Explore the vast range of titles available.

Machine harvesting of cotton in Xinjiang has significantly improved harvesting efficiency; however, it has also resulted in a considerable increase in residual mulch content within the cotton, which has severely affected the quality and market value of cotton textiles. Existing mulch detection algorithms based on machine vision generally suffer from complex parameterization and insufficient real-time performance. To overcome these limitations, this study proposes a novel mulch detection algorithm, Mulch-YOLO, developed on the YOLOv11 framework. Specifically, an improved CBAM (Convolutional Block Attention Module) is incorporated into the BiFPN (Bidirectional Feature Pyramid Network) to achieve more effective fusion of multi-scale mulch features. To enhance the semantic representation of mulch features, a modified Content-Aware ReAssembly of Features module, CARAFE-Mulch (Content-Aware ReAssembly of Features), is designed to reorganize feature maps, resulting in stronger feature expressiveness compared with the original representations. Furthermore, the MobileOne module is optimized by integrating the DECA Dilated Efficient Channel Attention (Dilated Efficient Channel Attention) module, thereby reducing both the parameter count and computational load while improving detection efficiency in real time. To verify the effectiveness of the proposed approach, experiments were conducted on a real-world dataset containing 20,134 images of low-visual-saliency plastic mulch. The results indicate that Mulch-YOLO achieves a lightweight architecture and high detection accuracy. Compared with YOLOv11n, the proposed method improves mAP@0.5 by 4.7% and mAP@0.5:0.95 by 3.3%, with a 24% reduction in model parameters.

Background Malignant digestive tract tumors are highly prevalent and fatal tumor types globally, often diagnosed at advanced stages due to atypical early symptoms, causing patients to miss optimal treatment opportunities. Traditional endoscopic and pathological diagnostic processes are highly dependent on expert experience, facing problems such as high misdiagnosis rates and significant inter-observer variations. With the development of artificial intelligence (AI) technologies such as deep learning, real-time lesion detection with endoscopic assistance and automated pathological image analysis have shown potential in improving diagnostic accuracy and efficiency. However, relevant applications still face challenges including insufficient data standardization, inadequate interpretability, and weak clinical validation. Objective This study aims to systematically review the current applications of artificial intelligence in diagnosing malignant digestive tract tumors, focusing on the progress and bottlenecks in two key areas: endoscopic examination and pathological diagnosis, and to provide feasible ideas and suggestions for subsequent research and clinical translation. Methods A systematic literature search strategy was adopted to screen relevant studies published between 2017 and 2024 from databases including PubMed, Web of Science, Scopus, and IEEE Xplore, supplemented with searches of early classical literature. Inclusion criteria included studies on malignant digestive tract tumors such as esophageal cancer, gastric cancer, or colorectal cancer, involving the application of artificial intelligence technology in endoscopic diagnosis or pathological analysis. The effects and main limitations of AI diagnosis were summarized through comprehensive analysis of research design, algorithmic methods, and experimental results from relevant literature. Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. However, the scale and quality of data across different studies vary widely, and the generalizability of models to multi-center, multi-device environments remains to be verified. In pathological analysis, using convolutional neural networks, multimodal pre-training models, etc., automatic tissue segmentation, tumor grading, and assisted diagnosis can be achieved, showing good scalability in interactive question-answering. Nevertheless, clinical implementation still faces obstacles such as non-uniform data standards, lack of large-scale prospective validation, and insufficient model interpretability and continuous learning mechanisms. Conclusion Artificial intelligence provides new technological opportunities for endoscopic and pathological diagnosis of malignant digestive tract tumors, achieving positive results in early lesion identification and assisted decision-making. However, to achieve the transition from research to widespread clinical application, data standardization, model reliability, and interpretability still need to be improved through multi-center joint research, and a complete regulatory and ethical system needs to be established. In the future, artificial intelligence will play a more important role in the standardization and precision management of diagnosis and treatment of digestive tract tumors. Graphical Abstract Highlights Early symptoms of malignant digestive tract tumors are often atypical, resulting in high misdiagnosis rates, which urgently calls for more precise diagnostic methods; artificial intelligence has demonstrated significant application potential in the two core areas of endoscopy and pathology. Real-time endoscopic assisted detection systems driven by deep learning can significantly improve the detection rate of early lesions, reducing the risk of missed diagnoses due to physician inexperience or fatigue. Pathological AI technologies based on multimodal and vision-language pre-training models can achieve automatic segmentation, grading, and interactive diagnosis of digital slides, providing objective quantitative basis for individualized treatment decisions. The main obstacles to current AI applications in endoscopy and pathology include insufficient data standardization, poor model interpretability, and lack of large-scale prospective validation; multi-center collaboration and standardized regulation urgently need to be strengthened. With the continued advancement of multidisciplinary integration and technological breakthroughs, artificial intelligence is expected to further improve early diagnosis and precise management of digestive tract tumors, enhancing patient prognosis and promoting the standardized development of diagnostic and treatment processes.

