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Recent findings suggest that tumor microenvironment (TME) plays an important regulatory role in the occurrence, proliferation, and metastasis of tumors. Different from normal tissue, the condition around tumor significantly altered, including immune infiltration, compact extracellular matrix, new vasculatures, abundant enzyme, acidic pH value, and hypoxia. Increasingly, researchers focused on targeting TME to prevent tumor development and metastasis. With the development of nanotechnology and the deep research on the tumor environment, stimulation-responsive intelligent nanostructures designed based on TME have attracted much attention in the anti-tumor drug delivery system. TME-targeted nano therapeutics can regulate the distribution of drugs in the body, specifically increase the concentration of drugs in the tumor site, so as to enhance the efficacy and reduce adverse reactions, can utilize particular conditions of TME to improve the effect of tumor therapy. This paper summarizes the major components and characteristics of TME, discusses the principles and strategies of relevant nano-architectures targeting TME for the treatment and diagnosis systematically.

Trastuzumab resistance remains a challenge for HER2-positive breast cancer treatment. Targeting metabolic reprogramming would provide novel insights for therapeutic strategies. Here, we integrated metabolomics, transcriptomics, and epigenomics data of trastuzumab-sensitive and primary-resistant HER2-positive breast cancer to identify metabolic alterations. Aberrant cysteine metabolism was discovered in trastuzumab primary-resistant breast cancer at both circulating and intracellular levels. The inhibition of SLC7A11 and cysteine starvation could synergize with trastuzumab to induce ferroptosis. Mechanistically, increased H3K4me3 and decreased DNA methylation enhanced SLC7A11 transcription and cystine uptake in trastuzumab-resistant breast cancer. The regulation of epigenetic modifications modulated cysteine metabolism and ferroptosis sensitivity. These results revealed an innovative approach for overcoming trastuzumab resistance by targeting specific amino acid metabolism.

Prosodic entrainment, the phenomenon of speakers adapting their speech patterns to each other, has been extensively studied in short turn-taking conversations. However, little is known about its dynamics in long-and-short turn-taking contexts, such as talk shows. This study investigates prosodic entrainment in Mandarin Chinese talk shows, focusing on the effects of gender and role on entrainment behaviour and the correlation between perceived similarity and acoustic-prosodic features. We analysed a corpus of 50 audio files from a popular Mandarin Chinese talk show, examining three acoustic-prosodic features: pitch, intensity, and speaking rate. Prosodic entrainment was measured using proximity and synchrony-related distances at both local and global levels. Additionally, a perceptual judgement task was conducted to assess perceived prosodic similarity. Results showed that negative entrainment was more prevalent than positive entrainment across all three feature sets, particularly in speaking rate synchrony. The female host demonstrated larger positive entrainment compared to both male and female guests. Gender-role interactions revealed complex entrainment patterns: mixed-gender pairs showed greater local synchrony, while same-gender pairs exhibited more global entrainment. Perceived similarity correlated moderately with pitch for male guests in both local proximity and synchrony, suggesting pitch plays a crucial role in listeners’ perception of prosodic similarity. These findings challenge conventional assumptions about positive entrainment’s benefits in communication and highlight the complex interplay between gender, role, and entrainment behaviour in talk show settings. The prevalence of negative entrainment suggests that contrasting speech patterns can contribute to engaging and dynamic conversations in specific contexts. This study enhances our understanding of prosodic entrainment in long-and-short turn-taking contexts and emphasises the need to consider gender, role, and communicative settings in future research on speech accommodation.

