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Abstract TP53 mutation (TP53-mut) correlates with inferior survival in many cancers, whereas its prognostic role in diffuse large B-cell lymphoma (DLBCL) is still in controversy. Therefore, more precise risk stratification needs to be further explored for TP53-mut DLBCL patients. A set of 2637 DLBCL cases from multiple cohorts, was enrolled in our analysis. Among the 2637 DLBCL patients, 14.0% patients (370/2637) had TP53-mut. Since missense mutations account for the vast majority of TP53-mut DLBCL patients, and most non-missense mutations affect the function of the P53 protein, leading to worse survival rates, we distinguished patients with missense mutations. A TP53 missense mutation risk model was constructed based on a 150-combination machine learning computational framework, demonstrating excellent performance in predicting prognosis. Further analysis revealed that patients with high-risk missense mutations are significantly associated with early progression and exhibit dysregulation of multiple immune and metabolic pathways at the transcriptional level. Additionally, the high-risk group showed an absolutely suppressed immune microenvironment. To stratify the entire cohort of TP53-mut DLBCL, we combined clinical characteristics and ultimately constructed the TP53 Prognostic Index (TP53PI) model. In summary, we identified the truly high-risk TP53-mut DLBCL patients and explained this difference at the mutation and transcriptional levels.

The traditional stir-fry process before pressing is crucial to manufacture Hainan camellia oil. To assess the effects of the stir-fry process on Hainan camellia oil, six samples across different stir-fry stages were analyzed. The stir-fry process modified odors, volatile metabolite profiles, and human health-promoting functions of Hainan camellia oil. Totally, 350 volatile metabolites were detected, and heterocyclic compounds were revealed as the main contributors of strong aroma. Potential indicators for monitoring the stir-fry degree were established. Eight key aroma volatile metabolites were identified, including three new ones (1-octen-3-one, 2,3-butanedione, and vanillin). Lipids degradation and the Millard reaction are probably the main pathways for aroma generation. Over-stir-fry treatment diminished the contents of some important volatile metabolites but increased the risk of arising burnt odor. Our work offered insights into the effects of the stir-fry process and over-stir-fry treatment on Hainan camellia oil, which is meaningful for improving the hot-pressing technique.

Water reuse is an effective way to solve the issues of current wastewater increments and water resource scarcity. Ultrafiltration, a promising method for water reuse, has the characteristics of low energy consumption, easy operation, and high adaptability to coupling with other water treatment processes. However, emerging organic contaminants (EOCs) in municipal wastewater cannot be effectively intercepted by ultrafiltration, which poses significant challenges to the effluent quality and sustainability of ultrafiltration process. Here, we develop a cobalt single-atom catalyst-tailored ceramic membrane (Co1-NCNT-CM) in conjunction with an activated peroxymonosulfate (PMS) system, achieving excellent EOCs degradation and anti-fouling performance. An interfacial reaction mechanism effectively mitigates membrane fouling through a repulsive interaction with natural organic matter. The generation of singlet oxygen at the Co-N3-C active sites through a catalytic pathway (PMS→PMS∗→OH∗→O∗→OO∗→1O2) exhibits selective oxidation of phenols and sulfonamides, achieving >90% removal rates. Our findings elucidate a multi-layered functional architecture within the Co1-NCNT-CM/PMS system, responsible for its superior performance in organic decontamination and membrane maintenance during secondary effluent treatment. It highlights the power of integrating Co1-NCNT-CM/PMS systems in advanced wastewater treatment frameworks, specifically for targeted EOCs removal, heralding a new direction for sustainable water management.