Background: The optimal treatment for gastric cancer with peritoneal metastasis (GCPM) remains debatable. This study aimed to compare the efficacy and safety of neoadjuvant intraperitoneal and systemic chemotherapy (NIPS) versus neoadjuvant systemic chemotherapy (NSC) for GCPM. Methods: Patients of GCPM received neoadjuvant chemotherapy with docetaxel, oxaliplatin and S-1 between January 2011 and June 2019 were retrospectively evaluated. Propensity score matched (PSM) analysis was carried out to reduce the selection bias. Multivariate Cox regression model was applied to screen the prognostic factors. Results: After PSM processing, 71 patients in each group were matched among the 186 GCPM patients included. NIPS yielded a better ascites and cytology response to chemotherapy, higher conversion resection rate and R0 resection rate than NSC. The overall survival (OS) rate in NIPS group was better than that in NSC group. Multivariate analysis revealed that the P stage, ascites response, conversion surgery rate and R0 resection rate were independent prognostic factors. Subgroup analysis indicated that NIPS showed a survival benefit over NSC only in patients with cT3-4a, P1-2, whose cytology turned negative, and who received conversion surgery; while not in patients with cT4b, P0 or P3, whose cytology did not turn negative, or who did not receive conversion surgery. Conclusions: NIPS is a safe and feasible treatment for GCPM, which showed more benefit than NSC.

Gastric cancer remains a major clinical issue and little progress has been made in the treatment of gastric cancer patients during recent decades. Nanoparticles provide a versatile platform for the diagnosis and treatment of gastric cancer. We prepared 7-ethyl-10-hydroxycamptothecin (SN-38) I-radiolabelled biodegradable nanoparticles with folate surface modification ( I-SN-38-FA-NPs) as a novel nanoplatform for targeted gastric carcinoma theranostics. We characterized this system in terms of particle size, morphology, radiostability, and release properties and examined the in vitro cytotoxicity and cellular uptake properties of I-SN-38-FA-NPs in MNK 7 and NCI-N7 cells. The pharmacokinetics and biodistribution of I-SN-38-FA-NPs were imaged by single photon emission computer tomography (SPECT). An MNK7 tumor-bearing model were established and the in vivo antitumor activity of I-SN-38-FA-NPs was evaluated. SN-38 was readily radiolabeled with I and exhibited high radiostability. Poly-lactic-co-glycolic acid (PLGA) nanoparticles (NPs) were formed by solvent exchange, and displayed spherical morphology of 100 nm in diameter as characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). A 2.5-fold greater uptake of I-radiolabelled SN-38-loaded folate-decorated PLGA nanoparticles ( I-SN-38-FA-NPs) than I-radiolabelled SN-38-loaded PLGA nanoparticles ( I-SN-38-NPs) were record in MKN7 tumor cells. NPs and folate-decorated PLGA nanoparticles (FA-NPs) also had good biocompatibility in methyl thiazolyl tetrazolium (MTT) assays. Pharmacokinetic, biodistribution and SPECT imaging studies showed that I-SN-38-FA-NPs had prolonged circulation, were distributed in the reticuloendothelial system, and had high uptake in tumors with a higher tumor accumulation of I-SN-38-FA-NPs than I-SN-38-NPs recorded at 24 h postinjection. In vivo SN-38-FA-NPs significantly inhibited tumor growth without causing obvious side effects. Folate receptor alpha (FOLR1) targeted drug-loaded nanoparticles enable SPECT imaging and chemotherapy, and provide a novel nanoplatform for gastric carcinoma active targeting theranostics.

