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The fibroblast growth factor receptor (FGFR) is a crucial receptor tyrosine kinase involved in essential biological processes, including growth, development, and tissue repair. However, FGFR gene mutations, including amplification, fusion, and mutation, can disrupt epigenetics, transcriptional regulation, and tumor microenvironment interactions, leading to cancer development. Targeting these kinase mutations with small molecule drugs or antibodies has shown clinical benefits. For example, erdafitinib is approved for treating locally advanced or metastatic urothelial cancer patients with FGFR2/FGFR3 mutations, and pemigatinib is approved for treating cholangiocarcinoma with FGFR2 fusion/rearrangement. Effective screening of FGFR variant patients is crucial for the clinical application of FGFR inhibitors. Various detection methods, such as polymerase chain reaction, next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry, are available, and their selection should be based on diagnostic and treatment decision-making needs. Our developed expert consensus aims to standardize the diagnosis and treatment process for FGFR gene mutations and facilitate the practical application of FGFR inhibitors in clinical practice.

Abstract Background The most widely used anti-malarial drug artemisinin (ART) is metabolized extensively, but the therapeutic capacity of its major metabolite remains unknown. Whether the major metabolite of ART (ART-M) contributes to its antiplasmodial potency was investigated in this study. Methods The metabolite identification and enzyme phenotyping of ART were performed using human liver microsomes (HLMs). The stereostructure of the major metabolite ART-M was elucidated by spectroscopic and X-ray crystallographic analysis. The anti-malarial activity of ART-M against two reference Plasmodium strains (Pf3D7 and PfDd2) was evaluated. The pharmacokinetic profiles of ART and its metabolite ART-M were investigated in healthy Chinese subjects after a recommended two-day oral dose of ART plus piperaquine. Pharmacodynamic parameters based on minimum inhibitory concentration (MIC50) and free plasma concentration were employed to evaluate the therapeutic potency of ART-M, including fAUC0-t/MIC50, fCmax/MIC50 and T > MIC50. Results A major metabolite 10β-hydroxyartemisinin (ART-M) was found for ART in human, and CYP3A4/3A5 was the major enzymes responsible for ART 10β-hydroxylation. Compared with ART (MIC50, 10.1 nM against Pf3D7), weaker antiplasmodial activity was found for ART-M (MIC50, 61.4 nM against Pf3D7). However, a 3.5-fold higher maximal free plasma concentration was achieved for ART-M (fCmax, 180.0 nM vs. 51.8 nM for ART). ART-M displayed comparable antiplasmodial potency to ART, in terms of fAUC0-t/MIC50 (12.5 h), fCmax/MIC50 (2.8) and T > MIC50 (5 h). Conclusions The major metabolite 10β-hydroxyartemisinin contributes to the antiplasmodial efficacy of ART, which should be considered when evaluation of ART dosing regimens and/or clinical outcomes.

In this study, a series of Ti50–ZrVNbCr alloys were designed under with the constant atomic radius mismatch. It was suggested that valence electron concentration (VEC) and lattice constant, which evolve oppositely in the series of the Ti50–ZrVNbCr alloys, jointly influence the mechanical properties. Based on modeling, the evolution of ductility and yield strength of the designed alloys was predicted. Ductility was predicted to be superior in the VEC range from 4.22 to 4.25, with the lattice constant correspondently ranging from 3.340 Å to 3.334 Å. The optimization of strength-ductility synergy was discussed in terms of coordinately adjusting VEC and lattice constant. The experimental results were quite consistent with the prediction results, showing that the alloy with the VEC value of 4.25 and the lattice constant of 3.334 Å, which consisted of 50 at.%Ti, 28.1 at.%Zr, 9.4 at.%V, 9.4 at.%Nb, and 3.1 at.%Cr, possessed the best ductility and superior strength-ductility synergy.

The adsorption of toxic and harmful gases through porous materials is an effective means of air pollution control. A multi-level porous carbon material with ultra-high-specific surface area was made based on rice husk biomass to improve the air pollution controlling efficiency and reduce its cost. The rice husk substrate was pretreated using T.viride spore suspension during the preparation of this material. This changes the proportion of various components in the matrix, thereby achieving an increase in the multi-level porous carbon material’s specific surface area. Its performance was analyzed through various means in the study. The results confirmed that when the activation treatment time was 60 minutes, the porous carbon material’s specific surface area was the highest, reaching 3714 m2/g. After 30 days of treatment with T.viride spore suspension, the cellulose content in rice husks decreased by about 40 g/kg. Compared to untreated porous carbon materials, after 20 days of treatment, the micropores and mesopores of these materials significantly increased. The research has successfully increased the multi-level porous carbon material’s specific surface area and achieved rapid absorption of atmospheric volatile organic compounds. The multi-level porous carbon material can enhance the air pollution controlling efficiency and reduce its cost.

