PGD: Shared gene linking polycystic ovary syndrome and endometrial cancer, influencing proliferation and migration through glycometabolism.

The relationship among polycystic ovary syndrome (PCOS), endometrial cancer (EC), and glycometabolism remains unclear. We explored shared genes between PCOS and EC, using bioinformatics to unveil their pathogenic connection and influence on EC prognosis. Gene Expression Omnibus datasets GSE226146 (PCOS) and GSE196033 (EC) were used. A protein-protein interaction (PPI) network was constructed to identify the central genes. Candidate markers were screened using dataset GSE54250. Differences in marker expression were confirmed in mouse PCOS and human EC tissues using RT-PCR and immunohistochemistry. The effect of PGD on EC proliferation and migration was explored using Ki-67 and Transwell assays. PGD's impact on the glycometabolic pathway within carbon metabolism was assessed by quantifying glucose content and lactic acid production. R software identified 31 common genes in GSE226146 and GSE196033. Gene Ontology functional classification revealed enrichment in the "purine nucleoside triphosphate metabolism process," with key Kyoto Encyclopedia of Genes and Genomes pathways related to "carbon metabolism." The PPI network identified 15 hub genes. HK2, NDUFS8, PHGDH, PGD, and SMAD3 were confirmed as candidate markers. The RT-PCR analysis validated distinct HK2 and PGD expression patterns in mouse PCOS ovarian tissue and human EC tissue, as well as in normal and EC cells. Transfection experiments with Ishikawa cells further confirmed PGD's influence on cell proliferation and migration. Suppression of PGD expression impeded glycometabolism within the carbon metabolism of EC cells, suggesting PGD as a significant PCOS risk factor impacting EC proliferation and migration through modulation of single carbon metabolism. These findings highlight PGD's pivotal role in EC onset and prognosis.

Photoinduced copper catalyzed nitrogen-to-alkyl radical relay Sonogashira-type coupling of o-alkylbenzamides with alkynes.

This report describes a copper-catalyzed, photoinduced N-to-alkyl radical relay Sonogashira-type reactions at benzylic sites in o-alkylbenzamides with alkynes. The process employs an N-to-alkyl radical mechanism, initiated through the copper-catalyzed reductive generation of nitrogen radicals. Radical translocation is facilitated by a 1,5-hydrogen atom transfer (1,5-HAT), leading to the formation of translocated carbon radicals. These radicals are then subjected to copper-catalyzed alkynylation. The methodology exhibits broad sub-strate scope and applicability to the synthesis of complex natural products.

Integrating mRNA transcripts and genomic information into genomic prediction.

Genomic prediction has emerged as a pivotal technology for the genetic evaluation of livestock, crops, and for predicting human disease risks. However, classical genomic prediction methods face challenges in incorporating biological prior information such as the genetic regulation mechanisms of traits. This study introduces a novel approach that integrates mRNA transcript information to predict complex trait phenotypes. To evaluate the accuracy of the new method, we utilized a Drosophila population that is widely employed in quantitative genetics researches globally. Results indicate that integrating mRNA transcript data can significantly enhance the genomic prediction accuracy for certain traits, though it does not improve phenotype prediction accuracy for all traits. Compared with GBLUP, the prediction accuracy for olfactory response to dCarvone in male Drosophila increased from 0.256 to 0.274. Similarly, the accuracy for cafe in male Drosophila rose from 0.355 to 0.401. The prediction accuracy for survival_paraquat in male Drosophila is improved from 0.101 to 0.138. In female Drosophila, the accuracy of olfactory response to 1hexanol increased from 0.147 to 0.210. In conclusion, integrating mRNA transcripts can substantially improve genomic prediction accuracy of certain traits by up to 43%, with range of 7% to 43%. Furthermore, for some traits, considering interaction effects along with mRNA transcript integration can lead to even higher prediction accuracy.

