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With the rapid development of medical imaging technology, 3D image segmentation technology has gradually become a mainstream method, especially in brain tumour detection and diagnosis showing its unique advantages. The technique makes full use of 3D spatial information to locate and analyze tumours more accurately, thus playing an important role in improving diagnostic accuracy, optimising treatment planning and promoting research. However, it also suffers from significant computational expenditure and delayed processing pace. In this paper, we propose an innovative optimisation scheme to address this problem. We thoroughly investigate the MedNeXt network and propose Fast‐MedNeXt, which aims to increase the processing speed while maintaining accuracy. First, we introduce the partial convolution (PConv) technique, which replaces the deep convolutional layers in the network. This improvement effectively reduces computation and memory requirements while maintaining efficient feature extraction. Second, based on PConv, we propose PConv‐Down and PConv‐Up modules, which are applied to the up‐sampling and down‐sampling modules to further optimise the network structure and improve efficiency. To confirm the efficacy of the approach, we carried out a sequence of tests in the multimodal brain tumour segmentation challenge 2021 (BraTS2021). By comparing with the MedNeXt series network, the Fast‐MedNeXt reduced the latency by 22.1%, 20.5%, 15.8%, and 11.4% respectively, while the average accuracy also increased by 0.475% and 0.2% respectively. These significant performance improvements demonstrate the effectiveness of Fast‐MedNeXt in 3D medical image segmentation tasks and provide a new and more efficient solution for the field. [ABSTRACT FROM AUTHOR]

Abstract Objective CT-Urography combined with 3D printing technology, digital design, construction of individualized PCNL puncture guides, and preliminary analyze their efficacy, safety puncture positioning for PCNL. Methods Twenty-two patients with renal calculi were randomly selected at the affiliated Hospital of Xuzhou Medical University during 2017–2018. We randomly divided the patients into two groups: in 10 experimental groups, we used our 3D printing personalized percutaneous puncture guide access plate for PCNL, and in the control group, 12 patients with standard USG guide PCNL. The accuracy of puncture position, puncture time, and intraoperative blood loss was compared. Results In the experimental group, 10 patients with 3D printing personalized percutaneous puncture guide access plate. The puncture needle was accessed through the guide plate and verified by the color Doppler. The single puncture, needle position, and depth success rate were 100.00% (10/10). The angles were consistent with the preoperative design. In the control group, 12 patients via USG guided PCNL success rate was 75.00% (9/12). The puncture time and amount of hemorrhage was (7.78 ± 0.94) min and (49.31 ± 6.43) mL, and (9.04 ± 1.09) min and (60.08 ± 12.18) mL, respectively. The above data of the two groups were statistically significant (P

Remote sensing (RS) images play an indispensable role in many key fields such as environmental monitoring, precision agriculture, and urban resource management. Traditional deep convolutional neural networks have the problem of limited receptive fields. To address this problem, this paper introduces a hybrid network model that combines the advantages of CNN and Transformer, called MBT-UNet. First, a multi-branch encoder design based on the pyramid vision transformer (PVT) is proposed to effectively capture multi-scale feature information; second, an efficient feature fusion module (FFM) is proposed to optimize the collaboration and integration of features at different scales; finally, in the decoder stage, a multi-scale upsampling module (MSUM) is proposed to further refine the segmentation results and enhance segmentation accuracy. We conduct experiments on the ISPRS Vaihingen dataset, the Potsdam dataset, the LoveDA dataset, and the UAVid dataset. Experimental results show that MBT-UNet surpasses state-of-the-art algorithms in key performance indicators, confirming its superior performance in high-precision remote sensing image segmentation tasks. [ABSTRACT FROM AUTHOR]

