Jieduquyuziyin prescription alleviates lupus development via inhibiting neddylation pathway to promote Bim-induced apoptosis of double negative T cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Jieduquyuziyin prescription (JP) is an empirical prescription approved for application to treat systemic lupus erythematosus (SLE) in hospital within China. Despite the prominent treatment effect of JP clinically, further investigation is imperative to explore its underlying mechanisms. AIM OF THE STUDY: We aim to investigate the impact of JP on DN T cell apoptosis in the treatment of SLE and the specific regulation mechanisms. MATERIALS AND METHODS: Firstly, female MRL/lpr mice were treated with JP and the therapeutic efficacy of JP was evaluated via skin lesions, lymphoid organ enlargement, accumulation of autoantibodies and renal function. Then, flow cytometer analysis was performed to evaluate the proportions and the apoptosis of T cell subpopulations. Based on the above results, double-negative (DN) T cells were subjected to proteomic with subsequent differential screening. The expression of Ube2m and Bim was further validated using real-time PCR and Western blot. Subsequently, DN T cells were incubated with JP-contained serum in vitro, and cell apoptosis was quantified using flow cytometry. Additionally, the expression levels of Ube2m, Bim and other associated proteins were also assessed through western blotting. To further clarify whether Ube2m serves as the key target of JP in regulating DN T cell apoptosis, the mice that Ube2m was specific deleted in T cells with spontaneous lupus (Ube2m-/-lpr) were utilized. JP was administered to WTlpr or Ube2m-/-lpr mice, followed by assessment of the lupus condition and DN T cell apoptosis. RESULTS: JP administration effectively ameliorated the lupus phenotype. Then flow cytometry assay showed that JP treatment enhanced DN T cell apoptosis to reduce their accumulation and restored the immune homeostasis. Proteomic analysis revealed a significant inhibition of Ube2m for JP treatment, which is essential for maintaining homeostasis of DN T cells. Further experiments confirmed that JP treatment effectively downregulated the expression of Ube2m and subsequently upregulated the level of pro-apoptotic protein Bim with decreased Bim degradation. In vitro experiments also confirmed that JP-contained serum significantly facilitated DN T cell apoptosis and reduced DN T cell accumulation by inhibiting Ube2m expression. Furthermore, Ube2m-/-lpr mice were utilized and the impact of JP treatment on the apoptosis of DN T cells was found to be minimal in the absence of Ube2m. Mechanistic investigation reveals that JP exerts its effects by suppressing the expression of Ube2m, subsequently inhibiting CRL-dependent degradation of Bim, and ultimately promoting Bim-induced apoptosis in DN T cells. Furthermore, the blockade of Ube2m in T cells effectively prevents JP-induced apoptosis in DN T cells, underscoring Ube2m as one crucial therapeutic target of JP in mediating DN T cell apoptosis and managing SLE. CONCLUSIONS: Our findings indicate that JP treatment effectively restores the homeostasis of DN T cells in SLE by inhibiting Ube2m expression, thereby reducing Bim ubiquitination degradation. This ultimately enhanced DN T cell apoptosis and alleviated lupus phenotype.

Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network.

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.

MiR-214 promotes the antitumor effect of NK cells in colorectal cancer liver metastasis through USP27X/Bim.