Alloying is one of the effective approaches to boost the discharge property of magnesium (Mg) anodes for primary Mg-air batteries and recently micro-alloying is highly recommended at the aim of developing advanced primary Mg system. In this study, micro-alloyed extruded Mg0.5Zn0.2Ge (in wt.%) alloy is evaluated as an anode candidate for primary Mg-air batteries in both half-cell and Mg-air full cell configurations, in comparison with commercially accepted Mg anodes, typified by as-cast HP Mg and extruded AZ31 alloy. The corrosion behavior at open circuit potential (OCP) condition of the three materials is also compared through electrochemical tests. Mg0.5Zn0.2Ge alloy displays the most negative OCP value and the highest corrosion resistance at OCP. During discharge, Mg0.5Zn0.2Ge anode exhibits low wasteful-discharge rate and homogeneous dissolution that gives rise to the absence of “chunk effect”. Consequently, the anodic efficiency and specific capacity of Mg0.5Zn0.2Ge anode are superior to those of HP Mg and AZ31 anodes, e.g. 57.3% and 1257 mAh g−1 at 1 mA cm−2. Additionally, Mg-air battery based on Mg0.5Zn0.2Ge anode offers higher cell voltage and specific energy than those assembled with HP Mg and AZ31 anodes, which can be further optimized by addition of electrolyte additives. Therefore, micro-alloyed Mg0.5Zn0.2Ge alloy can serve as a promising candidate for anode material of primary Mg-air batteries.

The degradation behavior of biodegradable Mg alloys has become a research hotspot in the fields about biodegradable metallic materials. While the most of the related publications mainly focused on the degradation rate of Mg-based materials, but rare to care about the changes of their mechanical properties during the immersion period, which can significantly affect their service performance. The link between residual strength and Mg degradation is not appreciated enough. In this work, a series media were constructed based on Hanks’ solution, the effects of inorganic ions on the degradation rate and mechanical integrity of Mg-Zn-Y-Nd alloy were investigated. The results indicated that the degradation behavior of Mg alloy was mainly controlled by degradation products and there is no direct correspondence between the degradation rate change and mechanical integrity of Mg alloy. The relevant findings are beneficial for selecting the monitoring index in Mg corrosion tests and evaluating the service reliability of Mg alloys for biomedical applications.

Hypersonic vehicles play a crucial role in various applications and are complex systems that integrate aviation, electronics, computer control, electrical information, and sensing technologies. Owing to this complexity and their harsh working environment, hypersonic vehicles frequently face various faults or failures. Furthermore, these vehicles face a more challenging flight environment and complex dynamic characteristics than traditional aircraft. Building an accurate system model for hypersonic vehicles is considerably difficult. In recent years, extensive research has been conducted on fault diagnosis using deep learning and large datasets. However, the substantial success of deep learning techniques relies on the assumption that sufficient labeled training samples are available. In practical scenarios, problems such as data imbalance, insufficient labeled data, or even the absence of data are frequently encountered. This study investigates zero-shot fault identification for ultra-hypersonic aircraft. In particular, this study focuses on the diagnosis of faults in the flight control system actuators. This study aims to employ deep learning techniques to distinguish whether a specific fault is a loss-of-effectiveness (LoE) or locked-in-place (LiP) fault. In the context of this study, “zero-shot” indicates that no sample data related to the target faults has been included or introduced during the construction of the deep learning model for fault diagnosis. Therefore, the model must rely on alternative methods and features to infer and accurately identify unknown faults for effective fault recognition. To address this problem, artificial descriptions of faults are employed to characterize unknown faults. In particular, a relational network is used to compare the definitions of known fault samples with the descriptions of unknown faults. Furthermore, a deep neural network structure is built by combining convolutional neural networks with long short-term memory networks for feature extraction. Finally, zero-shot fault identification experiments are conducted on a high-hypersonic aircraft with a Winged-cone configuration. Fourteen types of faults, including seven types of LoE faults and seven types of LiP faults, are considered. The highest accuracies range from 81.44% to 89.92% over different types of faults. This demonstrates that it is possible to diagnose and classify different types of faults without training samples, realizing the initial objectives of the fault description-based method. This diagnosis is based on human-defined fault descriptions that allow for fault classification. The proposed zero-shot fault identification method aircraft can mitigate risks, enhance operational reliability, and improve safety in high-hypersonic aircraft operations.

