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"Qi, Lin"
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Chinese public’s knowledge, perceived severity, and perceived controllability of COVID-19 and their associations with emotional and behavioural reactions, social participation, and precautionary behaviour: a national survey
Background
The outbreak of the coronavirus disease-19 (COVID-19) has caused enormous stress among the public in China. Intellectual input from various aspects is needed to fight against COVID-19, including understanding of the public’s emotion and behaviour and their antecedents from the psychological perspectives. Drawing upon the cognitive appraisal theory, this study examined three cognitive appraisals (i.e., perceived severity, perceived controllability, and knowledge of COVID-19) and their associations with a wide range of emotional and behavioural outcomes among the Chinese public.
Methods
Participants were 4607 citizens (age range: 17–90 years, Mage = 23.71 years) from 31 provinces in China and they took part in a cross-sectional survey online.
Results
The results showed that the public’s emotional and behavioural reactions were slightly affected by the outbreak of COVID-19. Moreover, the public had limited participation in the events regarding COVID-19 but actively engaged in precautionary behaviour. In addition, results of structural equation model with latent variables revealed that the three appraisals were differentially related to the outcome variables (i.e., negative emotion, positive emotion, sleep problems, aggression, substance use, mobile phone use, social participation, and precautionary behaviour).
Conclusions
The findings highlight the utility of cognitive appraisal, as a core process of coping stress, in explaining the public’s emotion and behaviour in the encounter of public health concern. Practically, the findings facilitate the government and practitioners to design and deliver targeted intervention programs to the public.
Journal Article
Stereoselective synthesis of medium lactams enabled by metal-free hydroalkoxylation/stereospecific 1,3-rearrangement
Rearrangement reactions have attracted considerable interest over the past decades due to their high bond-forming efficiency and atom economy in the construction of complex organic architectures. In contrast to the well-established [3,3]-rearrangement, [1,3] O-to-C rearrangement has been far less vigorously investigated, and stereospecific [1,3]-rearrangement is extremely rare. Here, we report a metal-free intramolecular hydroalkoxylation/[1,3]-rearrangement, leading to the practical and atom-economical assembly of various valuable medium-sized lactams with wide substrate scope and excellent diastereoselectivity. Moreover, such an asymmetric cascade cyclization has also been realized by chiral Brønsted acid-catalyzed kinetic resolution. In addition, biological tests reveal that some of these medium-sized lactams displayed their bioactivity as antitumor agents against melanoma cells, esophageal cancer cells and breast cancer cells. A mechanistic rationale for the reaction is further supported by control experiments and theoretical calculations.
Stereospecific [1,3]-rearrangements are rarely reported method to efficiently build complex organic architectures. Here, the authors describe a metal-free intramolecular hydroalkoxylation/[1,3]-rearrangement sequence affording medium-sized lactams with wide scope, also in an asymmetric fashion.
Journal Article
Deep learning model for Chinese watercolor painting creation
Chinese watercolor painting, celebrated for its delicate brushwork, smooth tonal gradients, and expressive ink diffusion, embodies a rich historical and cultural heritage. This article introduces a hierarchical multi-scale generative framework for producing high-quality traditional watercolor paintings. The model is trained on a curated collection of high-resolution artworks from public museum archives and employs a pyramid of patch-based generative adversarial networks (GANs), each dedicated to learning visual features at a specific spatial scale. Residual learning across scales enables progressive refinement from coarse composition to intricate brushstroke details. Quantitative evaluation using Fréchet Inception Distance (FID) and Diversity Score shows significant performance gains over other well-known GAN-based models. Qualitative results further demonstrate the framework's ability to emulate the stylistic nuances of classical Chinese art, capturing brushwork precision, ink diffusion effects, and compositional harmony, while preserving both global structure and local texture.