Colorectal cancer (CRC) is a common tumor type, and liver metastasis reduces the long-term survival in CRC patients. Natural killer (NK) cells play an important role in anti-tumor immunity. The aim of this study was to investigate the mechanism of miR-214-5p on NK cells in CRC liver metastasis. We collected clinical samples of CRC liver metastasis and nonmetastatic tissues and purchased the human NK cell lines NK92 and liver metastatic CRC cells KM12L4 for research. RT‒qPCR, Western blot, CCK-8, Transwell, and flow cytometry methods were used to evaluate the effect of miR-214-5p/USP27X/Bim pathway regulating NK cell activity on CRC liver metastasis. In addition, we also investigated the potential targets and regulatory mechanisms of the signaling pathway of miR-214-5p. In this study, we found that miR-214-5p was downregulated in CRC liver metastasis tissues. After transfection of miR-214-5p mimic, the activity of NK cells was significantly enhanced, and the proliferation and migration ability of CRC liver metastasis cells were inhibited, while inducing tumor cell apoptosis. Further research proved that USP27X is a potential target for miR-214-5p and upregulates Bim level through deubiquitination. In addition, miR-214-5p mimic reduced the level of USP27X and Bim, thereby enhancing the antitumor effect of NK cells. In conclusion, our research results show that miR-214-5p promotes the antitumor effect of NK cells by regulating the USP27X/Bim pathway, thereby inhibiting CRC liver metastasis. This finding reveals the important role of miR-214-5p in regulating the immune function of NK cells, and provides new ideas for developing new immunotherapy strategies. Supplementary Information: The online version contains supplementary material available at 10.1007/s10616-024-00642-1.

An ISM-MICMAC-based study for identification and classification of preventable safety risk mitigation factors in mass housing projects following a BIM approach.

Construction operation is among the most high-risk sectors in terms of work-related accident, making it highly challenging to surveil the safety of such projects. In construction projects, failure to observe safety represents a leading cause of fatal accidents, not to mention the losses incurred by such accidents to national assets of the country. Accordingly, recent decades have witnessed the emergence of modern techniques for improving the occupational safety of construction projects. The main purpose of the present research is to identify and classify different preventable risk mitigation factors in mass housing projects following a building information modeling (BIM) approach. The research methodology included interviews with relevant experts and elites followed by analysis of the data on the 12 identified-as-significant variables for mitigating the preventable risk factors in mass house construction projects by means of the inferential - structural modeling (ISM) in MICMAC software. In order to explore the relationships among and succession of different criteria and further classify them at different levels, ISM was implemented, with the MICMAC software used to analyze the direct and indirect influences, develop influence/dependence maps, and judge about the role of each criterion. Findings of the present research showed that the mutual relations (H3), the reward system (H6), the reporting system (H7), and the supervisors' supervision (H8) are autonomous variables and hence impose the smallest contributions to the system. Accordingly, they can be eliminated from the model though their effects may not be completely ignored. On the other hand, the employees' empowering (H4), the safety management system (H5), the teamwork (H9), the self-efficiency (H10), and the knowledge and awareness (H11) were identified as the linkage variables that fill in the gap between the safety and occupational accident reduction in the mass house construction projects. Further, the continuous improvement (H2) and the safe behavior (H12) were identified as dependent variables, implying that they exhibit the weakest influence coupled with highest dependence on any change in the conditions of the system. Last but not the least, the management commitment (H1) was identified as the only dependent variable which deserves lots of attention. This information can be helpful to safety decision-makers, end users, research organizations, and academic institutes who work to reduce the preventable risk factors in mass house construction projects.

Anti-Mullerian Hormone Induces Foxo1 and Sirt1 Genes Expression in Mouse Ovary.

BACKGROUND: Anti-Mullerian hormone (AMH) plays a pivotal role in follicular growth and atresia. Recent studies highlighted the role of AMH in attenuating granulosa cell apoptosis and subsequent follicular atresia. Despite the raising understanding of the role of AMH in folliculogenesis, and its contribution to the pathophysiology of certain diseases such as polycystic ovary syndrome, the effect of AMH on the expression of genes regulating folliculogenesis is stills limited. OBJECTIVE: This study aims to gain insights into the effect of AMH on atresia regulating genes. METHOD: In vivo study was performed on C57BL/6J mice injected with AMH for one month. Thereafter, relative gene expression quantification of Foxo1, Sirt1, p53, Bim, and Bax genes were performed using RT-PCR. RESULTS: In this study, AMH significantly enhanced the expression of Foxo1 and Sirt1 gene compared to the control group. On the contrary, AMH did not modulate the expression of p53, Bim, or Bax genes. AMH was also found to increase serum FSH and LH levels in a dosedependent manner. CONCLUSION: This study demonstrated the capability of AMH to induce Foxo1 and Sirt1 genes. Moreover, our study revealed the role of AMH in elevating LH serum level which is a main contributor to the pathophysiology of polycystic ovary syndrome, opening new avenues for the study of AMH as a main contributor to the stalled follicular atresia and growth associated with the disease.