Background Previous research suggests that tumor-associated macrophages (TAMs) influence the cisplatin (DDP) tolerance of gastric cancer (GC) cells via the secretion of microRNA-containing exosomes. This study aims to investigate the role of exosomal miR-668-3p from M2 macrophages in modulating DDP resistance, using both in vitro and in vivo models to provide a comprehensive analysis. Materials and methods The expression profiles of DDP-resistant GC tissues were assessed through microarray, while immunofluorescence confirmed the uptake of these exosomes by GC cells. The role of miR-668-3p in regulating DDP resistance was explored using CCK8 assays, colony formation, EDU incorporation, and Western blotting. The interaction between miR-668-3p and ETS1 was validated through RIP and RNA pull-down assays. Furthermore, the regulatory role of the miR-668-3p/ETS1/EGFR axis in autophagy and DDP resistance was examined in GC cell lines and a tumor xenograft model. Results miR-668-3p was significantly upregulated in DDP-resistant GC tissues. Exosomes originating from M2 macrophages transfer miR-668-3p to GC cells, enhancing their DDP resistance. Additionally, miR-668-3p was found to bind to ETS1 mRNA, leading to its suppression and a consequent decrease in EGFR expression. This reduction in EGFR expression was closely linked to the activation of autophagy, further augmenting DDP resistance in GC cells. Conclusion M2 macrophage-derived exosomal miR-668-3p promotes DDP resistance in GC cells by targeting the ETS1/EGFR axis, thereby activating the autophagy pathway. Future research should focus on developing targeted inhibition strategies for miR-668-3p to effectively reverse DDP resistance in GC cells, optimizing its potential for clinical application.

Zhang X, Yan R, Wei Z, et al. Int J Nanomedicine. 2022;17:2493–2502. The authors wish to correct Figure 6 on page 2500 after it was found an incorrect H&E image for Liver, FA-NPs had been used. The error occurred during figure preparation and the correction does not impact the conclusions of the study. The correct Figure 6 is in Download Article. The authors apologise for this error.

Objectives Nasogastric tubes (NGT) have been routinely used after abdominal procedures, largely due to the accepted tradition, especially in China. However, studies recently questioned the role of routine NGT intubation by stating that it was overused and many complications occurred from its use. Methods Herein, we performed a systematic review and a meta-analysis evaluating the role of NGT in decompression after elective colon and rectum surgery. Results Four fixed-effect models and three randomized-effect models were used for statistics pooling of the relative risks (RR) for the different outcomes. A total of seven articles (1,416 patients) fulfilled the inclusion criteria. Patients in NGT group had less vomiting (p < 0.00001; RR = 2.85; 95% CI [2.12, 3.83]), less nasogastric tube replacement (p < 0.00001; RR = 3.90; 95% CI [2.34, 6.52]), but more pharyngolaryngitis (p < 0.00001 RR = 0.14; 95% CI [0.08, 0.26]) and more respiratory infection (p = 0.004; RR = 0.37; 95% CI [0.19, 0.74]). No statistically significant differences were noted in nausea, wound infection or intestinal obstruction. Conclusion In conclusion, routine NGT decompression did no good to the time to return gastrointestinal function, but increased the morbidity of pharyngolaryngitis and respiratory infection significantly. Routine NGT was not recommended for patients after elective colon and rectum surgery.

