Design Thinking Exploration From Three Disciplines That Influence Industry Development

This essay examines how design thinking impacts three different disciplines and fields via comparing the growing development on its definition during its extensive integration. Specifically, the comparison ranges from visual perception to the product development; in a larger scale, from management of individual organizations to social and global area. A few cases are utilized to elaborate the core design and development activities on product development, including the utilization of sketching in visual art, global business extension of Ford Motor Company. Then, by combining how design thinking speeds up the innovation in various industries, observations from the surveys and researches are also enlisted to generalize improvements achieved within certain aspects of the system. Furthermore, to sustain a better future environment, design thinking calls for more commitment in sustainability, especially in social and global aspects

A Representation Learning Approach for Predicting circRNA Back-Splicing Event via Sequence-Interaction-Aware Dual Encoder

Circular RNAs (circRNAs) play a crucial role in generegulation and association with diseases because of their uniqueclosed continuous loop structure, which is more stable and conserved than ordinary linear RNAs. As fundamental work to clarifytheir functions, a large number of computational approaches foridentifying circRNA formation have been proposed. However, thesemethods fail to fully utilize the important characteristics of backsplicing events, i.e., the positional information of the splice sitesand the interaction features of its flanking sequences, for predicting circRNAs. To this end, we hereby propose a novel approachcalled SIDE for predicting circRNA back-splicing events using onlyraw RNA sequences. Technically, SIDE employs a dual encoderto capture global and interactive features of the RNA sequence,and then a decoder designed by the contrastive learning to fuseout discriminative features improving the prediction of circRNAsformation. Empirical results on three real-world datasets showthe effectiveness of SIDE. Further analysis also reveals that theeffectiveness of SIDE

The Principal Parametric Resonance of Coupled van der Pol Oscillators under Feedback Control

The principal parametric resonance of two van der Pol oscillators under coupled position and velocity feedback control with time delay is investigated analytically and numerically on the assumption that only one of the two oscillators is parametrically excited and the feedback control is linear. The slow-flow equations are obtained by the averaging method and simplified by truncating the first term of Taylor expansions for those terms with time delay. It is found that nontrivial solutions corresponding to periodic motions exist only for one oscillator if no feedback control is applied although the two oscillators are nonlinearly coupled. Based on Levenberg-Marquardt method, the effects of excitation and control parameters on the amplitude of periodic solutions of the system are graphically given. It can be seen that both of the two oscillators can be excited in periodic vibration with proper feedback. However, the amplitudes of the periodic vibrations are independent of the sign of feedback gains. In addition, the influence of time delay on the response of the system is periodic. In terms of numerical simulations, it is shown that both of the two oscillators can also have quasi-periodic motions, periodic motions about a new equilibrium position and other complex motions such as relaxation oscillation when feedback control is considered

Identification of crosstalk genes and immune characteristics between Alzheimer’s disease and atherosclerosis

BackgroundAdvancements in modern medicine have extended human lifespan, but they have also led to an increase in age-related diseases such as Alzheimer’s disease (AD) and atherosclerosis (AS). Growing research evidence indicates a close connection between these two conditions.MethodsWe downloaded four gene expression datasets related to AD and AS from the Gene Expression Omnibus (GEO) database (GSE33000, GSE100927, GSE44770, and GSE43292) and performed differential gene expression (DEGs) analysis using the R package “limma”. Through Weighted gene correlation network analysis (WGCNA), we selected the gene modules most relevant to the diseases and intersected them with the DEGs to identify crosstalk genes (CGs) between AD and AS. Subsequently, we conducted functional enrichment analysis of the CGs using DAVID. To screen for potential diagnostic genes, we applied the least absolute shrinkage and selection operator (LASSO) regression and constructed a logistic regression model for disease prediction. We established a protein-protein interaction (PPI) network using STRING (https://cn.string-db.org/) and Cytoscape and analyzed immune cell infiltration using the CIBERSORT algorithm. Additionally, NetworkAnalyst (http://www.networkanalyst.ca) was utilized for gene regulation and interaction analysis, and consensus clustering was employed to determine disease subtypes. All statistical analyses and visualizations were performed using various R packages, with a significance level set at p<0.05.ResultsThrough intersection analysis of disease-associated gene modules identified by DEGs and WGCNA, we identified a total of 31 CGs co-existing between AD and AS, with their biological functions primarily associated with immune pathways. LASSO analysis helped us identify three genes (C1QA, MT1M, and RAMP1) as optimal diagnostic CGs for AD and AS. Based on this, we constructed predictive models for both diseases, whose accuracy was validated by external databases. By establishing a PPI network and employing four topological algorithms, we identified four hub genes (C1QB, CSF1R, TYROBP, and FCER1G) within the CGs, closely related to immune cell infiltration. NetworkAnalyst further revealed the regulatory networks of these hub genes. Finally, defining C1 and C2 subtypes for AD and AS respectively based on the expression profiles of CGs, we found the C2 subtype exhibited immune overactivation.ConclusionThis study utilized gene expression matrices and various algorithms to explore the potential links between AD and AS. The identification of CGs revealed interactions between these two diseases, with immune and inflammatory imbalances playing crucial roles in their onset and progression. We hope these findings will provide valuable insights for future research on AD and AS