LCA and economic cradle-to-gate analysis on the reuse of a temporary building.

In recent decades, the significant negative environmental impacts of the construction industry have caused a lot of concern, especially from the large number of temporary buildings required for mega projects. Reusing building components can help reduce pollution and preserve resources, but the economic and environmental effects are not well understood. This study has addressed the economic and environmental effects of reusing temporary building elements using life cycle assessment (LCA). The product system and functional unit in the current study is an office building equipment workshop with an area of 80 m2 and the system boundary is from cradle to gate. Life cycle assessment was accomplished using Simapro software and several life cycle assessment methods such as CML-la Baseline, BEES + , and IPCC was used to verify the results. The findings show that reusing disassembled building parts can reduce environmental damage by 79% and environmental damage costs by 77%. These results are important for construction managers seeking to make sustainable decisions that minimize environmental harm. Future research should expand the system boundary to include the entire building life cycle and apply the methodology to a wider range of building types and climates. Developing design guidelines for disassembly and reuse would also help promote sustainable construction practices. Overall, this study provides a robust framework for assessing the environmental and economic impacts of reusing building components, which is crucial for achieving sustainable development in the construction industry.

Pokemon inhibits Bim transcription to promote the proliferation, anti-anoikis, invasion, histological grade, and dukes stage of colorectal neoplasms.

PURPOSE: This study aims to determine whether Pokemon regulates Bim activity in colorectal carcinoma (CRC) carcinogenesis. METHODS: Clinical tissue samples were analyzed to detect the expression and clinicopathological significance of Pokemon and Bim in CRC. Proliferation, apoptosis, and invasion assays were conducted to identify the regulatory effect of Pokemon on Bim. The combined treatment effects of Pokemon knockdown and diamminedichloroplatinum (DDP) were also examined. RESULTS: Immunohistochemical analysis of 80 samples of colorectal epithelia (CRE), 80 cases of colorectal adenoma (CRA), and 160 of CRC samples revealed protein expression rates of 23.8%, 38.8%, and 70.6% for Pokemon, and 88.8%, 73.8%, and 31.9% for Bim, respectively. A significant negative correlation was observed between Pokemon and Bim expression across the CRE, CRA, and CRC lesion stages. In CRC, higher Pokemon and lower Bim expression correlated with higher histological grades, advanced Dukes stages, and increased cancer invasion. In both LoVo and HCT116 cells, overexpression of Pokemon significantly reduced Bim expression, leading to increased proliferation, resistance to anoikis, and cell invasion. Additionally, Pokemon overexpression significantly decreased DDP-induced Bim expression, reduction of anti-apoptosis and invasion, whereas Pokemon knockdown resulted in the opposite effects. CONCLUSION: These findings suggest that Pokemon inhibits Bim transcription, thereby promoting CRC proliferation, resistance to apoptosis, invasion, and advancing histological grade and Dukes staging. Pokemon knockdown enhances the therapeutic efficacy of DDP in the treatment of CRC.

Configuration of two cysteine residues in a ring within a stapled Bim peptide affects the secondary structure and apoptotic activity.

Many reports have shown that stabilization of secondary structure by stapling functional peptides enhances the intracellular bioactivity. However, no report has discussed the correlation between stabilization and biological activity based on the configuration of amino acid residues used as anchors for stapling. To clarify this, we investigated the helix content and apoptotic efficiency of an apoptosis-inducing peptide, Bim, and four stapled Bim peptides containing stapling-related Cys residues introduced with different configurations within the sequence. The results demonstrated that the configuration of Cys residues in stapled Bim peptides affected the secondary structure and intracellular activity of the peptides, and furthermore, there was a correlation between these latter two variables.

