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Abstract Background Although it is traditionally believed that ATP binding cassette subfamily C member 2 (ABCC2) is a multidrug resistance‐associated protein correlated with a worse prognosis, our previous and several other studies demonstrated the contrary to be true in gastric cancer (GC). We aim to explore the underlying mechanism of this discovery. Methods Our study utilized whole‐exome sequencing (WES), RNA sequencing, and droplet digital PCR (ddPCR) analysis of 80 gastric cancer samples, along with comprehensive immunohistochemical (IHC) analysis of 1044 human GC tissue samples.By utilizing CRISPRCas9 to genetically modify cell lines with the ABCC2‐24C > T (rs717620) point mutation and conducting dual‐luciferase reporter assays, we identified that transcription factors SOX9 and ETS1 serve as negative regulators of ABCC2 expression. Seahorse assay and mass spectrometry were used to discover altered metabolic patterns. Gain and loss‐of‐function experiments in GC cell lines and preclinical models were carried out to validate ABCC2 biological function. Results ABCC2 high expression correlated with better prognosis, and rs717620 can influence ABCC2 expression by disrupting the binding of ETS1 and SOX9. Gain and loss‐of‐function experiments in GC cell lines demonstrated amino acid deprivation reduces proliferation, migration, and drug resistance in ABCC2‐high GC cells. ABCC2 leads to reduced intracellular amino acid pools and disruption of cellular energy metabolism. This phenomenon depended on ABCC2‐mediated GSH extrusion, resulting in alterations in redox status, thereby increasing the cell's susceptibility to ferroptosis. Furthermore, patient‐derived organoids and patient‐derived tumor‐like cell clusters were used to observe impact of ABCC2 on therapeutic effect. In the xenograft model with high ABCC2 expression, we observed that constricting amino acid intake in conjunction with GPX4 inactivation resulted in notable tumor regression. Conclusions Our findings demonstrate a significant role of ABCC2 in amino acid metabolism and ferroptosis by mediating GSH efflux in GC. This discovery underlines the potential of combining multiple ferroptosis targets as a promising therapeutic strategy for GC with high ABCC2 expression. Highlights ABCC2 plays a crucial role in inducing metabolic vulnerability and ferroptosis in gastric cancer through enhanced glutathione efflux. The ABCC2 24C > T polymorphism is a key factor influencing its expression. These results highlight the potential of ABCC2 as a predictive biomarker and therapeutic target in gastric cancer.

Abstract Idiopathic short stature (ISS) is a common childhood condition with largely unknown underlying causes. Recent research highlights the role of circulating exosomes in the pathogenesis of various disorders, but their connection to ISS remains unexplored. In the experiments, human chondrocytes are cocultured with plasma exosomes from ISS patients, leading to impaired chondrocyte growth and bone formation. Elevated levels of a specific long non‐coding RNA (lncRNA), ISSRL, are identified as a distinguishing factor in ISS, boasting high specificity and sensitivity. Silencing ISSRL in ISS plasma exosomes reverses the inhibition of chondrocyte proliferation and bone formation. Conversely, overexpression of ISSRL in chondrocytes impedes their growth and bone formation, revealing its mechanism of action through the miR‐877‐3p/GZMB axis. Subsequently, exosomes (CT‐Exo‐siISSRL‐oeGH) with precise cartilage‐targeting abilities are engineered, loaded with customized siRNA for ISSRL and growth hormone. This innovative approach offers a therapeutic strategy to address ISS by rectifying abnormal non‐coding RNA expression in growth plate cartilage and delivering growth hormone with precision to promote bone growth. This research provides valuable insights into ISS diagnosis and treatment, highlighting the potential of engineered exosomes.

Abstract Objective As disc fragment completely loses contact with the parent disc and can migrate in all directions of the epidural space, making it appear similar to schwannoma, it is fairly difficult to make a definitive diagnosis for mimicking tumor discs. The aim of this research is to differentially diagnose mimicking tumor discs and schwannomas using coronal magnetic resonance imaging (MRI) of three‐dimensional fast‐field echo with water‐selective excitation (CMRI). Methods Among 76 patients (38 men and 38 women; mean age, 52.88 ± 15.80 [range, 18–78 years]) who were retrospectively examined in this study, 38 were primarily diagnosed with schwannomas and pathologically diagnosed with mimicking tumor discs after surgery, and 38 were primarily diagnosed with neurogenic tumors and pathologically diagnosed with schwannomas after surgery. Open surgery was performed in all the patients between March 2016 and April 2020. The preliminary diagnosis of all patients was considered an intraspinal tumor based on conventional two‐dimensional MRI sequences. After open surgery, the final diagnosis was confirmed to mimic a tumor disc or schwannoma based on postoperative pathology reports. The sensitivity, specificity, and reliability of CMRI and conventional MRI for identifying mimicking tumor discs and schwannomas were compared. Chi‐square and McNemar tests were used for statistical analyses. Results Symptoms were considerably relieved in all the patients after surgery. Seven patients had grade 1 extensor digitorum longus, triceps surae, or quadriceps femoris muscle strength prior to surgery. No nerve root injury was observed in any of the patients. CMRI showed significantly higher sensitivity (94.74%) and specificity (94.74%) than conventional MRI (71.05% and 92.11%, respectively; p = 0.012 0.05, respectively) for differential identification between mimicking tumor discs and schwannomas. Moreover, CMRI showed a higher reliability (kappa value = 0.787) than conventional MRI (kappa value = 0.374). Conclusions CMRI is a better non‐invasive technology for the identification of intraspinal lesions, especially for differentiating between mimicking tumor discs and schwannomas.

The dynamics of a discrete-time SIS epidemic model are reported in this paper. Three types of codimension one bifurcation, namely, transcritical, flip, Neimark–Sacker (N-S) bifurcations, and their intersection codimension two bifurcations including 1 : 2, 1 : 3, and 1 : 4 resonances are discussed. The necessary and sufficient conditions for detecting these types of bifurcation are derived using algebraic criterion methods. Numerical simulations are conducted not only to illustrate analytical results but also to exhibit complex behaviors which include period-doubling bifurcation in period −2,−4,−8,−16 orbits, invariant closed cycles, and attracting chaotic sets. Especially, here we investigate the parameter space of the discrete model. We also investigate the organization of typical periodic structures embedded in a quasiperiodic region. We identify period-adding, Farey sequence of periodic structures embedded in this quasiperiodic region.

Graphs have been widely used to model the complex relationships among entities. Community search is a fundamental problem in graph analysis. It aims to identify cohesive subgraphs or communities that contain the given query vertices. In social networks, a user is usually associated with a weight denoting its influence. Recently, some research is conducted to detect influential communities. However, there is a lack of research that can support personalized requirement. In this study, we propose a novel problem, named personalized influential k-ECC (PIKE) search, which leverages the k-ECC model to measure the cohesiveness of subgraphs and tries to find the influential community for a set of query vertices. To solve the problem, a baseline method is first proposed. To scale for large networks, a dichotomy-based algorithm is developed. To further speed up the computation and meet the online requirement, we develop an index-based algorithm. Finally, extensive experiments are conducted on 6 real-world social networks to evaluate the performance of proposed techniques. Compared with the baseline method, the index-based approach can achieve up to 7 orders of magnitude speedup.