A through-space charge transfer pyrene-based fluorophore with anti-quenching behavior for deep-blue organic light-emitting devices.

A through-space charge transfer pyrene-based fluorophore has been developed for organic light-emitting devices (OLEDs). This material exhibits deep-blue fluorescence, bipolar characteristics, and anti-quenching behavior in the solid state. It proves to be an effective emitter for both doped and nondoped deep-blue OLEDs.

Probing the Structural and Electronic Properties of the Anionic and Neutral Tellurium-Doped Boron Clusters TeBnq (n = 3-16, q = 0, -1).

In this study, we employ density functional theory along with the artificial bee colony algorithm for cluster global optimization to explore the low-lying structures of TeBnq (n = 3-16, q = 0, -1). The primary focus is on reporting the structural properties of these clusters. The results reveal a consistent doping pattern of the tellurium atom onto the in-plane edges of planar or quasi-planar boron clusters in the most energetically stable isomers. Additionally, we simulate the photoelectron spectra of the cluster anions. Through relative stability analysis, we identify three clusters with magic numbers -TeB7-, TeB10, and TeB12. The aromaticity of these clusters is elucidated using adaptive natural density partitioning (AdNDP) and magnetic properties analysis. Notably, TeB7- exhibits a perfect σ-π doubly aromatic structure, while TeB12 demonstrates strong island aromaticity. These findings significantly contribute to our understanding of the structural and electronic properties of these clusters.

TAX1BP1 and FIP200 orchestrate non-canonical autophagy of p62 aggregates for mouse neural stem cell maintenance.

Autophagy plays a pivotal role in diverse biological processes, including the maintenance and differentiation of neural stem cells (NSCs). Interestingly, while complete deletion of Fip200 severely impairs NSC maintenance and differentiation, inhibiting canonical autophagy via deletion of core genes, such as Atg5, Atg16l1, and Atg7, or blockade of canonical interactions between FIP200 and ATG13 (designated as FIP200-4A mutant or FIP200 KI) does not produce comparable detrimental effects. This highlights the likely critical involvement of the non-canonical functions of FIP200, the mechanisms of which have remained elusive. Here, utilizing genetic mouse models, we demonstrated that FIP200 mediates non-canonical autophagic degradation of p62/sequestome1, primarily via TAX1BP1 in NSCs. Conditional deletion of Tax1bp1 in fip200 hGFAP conditional knock-in (cKI) mice led to NSC deficiency, resembling the fip200 hGFAP conditional knockout (cKO) mouse phenotype. Notably, reintroducing wild-type TAX1BP1 not only restored the maintenance of NSCs derived from tax1bp1-knockout fip200 hGFAP cKI mice but also led to a marked reduction in p62 aggregate accumulation. Conversely, a TAX1BP1 mutant incapable of binding to FIP200 or NBR1/p62 failed to achieve this restoration. Furthermore, conditional deletion of Tax1bp1 in fip200 hGFAP cKO mice exacerbated NSC deficiency and p62 aggregate accumulation compared to fip200 hGFAP cKO mice. Collectively, these findings illustrate the essential role of the FIP200-TAX1BP1 axis in mediating the non-canonical autophagic degradation of p62 aggregates towards NSC maintenance and function, presenting novel therapeutic targets for neurodegenerative diseases.

A prediction nomogram for fractured vertebra re-collapse after posterior reduction and pedicle screw fixation in thoracolumbar fractures.