Temporal evolution and thematic shifts in sustainable construction and demolition waste management through building information modeling technologies: A text-mining analysis.

Construction and demolition activities are significant contributors to waste generation worldwide. As population growth accelerates worldwide, the amount of construction and demolition waste (C&DW) will increase proportionally unless proactive measures are implemented. This study analyzes the evolving research landscape on utilizing Building Information Modeling (BIM) technologies to advance sustainable C&DW management practices. A comprehensive text-mining analysis is conducted on 493 scholarly publications covering evolutions from January 2009 to February 2024 using the PRISMA framework. The research objectives are: (i) to identify key themes in domain of BIM technology in C&DW management using VOSviewer, (ii) to map the temporal evolution of research focus using SciMAT, and (iii) to identify emerging thematic trends.Co-occurrence analysis reveals three major research themes: (i) the use of digital twins and prefabrication for waste reduction, (ii) integrating environmental impact assessments, and (iii) data-driven decision-making. Strategic diagrams produced by SciMAT software uncover shifting priorities over the study period, with "reuse and recycling" emerging as motor themes, and "Prefabrication" (CIT = 481), "Decision Making" (CIT = 66), "Material Passport" (CIT = 92), and "Digital Twin" (CIT = 44) emerging as high-centrality and transversal themes. Temporal evolution mapping unveiled progressive integration of BIM tools such as (i) digital twins (TLS = 34, OCC = 9) and (ii) prefabrication (TLS = 40, OCC = 14), presenting opportunities to optimize waste reduction. This study offers a robust overview of the field, aiming to inform a diverse audience, including researchers from various disciplines, policymakers and industry professionals interested in advancing sustainable practices in C&DW management through innovative digital solutions.

Deep learning-based corrosion inspection of long-span bridges with BIM integration.

Infrastructure operation and maintenance is essential for societal safety, particularly in Japan where the aging of infrastructures built during the period of high economic growth is advancing. However, there are issues such as a shortage of engineers and inefficiencies in work, requiring improvements in efficiency and automation for their resolution. Nevertheless, there are still many inefficiencies in the current procedures for bridge inspections. Usually, inspection engineers check for damage on bridges through close visual inspections at the site, then photograph the damaged parts, measure the size by touch, and create a report. A three-dimensional representation, considering the front and back of the structural elements, is needed for identifying damage, necessitating the creation of multi-directional three-dimensional drawings. However, this process is labor-intensive and prone to errors. Furthermore, due to the lack of uniformity in records, it is challenging to refer to past inspection histories. Especially for long bridges, without resolving such issues, the required labor and the number of mistakes could exceed acceptable limits, making proper management difficult. Therefore, in this study, we developed a method for automatically measuring the position and area of corroded parts by capturing images of the lower surface of the stiffening girder using a bridge inspection vehicle and utilizing image diagnosis technology. By integrating these results into a 3D model called BIM (Building Information Modeling), it becomes possible to manage the bridge more efficiently. We verified this method on actual long bridges and confirmed its effectiveness.

Indoor augmented reality (AR) pedestrian navigation for emergency evacuation based on BIM and GIS.

Nowadays with the increase of high-rise buildings, emergency evacuation is an indispensable part of urban environment management. Due to various disaster incidents occurred in indoor environments, research has concentrated on ways to deal with the different difficulties of indoor emergency evacuation. Although global navigation satellite systems (GNSSs) such as global positioning system (GPS) come in handy in outdoor spaces, they are not of much use in enclosed places, where satellite signals cannot penetrate easily. Therefore, other approaches must be considered for pedestrian navigation to cope with the indoor positioning problem. Another problem in such environments is the information of the building indoor space. The majority of the studies has used prepared maps of the building, which limits their methodology to that specific study area. However, in this study we have proposed an end-to-end method that takes advantage of BIM model of the building, thereby applicable to every structure that has an equivalent building information model (BIM). Moreover, we have used a mixture of Wi-Fi fingerprinting and pedestrian dead reckoning (PDR) method with relatively higher accuracy compared to other similar methods for navigating the user to the exit point. For implementing PDR, we used the sensors in smartphones to calculate user steps and direction. In addition, the navigational information was superimposed on the smartphone screen using augmented reality (AR) technology, thus communicating the direction information in a user-friendly manner. Finally, the AR mobile emergency evacuation application developed was assessed with a sample audience. After an experience with the app, they filled out a questionnaire which was designed in the system usability scale test (SUS) format. The evaluation results showed that the app achieved an acceptable suitability for usage.