Journal Article
Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography
ObjectivesTo explore the role of dual-energy spectral computed tomography (DESCT) quantitative characteristics for the identification of epidermal growth factor receptor (EGFR) mutation status in a cohort of East Asian patients with pulmonary adenocarcinoma.Materials and methodsPatients with lung adenocarcinoma who underwent both DESCT chest examination and EGFR test were retrospectively selected from our institution’s database. The DESCT visual morphological features and quantitative parameters, including the CT number at 70 keV, normalized iodine concentration (NIC), normalized water concentration, and slopes of the spectral attenuation curves (slope λ HU [Hounsfield unit]), were evaluated or calculated. The patients were divided into two groups: the EGFR mutation group and EGFR wild-type group. Statistical analyses were performed to identify the DESCT quantitative parameters for diagnosis of EGFR mutation status.ResultsEGFR mutations were detected in 66 (55.0%) of the 120 enrolled patients. The univariate analysis revealed that sex, smoking history, CT texture, NIC, and slope λ HU were significantly associated with EGFR mutation status (p = 0.037, 0.001, 0.047, 0.010, and 0.018, respectively). The multivariate logistic analysis revealed that smoking history (odds ratio [OR] = 3.23, p = 0.005) and NIC (OR = 58.026, p = 0.049) were the two significant predictive factors associated with EGFR mutations. Based on this analysis, the smoking history and NIC were combined to determine the predictive value for EGFR mutations with the area under the curve of 0.702.ConclusionsNIC may be a potential quantitative DESCT parameter for predicting EGFR mutations in patients with pulmonary adenocarcinoma.Key Points• DESCT can provide multiple quantitative image parameters compared to conventional CT.• Identification of the radio-genomic relation between DESCT and EGFR status can help to define molecular subcategories of lung adenocarcinoma, which is valuable for personalized clinical targeted therapy.• NIC may be a potential DESCT quantitative parameter for predicting EGFR mutations in pulmonary adenocarcinoma.
Journal Article
Current Advances on Nanomaterials Interfering with Lactate Metabolism for Tumor Therapy
Increasing numbers of studies have shown that tumor cells prefer fermentative glycolysis over oxidative phosphorylation to provide a vast amount of energy for fast proliferation even under oxygen‐sufficient conditions. This metabolic alteration not only favors tumor cell progression and metastasis but also increases lactate accumulation in solid tumors. In addition to serving as a byproduct of glycolytic tumor cells, lactate also plays a central role in the construction of acidic and immunosuppressive tumor microenvironment, resulting in therapeutic tolerance. Recently, targeted drug delivery and inherent therapeutic properties of nanomaterials have attracted great attention, and research on modulating lactate metabolism based on nanomaterials to enhance antitumor therapy has exploded. In this review, the advanced tumor therapy strategies based on nanomaterials that interfere with lactate metabolism are discussed, including inhibiting lactate anabolism, promoting lactate catabolism, and disrupting the “lactate shuttle”. Furthermore, recent advances in combining lactate metabolism modulation with other therapies, including chemotherapy, immunotherapy, photothermal therapy, and reactive oxygen species‐related therapies, etc., which have achieved cooperatively enhanced therapeutic outcomes, are summarized. Finally, foreseeable challenges and prospective developments are also reviewed for the future development of this field. Lactate has long been overlooked in tumors, confined to the roles of a glycolysis waste product and a biomarker of malignancy. With in‐depth research, lactate has recently been recognized as an important factor in tumor progression, metastasis, and therapeutic resistance. This review comprehensively summarizes the recent progress in nanomaterial‐mediated lactate metabolism modulation for oncotherapy.
Journal Article
A compact and miniaturized implantable antenna for ISM band in wireless cardiac pacemaker system
A tiny and compact implantable antenna for wireless cardiac pacemaker systems is designed. The antenna works in the Industrial Scientific Medical (ISM) frequency band (2.4–2.48 GHz). The size of the antenna is greatly reduced with the adoption of a high dielectric constant medium and a folded meander structure. The volume of the antenna is 4.5 mm
3
, and the size is only 3 mm × 3 mm × 0.5 mm. Based on the literature research, it was found that the design was the smallest among the same type of implanted antenna. The antenna is optimized and loaded with a defective slotted structure, which improves the efficiency of the overall performance of the antenna and thus the gain thereof. The antenna maintains good impedance matching in the ISM frequency band, covering the entire ISM frequency band. The actual bandwidth of the antenna is 22%, with the peak gain of − 24.9 dBi. The antenna is processed and manufactured in such a manner that the simulation keeps consistent with the actual measurement. In addition, the specific absorption rate of the antenna is also evaluated and analyzed. The result shows that this kind of antenna is the best choice to realize the wireless biological telemetry communication in the extremely compact space of the wireless cardiac pacemaker system.