As the largest emitter of carbon dioxide all over the world, China requires a rapid breakthrough and large-scale commercial application of carbon capture, utilization and sequestration (CCUS) technology to achieve the 2060 carbon neutrality target. However, the process of CCUS technology commercialization in China is quite slow. Firstly, an obstacle system with 15 factors is established based on a literature review and expert consultation, namely on economic, technical, political, market, and social obstacles. Secondly, taking into account the uncertainty and randomness inherent in subjective judgment, Vague set is introduced for the first time to improve the DEMATEL-ANP (DANP) method in order to analyze comprehensive importance and causal relationship of obstacles. According to the study, in advancing CCUS’s commercialization in China, economic obstacles are simply the tip of the iceberg, with the deeper reasons rooted in political obstacles. Specifically, seven critical obstacles are lack of standards and regulations, inadequate legal and regulatory framework, insufficient incentive policies, limited carbon dioxide conversion efficiency, high energy consumption, low rate of return on investments and low investment enthusiasm of enterprise. We conclude with a series of recommendations to address these obstacles, and these findings can be used as a guide for government regulation and business practice.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease with limited treatment options and frequent drug resistance. Novel therapeutic targets are urgently needed. We performed a druggable genome‐wide Mendelian randomization (MR) analysis using blood cis‐expression quantitative trait locus (eQTL) and HS genome‐wide association study (GWAS) data. Colocalization, transcriptomic validation, single‐cell RNA sequencing, and cell–cell communication analyses were integrated to explore gene function and cell‐type specificity. We identified eight genes that showed significant associations with HS through MR analysis. Colocalization analysis further prioritized PSMA4 and MAST3 as the most promising druggable targets for HS. Specifically, PSMA4 (single nucleotide polymorphisms [SNPs] = 10; inverse‐variance weighted [IVW] OR = 1.912, 95% CI: 1.492–2.450, p < 0.001; PP.H4 = 0.975) and MAST3 (SNPs = 15; IVW OR = 0.557, 95% CI: 0.453–0.686, p < 0.001; PP.H4 = 0.832) exhibited strong statistical associations. Transcriptomic validation revealed that PSMA4 was upregulated and MAST3 was downregulated in HS lesions. Further single‐cell analysis revealed that PSMA4 was predominantly enriched in CD4 + T cells and involved in pro‐inflammatory signaling, particularly the tumor necrosis factor (TNF) pathway. PSMA4 and MAST3 are potential therapeutic targets for HS. PSMA4 may promote inflammation via CD4 + T cell‐mediated signaling, offering a novel avenue for treatment development.

Psoriasis is a chronic inflammatory skin disorder with complex molecular mechanisms. While previous studies have demonstrated altered levels of arachidonic acid and its metabolites in psoriatic lesions, the specific roles of arachidonic acid metabolism (AAM) genes in the molecular pathogenesis and immune dysregulation of psoriasis remain poorly understood. This study aimed to investigate the role of AAM genes in the pathogenesis and immune dysregulation of psoriasis using an integrative bioinformatics approach. Gene expression data from psoriasis patients and healthy controls were obtained from the Gene Expression Omnibus database and analyzed. Differentially expressed genes were identified, and functional enrichment analyses were performed. Weighted gene co-expression network analysis (WGCNA) and machine learning techniques were employed to identify psoriasis associated AAM genes. Single-sample gene set enrichment analysis (ssGSEA) and immune cell composition analysis were conducted to explore functional implications. Transcription factor prediction analysis was performed to identify potential regulators of key AAM genes. Differential expression analysis revealed 469 dysregulated genes in psoriasis, with functional enrichment highlighting the involvement of epidermis development, immune response, and inflammation. WGCNA and machine learning approaches identified , and as key AAM genes. ssGSEA showed elevated inflammation and immune response in psoriasis, with key AAM genes correlating with specific pathways. Immune cell composition analysis revealed increased infiltration of inflammatory cells in psoriatic skin. Transcription factor prediction analysis identified shared transcription factors for the key AAM genes, suggesting coordinated regulation of their expression in psoriasis. This integrative analysis identified key AAM genes associated with psoriasis pathogenesis and immune dysregulation, providing novel insights into the molecular basis of psoriasis. The findings highlight potential therapeutic targets and biomarkers, which could lead to improved diagnosis and treatment strategies for this chronic inflammatory skin disorder.