Surface Defect-Extended BIM Generation Leveraging UAV Images and Deep Learning.

Defect inspection of existing buildings is receiving increasing attention for digitalization transfer in the construction industry. The development of drone technology and artificial intelligence has provided powerful tools for defect inspection of buildings. However, integrating defect inspection information detected from UAV images into semantically rich building information modeling (BIM) is still challenging work due to the low defect detection accuracy and the coordinate difference between UAV images and BIM models. In this paper, a deep learning-based method coupled with transfer learning is used to detect defects accurately; and a texture mapping-based defect parameter extraction method is proposed to achieve the mapping from the image U-V coordinate system to the BIM project coordinate system. The defects are projected onto the surface of the BIM model to enrich a surface defect-extended BIM (SDE-BIM). The proposed method was validated in a defect information modeling experiment involving the No. 36 teaching building of Nantong University. The results demonstrate that the methods are widely applicable to various building inspection tasks.

BIM-enabled built-asset information management conceptual framework: A case of public university buildings in Addis Ababa, Ethiopia.

The integration of BIM with other digital advancements has demonstrably led to an increase of performance in the Architecture, Engineering, Construction and Operation (AECO) industry. This integration not only is showing promising results in boosting the industry's performance, but also the productivity and promotes data-driven decision-making. Despite these benefits, there are limited studies that address the integration of BIM and digital data for managing built-assets in general and in developing countries in particular. To fill this gap, a closer assessment of current built-asset information management practice is necessary. The assessment of the practice examines how digital processes and/or technology can be seamlessly integrated into existing practices. In this regard, this study aims to provide valuable insights into increasing the maturity of built-asset information management by integrating digital data with BIM. The study uses a case-based research design using built-assets (universities in Addis Ababa) as public building representative to capture the prevailing information management practices in Ethiopian public buildings. The findings reveal that traditional paper-based practices still dominate the management of built-assets. This leads to difficulties in terms of data loss, unavailability, inaccuracy, and unreliability, all of which are detrimental to the overall performance. Based on these findings, a conceptual framework is designed to improve the performance of built-assets and help owners, end-users, and managers in defining data and information requirements for BIM-enabled asset information management. The framework delineates processes for structured information requirements definition and validation of various asset data from varying sources. The framework utilizes a BIM-enabled platform as a single source of truth and offers a comprehensive solution to the identified challenges. The findings of this study holds significant promise for improving the existing practice of built-asset information management within the study context.

Innovative BIM technology application in the construction management of highway.

Within the global architecture, engineering, and construction industry, the use of Building Information Modeling (BIM) technology has significantly expanded. However, given the unique characteristics of road infrastructure, the application of BIM technology is still being explored. This article focuses on the Yuanchen Expressway, exploring innovative applications of BIM technology in comprehensive construction management. The project employs advanced technologies, including BIM, Geographic Information Systems (GIS), and the Internet of Things (IoT), to precisely identify critical nodes and breakthroughs. Supported by a detailed BIM model and a multi-level, diversified digital management platform, the project effectively addresses construction challenges in multiple tunnels, bridges, and complex interchanges, achieving intelligent construction innovation throughout the Yuanchen Expressway with BIM technology. By guiding construction through BIM models, utilizing a BIM+GIS-based management cloud platform system, and employing VR safety briefings, the project effectively reduces the difficulty of communication and coordination in project management, shortens the project measurement cycle, improves on-site work efficiency, and ensures comprehensive control and safety management. This article provides an exemplary case for the application of full-line construction management using BIM technology in the highway sector both in China and globally, offering new perspectives and strategies for highway construction management.