OBJECTIVE: This study aimed to establish a predictive nomogram model for re-collapse of fractured vertebra after posterior pedicle screw fixation in thoracolumbar fractures (TLFs). METHODS: Patients undergoing posterior pedicle screw fixation for TLFs at our hospital between January 2016 and December 2021 were retrospectively reviewed. Patients were divided into two groups according to the presence or absence of re-collapse of the fractured vertebra at the final follow-up. The predictors for fractured vertebra re-collapse were identified by univariate and multivariable logistic regression analysis, and a nomogram model was developed. The prediction performance and internal validation were established. RESULTS: A total of 224 patients were included in this study. Of these, 46 (20.5%) patients developed re-collapse of fractured vertebra. Age, thoracic and lumbar injury severity score (TLICS), screw distribution in the fractured vertebra, and anterior vertebral height compression (AVHC) ratio were associated with vertebral re-collapse. These predictors were used to construct a predictive nomogram. The area under the receiver operating characteristic curve (AUC) of the nomogram model was 0.891. The concordance index (C-index) was 0.891, and it was 0.877 with bootstrapping validation. The calibration curves and decision curve analysis (DCA)also suggested that the nomogram model had excellent predictive performances for fractured vertebra re-collapse. CONCLUSIONS: A clinical nomogram incorporating four variables was constructed to predict fractured vertebra re-collapse after posterior pedicle screw fixation for TLFs. The nomogram demonstrated good calibration and discriminative abilities, which may help clinicians to make better treatment decisions.

Curcumin-activated Wnt5a pathway mediates Ca2+ channel opening to affect myoblast differentiation and skeletal muscle regeneration.

BACKGROUND: Skeletal muscle injury is one of the most common sports injuries; if not properly treated or not effective rehabilitation treatment after injury, it can be transformed into chronic cumulative injury. Curcumin, an herbal ingredient, has been found to promote skeletal muscle injury repair and regeneration. The Wnt5a pathway is related to the expression of myogenic regulatory factors, and Ca2+ promotes the differentiation and fusion process of myoblasts. This study explored the effect and mechanism of curcumin on myoblast differentiation during the repair and regeneration of injured skeletal muscle and its relationship with the Wnt5a pathway and Ca2+ channel. METHODS: Myogenic differentiation of C2C12 cells was induced with 2% horse serum, and a mouse (male, 10 weeks old) model of acute skeletal muscle injury was established using cardiotoxin (20 µL). In addition, we constructed a Wnt5a knockdown C2C12 cell model and a Wnt5a knockout mouse model. Besides, curcumin was added to the cell culture solution (80 mg/L) and fed to the mice (50 mg/kg). Fluorescence microscopy was used to determine the concentration of Ca2+. Western blot and RT-qPCR were used to detect the protein and mRNA levels of Wnt5a, CaN, NFAT2, MyoD, Myf5, Pax7, and Myogenin. The expression levels of MyoD, Myf5, Myogenin, MHC, Desmin, and NFAT2 were detected using immunofluorescence techniques. In addition, MyoD expression was observed using immunohistochemistry, and morphological changes in mouse muscle tissue were observed using HE staining. RESULTS: During myoblast differentiation and muscle regeneration, Wnt5a expression was upregulated (P < 0.001) and the Wnt5a signalling pathway was activated. Wnt5a overexpression promoted the expression of MyoD, Myf5, Myogenin, MHC, and Desmin (P < 0.05), and conversely, knockdown of Wnt5a inhibited their expression (P < 0.001). The Wnt5a pathway mediated the opening of Ca2+ channels, regulated the expression levels of CaN, NFAT2, MyoD, Myf5, Myogenin, MHC, and Desmin (P < 0.01) and promoted the differentiation of C2C12 myoblasts and the repair and regeneration of injured skeletal muscle. The expression of Wnt5a, CaN, NFAT2, MyoD, Myogenin, Myf5, and MHC in C2C12 myoblast was significantly increased after curcumin intervention (P < 0.05); however, their expression decreased significantly after knocking down Wnt5a on the basis of curcumin intervention (P < 0.05). Similarly, in Wnt5a knockout mice, the promotion of muscle regeneration by curcumin was significantly attenuated. CONCLUSIONS: Curcumin can activate the Wnt5a signalling pathway and mediate the opening of Ca2+ channels to accelerate the myogenic differentiation of C2C12 cells and the repair and regeneration of injured skeletal muscle.