In a genome-wide association study, we identified a rice UDP-glycosyltransferase gene, OsUGT706D2, whose transcription was activated in response to cold and submergence stress and to exogenous abscisic acid (ABA). OsUGT706D2 positively regulated the biosynthesis of tricin-4′-O-(syringyl alcohol) ether-7-O-glucoside at both the transcriptional and metabolic levels. OsUGT706D2 mediated cold and submergence tolerance by modulating the expression of stress-responsive genes as well as the abscisic acid (ABA) signaling pathway. Gain of function of OsUGT706D2 increased cold and submergence tolerance and loss of function of OsUGT706D2 reduced cold tolerance. ABA positively regulated OsUGT706D2-mediated cold tolerance but reduced submergence tolerance. These findings suggest the potential use of OsUGT706D2 for improving abiotic stress tolerance in rice.

Abstract Background The role of mast cells in malignancies remains unclear, and there is no clear correlation between mast cells and tumor microvessels, tumor growth, or lung adenocarcinoma (LUAD) prognosis. This study aims to explore the association between mast cell density (MCD) and intratumoral microvessel density (MVD), clinicopathological parameters, and prognosis in LUAD, by evaluating mast cell infiltration characteristics and their prognostic significance. Methods This retrospective investigation involved 238 patients with LUAD undergoing complete resection. Tumor and normal lung tissue sections outside the tumor were immunohistochemically stained for MCD in the intratumoral and outside regions, respectively. CD34 polyclonal antibody was used to measure intratumoral MVD. Results Intratumoral regions of LUAD had a higher MCD (P

Abstract Background The incidence of checkpoint inhibitor-associated pneumonitis (CIP) in advanced non-small cell lung cancer (NSCLC) has been substantiated through large-scale clinical trials or real-world studies. However, reports on CIP incidence within the context of neoadjuvant immunotherapy for resectable NSCLC remain scarce. This study endeavors to investigate the incidence, risk factors, and outcomes of CIP in patients with resectable NSCLC receiving neoadjuvant immunochemotherapy. Methods A retrospective, case-control study was conducted on patients diagnosed with NSCLC stages IIA–IIIB who received neoadjuvant immunochemotherapy between January 2018 and September 2022. Patients were stratified into two groups based on the presence or absence of CIP, facilitating a comparative analysis of clinical characteristics, treatment modalities, physiological indicators, and prognostic outcomes . Results The study cohort comprised 245 patients, with 11.4% (28/245) experiencing CIP. The median period of CIP onset was 70 (range, 40–221) days. The incidence of severe CIP (grade 3–4) was 3.7% (9/245). Patients with CIP showed a higher all-cause mortality rate of 21.4% (6/28) compared to that of patients without CIP. Those who developed CIP exhibited elevated body mass index (BMI) values (p = 0.028) and increased fibrinogen (FIB) levels (p

Abstract Plant metabolites including anthocyanins play an important role in the growth of plants, as well as in regulating biotic and abiotic stress responses to the environment. Here we report comprehensive profiling of 3315 metabolites and a further metabolic-based genome-wide association study (mGWAS) based on 292,485 SNPs obtained from 311 rice accessions, including 160 wild and 151 cultivars. We identified hundreds of common variants affecting a large number of secondary metabolites with large effects at high throughput. Finally, we identified a novel gene namely OsLSC6 (Oryza sativa leaf sheath color 6), which encoded a UDP 3-O-glucosyltransferase and involved in the anthocyanin biosynthesis of Cyanidin-3-Galc (sd1825) responsible for leaf sheath color, and resulted in significant different accumulation of sd1825 between wild (purple) and cultivars (green). The results of knockout transgenic experiments showed that OsLSC6 regulated the biosynthesis and accumulation of sd1825, controlled the purple leaf sheath. Our further research revealed that OsLSC6 also confers resistance to cold stress during the seedling stage in rice. And we identified that a SNP in OsLSC6 was responsible for the leaf sheath color and chilling tolerance, supporting the importance of OsLSC6 in plant adaption. Our study could not only demonstrate that OsLSC6 is a vital regulator during anthocyanin biosynthesis and abiotic stress responses, but also provide a powerful complementary tool based on metabolites-to-genes analysis by mGWAS for functional gene identification andpromising candidate in future rice breeding and improvement.

