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The rapid development of imaging technologies provides a visual diagnostic tool for scientists and surgeons to comprehensively and accurately understand the pathogenesis and pathological processes of complicated diseases, especially cancer. Theranostic platforms integrating various imaging technologies and treatment strategies for the diagnosis and treatment of cancer have been extensively studied. Notably, metal‐organic frameworks (MOFs) – an emerging porous organic‐inorganic hybrid material composed of metal ions/ion clusters as nodes and organic ligands as linkers bridged by coordination bonds – have been widely used as intelligent carriers for cancer theranostics in recent years due to their fascinating properties, including facile synthesis, diverse compositions, high surface areas and porosities, tailorable sizes, multiple physicochemical properties, easy surface functionalization, and good biocompatibility. This review summarizes the recent advanced developments and achievements of MOFs as smart theranostic platforms for effective cancer diagnosis and treatment guided by monomodal imaging technologies, including optical imaging, magnetic resonance imaging, computed tomography imaging, positron emission tomography imaging, and photoacoustic imaging, and multimodal imaging technologies. Moreover, the development prospects and critical challenges of MOFs for cancer theranostics are also addressed. The advanced achievements of MOFs as theranostic platforms for effective cancer diagnosis and treatment guided by monomodal imaging technologies, including OI, MRI, CT imaging, PET imaging, and PA imaging, and multimodal imaging technologies are summarized, and the development prospects and critical challenges of MOF‐based theranostic systems are also discussed.

Emergency Department (ED) healthcare workers (HCWs) have had one of the highest incidences of burnout [4-6] even prior to the pandemic. To evaluate the prevalence of burnout in this population and the preferred methods of coping with the COVID-19 situation, we conducted a cross-sectional study amongst doctors and nurses in our regional health cluster's Emergency Departments (EDs) and Urgent Care Center (UCC). Besides the use of technological media, spending time with family and friends and acts of gratitude from the department and peers were preferred methods for coping with the pandemic.

Cancer remains a severe threat to human health. To date, although various therapeutic methods, including radiotherapy (RT), chemotherapy, chemodynamic therapy (CDT), phototherapy, starvation therapy, and immunotherapy, have entered a new stage of rapid progress in cancer theranostics, their limited therapeutic effect and significant side effects need to be considered carefully. With the rapid development of nanotechnology, the marriage of nanomaterials and therapeutic methods provides the practical possibility to improve the deficiencies in cancer therapy. Notably, metal-organic frameworks (MOFs) composed of ions/clusters and bridging ligands through coordination bonds have been widely applied in cancer therapy to deal with the drawbacks of different therapeutic methods, such as severe side effects, low stability, and poor efficacy, owing to their controllable morphologies, tailorable diameters, diverse compositions, tunable porosities, high specific surface areas, facile functionalization, and good biocompatibility. This review summarizes the recent advanced developments and achievements of multifunctional MOF-based nanoplatforms for cancer therapy through single therapy methods, including RT, chemotherapy, CDT, phototherapy (photodynamic and photothermal therapy), starvation therapy and immunotherapy, and combination therapy methods. Moreover, the prospects and challenges of MOF-based nanoplatforms used in tumor therapy are also discussed.

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

Interpersonal interaction through vocal music language has become an important channel for cross-cultural social life. How to skillfully use vocal music language to stimulate the audience’s emotional arousal and trigger their immersive experience has become a research focus in the field of music. At present, the academic research on vocal music language is diversified, and has explored the path of vocal music occurrence and its development direction under specific circumstances. However, the process of immersive experience arousal from the perspective of “music” language and “lyrics” language is a hidden code study. In order to comprehensively consider various styles of vocal music, we selected the music of three different singing styles including folk style singing, bel canto and popular singing as experimental materials to study the arousal process of the audiences’ immersive experience of vocal music language when listening to music. The results indicate that both “music” and “lyrics” language perceptions exert a significantly positive impact on the audience’s emotional arousal and immersive experience, and in addition, arousal plays a significant mediating role between vocal music language and immersive experience. Therefore, by means of clarifying the internal logic of the audience’s immersive experience from the perspectives of “music” and “lyrics” in the vocal music language, this study provides new theoretical insights for the applicable boundary of telepresence in the vocal music field, facilitate operators to design on-the-scene vocal music art environment to convey the emotional connotation of vocal music, and further promote the development of the vocal music field. Plain language summary This paper conducts a study on the arousal process of the audiences’ immersive experience of vocal music language when listening to music through PLS-SEM analysis. The findings indicate that both “music” and “lyrics” language perceptions exert a significantly positive impact on the audience’s emotional arousal and immersive experience, and in addition, arousal plays a significant mediating role between vocal music language and immersive experience. We believe that our study significantly contributes to current literature because it provides new theoretical insights for the applicable boundary of telepresence in the vocal music field: This study aims to clarify the internal logic of the audience’s immersive experience from the perspective of “music” and “lyrics” in the vocal music language through analyzing the path mechanism in a bid to explore the audience’s emotional arousal and flow experience regularities of vocal music, and confirm the existence and applicability of arousal and immersive experience in the vocal music language.