Orientation selectivity mapping in the visual cortex.

The orientation map is one of the most well-studied functional maps of the visual cortex. However, results from the literature are of different qualities. Clear boundaries among different orientation domains and blurred uncertain distinctions were shown in different studies. These unclear imaging results will lead to an inaccuracy in depicting cortical structures, and the lack of consideration in experimental design will also lead to biased depictions of the cortical features. How we accurately define orientation domains will impact the entire field of research. In this study, we test how spatial frequency (SF), stimulus size, location, chromatic, and data processing methods affect the orientation functional maps (including a large area of dorsal V4, and parts of dorsal V1) acquired by intrinsic signal optical imaging. Our results indicate that, for large imaging fields, large grating stimuli with mixed SF components should be considered to acquire the orientation map. A diffusion model image enhancement based on the difference map could further improve the map quality. In addition, the similar outcomes of achromatic and chromatic gratings indicate two alternative types of afferents from LGN, pooling in V1 to generate cue-invariant orientation selectivity.

Multisystem inflammatory syndrome in neonates (MIS-N): an updated systematic review.

Introduction: The aim of the study was to summarize and update clinical features and outcomes of multisystem inflammatory syndrome in neonates (MIS-N). Methods: A systematic literature search was conducted of studies on MIS-N published in PubMed, MEDLINE, EMBASE, CNKI, and WHO COVID-19 databases between 1 December 2019 and 30 June 2023. Reference lists of selected articles, Google Scholar, and pre-print servers were searched for additional studies. The methodological quality of included studies was assessed. Results: Of 1,572 records screened after the initial search, 35 studies involving a total of 201 neonates with MIS-N were included. One study was retrieved from a pre-print server. For those with available data, 34/47 (78.7%) mothers were infected in the third trimester. Of the 199 mothers (two with twin pregnancies), 183 (92.0%) were from India. The median age of neonates at presentation was 2.0 days (interquartile range 1.0-9.5). Over two-thirds (144/201, 71.6%) presented with respiratory distress, while 112 (55.7%) had cardiac involvement, such as ventricular dysfunctions, involvement of coronary arteries, and atrioventricular blocks. Arrhythmias and thrombosis were reported in 15/201 (7.5%) and 2/201 (3.0%) neonates, respectively. All neonates, except one, required critical care; 64/160 (40.0%) required inotropic support and 105/187 (56.1%) required respiratory support, of whom 59/105 (56.2%) were specified to require intubation. The mortality rate was 5.0% (10/201). Discussion/Conclusion: MIS-N should be considered in ill neonates presenting with involvement of two or more organ systems, especially among those neonates with cardiorespiratory dysfunctions, in the presence of proven or suspected maternal COVID-19 infection during pregnancy. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021278717, PROSPERO, identifier CRD42021278717.

Nanofillers in Novel Food Packaging Systems and Their Toxicity Issues.