Purpose: Numerous indicators can be used to predict tumor patients' prognosis and tumor regression grade (TRG). The role of the neutrophil-lymphocyte ratio (NLR) among individuals with locally advanced rectal cancer (LARC) following neoadjuvant chemoradiotherapy (nCRT) hasn't been studied, nevertheless. This study aims to explore the predictive value of the NLR before nCRT (pre-NLR) in TRG and prognosis of LARC patients undergoing nCRT.. Methods: In this retrospective investigation, 326 LARC patients receiving nCRT in total were included. The link between the pre-NLR and TRG was examined using a logistic regression analysis. A Cox-based nomogram was created in the meanwhile to forecast overall survival (OS). With the use of calibration plots and receiver operating characteristic (ROC) curves, we evaluated the nomogram's predictive capabilities. Results: The median pre-NLR across 326 patients was 2.2 (interquartile range, IQR: 1.7-2.7). In the logistic regression analysis, only the pre-NLR for TRG in LARC patients receiving nCRT was statistically significant (odds ratio, OR = 0.62, 95% CI: 0.47-0.80, P < 0.001). Pre-NLR, nCRT with surgery interval, ypTNM stage, TRG, vascular invasion, adjuvant chemotherapy, and carbohydrate antigen 19–9 before nCRT were revealed to be OS predictors in the Cox multivariate analysis. According to calibration plots and ROC curves, the predictive nomogram demonstrated high statistical performance on internal validation. Conclusion: This study demonstrated that a lower pre-NLR was probably associated with a greater rate of TRG in LARC patients undergoing nCRT. Furthermore, the pre-NLR was credibly correlated with OS in LARC patients undergoing nCRT. Meanwhile, we constructed a nomogram for predicting the prognosis in LARC patients undergoing nCRT. [ABSTRACT FROM AUTHOR]

Background and Aim: Radiation therapy (RT) is a crucial modality for the local control of esophageal cancer (EC), but the effect of RT on the development of secondary thoracic malignancies is still unclear. This study aims to identify the association between RT for the treatment of primary EC and subsequent secondary thoracic cancer (STC). Methods: The primary EC patients were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Fine‐Gray competing risk regression and standardized incidence ratio (SIR) were used to evaluate the radiotherapy‐associated cancer risk. Overall survival (OS) was compared by Kaplan–Meier analysis. Results: A total of 40 255 EC patients from the SEER database were identified, of which 17 055 patients (42.37%) did not receive radiotherapy (NRT) and 23 200 patients (57.63%) had been treated with RT. After 12 months of latency, 162 patients (0.95%) in the NRT group and 272 patients (1.17%) in the RT group developed STC. The incidences of the RT group were significantly higher than the NRT group. Patients who have primary EC were at an increased risk of developing STC (SIR = 1.79, 95% CI: 1.63–1.96). The SIR of STC was 1.37 (95% CI: 1.16–1.60) in the NRT group and 2.10 (95% CI: 1.87–2.34) in the RT group. The OS of STC patients in the RT group was significantly lower than the NRT group (P = 0.006). Conclusion: The RT for primary EC was associated with higher risks of developing STC than patients unexposed to radiotherapy. The EC patients treated with RT, especially young patients, require long‐term monitoring of the risk of STC. [ABSTRACT FROM AUTHOR]

Objective. To screen genes associated with poor prognosis of clear cell renal cell carcinoma (CcRCC) from the public databases HPA (Human Protein Atlas), UALCAN, and GEPIA (Gene Expression Profiling Interactive Analysis) and to investigate the expression of FKBP10 in CcRCC and the effect on prognosis of the patients and the biological behavior of CcRCC cells. Methods. The tumor tissues and adjacent noncancerous tissues of 42 patients with CcRCC diagnosed and treated in our hospital were collected, and the general information of the patients was recorded. FKBP10 expression in the tissues was determined by qRT-PCR and western blot, and its relationship with general information and prognosis of patients was analyzed. Knockdown or overexpression experiments were carried out with the human proximal tubule epithelial cell line HK-2 and CcRCC cell lines Caki-1, 786-O, ACHN, and A498 to verify the relationship between FKBP10 expression and cell proliferation and adhesion ability using MTT assay and fibronectin adhesion assay, respectively. Western blot was utilized to examine the protein expression level of c-Myc, cyclin D1, and Bcl-2 in the cells. Results. FKBP10 was highly expressed in CcRCC tissues and cells and was correlated with poor prognosis. In addition, FKBP10 expression was positively correlated with CcRCC tumor size and staging and negatively correlated with tumor differentiation. Moreover, knockdown of FKBP10 significantly inhibited the proliferation of CcRCC cells, notably declined the protein expression of c-Myc, cyclin D1, and Bcl-2, and promoted cell adhesion. Conclusion. FKBP10 is highly expressed in CcRCC tissues and cells and is associated with poor prognosis in patients. FKBP10 participated in the occurrence and development of CcRCC by promoting cell proliferation and inhibiting apoptosis and adhesion. [ABSTRACT FROM AUTHOR]

Rice is one of the important staple foods for human beings. Germ integrity is an important indicator of rice processing accuracy. Traditional detection methods are time-consuming and highly subjective. In this paper, an EfficientNet–B3–DAN model is proposed to identify the germ integrity. Firstly, ten types of rice with different germ integrity are collected as the training set. Secondly, based on EfficientNet–B3, a dual attention network (DAN) is introduced to sum the outputs of two channels to change the representation of features and further focus on the extraction of features. Finally, the network is trained using transfer learning and tested on a test set. Comparing with AlexNet, VGG16, GoogleNet, ResNet50, MobileNet, and EfficientNet–B3, the experimental illustrate that the detection overall accuracy of EfficientNet–B3–DAN is 94.17%. It is higher than other models. This study can be used for the classification of rice germ integrity to provide guidance for rice and grain processing industries. [ABSTRACT FROM AUTHOR]

For the quality inspection of brown rice, the segmentation of connected brown rice and the identification of germ integrity are very important. However, there is no better traditional algorithm to achieve better segmentation and recognition results. This paper improves the brown rice (BR) segmentation algorithm based on background skeleton. The candidate matching points are obtained by the background skeleton method, and the optimal matching points are found by the ant colony algorithm. Experimental results show that the proposed segmentation algorithm achieves 96% accuracy, indicating that it can effectively suppress the interference from the endosperm surface. After segmentation is complete, identification of embryo integrity is performed. Firstly, a convolutional neural network (CNN) is built to identify the germ direction; then, the germ direction is normalized; finally, an improved Inception-v3 network is built to identify the germ integrity. On the basis of the Inception-v3 network, additional branches are added to improve the detection accuracy of small objects. In addition, mutual-channel loss and mlpconv are added to enable the model to better approximate the abstraction of the latent space. The experimental results show that the comprehensive recognition accuracy of the proposed algorithm is as high as 94.83%, which is significantly higher than the current mainstream recognition algorithms. [ABSTRACT FROM AUTHOR]

Background: Colon cancer (CC) remains one of the most common malignancies with a poor prognosis. Pyroptosis, referred to as cellular inflammatory necrosis, is thought to influence tumor development. However, the potential effects of pyroptosis-related regulators (PRRs) on the CC immune microenvironment remain unknown. Methods: In this study, 27 PRRs reported in the previous study were used to cluster the 1,334 CC samples into three pyroptosis-related molecular patterns. Through subtype pattern differential analysis and structure network mining using Weighted Gene Co-expression Network Analysis (WGCNA), 854 signature genes associated with the PRRs were discovered. Further LASSO-penalized Cox regression of these genes established an eight-gene assessment model for predicting prognosis. Results: The CC patients were subtyped based on three distinct pyroptosis-related molecular patterns. These pyroptosis-related patterns were correlated with different clinical outcomes and immune cell infiltration characteristics in the tumor microenvironment. The pyroptosis-related eight-signature model was established and used to assess the prognosis of CC patients with medium-to-high accuracy by employing the risk scores, which was named "PRM-scores." Greater inflammatory cell infiltration was observed in tumors with low PRM-scores, indicating a potential benefit of immunotherapy in these patients. Conclusions: This study suggests that PRRs have a significant effect on the tumor immune microenvironment and tumor development. Evaluating the pyroptosis-related patterns and related models will promote our understanding of immune cell infiltration characteristics in the tumor microenvironment and provide a theoretical basis for future research targeting pyroptosis in cancer. [ABSTRACT FROM AUTHOR]

Multifunctional drug carriers have great applications in biomedical field. In this study, we introduced both polydopamine (PDA) and zwitterionic polymer of poly(3-(3-methacrylamidopropyl-(dimethyl)-ammonio)propane-1-sulfonate) (PSPP) onto the surface of mesoporous silica nanoparticles (MSNs) to develop a novel nanoparticle (MSNs@PDA-PSPP), which was employed as a new kind of drug carrier for the delivery of doxorubicin (DOX). The PDA coating, as a gatekeeper, could endow the drug carrier with pH-sensitive drug release performance. The outermost PSPP layer would make the drug carrier possess protein resistance performance. The chemical structure and properties were characterized by Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), dynamic light scattering (DLS) and thermogravimetric analysis (TGA). MSNs@PDA-PSPP could keep good colloidal stability within 72 h in phosphate buffered saline (PBS) and protein solutions. Meanwhile, MSNs@PDA-PSPP exhibited a high drug loading for DOX. In vitro drug release experiments suggested MSNs-DOX@PDA-PSPP exhibited pH-dependent drug release behaviors. Besides, MSNs@PDA-PSPP had no cytotoxicity to human hepatocellular carcinoma cells (HepG2 cells) even at a concentration of 125 μg/mL. More importantly, cellular uptake and in vitro anticancer activity tests suggested that MSNs-DOX@PDA-PSPP could be taken up by HepG2 cells and DOX could be successfully released and delivered into the cell nuclei. Taken together, MSNs@PDA-PSPP have great potential in the biomedical field. [ABSTRACT FROM AUTHOR]

Object: In recent times, many published papers reported the diagnostic performance of CT, MRI, positron emission tomography (PET) using 2-[18F] fluoro-2-deoxy-D-glucose (FDG) and diffusion-weighted magnetic resonance imaging (DW-MRI) for detecting the lymph nodes (LNs) metastases in patients with cervical cancer. This study is aimed at assessing and comparing the diagnostic value of those non-invasive modalities in detecting the LNs metastases in cervical cancer patients.Methods: Studies on the non-invasive modalities for the detection of metastatic LNs were searched in PubMed, Medline, Web of Science, Cochrane Library and Embase databases. Pooled positive likelihood ratios and negative likelihood ratios, diagnostic OR, area under curve (AUC), summary receiver operating characteristics were calculated as evaluation indices.Results: In region- or node-based analysis, the AUC of DWI-MRI (0.92) and PET or PET/CT (0.90) were better than CT (0.83), and the difference was significant (DWI-MRI vs. CT: Z = 4.61, p < 0.001; PET or PET/CT vs. CT: Z = 3.61, p = 0.001).Conclusion: Among the 4 non-invasive modalities, the PET or PET/CT has the highest specificity, and DWI-MRI has the highest sensitivity. [ABSTRACT FROM AUTHOR]

At present, rice is generally in a state of dense adhesion and small granular volume during processing, resulting in no effective semantic segmentation method for rice to extract complete rice. Aiming at the above problems, this paper designs a small object semantic segmentation network model based on multi-view feature fusion. The overall structure of the network is divided into a multi-view feature extraction module, a super-resolution feature building module and a semantic segmentation module. The extraction ability of small target features is improved by super-resolution construction of small target detail features, and the learning ability of the network for small target features is enhanced and expanded through multi-view. At the same time, a dataset of quality inspection during rice processing was constructed. We train and test the model on this dataset. The results show that the average segmentation accuracy of the semantic segmentation model in this paper reaches 87.89%. Compared with the semantic segmentation models such as SegNet, CBAM, RefineNet, DeepLabv3+ and G-FRNet, it has obvious advantages in various indicators, which can provide rice quality detection and an efficient method of rice grain extraction. [ABSTRACT FROM AUTHOR]

• A new magnetic covalent organic framework (COF) was constructed. • The prepared magnetic COF exhibited excellent affinity to benzoylurea insecticides. • A sensitive method was developed for detection of five benzoylurea insecticides. • The magnetic COF could be used for selective extraction of benzoylurea insecticides. A magnetic covalent organic framework (COF) was constructed with ethidium bromide (EB) and 1,3,5-triformylphloroglucinol as building blocks. The prepared magnetic COF (named as EB-COF@Fe 3 O 4) exhibited high adsorption ability for five benzoylurea insecticides (BUs). By combining EB-COF@Fe 3 O 4 based magnetic solid-phase extraction with high performance liquid-phase chromatographic detection, a novel method was developed for determination of five BUs in water and food samples. Under the optimized conditions, a good linearity was obtained to be 0.03–100.0 ng mL−1 for water and juice, 0.9–500 ng g−1 for tomato. The detection limits of the method were 0.01–0.09 ng mL−1, 0.03–0.3 ng mL−1 and 0.3–2.0 ng g−1 for water, juice and tomato samples, respectively. Satisfactory method recoveries were achieved in the range of 80.0%-116.0% with the intra-day and inter-day relative standard deviations below 10%. Moreover, the EB-COF@Fe 3 O 4 can be reused at least 25 times. Therefore, the established method is sensitive and robust for determining BUs in real samples. [ABSTRACT FROM AUTHOR]

