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Fine particulate matter (PM2.5) is the primary air pollutant that is able to induce airway injury. Compelling evidence has shown the involvement of IL‐17A in lung injury, while its contribution to PM2.5‐induced lung injury remains largely unknown. Here, we probed into the possible role of IL‐17A in mouse models of PM2.5‐induced lung injury. Mice were instilled with PM2.5 to construct a lung injury model. Flow cytometry was carried out to isolate γδT and Th17 cells. ELISA was adopted to detect the expression of inflammatory factors in the supernatant of lavage fluid. Primary bronchial epithelial cells (mBECs) were extracted, and the expression of TGF signalling pathway‐, autophagy‐ and PI3K/Akt/mTOR signalling pathway‐related proteins in mBECs was detected by immunofluorescence assay and Western blot analysis. The mitochondrial function was also evaluated. PM2.5 aggravated the inflammatory response through enhancing the secretion of IL‐17A by γδT/Th17 cells. Meanwhile, PM2.5 activated the TGF signalling pathway and induced EMT progression in bronchial epithelial cells, thereby contributing to pulmonary fibrosis. Besides, PM2.5 suppressed autophagy of bronchial epithelial cells by up‐regulating IL‐17A, which in turn activated the PI3K/Akt/mTOR signalling pathway. Furthermore, IL‐17A impaired the energy metabolism of airway epithelial cells in the PM2.5‐induced models. This study suggested that PM2.5 could inhibit autophagy of bronchial epithelial cells and promote pulmonary inflammation and fibrosis by inducing the secretion of IL‐17A in γδT and Th17 cells and regulating the PI3K/Akt/mTOR signalling pathway.

A durable and easy-to-operate treatment, modified epoxy composite coating (MECC), was proposed in this study as a potential alternative to traditional epoxy resin protectants to enhance the protection of concrete structures. This new material consists of epoxy resin as the base material, dimethyl carbonate as the solvent, and modified amines and polyaniline as a composite curing agent that reacts with epoxy resin to form a film over the surface of concrete, thus protecting concrete structures from surface cracking, peeling, and spalling when exposed to chloride. Salt frost resistance tests indicated that MECC specimens had lower water absorption and much higher salt frost resistance. Compared with non-coating (NS) specimens, after 200 freeze–thaw cycles, the relative dynamic elastic modulus (RDEM) was 21.62% higher, and the mass loss was merely 19.14% of that of the NS specimens. Better performance was achieved as compared with ordinary epoxy resin coating (EC) and silicate coating (SC) too. After 120 days of erosion in 10.0% NaCl, the coating could effectively prevent environmental liquids and chloride from intruding through the cracks. The reason behind the increased salt frost durability is that treatment with MECC improved the internal structure of concrete and made its surface dense enough to prevent the intrusion of environmental liquids and chloride. Under repeated freezing and thawing, the degree of chloride-induced damage and the icing pressure inside the concrete were greatly reduced. This relieved the frost damage inside the concrete and elongated the service life of the concrete.

Hepatocellular carcinoma (HCC) is one of the most prevalent and life-threatening malignancies worldwide. There are few diagnostic and prognostic biomarkers and druggable targets for HCC. Aldehyde dehydrogenase 1 (ALDH1) is a marker of stem cells in a variety of cancers, but the mRNA levels and prognostic value of ALDH1 isoforms in HCC patients remain unknown. In the present study, gene ontology annotation of the ALDH1 family was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID), and the gene pathway analsis was performed using GeneMANIA software. The initial prognostic value of ALDH1 expression in 360 HCC patients was assessed using the OncoLnc database. The expression levels of ALDH1 isoforms in normal liver tissues and clinical specimens of cancer vs. normal control datasets were determined using the GTEx and Oncomine databases, respectively. We then analyzed the prognostic value of ALDH1 expression in 212 hepatitis B virus (HBV)-related HCC patients using the GEO database. We found that the ALDH1 isoform showed high aldehyde dehydrogenase activity. The ALDH1A1, ALDH1B1, and ALDH1L1 genes encoded for the ALDH1 enzyme. High ALDH1B1 expression had protective qualities in HCC patients. Moreover, HBV-related HCC patients who showed high ALDH1L1 gene expression had a better clinical outcomes. In addition, high ALDH1A1 expression was associated with a 57-month recurrence-free survival in HBV-related HCC patients. High ALDH1B1 expression was protective for HCCs with multiple nodules and high serum alpha-fetoprotein (AFP) level. Furthermore, high serum AFP levels contributed to lower ALDH1L1. ALDH1A1, ALDH1B1, and ALDH1L1, all of which were considered promising diagnostic and prognostic markers as well as potential drug targets.