Abstract Indoleamine 2,3‐dioxygenase 1 (IDO1), the key enzyme in the catabolism of the essential amino acid tryptophan (Trp) through kynurenine pathway, induces immune tolerance and is considered as a critical immune checkpoint, but its impacts as a metabolism enzyme on glucose and lipid metabolism are overlooked. We aim to clarify the potential role of IDO1 in aerobic glycolysis in pancreatic cancer (PC). Analysis of database revealed the positive correlation in PC between the expressions of IDO1 and genes encoding important glycolytic enzyme hexokinase 2 (HK2), pyruvate kinase (PK), lactate dehydrogenase A (LDHA) and glucose transporter 1 (GLUT1). It was found that IDO1 could modulate glycolysis and glucose uptake in PC cells, Trp deficiency caused by IDO1 overexpression enhanced glucose uptake by stimulating GLUT1 translocation to the plasma membrane of PC cells. Besides, Trp deficiency caused by IDO1 overexpression suppressed the apoptosis of PC cells via promoting glycolysis, which reveals the presence of IDO1–glycolysis–apoptosis axis in PC. IDO1 inhibitors could inhibit glycolysis, promote apoptosis, and exhibit robust therapeutic efficacy when combined with GLUT1 inhibitor in PC mice. Our study reveals the function of IDO1 in the glucose metabolism of PC and provides new insights into the therapeutic strategy for PC.

Over the last decades, ultrafiltration (UF) has been and will continue to play an important role in the Chinese drinking water industry. The hybrid membrane processes have been emerging as promising alternatives to traditional treatment processes. This review paper offers a thorough overview of the current status of UF technology in the drinking water industry in China, while also evaluating the landscape of different hybrid membrane processes. The paper conducts statistical analysis on the projects operational between 2004 and 2022; and those currently under construction. This analysis accentuates the evolution of scale and capacity, geographical distribution characteristics, and the driving forces. Furthermore, the characteristics and application scenarios of several hybrid membrane processes are emphatically described, including direct UF, gravity-driven membrane process, coagulation-UF, activated carbon-UF, medium-flow process, long-flow process, and double-membrane process. A granular dissection of UF membrane market distribution follows, including an incisive comparison between submerged and pressurized UF membrane systems. Finally, the potential trajectory of UF in the Chinese drinking water industry is prospected. UF applications have grown significantly in China's drinking water industry, with the dominance of medium- and long-flow membrane processes. UF technology will contribute to future decentralized water supply. HIGHLIGHTS The development of UF full-scale applications in drinking water treatment in China is revisited.; The review provides the geographic distribution of UF DWTPs and driving forces.; The characteristics and application scenarios of four hybrid membrane processes are described.; The UF membrane market distribution is identified.; The insights for the future application of UF technology are highlighted.;

With the continuous development of science and technology (especially computational devices with powerful computing capabilities), the image generation technology based on deep learning has also made significant achievements. Most cross-modal technologies based on deep learning can generate information from text into images, which has become a hot topic of current research. Text-to-image (T2I) synthesis technology has applications in multiple fields of computer vision, such as image enhancement, artificial intelligence painting, games and virtual reality. The T2I generation technology using generative adversarial networks can generate more realistic and diverse images, but there are also some shortcomings and challenges, such as difficulty in generating complex backgrounds. This review will be introduced in the following order. First, we introduce the basic principles and architecture of basic and classic generative adversarial networks (GANs). Second, this review categorizes T2I synthesis methods into four main categories. There are methods based on semantic enhancement, methods based on progressive structure, methods based on attention and methods based on introducing additional signals. We have chosen some of the classic and latest T2I methods for introduction and explain their main advantages and shortcomings. Third, we explain the basic dataset and evaluation indicators in the T2I field. Finally, prospects for future research directions are discussed. This review provides a systematic introduction to the basic GAN method and the T2I method based on it, which can serve as a reference for researchers.