Acidizing is an effective and routine measure for oil and gas extraction, but acid liquor can cause severe corrosion to oil and gas pipeline columns, especially in high-temperature reservoirs. The high-temperature wells are often acidified by a combination of organic acids and hydrochloric acid to reduce the corrosion of oil and gas pipeline columns caused by acid. In order to effectively reduce the corrosion of oil and gas pipeline columns caused by acidizing, the high-temperature(200 ℃) corrosion behavior of 22Cr steel in various acidic solutions was studied through electrochemical experiments and weight loss experiments. The surface corrosion morphology of steel samples in different systems was observed using a scanning electron microscope(SEM). An X-ray energy dispersive spectrometer(EDS) was used to analyzed the elemental composition and distribution on the surfaces of samples before and after corrosion. X-ray diffraction(XRD) was utilized to determine the composition of corrosion products on the surface of samples. Results showed that 22Cr steel had good corrosion resistance in different concentrations of acetic acid solution, but the increase in Cl- concentration in the acetic acid solution accelerated the corrosion of 22Cr steel. 22Cr steel was severely corroded in low-concentration HCl solution. The composite acid liquor system, composed of low concentration HCl and low concentration acetic acid, was found to have a synergistic effect on the corrosion of 22Cr steel and accelerated the corrosion of 22Cr steel. At 200 ℃, the composite inhibitor, composed of corrosion inhibitor QASE and corrosion inhibitor synergist Sb2O3, was effectively able to inhibit the corrosion of 22Cr steel in the hydrochloric acid and acetic acid composite acid solution.

This paper briefly summarizes the importance, current situation and existing problems of earthquake science popularization in primary and secondary schools, and focuses on the development path of earthquake science popularization based on STEAM education concept. On the basis of clarifying the main purpose, service target group of earthquake science popularization education, and effective popular science content and form, this paper applies the concept of STEAM education to propose the effective path of earthquake science popularization in primary and secondary schools. Taking the junior high school section as an example to make a specific case analysis, this paper suggests to build an earthquake science popularization ecosystem from the perspective of STEAM education. STEAM education is an interdisciplinary education concept that integrates science, technology, engineering, arts and mathematics, emphasizing the integration of disciplines. It is a new form of learning in which taking projects as the main line, teachers as the lead, and students as the main body. This study argues that STEAM education needs to be integrated into the earthquake science popularization, and a high-quality science education system should be constructed, covering both on- and off-campus educational activities and active learning ability, so as to create an ecosystem suitable for the development of science popularization education.

Background: Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors are targeted therapies designed to selectively block CDK4/6, crucial regulators of the cell cycle. These inhibitors play a pivotal role in restoring cell cycle control, particularly in breast cancer cases marked by abnormal CDK regulation, ultimately inhibiting uncontrolled cell division and tumor growth. Objectives: This analysis aimed to comprehensively examine adverse effects in CDK4/6 inhibitors using the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. Design: Disproportionality analysis was conducted to analyze the adverse event (AE) reports related to CDK4/6 inhibitor submitted to the FAERS database. Methods: We collected AE reports regarding palbociclib, ribociclib, abemaciclib, trilaciclib, and dalpiciclib submitted to the FAERS from 2015Q1 to 2023Q1. We used the system organ class and the Standardized MedDRA Query to perform a comprehensive search for AEs at the preferred term (PT) level, using case reports as our data source. After removing duplicate reports, we performed disproportionality analysis and sensitivity analysis to identify safety signals. Results: A total of 85,635 reports encompassing 280,211 AEs were extracted for analysis. Among 3681 scrutinized PTs, approximately 484 were detected as statistically significant signals associated with CDK4/6 inhibitors. It was noteworthy that palbociclib and ribociclib had comparable safety profiles, whereas abemaciclib exhibited distinctive safety patterns. Notably, our analysis found novel safety signals linked to CDK4/6 inhibitors, including nail-related disorders such as onychoclasis, nail disorder, and nail discoloration, and psychiatric concerns, including eating disorders and emotional disorder. Conclusion: Overall, the present study identified several new safety signals of CDK4/6 inhibitors, as well as differences among various drugs within the CDK4/6 category, through the use of the FDA FAERS, which deserve more careful monitoring in the clinic.