Saikosaponins (SSs, including SSA, SSB, SSC, and SSD), the major bioactive compounds in the traditional medicine Radix Bupleuri , are emerging agents exhibiting anti-tumor efficacy in several cancers. However, the respective anti-tumor efficacy of these agents and mechanisms in cancers remains unclear. Here, we reported that SSD, among SSs, possessed a significant anti-tumor role across different cancer types in vivo and in vitro by downregulating alternative splicing factors and rewiring oncogenic alternative splicing events. Mechanistically, SSD directly targets PIM1 and blocks the interaction between PIM1 and Myc, and decreases PIM1-mediated Myc phosphorylation at serine 62 and Myc protein stability, resulting in global restraining of Myc-governed alternative splicing factors transcription and inducing oncogenic alternative splicing rewiring. Transcript-specific ablation of SSD-regulated alternative spliced products with CIRSPR-Cas13 or targeting PIM1/Myc with specific small inhibitors significantly desensitizes cancer cells and patient-derived organoids (PDOs) to SSD treatments. These studies demonstrated the potent anti-tumor efficacy of SSD and exposed a PIM1/Myc axis by which SSD modulates the expression of an oncogenic alternative splicing regulatory network that mediates SSD’s anti-tumor role in cancers.

Background Cell division cycle 42 (CDC42), an important member of the Rho family, is overexpressed in various human cancers. However, its expression and role in pancreatic cancer (PC) are not well understood. Aim The present study was designed to investigate the expression patterns and underlying cellular mechanisms of CDC42 in PC. Methods First, immunohistochemical analysis, quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting were performed to detect CDC42 expression in clinical pancreatic carcinoma and adjacent tissues. Second, differential expression of CDC42 between PC cells and normal cells was evaluated by qRT-PCR and Western blotting. Third, the correlation between CDC42 expression as well as clinicopathological characteristics and patient survival was analyzed. Finally, CDC42 was knocked down to examine its role both in vivo and in vitro. Results The results showed significantly increased CDC42 expression in pancreatic tumor tissues compared with adjacent normal tissues, as revealed by qRT-PCR, Western blotting and immunostaining. Compared to PanC-1 cells, CDC42 expression was downregulated in HPDE6-C7 cells as shown by qRT-PCR and Western blotting. High CDC42 expression was observed in 69.2% (83/120) of pancreatic adenocarcinoma patients and was significantly associated with tumor differentiation ( p  = 0.013), median tumor size ( p  = 0.005), tumor infiltration (pT stage, p  = 0.04), lymph nodal status (pN stage, p  = 0.044) and TNM staging ( p  = 0.003). Multivariate Cox regression analysis revealed CDC42 expression to be an independent predictor of survival of PC patients (HR 3.0, 95% CI 1.60–5.61, p  = 0.001). Finally, we found that CDC42 promoted the proliferation of PanC-1 cells both in vivo and in vitro. Conclusions Our findings reveal that CDC42 might play an important role in promoting PC development, and the findings suggest that CDC42 might serve as a potential prognostic indicator of PC.

It is worldwide accepted that lncRNA PTCSC3 is a tumor suppressor in glioma and thyroid cancer, whereas its role in the recurrence of gastric cancer is unknown. We recruited 80 GC patients (46 males and 34 females, 44 to 68 years, 56.3±6.7 years) in our study. Two human GC cell lines AGS and SNU-1 were transfected with PTCSC3 and HOXA11-AS expression vectors. Then, qPCR was used to detect the level of relative mRNA. Both invasion and migration assays were performed to detect the effect of the lncRNA on gastric cancer cell motility. In the present study, we showed that PTCSC3 was downregulated in plasma of gastric cancer patients than in plasma of healthy controls. Follow-up study indicated that PTCSC3 was further downregulated in patients with distant-recurrence but not in patients with local recurrence only or non-recurrence. LncRNA HOXA11-AS was upregulated in plasma of gastric cancer cells than in plasma of healthy controls and was inversely correlated with PTCSC3 in plasma of gastric cancer patients. PTCSC3 overexpression mediated the downregulation of HOXA11-AS in gastric cancer cells, while HOXA11-AS overexpression failed to significantly affect PTCSC3. PTCSC3 overexpression led to inhibited, while HOXA11-AS overexpression led to promoted migration and invasion of gastric cancer cells. In addition, HOXA11-AS overexpression reduced the effects of PTCSC3 overexpression. Therefore, lncRNA PTCSC3 alleviates in the postoperative distant recurrence of gastric cancer possible by suppression of HOXA11-AS.