Objective: To realize the rapid traceability detection of Astragalus membranaceus from different origins. Methods: This study proposed a rapid detection method for the origin of Astragalus membranaceus based on the improved MobileNetv3 network based on the combination of electronic tongue and electronic eye. The electronic tongue and electronic eye were used to collect the one-dimensional fingerprint and two-dimensional appearance image information of different samples of Astragalus membranaceus. The Gramian Angular Field (GAF) was used to convert the one-dimensional electronic tongue signal into two-dimensional image information, retain the time series related features in the electronic tongue signal, and then fused them with the image information collected by the electronic eye. Finally, the MobileNetv3 model improved based on Pyramid Split Attention (PSA) was adopted to realize the classification and recognition of Astragalus samples from different habitats. Results: The experimental results showed that the method in this paper had higher recognition accuracy than using electronic tongue or electronic eye alone. The accuracy, precision, rrecall and F1-score of the test set were 98.8%, 98.8%, 98.8% and 0.99, respectively. The classification accuracy of the improved MobileNetv3 network was 8% higher than that of the original model, and the parameter quantity was only about 1/5 of the original parameter quantity. Conclusion: The improved MobileNetv3 network can effectively reduce the calculation of parameters and improve the recognition accuracy of Astragalus membranaceus from different origins.

Net photosynthetic rate (Pn) is a common indicator used to measure the efficiency of photosynthesis and growth conditions of plants. In this study, soybeans under different moisture gradients were selected as the research objects. Fourteen vegetation indices (VIS) and five canopy structure characteristics (CSC) (plant height (PH), volume (V), canopy cover (CC), canopy length (L), and canopy width (W)) were obtained using an unmanned aerial vehicle (UAV) equipped with three different sensors (visible, multispectral, and LiDAR) at five growth stages of soybeans. Soybean Pn was simultaneously measured manually in the field. The variability of soybean Pn under different conditions and the trend change of CSC under different moisture gradients were analysed. VIS, CSC, and their combinations were used as input features, and four machine learning algorithms (multiple linear regression, random forest, Extreme gradient-boosting tree regression, and ridge regression) were used to perform soybean Pn inversion. The results showed that, compared with the inversion model using VIS or CSC as features alone, the inversion model using the combination of VIS and CSC features showed a significant improvement in the inversion accuracy at all five stages. The highest accuracy (R2 = 0.86, RMSE = 1.73 µmol m−2 s−1, RPD = 2.63) was achieved 63 days after sowing (DAS63).

Abstract Structural flexibility is a critical issue that limits the application of metal-organic framework (MOF) membranes for gas separation. Herein we propose a mixed-linker approach to suppress the structural flexibility of the CAU-10-based (CAU = Christian-Albrechts-University) membranes. Specifically, pure CAU-10-PDC membranes display high separation performance but at the same time are highly unstable for the separation of CO2/CH4. A partial substitution (30 mol.%) of the linker PDC with BDC significantly improves its stability. Such an approach also allows for decreasing the aperture size of MOFs. The optimized CAU-10-PDC-H (70/30) membrane possesses a high separation performance for CO2/CH4 (separation factor of 74.2 and CO2 permeability of 1,111.1 Barrer under 2 bar of feed pressure at 35°C). A combination of in situ characterization with X-ray diffraction (XRD) and diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy, as well as periodic density functional theory (DFT) calculations, unveils the origin of the mixed-linker approach to enhancing the structural stability of the mixed-linker CAU-10-based membranes during the gas permeation tests.

Background Pain is a common non-motor symptom in patients with Parkinson's disease (PD) , which has a serious impact on patients' quality of life. Current scholars have explored the factors influencing the occurrence of pain in patients with PD, but there is some variability in the findings. Objective To evaluate the influencing factors of pain in PD patients. Methods We searched the CNKI, Wanfang Data, VIP, SinoMed, Web of Science, PubMed, Medline, Embase and Cochrane Library databases for studies on factors influencing pain in patients with PD from database establishment to April 12, 2022. Two researchers independently conducted literature screening and relevant information extraction. We used the Agency for Healthcare Research and Quality (AHRQ) Scale and the Newcastle-Ottawa Scale (NOS) to evaluate the risk of bias in cross-sectional studies and case-control studies, respectively. We performed a descriptive analysis of all influencing factors of pain, and implemented a meta-analysis of these influencing factors using RevMan 5.3. Results Sixteen studies were finally included, with a total sample size of 2 855 cases, and 24 influencing factors of pain identified. There were two protective factors and 22 risk factors in descriptive analysis. The meta-analysis showed that, female〔OR=3.73, 95%CI (1.75, 7.96) , P=0.000 7〕, long duration of PD〔OR=1.35, 95%CI (1.15, 1.60) , P=0.000 3〕, depressed mood 〔OR=1.14, 95%CI (1.07, 1.22) , P

Glioma is characterized by strong immunosuppression and excessive angiogenesis. Based on existing reports, it can be speculated that the resistance to anti-angiogenic drug vascular endothelial growth factor A (VEGFA) antibody correlates to the induction of novel immune checkpoint indoleamine 2,3-dioxygenase 1 (IDO1), while IDO1 has also been suggested to be related to tumor angiogenesis. Herein, we aim to clarify the potential role of IDO1 in glioma angiogenesis and the mechanism behind it. Bioinformatic analyses showed that the expressions of IDO1 and angiogenesis markers VEGFA and CD34 were positively correlated and increased with pathological grade in glioma. IDO1-overexpression-derived-tryptophan depletion activated the general control nonderepressible 2 (GCN2) pathway and upregulated VEGFA in glioma cells. The tube formation ability of angiogenesis model cells could be inhibited by IDO1 inhibitors and influenced by the activity and expression of IDO1 in condition medium. A significant increase in serum VEGFA concentration and tumor CD34 expression was observed in IDO1-overexpressing GL261 subcutaneous glioma-bearing mice. IDO1 inhibitor RY103 showed positive anti-tumor efficacy, including the anti-angiogenesis effect and upregulation of natural killer cells in GL261 glioma-bearing mice. As expected, the combination of RY103 and anti-angiogenesis agent sunitinib was proved to be a better therapeutic strategy than either monotherapy.

Drought stress is a significant factor affecting soybean growth and yield. A lack of suitable high-throughput phenotyping techniques hinders the drought tolerance evaluation of multi-genotype samples. A method for evaluating drought tolerance in soybeans is proposed based on multimodal remote sensing data from an unmanned aerial vehicle (UAV) and machine learning. Hundreds of soybean genotypes were repeatedly planted under well water (WW) and drought stress (DS) in different years and locations (Jiyang and Yazhou, Sanya, China), and UAV multimodal data were obtained in multiple fertility stages. Notably, data from Yazhou were repeatedly obtained during five significant fertility stages, which were selected based on days after sowing. The geometric mean productivity (GMP) index was selected to evaluate the drought tolerance of soybeans. Compared with the results of manual measurement after harvesting, support vector regression (SVR) provided better results (N = 356, R2 = 0.75, RMSE = 29.84 g/m2). The model was also migrated to the Jiyang dataset (N = 427, R2 = 0.68, RMSE = 15.36 g/m2). Soybean varieties were categorized into five Drought Injury Scores (DISs) based on the manually measured GMP. Compared with the results of the manual DIS, the accuracy of the predicted DIS gradually increased with the soybean growth period, reaching a maximum of 77.12% at maturity. This study proposes a UAV-based method for the rapid high-throughput evaluation of drought tolerance in multi-genotype soybean at multiple fertility stages, which provides a new method for the early judgment of drought tolerance in individual varieties, improving the efficiency of soybean breeding, and has the potential to be extended to other crops.

Camellia polyodonta flowers are rich sources of phenolics and less attention has been paid to their potential biological activity. This study aims to explore the crude extracts and resulting purified fractions (CPFP-I, II, III, and IV) through compositional analysis and antioxidant and hypolipidemic activities in vitro and in vivo. Among four fractions, CPFP-II contained the highest total phenolic content and flavonoid content, while CPFP-III exhibited the greatest total proanthocyanidin content. Among the 14 phenolic compounds, CPFP-II displayed the highest content of procyanidin B2, B4, and C1, whereas CPFP-III contained the highest amount of 1,2,3,6-tetragalloylglucose. The DPPH, ABTS, and FRAP assessments demonstrated a consistent trend: CPFP-II > CPFP-III > CPFP-I > CPFP-IV. In vivo experiments showed that that all four fractions significantly reduced lipid levels in hyperlipidemic C. elegans (p < 0.05), with CPFP-II exhibiting the most potent effect. Furthermore, CPFP-II effectively bound to bile acids and inhibited the enzymatic activity of pancreatic lipase in vitro. Consequently, CPFP-II should be prioritized as a promising fraction for further exploration and should provide substantial support for the feasibility of the C. polyodonta flower as a natural alternative.

Tumor mutation burden (TMB) has emerged as an essential biomarker for assessing the efficacy of cancer immunotherapy. However, due to the inherent complexity of tumors, TMB is not always correlated with the responsiveness of immune checkpoint inhibitors (ICIs). Thus, refining the interpretation and contextualization of TMB is a requisite for enhancing clinical outcomes. In this study, we conducted a comprehensive investigation of the relationship between TMB and multi-omics data across 33 human cancer types. Our analysis revealed distinct biological changes associated with varying TMB statuses in STAD, COAD, and UCEC. While multi-omics data offer an opportunity to dissect the intricacies of tumors, extracting meaningful biological insights from such massive information remains a formidable challenge. To address this, we developed and implemented the PGLCN, a biologically informed graph neural network based on pathway interaction information. This model facilitates the stratification of patients into subgroups with distinct TMB statuses and enables the evaluation of driver biological processes through enhanced interpretability. By integrating multi-omics data for TMB prediction, our PGLCN model outperformed previous traditional machine learning methodologies, demonstrating superior TMB status prediction accuracy (STAD AUC: 0.976 ± 0.007; COAD AUC: 0.994 ± 0.007; UCEC AUC: 0.947 ± 0.023) and enhanced interpretability (BA-House: 1.0; BA-Community: 0.999; BA-Grid: 0.994; Tree-Cycles: 0.917; Tree-Grids: 0.867). Furthermore, the biological interpretability inherent to PGLCN identified the Toll-like receptor family and DNA repair pathways as potential combined biomarkers in conjunction with TMB status in gastric cancer. This finding suggests a potential synergistic targeting strategy with immunotherapy for gastric cancer, thus advancing the field of precision oncology.

In Alzheimer’s disease, the transporter P-glycoprotein is responsible for the clearance of amyloid-β in the brain. Amyloid-β correlates with the sphingomyelin metabolism, and sphingomyelin participates in the regulation of P-glycoprotein. The amyloid cascade hypothesis describes amyloid-β as the central cause of Alzheimer’s disease neuropathology. Better understanding of the change of P-glycoprotein and sphingomyelin along with amyloid-β and their potential association in the pathological process of Alzheimer’s disease is critical. Herein, we found that the expression of P-glycoprotein in APP/PS1 mice tended to increase with age and was significantly higher at 9 and 12 months of age than that in wild-type mice at comparable age. The functionality of P-glycoprotein of APP/PS1 mice did not change with age but was significantly lower than that of wild-type mice at 12 months of age. Decreased sphingomyelin levels, increased ceramide levels, and the increased expression and activity of neutral sphingomyelinase 1 were observed in APP/PS1 mice at 9 and 12 months of age compared with the levels in wild-type mice. Similar results were observed in the Alzheimer’s disease mouse model induced by intracerebroventricular injection of amyloid-β1–42 and human cerebral microvascular endothelial cells treated with amyloid-β1–42. In human cerebral microvascular endothelial cells, neutral sphingomyelinase 1 inhibitor interfered with the changes of sphingomyelin metabolism and P-glycoprotein expression and functionality caused by amyloid-β1–42 treatment. Neutral sphingomyelinase 1 regulated the expression and functionality of P-glycoprotein and the levels of sphingomyelin and ceramide. Together, these findings indicate that neutral sphingomyelinase 1 regulates the expression and function of P-glycoprotein via the sphingomyelin/ceramide pathway. These studies may serve as new pursuits for the development of anti-Alzheimer’s disease drugs.

Ultrafiltration (UF) has been increasingly implemented in drinking water treatment plants; however, algae and their secretions can cause severe membrane fouling and pose great challenges to UF in practice. In this study, a simple and practical chemically enhanced backwashing (CEB) process was developed to address such issues using various cleaning reagents, including sodium hypochlorite (NaClO), sodium chloride (NaCl), sodium hydroxide (NaOH), sodium citrate, and their combinations. The results indicate that the type of chemical played a fundamental role in alleviating the hydraulically irreversible membrane fouling (HIMF), with NaClO as the best-performing reagent, followed by NaCl. Furthermore, a CEB process using a combination of NaClO with NaCl, NaOH, or sodium citrate delivered little improvement in the alleviation of membrane fouling compared with NaClO alone. The optimized dosage and dosing frequency of NaClO were 10 mg·L−1 two times per day. Long-term pilot-scale and full-scale experiments further verified the feasibility of the CEB process in relieving algae-derived membrane fouling. Compared with the conventional hydraulic backwashing without chemical involvement, the CEB process can effectively remove the organic foulants including biopolymers, humic substances, and protein-like substances by means of oxidization, thereby weakening the cohesive forces between the organic foulants and the membrane surface. Therefore, the CEB process can efficiently alleviate the algae-related membrane fouling with lower chemical consumption, and is proposed as an alternative to control membrane fouling in treating the algae-containing surface water.

At present, many studies have been carried out on the fatigue mechanical properties of conventional rocks, but there are few studies on the mechanical properties of rocks after water rock interaction. The aim is to better study the fatigue mechanical characteristics of sandstone after dry wet cycle and the research object we take was sandstone samples after a certain number of drying and wetting cycles. The WAW-2000 electro-hydraulic servo pressure system was used to carry out uniaxial fatigue cyclic loading and unloading tests with different amplitudes and different upper limit stresses. The test found that: when the sample is damaged under fatigue load, the stress-strain curve shows a sharp downward trend and a sudden instability failure occurred in the sample.With the increase of the upper limit stress and amplitude, the life of the sample decreases gradually which also conforms to the change of power function. Then the relationship between fatigue life and stress is obtained. The fatigue stress-strain curve is characterized by sparse-dense-sparse. With the increase of cycle time, the axial strain of the sample shows an inverted “S” shape. The strain change can be divided into three stages: initial stage, constant velocity stage and acceleration stage.

IntroductionAs a developing country with the largest older adult population in the world, strengthening the research on falls among the older adults is undoubtedly an urgent item in China. This study aimed to explore the prevalence and risk factors associated with falls and injury from falls among community-dwelling older adults in Guangzhou, China, particularly focusing on their associations with chronic diseases.MethodsA total of 1,629 participants aged 65 years and above were selected from 11 counties in Guangzhou by the multi-stage stratified random sampling method in 2021. Socio-demographic characteristics, health and lifestyle factors, the status of falls, and injury from falls were measured by structured questionnaires through face-to-face interviews. Chi-square tests and logistic regression analysis were used to identify factors associated with falls and injury from falls. Chord diagrams were used to explore their associations with chronic diseases.ResultsA total of 251 participants (15.41%, 95% CI: 13.98%−17.25%) reported falls, and 162 participants (9.46%, 95% CI:7.72%−11.55%) indicated an injury from falls. Logistic regression analysis showed the results as follows: female patients (adjusted OR = 1.721, 95% CI: 1.681–1.761) aged ≥80 years (1.910, 1.847–1.975), unemployed (1.226, 1.171–1.284), uninsured (1.555, 1.448–1.671), average monthly household income of 2,001–4,000 CNY (1.878, 1.827–1.930), number of services provided by the community health center ≥13 times per year (1.428, 1.383–1.475), illness within 2 weeks (1.633, 1.595–1.672), high-intensity physical activity (2.254, 2.191–2.32), sedentary (1.094, 1.070–1.117), and number of chronic disease illnesses ≥3 (1.930, 1.870–1.993). Meanwhile, those risk factors were also associated with injury from falls. The older adults with medium-intensity physical activity were at lower risk (0.721, 0.705–0.737) of falls and higher risk (1.086, 1.057–1.117) of being injured from falls. Chord diagrams showed the correlations between chronic diseases and falls and injury from falls among community-dwelling older adults in Guangzhou, China.ConclusionThe high prevalence of falls is found among community-dwelling older adults in Guangzhou, China, which is related to multiple factors such as demographic variables, lifestyle, and health status, especially for chronic diseases. Therefore, targeted interventions should be developed and implemented urgently.

Underwater object detection currently faces many challenges, such as the large number of parameters in existing object detection models, slow inference speed, blurring of underwater images, and aggregation of small targets, making it difficult to conduct efficient underwater object detection. This paper proposes a lightweight underwater object detection algorithm based on YOLOv5.The method uses depth-wise separable convolution instead of ordinary convolution to reduce the number of parameters and computational complexity. A C3 module based on Ghost convolution is designed to further compress the model size and improve the computational speed. In the feature extraction stage, a RepVgg module based on structural reparameterization is used to convert the multi -branch structure into a single-branch structure in the inference stage, improving the feature extraction ability of the model and increasing the inference speed. A Rep-ECA module is designed to embed the efficient channel attention module ECANet into the RepVGG module, selecting more effective channel information and improving the model’s feature extraction ability for small objects in blurred images, thereby improving detection precision. Experimental results show that in the URPC underwater object detection dataset, the proposed algorithm has a 39% lower model parameter count compared to the original model, a 42% reduction in computational complexity. The model can achieve a frame rate of 85 on a single Nvidia GTX 1080ti GPU, which is a 24% improvement over the original model, while mAP reaches 85.1%, a 1.1% improvement over the original model. The algorithm can improve the detection precision and achieve lightweight, which lays a foundation for the deployment of underwater equipment.

Hepatotoxicity is a common side effect for patients treated with gefitinib, but the related pathogenesis is unclear and lacks effective predictor and management strategies. A multi-omics approach integrating pharmacometabolomics, pharmacokinetics and pharmacogenomics was employed in non-small cell lung cancer patients to identify the effective predictor for gefitinib-induced hepatotoxicity and explore optional therapy substitution. Here, we found that patients with rs4946935 AA, located in Forkhead Box O3 (FOXO3) which is a well-known autophagic regulator, had a higher risk of hepatotoxicity than those with the GA or GG variant (OR = 18.020, 95%CI = 2.473 to 459.1784, P = 0.018) in a gefitinib-concentration dependent pattern. Furthermore, functional experiments identified that rs4946935_A impaired the expression of FOXO3 by inhibiting the promotor activity, increasing the threshold of autophagy initiation and inhibiting the autophagic activity which contributed to gefitinib-induced liver injury. In contrast, erlotinib-induced liver injury was independent on the variant and expression levels of FOXO3. This study reveals that FOXO3 mutation, leading to autophagic imbalance, plays important role in gefitinib-induced hepatotoxicity, especially for patients with high concentration of gefitinib. In conclusion, FOXO3 mutation is an effective predictor and erlotinib might be an appropriately and well-tolerated treatment option for patients carrying rs4946935 AA.

Abstract As a critical node for insulin/IGF signaling, insulin receptor substrate 1 (IRS-1) is essential for metabolic regulation. A long and unstructured C-terminal region of IRS-1 recruits downstream effectors for promoting insulin/IGF signals. However, the underlying molecular basis for this remains elusive. Here, we found that the C-terminus of IRS-1 undergoes liquid-liquid phase separation (LLPS). Both electrostatic and hydrophobic interactions were seen to drive IRS-1 LLPS. Self-association of IRS-1, which was mainly mediated by the 301–600 region, drives IRS-1 LLPS to form insulin/IGF-1 signalosomes. Moreover, tyrosine residues of YXXM motifs, which recruit downstream effectors, also contributed to IRS-1 self-association and LLPS. Impairment of IRS-1 LLPS attenuated its positive effects on insulin/IGF-1 signaling. The metabolic disease-associated G972R mutation impaired the self-association and LLPS of IRS-1. Our findings delineate a mechanism in which LLPS of IRS-1-mediated signalosomes serves as an organizing center for insulin/IGF-1 signaling and implicate the role of aberrant IRS-1 LLPS in metabolic diseases.

Single-atom-supported metal oxides have attracted extensive interest in energy catalysis, offering a promising avenue for mitigating greenhouse gas emissions and environmental pollution. This study presents a facile synthesis of single-atom Fe-modified Bi2WO6 photocatalysts. By carefully tuning the Fe ratios, the 1.5Fe-Bi2WO6 sample demonstrates exceptional photocatalytic efficiency in CO2 to CO reduction (36.78 μmol g−1). Additionally, an outstanding NO removal performance is also achieved through this photocatalyst with an impressively low conversion of toxic NO2 at just 0.37%. The reaction intermediates and mechanisms governing the photocatalytic reduction of CO2 into CO are elucidated using in situ DRIFTS and in situ XAS techniques. Regarding NO removal, the introduction of Fe single-atoms, along with induced oxygen vacancies, plays a pivotal role in facilitating the transformation of NO and NO2 into nitrate by stabilizing NO and NO2 species. Mechanistic insights into photocatalytic NO oxidation are garnered through scavenger trapping and EPR experiments employing DMPO. This study emphasizes single-atom-supported metal oxide's potential in sustainable chemistry and air purification, providing a promising solution for urgent environmental challenges. [ABSTRACT FROM AUTHOR]

Link prediction is crucial in forecasting potential distribution channels within the dynamic and heterogeneous Xinjiang jujube sales market. This study utilizes knowledge graphs to represent entities and constructs a complex network model for market analysis. Graph neural networks (GNNs) have shown excellent performance in handling graph-structured data, but they do not necessarily significantly outperform in link prediction tasks due to an overreliance on node features and a neglect of structural information. Additionally, the Xinjiang jujube dataset exhibits unique complexity, including multiple types, attributes, and relationships, distinguishing it from typical GNN datasets such as DBLP and protein-protein interaction datasets. To address these challenges, we introduce the Heterogeneous Multi-Head Attention Graph Neural Network model (HMAGNN). Our methodology involves mapping isomeric nodes to common feature space and labeling nodes using an enhanced Weisfeiler–Lehman (WL) algorithm. We then leverage HMAGNN to learn both structural and attribute features individually. Throughout our experimentation, we identify the critical influence of local subgraph structure and size on link prediction outcomes. In response, we introduce virtual nodes during the subgraph extraction process and conduct validation experiments to underscore the significance of these factors. Compared to alternative models, HMAGNN excels in capturing structural features through our labeling approach and dynamically adapts to identify the most pertinent link information using a multi-head attention mechanism. Extensive experiments on benchmark datasets consistently demonstrate that HMAGNN outperforms existing models, establishing it as a state-of-the-art solution for link prediction in the context of jujube sales market analysis. [ABSTRACT FROM AUTHOR]

Double‐atom site catalysts (DASs) have emerged as a recent trend in the oxygen reduction reaction (ORR), thereby modifying the intermediate adsorption energies and increasing the activity. However, the lack of an efficient dual atom site to improve activity and durability has limited these catalysts from widespread application. Herein, the nitrogen‐coordinated iron and tin‐based DASs (Fe‐Sn‐N/C) catalyst are synthesized for ORR. This catalyst has a high activity with ORR half‐wave potentials (E1/2) of 0.92 V in alkaline, which is higher than those of the state‐of‐the‐art Pt/C (E1/2 = 0.83 V), Fe‐N/C (E1/2 = 0.83 V), and Sn‐N/C (E1/2 = 0.77 V). Scanning electron transmission microscopy analysis confirmed the atomically distributed Fe and Sn sites on the N‐doped carbon network. X‐ray absorption spectroscopy analysis revealed the charge transfer between Fe and Sn. Both experimental and theoretical results indicate that the Sn with Fe‐NC (Fe‐Sn‐N/C) induces charge redistribution, weakening the binding strength of oxygenated intermediates and leading to improved ORR activity. This study provides the synergistic effects of DASs catalysts and addresses the impacts of P‐block elements on d‐block transition metals in ORR. [ABSTRACT FROM AUTHOR]