With the huge amount of uncharacterized protein sequences generated in the post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful for both basic research and drug development in a timely manner. Although many efforts have been made in this regard, most of them were based on either sequence similarity or protein-protein interaction (PPI) information. However, the former often fails to work if a query protein has no or very little sequence similarity to any function-known proteins, while the latter had similar problem if the relevant PPI information is not available. In view of this, a new approach is proposed by hybridizing the PPI information and the biochemical/physicochemical features of protein sequences. The overall first-order success rates by the new predictor for the functions of mouse proteins on training set and test set were 69.1% and 70.2%, respectively, and the success rate covered by the results of the top-4 order from a total of 24 orders was 65.2%. The results indicate that the new approach is quite promising that may open a new avenue or direction for addressing the difficult and complicated problem.

Landslides are common geological hazards that cause significant losses. Anti-slide piles are commonly used in landslide engineering, and model testing is one of the means to study pile-supported structures. However, model tests face several challenges, including difficulty in controlling the experimental process, challenges in repeated tests, and difficulty in monitoring soil deformation around piles. To address these issues, this study presents a model test method using particle image velocimetry (PIV), transparent soil, and 3D printing technology. Using this method, a series of model tests were conducted, including single-row and double-row anti-slide piles. The experimental results indicate that, compared with single-row piles, double-row piles exhibit better supporting effects. In the pile‒soil interaction, the displacement of the extrusion of soil between piles was controlled under the combined action of the front and back rows of piles. The inclination angle of a single-row pile after the test was 8°, whereas that of a double-row pile was reduced by 62.5%. With respect to the displacement of the soil behind the piles, the phenomenon of a “displacement triangle” behind the piles was observed. An analysis of the change process in this area revealed that the relative displacement caused by pile‒soil interactions is mainly distributed in the surface layer of the soil. The experiments demonstrate that this system is suitable for pile-supported structure model tests.

Materials informatics employs techniques, tools, and theories drawn from the emerging fields of data science, internet, computer science and engineering, and digital technologies to the materials science and engineering to accelerate materials, products and manufacturing innovations. Manufacturing is transforming into shorter design cycles, mass customization, on-demand production, and sustainable products. Additive manufacturing or 3D printing is a popular example of such a trend. However, the success of this manufacturing transformation is critically dependent on the availability of suitable materials and of data on invertible processing–structure–property–performance life cycle linkages of materials. Experience suggests that the material development cycle, i.e. the time to develop and deploy new material, generally exceeds the product design and development cycle. Hence, there is a need to accelerate materials innovation in order to keep up with product and manufacturing innovations. This is a major challenge considering the hundreds of thousands of materials and processes, and the huge amount of data on microstructure, composition, properties, and functional, environmental, and economic performance of materials. Moreover, the data sharing culture among the materials community is sparse. Materials informatics is key to the necessary transformation in product design and manufacturing. Through the association of material and information sciences, the emerging field of materials informatics proposes to computationally mine and analyze large ensembles of experimental and modeling datasets efficiently and cost effectively and to deliver core materials knowledge in user-friendly ways to the designers of materials and products, and to the manufacturers. This paper reviews the various developments in materials informatics and how it facilitates materials innovation by way of specific examples.

This study investigates geochemical characteristics and resource potential of water-soluble lithium in lithium-rich salt lake sediments from the Qaidam Basin, focusing on the East Taijinar Salt Lake and Bieletan area. Through X-ray diffraction (XRD), elemental analysis (ICP-OES), and laser particle size analysis (LPSA), sediment samples were analyzed to assess mineral composition, lithium distribution and its occurrence forms. Results reveal distinct vertical zonation: lithium, boron, and potassium peak in clay-rich layers, contrasting with lower concentrations in halite-dominated layers. Regional patterns indicate that lithium enrichment in sediments aligns closely with brine, centered around Yiliping and East/West Taijinar Salt Lakes. Water-soluble lithium primarily originates from weak adsorption on clay minerals, with secondary contributions from intercrystalline brine, halite fluid inclusions, and gypsum dissolution. The clay layers exhibit lithium concentrations exceeding industrial grade and favorable Mg/Li ratios, comparable to brine mining standards. Co-enrichment of boron (415 ppm) and potassium highlights multi-resource potential. These findings highlight sediments as lithium reservoirs, which can serve as a sustainable potential supplement during brine depletion and enhance resource resilience in the Qaidam Basin. This study provides critical insights into lithium migration, enrichment mechanisms, and strategic resource management in evaporitic systems.