Characterization of the information system integrated to the construction project management systems.

The construction industry wields significant influence in the economies of various countries. However, compared to sectors like manufacturing and aeronautics, it has lagged in terms of digitalization of processes and project management advancement. This study aims to explore how the integration of Lean principles, Building Information Modeling (BIM), and Project Lifecycle Management methodologies within an information system can enhance decision-making in construction project management as a complex environment. A comprehensive literature review was conducted to establish a conceptual framework and gather necessary information for designing an information system. The design was based on the viable systems model and the soft systems methodology, from a systemic perspective that encourages the synergistic interaction of these methodologies. The resulting abstract model would facilitate a comprehensive understanding of the interconnectedness of these methodologies, emphasizing collaborative work environments for efficient information management. This approach aims to replace the current isolated application of each of those methodologies and promises improved project management performance.

Practices improvement of building information modeling in the Egyptian construction projects.

Reduced Reinforced Concrete Material Waste (RRCMW) in building projects is regarded as a critical issue that must be managed. The main purpose of the research is to illustrate the importance of BIM in construction. Also, it is found that the main objectives of this paper are to study the improvement of practicing BIM in Egypt and, practicing of BIM in construction industry in Egypt is also measured. Two questionnaires survey are conducted. The first questionnaire is to measure the improvement of using BIM during the last 7 years and it is discovered that there is a massive improvement in using BIM in this period. The second questionnaire is to determine the adopting value of BIM in Egyptian projects in order to meet the study objective. So, based on the questionnaire analysis, it is discovered that about 94% of consultants actually practicing BIM in 3D while about 72% of contractors agree with practicing BIM in 3D. Also it is found that about 86% and 78% of consultants actually practicing BIM in 4D and 5D while only about 43% and 40% of contractors agree with practicing BIM 4D and 5D model respectively. Only about 61% and 58% considered that BIM is important in 6D and 7D respectively because it isn't widely used in Egypt and engineers use BIM up to 5D. As a result, the findings reveal that the number of consultant's site engineer's respondents are more than contractors because the usage of BIM is effective in the field of design and consultancy more than using in site and while BIM isn't extensively utilized in Egypt, engineers should be familiar with it because it will be a useful tool in the future. So, the main purpose of this study is to illustrate practicing of BIM in the Egyptian construction projects and study the improvement of using BIM during the last 7 years in Egypt because BIM is considered as an important technology used to reduce waste in construction projects from design stage to construction and operation stage but still not used in Egypt in a wide range till now, so it is very crucial to study this issue. Also, another main objective of this study is to compare the development done in using BIM during the last 8 years to make sure that using BIM in Egypt is going on and developed.

Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization.

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard's levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study's results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning.

Dual-mRNA Delivery Using Tumor Cell Lysate-Based Multifunctional Nanoparticles as an Efficient Colon Cancer Immunogene Therapy.

Background: Messenger RNA (mRNA)-based immunogene therapy holds significant promise as an emerging tumor therapy approach. However, the delivery efficiency of existing mRNA methods and their effectiveness in stimulating anti-tumor immune responses require further enhancement. Tumor cell lysates containing tumor-specific antigens and biomarkers can trigger a stronger immune response to tumors. In addition, strategies involving multiple gene therapies offer potential optimization paths for tumor gene treatments. Methods: Based on the previously developed ideal mRNA delivery system called DOTAP-mPEG-PCL (DMP), which was formed through the self-assembly of 1.2-dioleoyl-3-trimethylammonium-propane (DOTAP) and methoxypoly (ethylene glycol)-b-poly (ε-caprolactone) (mPEG-PCL), we introduced a fused cell-penetrating peptide (fCPP) into the framework and encapsulated tumor cell lysates to form a novel nanovector, termed CLSV system (CLS: CT26 tumor cell lysate, V: nanovector). This system served a dual purpose of facilitating the delivery of two mRNAs and enhancing tumor immunogene therapy through tumor cell lysates. Results: The synthesized CLSV system had an average size of 241.17 nm and a potential of 39.53 mV. The CLSV system could not only encapsulate tumor cell lysates, but also deliver two mRNAs to tumor cells simultaneously, with a transfection efficiency of up to 60%. The CLSV system effectively activated the immune system such as dendritic cells to mature and activate, leading to an anti-tumor immune response. By loading Bim-encoded mRNA and IL-23A-encoded mRNA, CLSV/Bim and CLSV/IL-23A complexes were formed, respectively, to further induce apoptosis and anti-tumor immunity. The prepared CLSV/dual-mRNA complex showed significant anti-cancer effects in multiple CT26 mouse models. Conclusion: Our results suggest that the prepared CLSV system is an ideal delivery system for dual-mRNA immunogene therapy.