High expression of SIGLEC7 may promote M2-type macrophage polarization leading to adverse prognosis in glioma patients

IntroductionGliomas are the most common primary intracranial tumors, known for their high invasiveness and destructiveness. Sialic acid-binding immunoglobulin-like lectin 7 (SIGLEC7) is present in various immune cells, especially macrophages, and significantly affects immune homeostasis and cancer cell response. However, research on the role and prognostic impact of SIGLEC7 in glioma patients is currently limited.MethodsWe utilized transcriptomic data from 702 glioma patients in The Cancer Genome Atlas (TCGA) and 693 glioma patients in the Chinese Glioma Genome Atlas (CGGA), along with clinical samples we collected, to comprehensively investigate the impact of SIGLEC7 on glioma expression patterns, biological functions, and prognostic value. We focused on its role in glioma-related immune responses and immune cell infiltration and analyzed its expression at the single-cell level. Finally, we validated the role of SIGLEC7 in gliomas through tissue and cell experiments.ResultsSIGLEC7 expression was significantly increased in glioma patients with malignant characteristics. Survival analysis indicated that glioma patients with high SIGLEC7 expression had significantly lower survival rates. Gene function analysis revealed that SIGLEC7 is primarily involved in immune and inflammatory responses and is strongly negatively correlated with tumor-associated immune regulation. Additionally, the expression of most immune checkpoints was positively correlated with SIGLEC7, and immune cell infiltration analysis clearly demonstrated a significant positive correlation between SIGLEC7 expression and M2 macrophage infiltration levels. Single-cell analysis, along with tissue and cell experiments, confirmed that SIGLEC7 enhances macrophage polarization towards the M2 phenotype, thereby promoting glioma invasiveness through the immunosuppressive effects of M2 macrophages. Cox regression analysis and the establishment of survival prediction models indicated that high SIGLEC7 expression is an unfavorable prognostic factor for glioma patients.DiscussionHigh SIGLEC7 expression predicts poor prognosis in glioma patients and is closely associated with M2 macrophages in the tumor environment. In the future, SIGLEC7 may become a promising target for glioma immunotherapy

Anticancer Therapy-Induced Atrial Fibrillation: Electrophysiology and Related Mechanisms

Some well-established immunotherapy, radiotherapy, postoperation, anticancer drugs such as anthracyclines, antimetabolites, human epidermal growth factor receptor 2 blockers, tyrosine kinase inhibitors, alkylating agents, checkpoint inhibitors, and angiogenesis inhibitors, are significantly linked to cardiotoxicity. Cardiotoxicity is a common complication of several cancer treatments. Some studies observed complications of cardiac arrhythmia associated with the treatment of cancer, including atrial fibrillation (AF), supraventricular arrhythmias, and cardiac repolarization abnormalities. AF increases the risk of cardiovascular morbidity and mortality; it is associated with an almost doubled risk of mortality and a nearly 5-fold increase in the risk of stroke. The occurrence of AF is also usually researched in patients with advanced cancer and those undergoing active cancer treatments. During cancer treatments, the incidence rate of AF affects the prognosis of tumor treatment and challenges the treatment strategy. The present article is mainly focused on the cardiotoxicity of cancer treatments. In our review, we discuss these anticancer therapies and how they induce AF and consequently provide information on the precaution of AF during cancer treatment

Non-volatile tunable multispectral compatible infrared camouflage based on the infrared radiation characteristics of Rosaceae plants

Most multispectral compatible infrared camouflage devices primarily focus on achieving low emissivity but neglect environmental emissivity matching when environmental emissivity exceeds that of the devices, this creates a "low-emissivity exposure" risk. To address this issue, we develop a tunable multispectral compatible infrared camouflage device using phase change material In3SbTe2 (IST). Simulation and experimental results demonstrate that in both the amorphous (aIST) and crystalline (cIST) states, the device achieves simulated plant infrared camouflage and ultra-low emissivity infrared camouflage within the atmospheric window bands (3–5 µm and 8–14 µm). To address thermal management, it utilizes two non-atmospheric window bands (2.5–3 µm and 5–8 µm) for heat dissipation. Additionally, laser stealth is realized at three specific wavelengths (1.064 µm, 1.55 µm, and 10.6 µm). In the visible spectrum, high absorptivity enables effective visible light camouflage. Adjusting the geometric parameters of top layer structure enables color variation. This work not only highlights potential applications in reversible switching, reconfigurable imaging, and dynamic coding using IST but also offers an effective strategy to counter multispectral detection technology

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels