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AIM: To investigate the proliferation regulatory effect of cone-rod homeobox (CRX) in retinal pigment epithelium (RPE) and retinoblastoma (RB) cells to explore the potential application and side effect (oncogenic potential) of CRX-based gene therapy in RPE-based retinopathies. METHODS: Adult human retinal pigment epithelial (ARPE)-19 and human retinal pigment epithelial (RPE)-1 cells and Y79 RB cell were used in the study. Genetic manipulation was performed by lentivirus-based technology. The cell proliferation was determined by a CellTiter-Glo Reagent. The mRNA and protein levels were determined by quantitative real-time polymerase chain reaction (qPCR) and Western blot assay. The transcriptional activity of the promoter was determined by luciferase reporter gene assay. The bindings between CRX and transcription factor 7 (TCF7) promoter as well as TCF7 and the promoters of TCF7 target genes were examined by chromatin immunoprecipitation (ChIP) assay. The transcription of the TCF7 was determined by a modified nuclear run-on assay. RESULTS: CRX overexpression and knockdown significantly increased (n=3, P

Abstract Clostridioides difficile infection (CDI) is a common healthcare-associated infection and the leading cause of gastroenteritis-related deaths worldwide. To investigate the effects of peptide composition of different protein products on CDI, we analyzed and compared the peptide sequences and compositions from Engraulis japonicus and Glycine max using Ultra High Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS). An animal model of CDI was also established to investigate the potential therapeutic effects of these peptides in vivo. The peptide compositions of E. japonicus and G. max differed, with only 11% of the peptide sequences being identical. Oral administration of the tested peptides could reduce intestinal inflammation, repair the intestinal barrier, increase the proportion of beneficial bacteria, and reduce the proportion of harmful bacteria, providing a therapeutic effect against CDI. However, the peptides may differ considerably in some aspects. E. japonicus peptides were superior to G. max peptides in promoting colon epithelial cell proliferation and repairing tight intestinal cell junctions. Interestingly, the two sources of peptides have different effects on the cecal microbiome. E. japonicus peptides can effectively restore the diversity and richness of intestinal microbiota, while G. max peptides have poor regulatory effects on the intestinal microbiota structure. Overall, E. japonicus peptides showed better results than G. max peptides in treating CDI. This study supports the potential treatment of CDI with natural peptides and promotes the development of specialty foods for CDI enteritis. Clostridioides difficile infection (CDI) is a common healthcare-associated infection and the leading cause of gastroenteritis-related deaths worldwide. To investigate the effects of peptide composition of different protein products on CDI, we analyzed and compared the peptide sequences and compositions from Engraulis japonicus and Glycine max using Ultra High Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS). An animal model of CDI was also established to investigate the potential therapeutic effects of these peptides in vivo. The peptide compositions of E. japonicus and G. max differed, with only 11% of the peptide sequences being identical. Oral administration of the tested peptides could reduce intestinal inflammation, repair the intestinal barrier, increase the proportion of beneficial bacteria, and reduce the proportion of harmful bacteria, providing a therapeutic effect against CDI. However, the peptides may differ considerably in some aspects. E. japonicus peptides were superior to G. max peptides in promoting colon epithelial cell proliferation and repairing tight intestinal cell junctions. Interestingly, the two sources of peptides have different effects on the cecal microbiome. E. japonicus peptides can effectively restore the diversity and richness of intestinal microbiota, while G. max peptides have poor regulatory effects on the intestinal microbiota structure.

Abstract Background Everolimus is an effective treatment for renal angiomyolipoma associated with TSC (TSC-RAML). However, its impact on hematologic parameters in TSC-RAML patients remains unclear. Methods Hematologic data were collected from TSC-RAML patients undergoing everolimus treatment in two registered clinical trials. Dynamic changes in hematologic parameters during treatment were analyzed. Additionally, we also explored variations in hematologic impact based on gender and age within the patient population. Result A total of 55 patients from the two clinical trials are included in this analysis. Hemoglobin, white blood cells (WBC), lymphocytes, neutrophils, and platelet showed significant decreases during everolimus treatment (P

Although many studies modelled writing quality by analysing basic skills (spelling, grammar, etc.), few focused on top-down compositional strategies at the discourse level. We propose that using both narrative and argument discourse modes in an argumentative essay (a multi-discourse mode [MDM] strategy) capitalizes on their complementary advantages, yielding higher quality argumentative essays. We tested whether MDM strategy and linguistic features were linked to essay scores in 695 Chinese high-stakes exam essays by upper secondary school students. Path analyses showed that essays with the MDM strategy had higher scores. MDM essays also featured more words, shorter sentences, more infrequent words, and more concrete words--all contributing to higher essay scores. Additionally, essays written from a picture prompt (versus a text prompt) had higher scores. This study captures how discourse strategies can improve essay writing.

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Abstract Halophyte shrubs, prevalent in arid regions globally, create saline fertile islands under their canopy. This study investigates the soil microbial communities and their energy utilization strategies associated with tamarisk shrubs in arid ecosystems. Shotgun sequencing revealed that high salinity in tamarisk islands reduces functional gene alpha-diversity and relative abundance compared to bare soils. However, organic matter accumulation within islands fosters key halophilic archaea taxa such as Halalkalicoccus, Halogeometricum, and Natronorubrum, linked to processes like organic carbon oxidation, nitrous oxide reduction, and sulfur oxidation, potentially strengthening the coupling of nutrient cycles. In contrast, bare soils harbor salt-tolerant microbes with genes for autotrophic energy acquisition, including carbon fixation, H2 or CH4 consumption, and anammox. Additionally, isotope analysis shows higher microbial carbon use efficiency, N mineralization, and denitrification activity in tamarisk islands. Our findings demonstrate that halophyte shrubs serve as hotspots for halophilic microbes, enhancing microbial nutrient transformation in saline soils.

Abstract Background Limited data exists on the efficacy of immune checkpoint inhibitor (ICI) combinations in non-small-cell lung cancer (NSCLC) with uncommon driver alterations in genes such as ERBB2, BRAF, RET, and MET. This study retrospectively assessed ICI-combination therapy outcomes in this molecular subset of NSCLC. Methods We retrospectively analyzed patients with advanced NSCLC confirmed with driver alterations in genes including ERBB2, BRAF, RET or MET, and received ICI combined with chemotherapy (ICI + chemo) and/or targeted therapy (ICI + chemo/TT) as first-line (1L) or second- or third-line (≥ 2L) treatment at Hunan Cancer Hospital between January 2018 and May 2024. Results Of the 181 patients included in the study, 131 patients received 1L-ICI + chemo (ERBB2, n = 64; BRAF, n = 34; RET, n = 23; and MET, n = 10), and 50 patients received ≥ 2L-ICI + chemo/TT (ERBB2, n = 16; BRAF, n = 7; RET, n = 14; MET, n = 13). The full cohort had an overall response rate (ORR) of 45.9% and disease control rate of 84.0%. Among patients who received 1L-ICI + chemo, ORR ranged between 51.6% and 60.0%, with the median progression-free survival (mPFS) and overall survival (mOS) of 8.2 and 21.0 months for those with ERBB2-altered tumors, 10.0 and 15.0 months for BRAF-altered tumors, 12.1 months and OS not reached for RET-altered tumors, and 6.2 and 28.0 months for MET-altered tumors, respectively. Additionally, ORR ranged between 14.3% and 30.8% for ≥ 2L-ICI + chemo/TT; mPFS and mOS were 5.4 and 16.2 months for patients with ERBB2-altered tumors, 2.7 and 5.0 months for BRAF-altered tumors, 6.2 and 14.3 months for RET-altered tumors, and 5.7 and 11.5 months for MET-altered tumors, respectively. Conclusion ICI-based combination therapies, regardless of treatment line, were effective in treating patients with advanced NSCLC harboring driver alterations in ERBB2, BRAF, RET, or MET. This suggests their potential as alternative treatment options in this patient population.

Abstract Global changes and drug abuse are forcing humanity to face various disease problems, and alternative therapies with safe natural substances have important research value. This paper combines various techniques in quantum chemical calculations and molecular simulations to provide molecular-level insight into the dynamics of the self-assembly of N-isopropylacrylamide (NIPAM) for loading curcumin (CUR). The results indicate that increasing the chain length of NIPAM molecules reduces their efficiency in encapsulating and locking CUR, and electrostatic interactions and van der Waals interactions are the main driving forces behind the evolution of system configurations in these processes. The isopropyl groups of NIPAM and the two phenolic ring planes of CUR are the main contact areas for the interaction between the two types of molecules. The thermosensitive effect of NIPAM can alter the distribution of isopropyl groups in NIPAM molecules around CUR. As a result, when the temperature rises from ambient temperature (300 K) to human characteristic temperature (310 K), the NIPAM-CUR interactions and radial distribution functions suggest that body temperature is more suitable for drug release. Our findings offer a vital theoretical foundation and practical guidance for researchers to develop temperature-sensitive drug delivery systems tailored for CUR, addressing its clinical application bottleneck.

Low back pain is among the most grave public health concerns worldwide and the major clinical manifestation of intervertebral disc degeneration (IVDD). The destruction of annulus fibrosus (AF) is the primary cause of IVDD. A sustainable and stable treatment system for IVDD is lacking because of the special organizational structure and low nutrient supply of AF. We here found that IVDD results in the impaired mitochondrial function of AF tissue, and mitochondrial autophagy (mitophagy) plays a protective role in this process. We therefore reported a thread-structural microneedle (T-MN) matching the ring structure of AF. Based on the adsorption effect of laminin, our T-MN could load with bone marrow mesenchymal stem cell-derived exosomes to envelope the regulating mitophagy microRNA (miRNA 378), named as T-MN@EXO@miR−378. In general, we offered in situ locking in the defect site of AF to prevent nucleus pulposus leakage and promoted AF repair. The design of the thread structure was aimed at bionically matching the layered AF structure, thereby providing stronger adhesion. The T-MN@EXO@miR−378 effectively attached to AF and slowly released therapeutic engineered exosomes, and prevented IVDD progression by restoring mitophagy, promoting AF cell proliferation and migration, and inhibiting the pathological remodeling of the extracellular matrix. This functional system can be used as an excellent tool for sustained drug release and has a certain prospect in substituting the conventional treatment of IVDD.

Abstract Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Abstract Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

Generative AI (GenAI) has witnessed remarkable progress in recent years and demonstrated impressive performance in various generation tasks in different domains such as computer vision and computational design. Many researchers have attempted to integrate GenAI into visualization framework, leveraging the superior generative capacity for different operations. Concurrently, recent major breakthroughs in GenAI like diffusion models and large language models have also drastically increased the potential of GenAI4VIS. From a technical perspective, this paper looks back on previous visualization studies leveraging GenAI and discusses the challenges and opportunities for future research. Specifically, we cover the applications of different types of GenAI methods including sequence, tabular, spatial and graph generation techniques for different tasks of visualization which we summarize into four major stages: data enhancement, visual mapping generation, stylization and interaction. For each specific visualization sub-task, we illustrate the typical data and concrete GenAI algorithms, aiming to provide in-depth understanding of the state-of-the-art GenAI4VIS techniques and their limitations. Furthermore, based on the survey, we discuss three major aspects of challenges and research opportunities including evaluation, dataset, and the gap between end-to-end GenAI methods and visualizations. By summarizing different generation algorithms, their current applications and limitations, this paper endeavors to provide useful insights for future GenAI4VIS research.

Objective: To investigate the combined effect of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation on improving lower limb function in stroke patients. Design: Randomized controlled trial. Subjects/Patients: Subacute stroke patients. Methods: 169 post-stroke hemiplegia patients were randomly divided into 4 groups (control, transcranial direct current stimulation, transcutaneous auricular vagus nerve stimulation, and transcutaneous auricular vagus nerve stimulation combined with transcranial direct current stimulation) and evaluated using the Fugl-Meyer Assessment-Lower Extremity (FMA-LL), Timed Up-and-Go (TUG) test, Modified Barthel Index (MBI), Berg Balance Scale (BBS), gait parameters, and surface electromyography (sEMG). Results: Significant improvements in FMA-LL, MBI, BBS, TUG, gait parameters, and sEMG were noted in the intervention groups compared with the control, with the transcutaneous auricular vagus nerve stimulation combined with transcranial direct current stimulation group showing the most pronounced improvements. Differences in some outcomes were also notable between the transcutaneous auricular vagus nerve stimulation and transcranial direct current stimulation groups. Conclusion: The combination of transcutaneous auricular vagus nerve stimulation and transcranial direct current stimulation effectively enhances gait, balance, and daily living activities in subacute stroke patients. These benefits are likely due to transcutaneous auricular vagus nerve stimulation activating the solitary and trigeminal nuclei and transcranial direct current stimulation stimulating the motor cortex. Wearable gait analysis systems and electromyography are valuable in clinical gait assessment for these patients.

Summary: This retrospective study demonstrated that patients with advanced non-small cell lung cancer who experienced any-grade or grade 1–2 immune-related adverse events (irAEs) with immune checkpoint inhibitor plus chemotherapy (ICI+Chemo) as first-line treatment regimen had significantly longer progression-free survival (PFS; p

AimsThis study aimed to evaluate the impact of subsurface drip fertigation (SDF) on soil moisture content, potato growth, and tuber yield in loam soils, and compare these results with conventional surface drip fertigation (CF). The focus was on determining whether SDF could improve water use efficiency and yield quality, particularly in water-scarce regions.MethodsThe experiment was conducted during the 2022 spring growing season in Xunyang, Ankang, Shaanxi Province, China. A randomized complete block design (RCBD) was used with three treatments: subsurface drip fertigation (SDF), conventional surface drip fertigation (CF), and a no-fertilization control (NF), with four replications per treatment. Soil moisture content at a 20 cm depth was monitored, and plant growth parameters such as plant height, stem diameter, leaf color index, and chlorophyll fluorescence index were measured during the flowering and harvest stages. Tuber yield characteristics, including tuber diameter, number of tubers per plant, total yield, and marketable yield, were also assessed.Important findingsThe results indicated that subsurface drip fertigation significantly improved soil moisture content, with up to 45.5% higher moisture retention compared to conventional fertigation, particularly in the early stages of fertilization. This improved moisture availability led to enhanced plant growth and tuber development. Tuber diameter increased by 6.9 mm, and the number of tubers per plant increased by 18.1% under SDF. Marketable tuber yield was approximately 10% higher in the SDF treatment compared to CF. However, the study found that soil texture plays a critical role in the effectiveness of SDF, and further research is needed to explore its application in other soil types.

Since December 2019, coronavirus disease 2019 (COVID-19) has been spreading worldwide with devastating immediate or long-term effects on people’s health. Although the lungs are the primary organ affected by COVID-19, individuals infected with SARS-CoV-2 also develop systemic lesions involving multiple organs throughout the body, such as the cardiovascular system. Emerging evidence reveals that COVID-19 could generate myocardial fibrosis, termed “COVID-19-associated myocardial fibrosis.” It can result from the activation of fibroblasts via the renin-angiotensin-aldosterone system (RAAS), transforming growth factor-β1 (TGF-β1), microRNAs, and other pathways, and can also occur in other cellular interactions with SARS-CoV-2, such as immunocytes, endothelial cells. Nonetheless, to gain a more profound insight into the natural progression of COVID-19-related myocardial fibrosis, additional investigations are necessary. This review delves into the underlying mechanisms contributing to COVID-19-associated myocardial fibrosis while also examining the antifibrotic potential of current COVID-19 treatments, thereby offering guidance for future clinical trials of these medications. Ultimately, we propose future research directions for COVID-19-associated myocardial fibrosis in the post-COVID-19 era, such as artificial intelligence (AI) telemedicine. We also recommend that relevant tests be added to the follow-up of COVID-19 patients to detect myocardial fibrosis promptly.

With potato starch (PS) and corn starch (CS) as the controls, the structure and physicochemical properties of grain amaranth starch (GAS) and its binding with dihydromyricetin were investigated in this study. The results indicated that GAS granules were small in size (3.21 ± 0.13 μm) and had a low amylose content (11.57 ± 0.91%). GAS exhibited low paste clarity, solubility, and swelling power, but demonstrated good freeze-thaw stability and resistance to retrogradation. Although the pasting temperature of GAS was high (75.88 ± 0.03 °C), its peak viscosity, breakdown viscosity, and setback viscosity were significantly lower than those of PS and CS. GAS was classified as A-type starch, with a high molecular weight and broad distribution (Mw, 3.96 × 107 g/mol; PDI, 2.67). For its chain length distribution, chain B1 had the highest proportion (50.09%), while chain B3 had the lowest proportion (13.50%). The complexation of GAS with dihydromyricetin effectively enhanced its ABTS and DPPH free radical scavenging capacities.

Abstract Objective To investigate the extent of knowledge about breastfeeding and attitudes towards infant feeding among spouses of puerperas at the time of discharge from hospital, and explore the factors influencing spousal attitudes toward breastfeeding. Methods We conducted a questionnaire survey among 204 spouses of puerperas who were admitted in the maternity wards at a tertiary hospital in Shaanxi Province between October 2021 and December 2021. Respondents who fulfilled the inclusion criteria were identified using convenient sampling. Results (1) The score of breastfeeding knowledge among spouses prior to discharge from the hospital was (10.56 ± 3.78), with an accuracy rate of 59.6%, and the lowest accuracy rate was for Item 1 “Newborns should be fed on time, not on demand” (42.6%) and Item 5 “Breastfeeding can prevent infant rickets” (49.5%). (2) The average score of spouses’ infant feeding attitudes was (58.15 ± 5.55), and the lowest scoring was for Item 17 “Daily urine volume of infants is a reliable indicator to judge whether they get enough breast milk” (1.99 ± 1.14). (3) Generalized linear model analysis showed a more positive attitude (higher score) among spousal attitudes towards infant feeding in those who had received breastfeeding education [OR = 4.588, 95% CI (0.160 ∼ 3.598)] and those with a master’s degree or above [OR = 18.278, 95% CI (3.471 ∼ 9.346)]. Conclusion (1) Spouses that received breastfeeding education and those that had a Masters Degree and above had more positive attitude towards infant feeding. (2) Medical staff should focus on puerperas’spouses with degrees below master’s level who had not received breastfeeding education. We recommend using a variety of education methods to enable them to acquire more knowledge on breastfeeding and develop a more positive attitude towards breastfeeding, which will further enhance spousal support for breastfeeding, thus positivizing postpartum co-parenting attitudes and improving the rate of exclusive breastfeeding.

Abstract Background The intricate etiology of autoimmune liver disease (AILD) involves genetic, environmental, and other factors that yet to be completely elucidated. This study comprehensively assessed the causal association between genetically predicted modifiable risk factors and AILD by employing Mendelian randomization. Methods Genetic variants associated with 29 exposure factors were obtained from genome-wide association studies (GWAS). Genetic association data with autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) were also obtained from publicly available GWAS. Univariate and multivariate Mendelian randomization analyses were performed to identify potential risk factors for AILD. Results Genetically predicted rheumatoid arthritis (RA) (OR = 1.620, 95%CI 1.423–1.843, P = 2.506 × 10− 13) was significantly associated with an increased risk of AIH. Genetically predicted smoking initiation (OR = 1.637, 95%CI 1.055–2.540, P = 0.028), lower coffee intake (OR = 0.359, 95%CI 0.131–0.985, P = 0.047), cholelithiasis (OR = 1.134, 95%CI 1.023–1.257, P = 0.017) and higher C-reactive protein (CRP) (OR = 1.397, 95%CI 1.094–1.784, P = 0.007) were suggestively associated with an increased risk of AIH. Genetically predicted inflammatory bowel disease (IBD) (OR = 1.212, 95%CI 1.127–1.303, P = 2.015 × 10− 7) and RA (OR = 1.417, 95%CI 1.193–1.683, P = 7.193 × 10− 5) were significantly associated with increased risk of PBC. Genetically predicted smoking initiation (OR = 1.167, 95%CI 1.005–1.355, P = 0.043), systemic lupus erythematosus (SLE) (OR = 1.086, 95%CI 1.017–1.160, P = 0.014) and higher CRP (OR = 1.199, 95%CI 1.019–1.410, P = 0.028) were suggestively associated with an increased risk of PBC. Higher vitamin D3 (OR = 0.741, 95%CI 0.560–0.980, P = 0.036) and calcium (OR = 0.834, 95%CI 0.699–0.995, P = 0.044) levels were suggestive protective factors for PBC. Genetically predicted smoking initiation (OR = 0.630, 95%CI 0.462–0.860, P = 0.004) was suggestively associated with a decreased risk of PSC. Genetically predicted IBD (OR = 1.252, 95%CI 1.164–1.346, P = 1.394 × 10− 9), RA (OR = 1.543, 95%CI 1.279–1.861, P = 5.728 × 10− 6) and lower glycosylated hemoglobin (HbA1c) (OR = 0.268, 95%CI 0.141–0.510, P = 6.172 × 10− 5) were positively associated with an increased risk of PSC. Conclusions Evidence on the causal relationship between 29 genetically predicted modifiable risk factors and the risk of AIH, PBC, and PSC is provided by this study. These findings provide fresh perspectives on the management and prevention strategies for AILD.

In order to investigate the effect of ABP (Agaricus bisporus powder) on the physicochemical properties of yogurt, ABP with different mass fractions (0.0%, 1.5%, 3.0%, 4.5%, 6.0% and 7.5%) was added to yogurt while using yogurt as the raw material, and the rheological and textural properties of yogurt were investigated at different ABP additions. The findings demonstrated that with the addition of ABP at 1.5%, the dynamic viscoelasticity, apparent viscosity, consistency, hardness, and cohesiveness of yogurt were decreased compared with the control group, while the dynamic viscoelasticity, apparent viscosity, consistency, hardness and cohesiveness of yogurt increased with a higher addition of ABP at over 1.5%. Moreover, the scanning electron microscopy results suggested that yogurt with ABP addition at 0.0% and 1.5% showed casein fibrillar network structure with more voids, and with the increase of ABP addition, the voids in the fibrous network were gradually filled by ABP particles, thus forming a dense and continuous spatial structure, which ultimately enhanced the hardness, consistency, and stability of the yogurt. According to the comprehensive analysis, the addition of ABP at 1.5%~3.0% will result in better rheological and textural properties of yogurt. In conclusion, these findings could provide theoretical and data support for the research and development of Agaricus bisporus-flavored dairy products.

In this work, the phase transition process of β-Ga2O3 thin films under heating and (or) electron irradiation condition was investigated by in-situ transmission electron microscopy. It is found that only under the high temperature, β-Ga2O3 did not undergo phase transition even when the temperature was up to 1000 °C. When under electron irradiation condition, the unconventional phase transition from β-Ga2O3 to δ-Ga2O3 occurred with a slow rate. When electron irradiation was coupled with a thermal field, the initial temperature of phase transition decreased, and the speed of phase transition also greatly accelerated. The new phase maintains crystallography relationship with the β-Ga2O3 parent phase as following: [010]β//[011‾]δ, (200)β//(2‾11)δ, and (402‾)β//(411)δ. The results reveal that electron irradiation can trigger the phase transition process from β-Ga2O3 to δ-Ga2O3, and the high temperature obviously accelerates the rate of phase transition process.

Xylitol with different content (0%~25%) was added to glutinous rice flour to construct a xylitol-glutinous rice flour blend system to investigate the effects of xylitol on the gelatinization properties, thermodynamic properties, gel texture, rheology properties and digestion properties of glutinous rice flour, as well as on the quality of rice dumpling made from xylitol-glutinous rice flour. The results showed that the addition of xylitol increased the gelatinization temperature, peak viscosity and final viscosity of the xylitol-glutinous rice flour, while reduced the degree of short-range order of xylitol-glutinous rice flour. The xylitol-glutinous rice flour system behaved as a pseudoplastic fluid with shear thinning behavior. Compared with the control group, when the addition of xylitol was 10%, the xylitol-glutinous rice flour blend system had the smallest retrogradation value and gel hardness, which were 405 cP and 14.952 g, respectively. At this time, the content of resistant starch in the system was 29.88%, showing good retrogradation resistance. However, high content of xylitol (15%~25%) promoted the short-term regeneration of the xylitol-glutinous rice flour blend system, increasing its regeneration value and elasticity. Furthermore, the addition of xylitol significantly reduced the water loss rate and juice permeability of rice dumpling made of xylitol glutinous rice flour. Rice dumpling made of glutinous rice flour with 10% xylitol had high hardness, elasticity, resilience and chewability, and its eating quality was the best. This study provides a theoretical and technical references for the improvement of the quality of glutinous rice flour through xylitol and the product development of glutinous rice flour.

Abstract Chinese media companies are facing opportunities and challenges brought about by digital transformation. Media economics takes the evaluation of the business results of media companies as the main research topic. However, overcoming the internal differences in the industry and comprehensively predicting the digital transformation of Chinese media companies from multiple dimensions has become an important issue to be understood. Based on the “TOE-I” theoretical framework, this study innovatively uses machine learning methods to predict the digital transformation of Chinese media companies and to analyze specific modes of the main driving factors affecting the digital transformation, using data from China’s A-share-listed media companies from 2010 to 2020. The study found that environmental drivers can most effectively and accurately predict the digital transformation of Chinese media companies. Therefore, under sustained and stable economic and financial policies, guiding inter-industry competition and providing balanced digital infrastructure conditions are keys to bridging internal barriers in the media industry and promoting digital transformation. In the process of transformation from traditional content to digital production, media companies should focus on policy changes, economic benefits, the decision-making role of core managers, and the training and preservation of digital technology talent.

Abstract Magnetic skyrmions with nontrivial topologies have great potential to serve as memory cells in novel spintronic devices. Small skyrmions were theoretically and experimentally confirmed to be generated under the influence of external fields in ferrimagnetic films via Dzyaloshinskii–Moriya interactions (DMIs). However, this topological state has yet to be verified in ferrimagnetic crystals, especially in the absence of external fields and DMIs. Here, spontaneous biskyrmions were directly observed in the Tb0.2Gd0.8Co2 ferrimagnetic crystal with a Kagome lattice using Lorentz transmission electron microscopy. The high-density biskyrmions exhibited a small size (approximately 50 nm) over a wide temperature range, were closely related to subtle magnetic interaction competition, and coexisted with some broken stripes that could be easily converted into zero-field biskyrmions by utilizing proper field-cooling manipulation. These results can be used to establish a platform for investigating functional sub-50-nm skyrmions in ferrimagnetic crystals and to facilitate advanced applications in magnetic devices.

Abstract In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional “one-size-fits-all” trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the “Precision Pro”, “Dynamic Precision”, and “Intelligent Precision”. This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Producing chemicals from alternative feedstocks such as biomass is promising route for sustainable manufacturing. In this study, we unravel the reaction mechanism and the nature of the active site for the dehydration of biobased lactic acid to acrylic acid through systematic in-situ diffuse reflectance infrared Fourier transform spectroscopic analysis. We demonstrated that the formation and the stability of lactate as the reaction intermediate on the catalyst surface is crucial to obtain high acrylic acid selectivity. The simultaneous presence of Lewis acid sites and stable lactate intermediates appear to be key in pushing the reaction equilibrium toward dehydration of lactic acid to acrylic acid. We suggest that lactate cannot be formed or is not stable in the presence of BrØnsted acid sites, resulting in low acrylic acid selectivity over HY catalysts. In addition, we have shown that alkali and alkaline-metal modification reduces the number of in-situ generated BrØnsted acid sites, promoting stable lactate intermediate formation and thus inhibiting side reactions catalyzed by BrØnsted acidic sites.

Salt-induced erosion from de-icing salts in Northern China and sea salt in Eastern coastal areas significantly compromises asphalt pavement integrity. A selection was made of four different types of foamed asphalt with different levels of water content, two types of aged asphalt, and three typical minerals (α-quartz, calcite, and bauxite), in addition to three chloride salt solutions (NaCl, CaCl2, MgCl2). It was found that (1) in dry conditions, the moisture level of foamed asphalt noticeably influences the adhesive performance at the juncture between asphalt and aggregates. Unlike acidic minerals, the bond strength between alkaline and neutral minerals and foamed asphalt increases as the water content of the foamed asphalt rises; (2) chloride salt solutions presence and increased levels significantly reduced the bond strength between asphalt and aggregates, particularly impacting neutral and alkaline minerals (in the presence of 10 % NaCl solution, the work of adhesion was reduced by 83.82 % and 87.48 %, respectively); (3) the influence of diverse chloride salts on the interfacial adhesive performance of asphalt mixtures varied, with the three chloride salts reducing the asphalt-aggregate interfacial adhesion work by 44.52 %, 21.90 %, and 34.94 %, respectively. (4) the investigation determined that the mineral composition considerably influences the hygroscopic sensitivity of asphalt mixtures. Minerals of an acidic nature exhibit superior moisture resistance when juxtaposed with alkaline counterparts, recommending the adoption of acidic aggregates in scenarios demanding elevated mixture stability.

BackgroundLower urinary tract symptoms (LUTS) are clinically frequent and seriously affect the psychological and mental health of children and adolescents. However, most studies on LUTS and its influence on the psychological behavior and mental health have focused on adults. This study aimed to investigate LUTS prevalence and associated factors in children and adolescents and explore its impact on psychological behavior.Materials and methodsFrom October 2019 to November 2021, an epidemiological LUTS survey was carried out on 6,077 children aged 6–15 years old in 12 primary and secondary schools in China by using anonymous questionnaires.ResultsA total of 5,500 valid questionnaires were collected, and the total prevalence of four representative symptoms of LUTS: urgency, frequency, daytime urinary incontinence, and nocturnal enuresis was 19.46%, 14.55%, 9.75%, and 8.4%, respectively. The prevalence decreased with age, which decreased rapidly in children aged 6–12 years old. The incidence of LUTS in those who did not continue to use disposable diapers (DD) and began to perform elimination communication (EC) after the age of 1 was significantly higher than that of those who stopped using DD and started EC before 1 year of age (P

Abstract Gene editing is a growing gene engineering technique that allows accurate editing of a broad spectrum of gene‐regulated diseases to achieve curative treatment and also has the potential to be used as an adjunct to the conventional treatment of diseases. Gene editing technology, mainly based on clustered regularly interspaced palindromic repeats (CRISPR)–CRISPR‐associated protein systems, which is capable of generating genetic modifications in somatic cells, provides a promising new strategy for gene therapy for a wide range of human diseases. Currently, gene editing technology shows great application prospects in a variety of human diseases, not only in therapeutic potential but also in the construction of animal models of human diseases. This paper describes the application of gene editing technology in hematological diseases, solid tumors, immune disorders, ophthalmological diseases, and metabolic diseases; focuses on the therapeutic strategies of gene editing technology in sickle cell disease; provides an overview of the role of gene editing technology in the construction of animal models of human diseases; and discusses the limitations of gene editing technology in the treatment of diseases, which is intended to provide an important reference for the applications of gene editing technology in the human disease.

ObjectiveThis study aims to evaluate the effectiveness of Integrated Soil-Crop System Management (ISSM) and provide technical support for sustainable high yield and efficiency in regional agriculture.MethodsThe study compared the effects of no fertilization (Control), conventional farmer practices (FP), high-yield management (HY), and ISSM on maize yield and plant nutrient uptake. Measurements included grain yield, plant biomass, plant nutrient absorption, and soil nutrient content across different management strategies.ResultsOver the 12-year experimental period, a significant decline in grain yield was observed under the Control treatment, with a slight decrease in the FP treatment. In contrast, consistent yield increases were noted for the HY and ISSM treatments. The ISSM approach significantly enhanced the average yield and plant uptake of P and K by 26%, 24%, and 32%, respectively, approaching 98%, 91%, and 85% of the levels achieved in the HY treatment. Furthermore, the average use efficiency of P and K fertilizers in the ISSM treatment exceeded those in the FP treatment by 18.7% and 1.2%, respectively, and those in the HY treatment by 17.4% and 24.8%, respectively. The adoption of ISSM led to a significant increase in total and available P and K content within the 0–20 cm and 20–40 cm soil layers and enhanced the available P and K content across all aggregate size fractions within the 0–20 cm soil layer.ConclusionISSM is capable of achieving long-term high and stable yields for spring maize, enhancing the uptake and utilization of P and K in plants, and bolstering the soil’s capacity to supply these nutrients, thereby fostering the sustainable development of the entire soil-crop system.

Background: We aimed to demonstrate the function of premelanosome protein (PMEL) as a biomarker to predict the effectiveness of mammalian target of rapamycin complex 1 (mTORC1) inhibitor treatment in renal angiomyolipomas (RAMLs) in tuberous sclerosis complex (TSC) patients. Methods: 95 whole blood samples from 49 patients diagnosed with TSC-RAMLs were collected. PMEL, N4BP2, and PCSK1N expression in the plasma samples were tested by quantitative sandwich ELISA. The target tumor volume assessed by maximum cross-sectional area (CSAmax) in CT scans. Correlation analysis was used to determine the relationship between PMEL expression and target tumors, as well as the tumor reduction rate. Results: The tumor size of TSC-RAMLs positivity correlated with PMEL expression (r = 0.30, p = 0.036) and PCSK1N expression (r = 0.23, p = 0.027), but had no significant relationship with N4BP2 (r = 0.06, p = 0.89). The positive correlation between TSC-RAML tumor volume and PMEL expression still existed in TSC patients before (r = 0.30, p = 0.026) and after mTORC1 inhibitor treatment (r = 0.41, p = 0.0017), but the correlation between tumor volume and PCSK1N expression no longer existed. Further analysis found that PMEL expression negatively correlated with the reduction rate of TSC-RAMLs after mTORC1 inhibitor treatment (r = −0.50, p = 0.0022), both after 3 months (r = −0.47, p = 0.048) and 6 months of treatment (r = −0.52, p = 0.028). Conclusion: PMEL expression positively correlated with the tumor size of TSC-RAMLs, and inversely with the reduction rate of TSC-RAMLs after mTORC1 inhibitor treatment, which may suggest that PMEL may serve as a predictive biomarker for the efficacy of mTORC1 inhibitor treatment.

ABSTRACT In previous studies, we developed a novel fusion protein named “melittin‐MIL‐2” which exhibited more anti‐tumor activity. However, it remains unclear whether melittin‐MIL‐2 possesses antitumor immune effect on lung adenocarcinoma. In this study, the immune effect and mechanism of melittin‐MIL‐2 inhibiting the growth and invasion of lung adenocarcinoma will be investigated, in order to provide novel perspectives for the immunotherapy of lung cancer. The results indicated that melittin‐MIL‐2 promoted T cell proliferation, enhanced NK cell cytotoxicity, and boosted IFN‐γ secretion in PBMCs. After melittin‐MIL‐2 stimulation, perforin expression and LAK/NK‐like killing activities of human PBMCs and NK cells were significantly enhanced. Melittin‐MIL‐2 is capable of hampering the development and proliferation of lung adenocarcinoma cell A549. ICAM‐1 and Fas expression in A549 cells exposed to melittin‐MIL‐2 rose significantly. The expression levels of TLR8 and VEGF in A549 cells decreased significantly after melittin‐MIL‐2 stimulation. In vivo, melittin‐MIL‐2 substantially impeded the growth of lung adenocarcinoma and formed an immune‐stimulating microenvironment locally in tumor tissues. In conclusion, the novel fusion protein melittin‐MIL‐2 exhibits strong anti‐tumor immune effect in lung adenocarcinoma cell A549 via activating the LFA‐1/ICAM‐1 and Fas/FasL pathways to enhance cytolytic activity, upregulating the secretion of IFN‐γ and perforin, and boosting LAK/NK‐like killing activities. Immuno‐effector cells and their secreted cytokines can form immune stimulation microenvironment locally in lung adenocarcinoma Lewis mice tissue.

Background Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment.Methods The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer.Results A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group.Conclusions High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

PurposeThe purpose of this study was to reveal the treatment preferences and current practices regarding open tibial shaft fracture (OTSF).Patients and methodsOnline surveys of treatment preferences and current practice of OTSF were conducted by orthopedic trauma doctors from various medical institutions in Zhejiang Province. The survey contains three modules. The first module is the basic information of the participants, the second module is the treatment patterns for Gustilo-Anderson type I-II (GA I/II), and the third module is the treatment patterns for Gustilo-Anderson type IIIA (GA IIIA). Furthermore, each treatment pattern was divided into four aspects, including antibiotic prophylaxis, irrigation and debridement, fracture stabilization, and wound management.ResultsA total of 132 orthopedic trauma doctors from 41 hospitals in Zhejiang province, participated the online surveys. In GA I-IIIA OTSF, more than three-quarters of participants considered

Abstract Phosphate solubilizing fungi Penicillium oxalicum (POX) and Red yeast Rhodotorula mucilaginosa (Rho) have been applied in Pb remediation with the combination of fluorapatite (FAp), respectively. The secretion of oxalic acid by POX and the production of extracellular polymers (EPS) by Rho dominate the Pb remediation. In this study, the potential of Pb remediation by the fungal combined system (POX and Rho) with FAp was investigated. After six days of incubation, the combination of POX and Rho showed the highest Pb remove ratio (99.7%) and the lowest TCLP-Pb concentration (2.9 mg/L). The EPS combined with POX also enhanced Pb remediation, which has a 99.3% Pb removal ratio and 5.5 mg/L TCLP-Pb concentration. Meanwhile, Rho and EPS can also stimulate POX to secrete more oxalic acid, which reached 1510.1 and 1450.6 mg/L in six days, respectively. The secreted oxalic acid can promote FAp dissolution and the formation of lead oxalate and pyromorphite. Meanwhile, the EPS produced by Rho can combine with Pb to form EPS-Pb. In the combined system of POX + Rho and POX + EPS, all of the lead oxalate, pyromorphite, and EPS-Pb were observed. Our findings suggest that the combined application of POX and Rho with FAp is an effective approach for enhancing Pb remediation.

Abstract Accurate labeling of lung nodules in computed tomography (CT) images is crucial in early lung cancer diagnosis and before nodule resection surgery. However, the irregular shape of lung nodules in CT images and the complex lung environment make it much more challenging to segment lung nodules accurately. On this basis, we propose an improved V-Net segmentation method based on pixel threshold separation and attention mechanism for lung nodules. This method first offers a data augment strategy to solve the problem of insufficient samples in 3D medical datasets. In addition, we integrate the feature extraction module based on pixel threshold separation into the model to enhance the feature extraction ability under different thresholds on the one hand. On the other hand, the model introduces channel and spatial attention modules to make the model pay more attention to important semantic information and improve its generalization ability and accuracy. Experiments show that the Dice similarity coefficients of the improved model on the public datasets LUNA16 and LNDb are 94.9% and 81.1% respectively, and the sensitivities reach 92.7% and 76.9% respectively. which is superior to most existing UNet architecture models and comparable to the manual level segmentation results by medical technologists.