Objective. Antimelanoma differentiation-associated protein 5 (anti-MDA5) autoantibody has been reported in dermatomyositis (DM) to be associated with rapidly progressive interstitial lung disease (RP-ILD). Our study is aimed at determining the clinical characteristics and prognostic factors underpinning anti-MDA5-associated RP-ILD. Methods. Patients with anti-MDA5-associated DM (aMDA5-DM) were identified at the Peking University People’s Hospital. The presence of anti-MDA5 antibody was determined by immunoblotting. Kaplan-Meier, chi-square test, univariate, and multivariate data analyses were used. Results. Out of 213 patients with DM and clinically amyopathic dermatomyositis (CADM), 20.7% (44/213) of patients were identified as aMDA5-DM. Amongst the aMDA5-DM patients, 63.6% (28/44) were identified as having anti-MDA5-associated RP-ILD. During the follow-up, 32.1% (9/28) of patients with anti-MDA5-associated RP-ILD died of respiratory failure. We identified older age and periungual erythema as two independent risk factors for RP-ILD mortality. Age≥57 years at disease onset was significantly associated with poor survival (P=0.02) in patients with anti-MDA5-associated RP-ILD, while patients with periungual erythema had a better survival rate than those without periungual erythema (P<0.05). Conclusions. Anti-MDA5-associated RP-ILD is significantly associated with poor survival rates in DM/CADM patients. More effective intervention should be administered to anti-MDA5-associated RP-ILD patients, especially to senior patients and those without periungual erythema.

Background Recently, chimeric antigen receptor-modified (CAR) T cell therapy for hematological malignancies has shown clinical efficacy. Hundreds of clinical trials have been registered and lots of studies have shown hematologic toxic effects were very common. The main purpose of this review is to systematically analyze hematologic toxicity in hematologic malignancies treated with CAR-T cell therapy. Methods We searched databases including PubMed, Web of Science, Embase and Cochrane up to January 2021. For safety analysis of overall hematologic toxicity, the rate of neutrophil, thrombocytopenia and anemia were calculated. Subgroup analysis was performed for age, pathological type, target antigen, co-stimulatory molecule, history of hematopoietic stem cell transplantation (HSCT) and prior therapy lines. The incidence rate of aspartate transferase (AST) increased, alanine transaminase (ALT) increased, serum creatine increased, APTT prolonged and fibrinogen decreased were also calculated. Results Overall, 52 studies involving 2004 patients were included in this meta-analysis. The incidence of any grade neutropenia, thrombocytopenia and anemia was 80% (95% CI: 68–89%), 61% (95% CI: 49–73%), and 68% (95%CI: 54–80%) respectively. The incidences of grade ≥ 3 neutropenia, thrombocytopenia and anemia were 60% (95% CI: 49–70%), 33% (95% CI: 27–40%), and 32% (95%CI: 25–40%) respectively. According to subgroup analysis and the corresponding Z test, hematological toxicity was more frequent in younger patients, in patients with ≥4 median lines of prior therapy and in anti-CD19 cases. The subgroup analysis of CD19 CAR-T cell constructs showed that 41BB resulted in less hematological toxicity than CD28. Conclusion CAR-T cell therapy has dramatical efficacy in hematological malignancies, but the relevant adverse effects remain its obstacle. The most common ≥3 grade side effect is hematological toxicity, and some cases die from infections or severe hemorrhage in early period. In long-term follow-up, hematological toxicity is less life-threatening generally and most suffered patients recover to adequate levels after 3 months. To prevent life-threatening infections or bleeding events, clinicians should pay attention to intervention of hematological toxicity in the early process of CAR-T cell therapy.

Colorectal cancer (CRC) is the third most common type of cancer. In recent decades, genomic analysis has played an increasingly important role in understanding the molecular mechanisms of CRC. However, its pathogenesis has not been fully uncovered. Identification of genes related to CRC as complete as possible is an important way to investigate its pathogenesis. Therefore, we proposed a new computational method for the identification of novel CRC-associated genes. The proposed method is based on existing proven CRC-associated genes, human protein–protein interaction networks, and random walk with restart algorithm. The utility of the method is indicated by comparing it to the methods based on Guilt-by-association or shortest path algorithm. Using the proposed method, we successfully identified 298 novel CRC-associated genes. Previous studies have validated the involvement of the majority of these 298 novel genes in CRC-associated biological processes, thus suggesting the efficacy and accuracy of our method.