Continued development of clustered regularly interspaced short palindromic repeats (CRISPR)‐powered biosensing system on the electrochemical interface is vital for accurate and timely diagnosis in clinical practice. Herein, an electrochemical biosensor based on manganese metal‐organic frameworks (MOFs)‐enhanced CRISPR (MME‐CRISPR) is proposed that enables the efficient detection of circulating tumor DNA (ctDNA). In this design, customized enzyme stimulants (Mn2+) are co‐assembled with Cas12a/crRNA to form enzyme‐MOF composites, which can be released quickly under mild conditions. The MOFs‐induced proximity effect can continuously provide adequate Mn2+ to sufficiently interact with Cas12a/crRNA during the release process, enhancing the trans‐cleavage activity of complex available for biosensor construction. The MOFs‐based enzyme biocomposites also afford efficient protection against various external stimulus. It is demonstrated that the developed biosensor can achieve ultrasensitive detection of epidermal growth factor receptor L858R mutation in ctDNA with a low detection limit of 0.28 fm without pre‐amplification. Furthermore, the engineered mismatch crRNA enables the biosensor based on MME‐CRISPR to detect single nucleotide variant with a high signal‐to‐noise ratio. More importantly, it has been successfully used to detect the targets in clinical practice, requiring low‐dose samples and a short time. This strategy is believed to shed new light on the applications of cancer diagnosis, treatment, and surveillance. This work designs manganese metal‐organic frameworks (Mn‐MOFs) co‐assembled with Cas12a/crRNA, enabling rapid release of Mn2⁺ under mild conditions. The MOFs‐induced proximity effect sustains Mn2⁺‐Cas12a/crRNA interactions, enhancing the trans‐cleavage activity of complex available to develop an electrochemical biosensor based on Mn‐MOFs‐enhanced clustered regularly interspaced short palindromic repeats   system, which offers a scalable platform for the ultrasensitive detection of circulating tumor DNA mutation.

In recent years, the microgrid system (MGS) has become an important method for the consumption of renewable energy sources (RES). In the actual operation process, the uncertainties of RES add to the complexity of the MGS operation. Furthermore, the MGS is often operated by multiple subsystem operators. The benefit distribution among subsystem operators is an important factor affecting the overall stable operation of the MGS. In order to resist the interference of the above factors, a two-stage optimization method is proposed in this paper, which includes a bi-level robust optimization (BRO) model in the overall scheduling stage of the MGS and a nucleolus-based cooperative game (NCG) model in the internal cost allocation stage among the subsystem operators. The simulations demonstrated the following outcomes: (1) the P2G device can reduce the operating cost of the MGS by converting electricity into natural gas when the electricity price is low; (2) the two-stage optimization method can ensure the stable operation of the MGS by resisting the disturbance of uncertain wind power outputs in the overall scheduling stage and realizing a reasonable cost allocation among the subsystem operators in the internal cost allocation stage.

Near-zero carbon emission power (NZCEP) plants, consisting of gas-fired units; wind turbines; power-to-gas (P2G); and carbon capture, utilization and storage (CCUS) systems, have recently received a lot of attention due to their enormous benefits in reducing carbon emissions and increasing the consumption of renewable energy. However, a complex environment of interest and a combination of risks makes their development very slow. This paper establishes a risk analysis framework for NZCEP considering multi-stakeholder participation. Firstly, a synthetic risk factor system was constructed based on stakeholders’ interests. Subsequently, interval type II trapezoidal fuzzy numbers were used and final weights were calculated from both subjective and objective aspects. Finally, we applied an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method to site selection to achieve a balance of interests of all stakeholders. In addition, a case study was conducted. The case result demonstrates that Zhengzhou in Henan Province is the best choice for a NZCEP power plant. A further finding is that government plays an important role in the development of NZCEP plants, with site selection results being the most sensitive to changes in the government’s risk appetite. Moreover, human resources are an important factor in the siting of an NZCEP plant.

Trichosporon infection is a rare but highly lethal infectious disease. Clinically, Trichosporon asahii is the strain most commonly isolated from patients with Trichosporon infections. T. asahii is an opportunistic pathogen that can cause local or invasive infections in immunocompromised patients. In this article, a case of breakthrough T. asahii infection in an immune thrombocytopenia (ITP) patient during caspofungin and isavuconazole combined therapy is reported. Metagenomic next-generation sequencing (mNGS) played a crucial role in the diagnosis of the breakthrough infection in this patient. Upon receiving combined therapy with intravenous voriconazole and nebulized amphotericin B, the patient demonstrated significant clinical improvement and was subsequently discharged.