Background: Environmental concerns about petroleum-based plastic packaging materials and the growing demand for food have inspired researchers and the food industry to develop food packaging with better food preservation and biodegradability. Nanocomposites consisting of nanofillers, and synthetic/biopolymers can be applied to improve the physiochemical and antimicrobial properties and sustainability of food packaging. Scope and approach: This review summarized the recent advances in nanofiller and their applications in improved food packaging systems (e.g., nanoclay, carbon nanotubes), active food packaging (e.g., silver nanoparticles (Ag NPs), zinc oxide nanoparticles (ZnO NPs)), intelligent food packaging, and degradable packaging (e.g., titanium dioxide nanoparticles (e.g., TiO2 NPs)). Additionally, the migration processes and related assessment methods for nanofillers were considered, as well as the use of nanofillers to reduce migration. The potential cytotoxicity and ecotoxicity of nanofillers were also reviewed. Key findings: The incorporation of nanofillers may increase Young's modulus (YM) while decreasing the elongation at break (EAB) (y = -1.55x + 1.38, R2 = 0.128, r = -0.358, p = 0.018) and decreasing the water vapor (WVP) and oxygen permeability (OP) (y = 0.30x - 0.57, R2 = 0.039, r = 0.197, p = 0.065). Meanwhile, the addition of metal-based NPs could also extend the shelf-life of food products by lowering lipid oxidation by an average of approx. 350.74% and weight loss by approx. 28.39% during the longest storage period, and significantly increasing antibacterial efficacy against S. aureus compared to the neat polymer films (p = 0.034). Moreover, the migration process of nanofillers may be negligible but still requires further research. Additionally, the ecotoxicity of nanofillers is unclear, as the final distribution of nanocomposites in the environment is unknown. Conclusions: Nanotechnology helps to overcome the challenges associated with traditional packaging materials. Strong regulatory frameworks and safety standards are needed to ensure the appropriate use of nanocomposites. There is also a need to explore how to realize the economic and technical requirements for large-scale implementation of nanocomposite technologies.

Pioneering Data Processing for Convolutional Neural Networks to Enhance the Diagnostic Accuracy of Traditional Chinese Medicine Pulse Diagnosis for Diabetes.

Traditional Chinese medicine (TCM) has relied on pulse diagnosis as a cornerstone of healthcare assessment for thousands of years. Despite its long history and widespread use, TCM pulse diagnosis has faced challenges in terms of diagnostic accuracy and consistency due to its dependence on subjective interpretation and theoretical analysis. This study introduces an approach to enhance the accuracy of TCM pulse diagnosis for diabetes by leveraging the power of deep learning algorithms, specifically LeNet and ResNet models, for pulse waveform analysis. LeNet and ResNet models were applied to analyze TCM pulse waveforms using a diverse dataset comprising both healthy individuals and patients with diabetes. The integration of these advanced algorithms with modern TCM pulse measurement instruments shows great promise in reducing practitioner-dependent variability and improving the reliability of diagnoses. This research bridges the gap between ancient wisdom and cutting-edge technology in healthcare. LeNet-F, incorporating special feature extraction of a pulse based on TMC, showed improved training and test accuracies (73% and 67%, respectively, compared with LeNet's 70% and 65%). Moreover, ResNet models consistently outperformed LeNet, with ResNet18-F achieving the highest accuracy (82%) in training and 74% in testing. The advanced preprocessing techniques and additional features contribute significantly to ResNet18-F's superior performance, indicating the importance of feature engineering strategies. Furthermore, the study identifies potential avenues for future research, including optimizing preprocessing techniques to handle pulse waveform variations and noise levels, integrating additional time-frequency domain features, developing domain-specific feature selection algorithms, and expanding the scope to other diseases. These advancements aim to refine traditional Chinese medicine pulse diagnosis, enhancing its accuracy and reliability while integrating it into modern technology for more effective healthcare approaches.

[Study on Down-regulation of Interleukin-1ß Secretion by Inhibiting ABCC1/MRP1 Transporter].

OBJECTIVE: To screen interleukin (IL)-1ß secretion-related membrane transporters by macrophage experiment in vitro and conventional knockout mice. METHODS: THP-1 cell line was differentiated to obtain human THP-1-derived macrophages, and the primary macrophages were obtained from human peripheral blood. FVB wild-type mice with the same sex and age were used as the controls of MRP1 knockout mice. The macrophages in abdominal cavity and bone marrow of mice were cultivated. The cells were treated with ABCC1/MRP1, ABCG2/BCRP, ABCB1/P-gp, OATP1B1, and MATE transporter inhibitors, then stimulated by lipopolysaccharide and adenosine triphosphate. The secretion level of IL-1ß was detected by ELISA, Western blot, and immunofluorescence. RESULTS: After inhibiting ABCC1/MRP1 transporter, the secretion of IL-1ß decreased significantly, while inhibition of the other 4 transporters had no effect. In animal experiment, the level of IL-1ß secreted by macrophages in bone marrow of MRP1 knockout mice was significantly lower than control group (P < 0.05). CONCLUSION: ABCC1/MRP1 transporter is a newly discovered IL-1ß secretion pathway, which is expected to become a new target for solving clinical problems such as cytokine release syndrome.

