer who present with COVID-19. China National Natural Science Foundation.

The photocatalytic activity of catalysts depends on the energy-harvesting ability and the separation or transport of photogenerated carriers. The light absorption capacity of graphitic carbon nitride (g-C 3 N 4 )-based composites can be enhanced by adjusting the surface plasmon resonance (SPR) of noble metal nanoparticles (e.g., Cu, Au, and Pd) in the entire visible region. Adjustments can be carried out by varying the nanocomponents of the materials. The SPR of noble metals can enhance the local electromagnetic field and improve interband transition, and resonant energy transfer occurs from plasmonic dipoles to electron–hole pairs via near-field electromagnetic interactions. Thus, noble metals have emerged as relevant nanocomponents for g-C 3 N 4 used in CO 2 photoreduction and water splitting. Herein, recent key advances in noble metals (either in single atom, cluster, or nanoparticle forms) and composite photocatalysts based on inorganic or organic nanocomponent-incorporated g-C 3 N 4 nanosheets are systematically discussed, including the applications of these photocatalysts, which exhibit improved photoinduced charge mobility in CO 2 photoconversion and H 2 production. Issues related to the different types of multi-nanocomponent heterostructures (involving Schottky junctions, Z-/S-scheme heterostructures, noble metals, and additional semiconductor nanocomponents) and the adjustment of dimensionality of heterostructures (by incorporating noble metal nanoplates on g-C 3 N 4 forming 2D/2D heterostructures) are explored. The current prospects and possible challenges of g-C 3 N 4 composite photocatalysts incorporated with noble metals (e.g., Au, Pt, Pd, and Cu), particularly in water splitting, CO 2 reduction, pollution degradation, and chemical conversion applications, are summarized.

In humans, risk attitude is highly context-dependent, varying with wealth levels or for different potential outcomes, such as gains or losses. These behavioral effects have been modelled using prospect theory, with the key assumption that humans represent the value of each available option asymmetrically as a gain or loss relative to a reference point. It remains unknown how these computations are implemented at the neuronal level. Here we show that macaques, like humans, change their risk attitude across wealth levels and gain/loss contexts using a token gambling task. Neurons in the anterior insular cortex (AIC) encode the ‘reference point’ (i.e., the current wealth level of the monkey) and reflect ‘loss aversion’ (i.e., option value signals are more sensitive to change in the loss than in the gain context) as postulated by prospect theory. In addition, changes in the activity of a subgroup of AIC neurons correlate with the inter-trial fluctuations in choice and risk attitude. Taken together, we show that the primate AIC in risky decision-making may be involved in monitoring contextual information used to guide the animal’s willingness to accept risk. Prospect theory predicts irrational effects in human decision-making, but relies on ad-hoc assumptions. Here, authors provide a neural basis for this by showing that anterior insular cortex encodes key economic variables proposed by prospect theory.

This review explores the diverse applications of gold nanoparticles (AuNPs) in neurological diseases, with a specific focus on Alzheimer’s disease (AD), Parkinson’s disease (PD), and stroke. The introduction highlights the pivotal role of neuroinflammation in these disorders and introduces the unique properties of AuNPs. The review’s core examines the mechanisms by which AuNPs exert neuroprotection and anti-neuro-inflammatory effects, elucidating various pathways through which they manifest these properties. The potential therapeutic applications of AuNPs in AD are discussed, shedding light on promising avenues for therapy. This review also explores the prospects of utilizing AuNPs in PD interventions, presenting a hopeful outlook for future treatments. Additionally, the review delves into the potential of AuNPs in providing neuroprotection after strokes, emphasizing their significance in mitigating cerebrovascular accidents’ aftermath. Experimental findings from cellular and animal models are consolidated to provide a comprehensive overview of AuNPs’ effectiveness, offering insights into their impact at both the cellular and in vivo levels. This review enhances our understanding of AuNPs’ applications in neurological diseases and lays the groundwork for innovative therapeutic strategies in neurology.

Impacts of small‐scale surface irregularities, or surface roughness, of atmospheric ice crystals on lidar backscattering properties are quantified. Geometric ice crystal models with various degrees of surface roughness and state‐of‐the‐science light‐scattering computational capabilities are utilized to simulate the single‐scattering properties across the entire practical size parameter range. The simulated bulk lidar and depolarization ratios of polydisperse ice crystals at wavelength 532 nm are strongly sensitive to the degree of surface roughness. Comparisons of these quantities between the theoretical simulations and counterparts inferred from spaceborne lidar observations for cold cirrus clouds suggest a typical surface‐roughness‐degree range of 0.03–0.15 in the cases of compact hexagonal ice crystals, which is most consistent with direct measurements of scanning electron microscopic images. To properly interpret lidar backscattering observations of ice clouds, it is necessary to account for the degree of surface roughness in light‐scattering computations involving ice crystals. Plain Language Summary Lidar (Light Detection and Ranging) instruments on satellites use reflected, or backscattered, laser beams to investigate ice clouds in the atmosphere. However, it has long been a challenge to interpret lidar signals, called backscattering properties, to infer ice cloud characteristics accurately. This study uses theoretical simulations to investigate how small‐scale surface irregularities of ice crystals affect the lidar signals associated with ice clouds. These simulations demonstrate the significant impacts of small‐scale surface irregularities of ice crystals on backscattering. Based on comparisons between the theoretical simulations and satellite lidar observations, it is necessary to assume a moderate degree of small‐scale surface irregularities to explain lidar observations of typical ice clouds. Key Points The sensitivity of the backscattering properties to the surface roughness of atmospheric ice crystals is theoretically investigated The depolarization ratio is substantially sensitive to the degree of surface roughness of ice crystals Compact hexagonal ice models with degrees of surface roughness ranging 0.03–0.15 reasonably explain the Cloud‐Aerosol Lidar with Orthogonal Polarization backscattering signals