TRIM33 plays a critical role in regulating dendritic cell differentiation and homeostasis by modulating Irf8 and Bcl2l11 transcription.

The development of distinct dendritic cell (DC) subsets, namely, plasmacytoid DCs (pDCs) and conventional DC subsets (cDC1s and cDC2s), is controlled by specific transcription factors. IRF8 is essential for the fate specification of cDC1s. However, how the expression of Irf8 is regulated is not fully understood. In this study, we identified TRIM33 as a critical regulator of DC differentiation and maintenance. TRIM33 deletion in Trim33fl/fl Cre-ERT2 mice significantly impaired DC differentiation from hematopoietic progenitors at different developmental stages. TRIM33 deficiency downregulated the expression of multiple genes associated with DC differentiation in these progenitors. TRIM33 promoted the transcription of Irf8 to facilitate the differentiation of cDC1s by maintaining adequate CDK9 and Ser2 phosphorylated RNA polymerase II (S2 Pol II) levels at Irf8 gene sites. Moreover, TRIM33 prevented the apoptosis of DCs and progenitors by directly suppressing the PU.1-mediated transcription of Bcl2l11, thereby maintaining DC homeostasis. Taken together, our findings identified TRIM33 as a novel and crucial regulator of DC differentiation and maintenance through the modulation of Irf8 and Bcl2l11 expression. The finding that TRIM33 functions as a critical regulator of both DC differentiation and survival provides potential benefits for devising DC-based immune interventions and therapies.

Internet of things-based study on online monitoring system of building equipment energy saving optimization control using building information modeling.

Smart building equipment monitoring is a well-established field focused on enhancing contemporary building comfort. The proliferation of Internet connectivity, facilitated by the internet of things (IoT), has transformed buildings from static structures into interactive environments. IoT has witnessed substantial growth across various aspects of daily life, from monitoring environmental conditions to managing building systems and storing data in the cloud. One critical application is the intelligent monitoring and control of building equipment, such as air conditioners, to optimize energy efficiency-a matter of increasing concern for building owners, design experts, and system integrators. Achieving comprehensive energy savings demands a meticulous approach to energy-efficient design and control. This paper's primary objective is to explore and analyze IoT-based energy-saving optimization techniques for intelligent building equipment, integrating building information modeling (BIM) technology. It particularly delves into the energy conservation control algorithm for air-conditioning systems. The research presents a challenge rooted in energy-saving optimization, established upon specific objective functions, followed by a detailed explanation of the energy-saving control algorithm. To validate their approach, the paper outlines a comprehensive experimental design. Over three sessions in August, they conducted control experiments in two distinct areas. Area 1 implemented the energy-saving control methodology discussed in the paper, utilizing virtual parameter enhancement mechanisms, while Area 2 adhered to conventional control methods. The results were enlightening. Area 1 demonstrated superior energy efficiency, consuming 735 kWh compared to Area 2's 819 kWh, signifying an impressive 11.43% reduction in energy consumption thanks to the optimized control strategy. This research underscores the practicality and significance of implementing IoT-based energy-saving strategies, with a focus on smart thermostats, HVAC controllers, and daylight sensors, in intelligent building equipment management to achieve substantial energy conservation gains.