Journal Article
Association between C-reactive protein-albumin-lymphocyte (CALLY) index and overall survival in patients with colorectal cancer: From the investigation on nutrition status and clinical outcome of common cancers study
Colorectal cancer (CRC) is among the most common malignant cancers worldwide, and its development is influenced by inflammation, nutrition, and the immune status. Therefore, we combined C-reactive protein (CRP), albumin, and lymphocyte, which could reflect above status, to be the CRP-albumin-lymphocyte (CALLY) index, and evaluated its association with overall survival (OS) in patients with CRC.
The clinicopathological and laboratory characteristics of 1260 patients with CRC were collected from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. Cox regression analysis was performed to assess the association between the CALLY index and OS. A nomogram including sex, age, the CALLY index and TNM stage was constructed. The Concordance Index (C-index) was utilized to evaluate the prognostic value of the CALLY index and classical CRC prognostic factors, such as modified Glasgow prognostic score (mGPS), neutrocyte to lymphocyte ratio (NLR), systemic immune inflammation index (SII), and platelet to lymphocyte ratio (PLR), as well as to assess the prognostic value of the nomogram and TNM stage.
Multivariate Cox regression analyses demonstrated that the CALLY index was independently associated with OS in patients with CRC [Hazard ratio (HR) = 0.91, 95% confidence interval (CI) = 0.87-0.95,
<0.001]. The CALLY index showed the highest prognostic value (C-index = 0.666, 95% CI = 0.638-0.694,
<0.001), followed by mGPS, NLR, SII, and PLR. The nomogram demonstrated higher prognostic value (C-index = 0.784, 95% CI = 0.762-0.807,
<0.001) than the TNM stage.
The CALLY index was independently associated with OS in patients with CRC and showed higher prognostic value than classical CRC prognostic factors. The nomogram could provide more accurate prognostic prediction than TNM stage.
Journal Article
Current Status and Future Trends of Meter-Level Indoor Positioning Technology: A Review
High-precision indoor positioning technology is regarded as one of the core components of artificial intelligence (AI) and Internet of Things (IoT) applications. Over the past decades, society has observed a burgeoning demand for indoor location-based services (iLBSs). Concurrently, ongoing technological innovations have been instrumental in establishing more accurate, particularly meter-level indoor positioning systems. In scenarios where the penetration of satellite signals indoors proves problematic, research efforts focused on high-precision intelligent indoor positioning technology have seen a substantial increase. Consequently, a stable assortment of location sources and their respective positioning methods have emerged, characterizing modern technological resilience. This academic composition serves to illuminate the current status of meter-level indoor positioning technologies. An in-depth overview is provided in this paper, segmenting these technologies into distinct types based on specific positioning principles such as geometric relationships, fingerprint matching, incremental estimation, and quantum navigation. The purpose and principles underlying each method are elucidated, followed by a rigorous examination and analysis of their respective technological strides. Subsequently, we encapsulate the unique attributes and strengths of high-precision indoor positioning technology in a concise summary. This thorough investigation aspires to be a catalyst in the progression and refinement of indoor positioning technologies. Lastly, we broach prospective trends, including diversification, intelligence, and popularization, and we speculate on a bright future ripe with opportunities for these technological innovations.
Journal Article
State reliability analysis methods for nonlinear systems integrating adaptive entropy weighted grey relation and Dempster-Shafer’s Theory
Under uncertain environmental conditions, a nonlinear system may encounter problems like information conflicts, ambiguity, loss, and unclear interdependencies, which can result in low accuracy in predicting abnormal system states. System failures lead to negative impacts. To address these issues, this study proposes an analysis model that incorporates factor weight adaptive adjustment and integrates Dempster-Shafer’s theory (D-S theory) algorithms to construct an evaluation model, and to quantify uncertainty factors and correlation factors within the system. This approach reduces the impact of uncertainty in information features on analysis accuracy, enhances the precision of system reliability state probability assessment, and improves decision-making management levels. The results of the wind turbine system case study indicate that the proposed algorithm achieves a system state identification accuracy of 97% and a system reliability probability of 65%, with an overall accuracy improvement of 4.5% compared to traditional algorithms and a reliability probability assessment accuracy improvement of 5.22%, better aligning with the actual system’s state probability distribution.
Journal Article