Due to the sheer volume and variety of data in industrial manufacturing, manually creating features can be costly. Therefore, appropriate feature processing methods become crucial. Most existing feature processing methods abstract feature engineering as a feature search problem, i.e., finding feature transformations that optimize model performance. However, for automated feature engineering, the number of searches and the number of transformation combinations are huge. Therefore, we use a factorization-based model that measures interactions in terms of vector products, automatically learns patterns of combined features, and generalizes them to unseen features. Prior to this paper, the DeepFM algorithm (which combines an FM model with a deep neural network model) and the xDeepFM algorithm (which proposes a novel Compressed Interaction Network (CIN) designed to make feature interactions explicit) were available. The LRCIN proposed in this paper focuses on improving the CIN network in the xDeepFM method, by introducing a low-rank approximation method in the CIN network to reduce the number of parameters, and adding an attention mechanism after the CIN to ensure the accuracy of the model. The experimental results show that our method can effectively reduce the time complexity of the model and improve the model accuracy to some extent.

Abstract Background Hair follicle stem cells (HFSCs) typically remain quiescent and are activated only during the transition from telogen to anagen to ensure that the hair follicle enters a new cycle. The metabolic behavior of stem cells in tissues is regulated by macroautophagy/autophagy, and changes in HFSC metabolism directly affect their activation and maintenance. However, the role of autophagy in the regulation of HFSC metabolism and function remains unclear. Methods Back skin samples were obtained from mice at different hair follicle cycle stages, and immunofluorescence staining was used to monitor autophagy in HFSCs. Mouse and human hair follicles were treated with rapamycin (Rapa, an autophagy activator) or 3-methyladenine (3-MA, an autophagy inhibitor). The effects of autophagy on the hair follicle cycle and HFSC were investigated by imaging, cell proliferation staining, and HFSC-specific marker staining. The influence and mechanism of autophagy on HFSC metabolism were explored using RNA sequencing, real-time polymerase chain reaction, immunohistochemical staining, and detection of lactate and glucose concentrations. Finally, the influence of autophagy-induced glycolysis on HFSC and the hair follicle cycle was verified by stem cell characteristics and in vivo functional experiments. Results Autophagy in HFSC was highest during the transition from telogen to anagen. Inhibiting autophagy with 3-MA led to early entry into catagen and prolonged telogen, whereas Rapa promoted autophagy and hair growth. Autophagy activated HFSC by increasing the expression and activity of HFSC lactate dehydrogenase (Ldha), thereby transforming HFSC metabolism into glycolysis. Inhibition of Ldha expression counteracted the effects of autophagy. Conclusions Autophagy activated HFSC by promoting the transition from HFSC metabolism to glycolysis, ultimately initiating the hair follicle cycle and promoting hair growth. Graphical Abstract

The unearthed artifacts from the ruins of the Weiyang Palace in the Han Dynasty’s Chang’an City include a large number of bone stick relics. The front and back of each bone stick form a pair, with similar appearances within each pair, indicating a matching relationship. However, the close resemblance in shape and complex texture features of the bone sticks make traditional image matching methods inefficient and less accurate. To address these challenges, this paper proposes a ConvNeXt-based Siamese network for bone stick image matching, utilizing feature similarity metrics. The method introduces a polarized self-attention module to enhance the model’s focus on the edges and texture features of the bone sticks, thereby improving the feature extraction capability of the ConvNeXt network. The utilization of DIS-Net for background normalization reduces noise interference, enhancing the precision of model matching. The adaptive adjustment of the learning rate using the cosine annealing algorithm accelerates network convergence. Additionally, transfer learning and contrastive learning methods are employed to pre-train the network, expediting convergence and improving matching accuracy. Experimental results demonstrate that compared to Siamese network algorithms with backbone networks such as VGG16, ResNet50, and MobileNet, the proposed method achieves an accuracy of 88.46% and 80% at Rank-10. This indicates a higher matching accuracy, providing an effective solution for automated bone stick matching.

Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and poor performance in multi-class classification tasks. To overcome these challenges, we proposed the Swin Routiformer, a new algorithm for moss image classification that enhances the Swin Transformer with bi-level routing attention. Addressing the issue of limited data, we constructed a dataset with images of 110 different moss types. Additionally, we propose the Crop-Similar data augmentation algorithm, specifically designed for moss images, to reduce background noise interference and prevent information loss due to feature scaling. Adopting the Swin Transformer model with its multi-level hierarchical architecture for visual feature extraction, we introduce the Swin Routiformer Block, which enhances the network’s feature interaction capabilities, reduces computational complexity, and improves classification accuracy and image processing speed for moss species. Our experimental results show that the Swin Routiformer achieves a top-1 accuracy of 82.19% and an f1-score of 82.79% on the test set, outperforming most mainstream models by 4.53% and 1.81% respectively compared to the baseline Swin Transformer model. These findings establish the Swin Routiformer as a valuable tool for the precise identification of moss species, offering significant contributions to the related fields.

The prediction of drug properties plays a vital role in drug research. However, the drug property prediction accuracy of traditional methods is limited due to their inability to fully capture molecular structure and function information. As a result, the use of graph neural networks has attracted significant attention as an effective drug property prediction approach. Nevertheless, traditional graph neural networks still exhibit certain drawbacks in this regard, including their disregard of the interaction information between nodes and edges, the loss of local information during global pooling operations, and the absence of feature fusion mechanisms. This study proposes an enhanced graph neural network (GNN) model that incorporates an attention mechanism, multiscale pooling, an adaptive weight generator, and an activation function to predict drug properties. A comparative analysis with the conventional graph neural network model reveals significant improvements in terms of predicting the side effects of drugs on the heart and liver, with increases of 1%, 7%, and 13%. Furthermore, the enhanced graph neural network model exhibits good performance across the remaining two datasets. Empirical findings underscore the efficacy of the model in drug property prediction tasks, and it is characterized by enhanced predictive precision and robust performance outcomes.