Abstract Programmed death‐ligand 1 (PD‐L1) is overexpressed in multiple cancers and critical for their immune escape. It has previously shown that the nuclear coactivator SRC‐1 promoted colorectal cancer (CRC) progression by enhancing CRC cell viability, yet its role in CRC immune escape is unclear. Here, we demonstrate that SRC‐1 is positively correlated with PD‐L1 in human CRC specimens. SRC‐1 deficiency significantly inhibits PD‐L1 expression in CRC cells and retards murine CRC growth in subcutaneous grafts by enhancing CRC immune escape via increasing tumor infiltration of CD8+ T cells. Genetic ablation of SRC‐1 in mice also decreases PD‐L1 expression in AOM/DSS‐induced murine CRC. These results suggest that tumor‐derived SRC‐1 promotes CRC immune escape by enhancing PD‐L1 expression. Mechanistically, SRC‐1 activated JAK‐STAT signaling by inhibiting SOCS1 expression and coactivated STAT3 and IRF1 to enhance PD‐L1 transcription as well as stabilized PD‐L1 protein by inhibiting proteasome‐dependent degradation mediated by speckle type POZ protein (SPOP). Pharmacological inhibition of SRC‐1 improved the antitumor effect of PD‐L1 antibody in both subcutaneous graft and AOM/DSS‐induced murine CRC models. Taken together, these findings highlight a crucial role of SRC‐1 in regulating PD‐L1 expression and targeting SRC‐1 in combination with PD‐L1 antibody immunotherapy may be an attractive strategy for CRC treatment.

Background: miRNA has been implicated in regulating cholesterol homeostasis, a critical factor in gallstone formation. Here, we focused on elucidating the role of miR-146a in this pathological process. Methods: C57BL/6 mice were fed with lithogenic diet (LD) and injected with miR-146 antagomir (anta-146) via the tail vein for various weeks. The gallbladders and liver tissues were collected for cholesterol crystal imaging, gallstone mass quantification, and molecular analysis. Levels of cholesterol, bile salt, phospholipids, and metabolic parameters in serum and bile were assessed by ELISA. A 3′ UTR reporter gene assay was used to verify the direct target genes for miR-146. The relative expression of metabolism genes was analyzed by quantitative real-time PCR and immunoblotting. Results: miR-146a-5p expression was reduced in mice and clinical samples with gallstones. Anta-146 treatment effectively prevented LD-induced gallstone formation in mice without hepatic and cholecystic damage. The mice treated with anta-146 exhibited beneficial alterations in bile cholesterol and bile acids and lipid levels in the blood. A key biliary cholesterol transporter-Megalin was identified as a direct target of miR-146. Anta-146 administration upregulated megalin expression, thereby ameliorating impaired gallbladder cholesterol absorption associated with the LXR-megalin/cubilin pathway. Conclusion: The data demonstrates that miR-146 modulates gallbladder cholesterol absorption by targeting megalin, and prevents the pathogenesis of cholesterol gallstones.

Deep Q-networks, as a representation of several classical techniques, have emerged as one of the primary branches in the field of value function-based reinforcement learning. The paper addresses two issues that come up in the realm of reinforcement learning for value function solving: estimating bias and maximizing projected action value function evaluation. By treating the estimation of the highest expected action value as a random selection estimation problem, the suggested approach addresses the estimation bias issue from the standpoint of random selection. A random choice estimate procedure forms the basis of the technique. Firstly, a proposed random choice estimator is presented and its theoretical fairness is established. Second, the estimator is applied to create a reinforcement learning method in a different application. Two techniques, namely stochastic two-depth Q-networks and double-Q learning, are suggested based on the random choice estimation technique. The main parameters of the suggested algorithms are then investigated, and parameter formulas for both predictable and unpredictable scenarios are created. Lastly, a random choice estimation perspective suggests a stochastic two-depth Q-network. The new approach may effectively remove bias in value function estimate, enhance learning performance, and stabilise the learning process, according to simulation findings on Grid World and Atari games.