Sarcopenia, with risk factors such as poor nutrition and physical inactivity, is becoming prevalent among the older population. The aims of this study were (i) to systematically review the existing data on sarcopenia prevalence in the older Chinese population, (ii) to generate pooled estimates of the sex-specific prevalence among different populations, and (iii) to identify the factors associated with the heterogeneity in the estimates across studies. A search was conducted in seven databases for studies that reported the prevalence of sarcopenia in Chinese older adults, aged 60 years and over, published through April 2020. We then performed a meta-analysis to estimate the pooled prevalence, and investigated the factors associated with the variation in the prevalence across the studies using meta-regression. A total of 58 studies were included in this review. Compared with community-dwelling Chinese older adults (men: 12.9%, 95% CI: 10.7–15.1%; women: 11.2%, 95% CI: 8.9–13.4%), the pooled prevalence of sarcopenia in older adults from hospitals (men: 29.7%, 95% CI:18.4–41.1%; women: 23.0%, 95% CI:17.1–28.8%) and nursing homes (men: 26.3%, 95% CI: 19.1 to 33.4%; women: 33.7%, 95% CI: 27.2 to 40.1%) was higher. The multivariable meta-regression quantified the difference of the prevalence estimates in different populations, muscle mass assessments, and areas. This study yielded pooled estimates of sarcopenia prevalence in Chinese older adults not only from communities, but also from clinical settings and nursing homes. This study added knowledge to the current epidemiology literature about sarcopenia in older Chinese populations, and could provide background information for future preventive strategies, such as nutrition and physical activity interventions, tailored to the growing older population.

Using a single or averaged OCV-SOC (open circuit voltage VS. state of charge) relationship obtained under charging or discharging condition will deteriorate battery SOC estimation of model-based methods. To address the issues, this paper proposes a novel SOC fusion estimation method considering charging and discharging OCV-SOC relationships. This method fully considers the actual working state of batteries in electric vehicles, which is beneficial for improving SOC estimation results. The SOC is respectively estimated using OCV-SOC relationship under discharging and charging conditions combined with fractional-order extended Kalman filter (FOEKF) algorithm. Both SOC estimation results using charging and discharging OCV-SOC relationships are obtained and then fuse them by the weighted summation for getting the final SOC. The fusion weights are established using the predicted voltage error. The US06 Highway Driving Schedule and Beijing Dynamic Stress Test (BJDST) are used for verifying the proposed method. The SOC root-mean square errors (RMSEs) compared to the regular technique that uses a single OCV-SOC relationship obtained under discharging condition decrease from 1.65% and 1.70–0.71% and 0.70% under the above two tests. The applicability of a certain OCV-SOC relationship for estimating SOC under all driving conditions is limited. Using multiple OCV-SOC relationships obtained under different conditions for SOC fusion estimation can effectively improve estimation accuracy. We have demonstrated the correctness and effectiveness of this paper’s ideas using BJDST test and US06 test.

Chronic, unresolved tissue inflammation is a well-described feature of obesity, type 2 diabetes mellitus (T2DM) and other insulin-resistant states. In this context, adipose tissue and liver inflammation have been particularly well studied; however, abundant evidence demonstrates that inflammatory processes are also activated in pancreatic islets from obese animals and humans with obesity and/or T2DM. In this Review, we focus on the characteristics of immune cell-mediated inflammation in islets and the consequences of this with respect to β-cell function. In contrast to type 1 diabetes mellitus, the dominant immune cell type causing inflammation in obese and T2DM islets is the macrophage. The increased macrophage accumulation in T2DM islets primarily arises through local proliferation of resident macrophages, which then provide signals (such as platelet-derived growth factor) that drive β-cell hyperplasia (a classic feature of obesity). In addition, islet macrophages also impair the insulin secretory capacity of β-cells. Through these mechanisms, islet-resident macrophages underlie the inflammatory response in obesity and mechanistically participate in the β-cell hyperplasia and dysfunction that characterizes this insulin-resistant state. These findings point to the possibility of therapeutics that target islet inflammation to elicit beneficial effects on β-cell function and glycaemia.The dominant immune cell type causing pancreatic islet inflammation in individuals with obesity and/or type 2 diabetes mellitus is the macrophage. In this Review, we focus on the characteristics of inflammation in obese or type 2 diabetes mellitus islets and the consequences of this with respect to β-cell function.