Transcriptomic and physiological analysis provide new insight into seed shattering mechanism in Pennisetum alopecuroides 'Liqiu'.

KEY MESSAGE: Through the histological, physiological, and transcriptome-level identification of the abscission zone of Pennisetum alopecuroides 'Liqiu', we explored the structure and the genes related to seed shattering, ultimately revealing the regulatory network of seed shattering in P. alopecuroides. Pennisetum alopecuroides is one of the most representative ornamental grass species of Pennisetum genus. It has unique inflorescence, elegant appearance, and strong stress tolerance. However, the shattering of seeds not only reduces the ornamental effect, but also hinders the seed production. In order to understand the potential mechanisms of seed shattering in P. alopecuroides, we conducted morphological, histological, physiological, and transcriptomic analyses on P. alopecuroides cv. 'Liqiu'. According to histological findings, the seed shattering of 'Liqiu' was determined by the abscission zone at the base of the pedicel. Correlation analysis showed that seed shattering was significantly correlated with cellulase, lignin, auxin, gibberellin, cytokinin and jasmonic acid. Through a combination of histological and physiological analyses, we observed the accumulation of cellulase and lignin during 'Liqiu' seed abscission. We used PacBio full-length transcriptome sequencing (SMRT) combined with next-generation sequencing (NGS) transcriptome technology to improve the transcriptome data of 'Liqiu'. Transcriptomics further identified many differential genes involved in cellulase, lignin and plant hormone-related pathways. This study will provide new insights into the research on the shattering mechanism of P. alopecuroides.

Rapid discrimination of Alismatis Rhizoma and quantitative analysis of triterpenoids based on near-infrared spectroscopy.

This study developed a rapid, accurate, objective and economic method to identify and evaluate the quality of Alismatis Rhizoma (AR) commodities. Traditionally, the identification of plant species and geographical origins of AR commodities mainly relied on experienced staff. However, the subjectivity and inaccuracy of human identification negatively impacted the trade of AR. Besides, liquid chromatographic methods such as ultra-high-performance liquid chromatography (UPLC) and high-performance liquid chromatography (HPLC), the major approach for the determination of triterpenoid contents in AR was time-consuming, expensive, and highly demanded in manoeuvre specialists. In this study, the combination of near-infrared (NIR) spectroscopy and chemometrics as the method was developed and utilised to address the two common issues of identifying the quality of AR commodities. Through the discriminant analysis (DA), the raw NIR spectroscopy data on 119 batches samples from two species and four origins in China were processed to the best pre-processed data. Subsequently, orthogonal partial least squares-discriminant analysis (OPLS-DA) and random forest (RF) as the major chemometrics were used to analyse the best pre-processed data. The accuracy rates by OPLS-DA and RF were respectively 100% and 97.2% for the two species of AR, and respectively100% and 94.4% for the four origins of AR. Meanwhile, a quantitative correction model was established to rapidly and economically predict the seven triterpenoid contents of AR through combining the partial least squares (PLS) method and NIR spectroscopy, and taking the triterpenoid contents measured by UPLC as the reference value, and carry out spectral pre-processing methods and band selection. The final quantitative model correlation coefficients of the seven triterpenoid contents of AR ranged from 0.9000 to 0.9999, indicating that prediction ability of this model had good stability and applicability.

Cloud inversion analysis of surrounding rock parameters for underground powerhouse based on PSO-BP optimized neural network and web technology.

Aiming at the shortcomings of the BP neural network in practical applications, such as easy to fall into local extremum and slow convergence speed, we optimized the initial weights and thresholds of the BP neural network using the particle swarm optimization (PSO). Additionally, cloud computing service, web technology, cloud database and numerical simulation were integrated to construct an intelligent feedback analysis cloud program for underground engineering safety monitoring based on the PSO-BP algorithm. The program could conveniently, quickly, and intelligently carry out numerical analysis of underground engineering and dynamic feedback analysis of surrounding rock parameters. The program was applied to the cloud inversion analysis of the surrounding rock parameters for the underground powerhouse of the Shuangjiangkou Hydropower Station. The calculated displacement simulated with the back-analyzed parameters matches the measured displacement very well. The posterior variance evaluation shows that the posterior error ratio is 0.045 and the small error probability is 0.999. The evaluation results indicate that the intelligent feedback analysis cloud program has high accuracy and can be applied to engineering practice.

Biomimetic ZIF-8 Nanoparticles: A Novel Approach for Biomimetic Drug Delivery Systems.

Metal-organic frameworks (MOFs) are porous materials resulting from the coordination of metal clusters or ions with organic ligands, merging macromolecular and coordination chemistry features. Among these, zeolitic imidazolate framework-8 (ZIF-8) stands out as a widely utilized MOF known for its robust stability in aqueous environments owing to the robust interaction between its constituent zinc ions (Zn2+) and 2-methylimidazole (2-MIM). ZIF-8 readily decomposes under acidic conditions, serving as a promising candidate for pH-responsive drug delivery systems. Moreover, biomimetic materials typically possess good biocompatibility, reducing immune reactions. By mimicking natural structures or surface features within the body, they enhance the targeting of nanoparticles, prolong their circulation time, and increase their bioavailability in vivo. This review explores the latest advancements in biomimetic ZIF-8 nanoparticles for drug delivery, elucidating the primary obstacles and future prospects in utilizing ZIF-8 for drug delivery applications.

Systematic analysis of IGF2BP family members in non-small-cell lung cancer.

BACKGROUND: The insulin-like growth factor-2 mRNA-binding proteins 1, 2, and 3 (IGF2BP1, IGF2BP2, and IGF2BP3) are known to be involved in tumorigenesis, metastasis, prognosis, and cancer immunity in various human cancers, including non-small cell lung cancer (NSCLC). However, the literature on NSCLC largely omits the specific context of lung squamous cell carcinoma (LUSC), an oversight we aim to address. METHODS: Our study evaluated the differential expression of IGF2BP family members in tumors and normal tissues. Meta-analyses were conducted to assess the prognostic value of IGF2BPs in lung adenocarcinoma (LUAD) and LUSC. Additionally, correlations between IGF2BPs and tumor immune cell infiltration, mutation characteristics, chemotherapy sensitivity, and tumor mutation burden (TMB) were investigated. GSEA was utilized to delineate biological processes and pathways associated with IGF2BPs. RESULTS: IGF2BP2 and IGF2BP3 expression were found to be upregulated in LUSC patients. IGF2BP2 mRNA levels were correlated with cancer immunity in both LUSC and LUAD patients. A higher frequency of gene mutations was observed in different IGF2BP1/2/3 expression groups in LUAD compared to LUSC. Meta-analyses revealed a significant negative correlation between overall survival (OS) and IGF2BP2/3 expression in LUAD patients but not in LUSC patients. GSEA indicated a positive association between VEGF and IGF2BP family genes in LUAD, while matrix metallopeptidase activity was inversely correlated with IGF2BP family genes in LUSC. Several chemotherapy drugs showed significantly lower IC50 values in high IGF2BP expression groups in both LUAD and LUSC. CONCLUSION: Our findings indicated that IGF2BPs play different roles in LUAD and LUSC. This divergence highlights the need for tailored therapeutic strategies and prognostic tools, cognizant of the unique molecular profiles of LUAD and LUSC.