• Novel tyrosine-functionalized hypercrosslinked polymer (HCP@Tyr) were synthesized. • HCP@Tyr showed high surface areas and good extraction performance to nitroimidazoles. • HCP@Tyr was used to detect nitroimidazoles in honey and chicken tissue. • Hydrogen bonding, π-stacking interactions played a vital role in the extraction. • HCP@Tyr exhibited good application prospect for determination of other compounds. The preparation of tyrosine-functional novel hypercrosslinked polymer (HCP@Tyr) was achieved by knitting 1,3,5-triphenylbenzene with l -tyrosine via simple Friedel-Crafts reaction. The HCP@Tyr displayed large surface area (1220 m2 g−1) and high adsorption capacity (30 mg g−1) for nitroimidazoles (NDZs). With HCP@Tyr as potent sorbent, an efficient extraction method was developed to simultaneously extract five NDZs from honey and chicken muscle samples before high performance liquid chromatography-diode array detection. Under optimized conditions, the proposed method provided a good linearity in the range of 0.75–200.0 ng g−1 for honey and 1.5–100.0 ng g−1 for chicken muscle sample. Low detection limits (S/N = 3) were obtained to be 0.10–0.24 ng g−1 for honey and 0.15–0.30 ng g−1 for chicken muscle. The method recovery was 80.7–120% with relative standard deviations below 9.2%. The HCP@Tyr based method can serve as a reliable and sensitive tool for detection of NDZs in honey and chicken muscle samples. [ABSTRACT FROM AUTHOR]

[Display omitted] • A sorbent with amino and triazine bifunctional groups (M-NH 2 -THCP) was prepared. • The M-NH 2 -THCP exhibited strong extraction ability for nitroimidazoles (NDZs). • M-NH 2 -THCP was used as magnetic solid phase sorbent for effective enriching NDZs. • M-NH 2 -THCP based method was established to detect NDZs in water, fish and shrimp. • M-NH 2 -THCP can serve as a promising sorbent for adsorbing more organic pollutants. In this paper, a novel magnetic hyper-crosslinked polymer with amino and triazine bifunctional groups (M-NH 2 -THCP) was developed. M-NH 2 -THCP has strong nitroimidazoles (NDZs) enrichment effect, and therefore it was used as an adsorbent to extract five NDZs from lake water, catfish and shrimp meat prior to HPLC. Polar interaction, π-π stacking interaction, hydrogen bond and Lewis acid-base interaction were attested to be the major adsorption mechanism. The method has a good linearity in the range of 0.1–100 ng mL−1 for lake water, 10–400 ng g−1 for catfish and shrimp muscle with R2 > 0.9964. The limits of detection of NDZs were 0.03–0.04 ng mL−1 for lake water, 1.0–2.0 ng g−1 for catfish and 2.0–2.5 ng g−1 for shrimp, which is superior to most reported method. The method recoveries were 87.6–119 %, and relative standard deviations were less than 8.7 %. M-NH 2 -THCP holds great application potential in pollutants enrichment, separation and removal. [ABSTRACT FROM AUTHOR]

• A novel magnetic knitting aromatic polymer (M-KAP) was successfully fabricated. • M-KAP showed high surface area, abundant porosity and high thermal stability. • M-KAP exhibited great affinity and reusability to six benzoylurea insecticides (BUs). • M-KAP was applied to sensitively determine BUs in honey and juice samples. • Hydrophobic interactions and π-π stacking played important role in the extraction. In this work, a novel knitting aromatic polymer (KAP) was fabricated for the first time by knitting ferrocene with 1,3,5-tris(bromomethyl)-2,4,6-trimethylbenzene via Friedel-Crafts reaction, and then the KAP was magnetically functionalized with Fe 3 O 4 nanoparticles to produce a magnetic KAP (M-KAP). Combining M-KAP based magnetic solid-phase extraction with high performance liquid chromatography-ultraviolet detection, a simple and sensitive method was developed for simultaneous determination of six benzoylurea insecticides (BUs) in honey and apple juice samples. In the optimized conditions, a good linearity for the BUs existed in the range of 1.67–1000 ng g−1 for honey sample and 0.500–100.0 ng mL−1 for apple juice sample. The limits of detection were 0.500–1.50 ng g−1 and 0.150–0.400 ng mL−1 for honey and apple juice sample, respectively. Satisfactory recoveries were in the range of 85.5–105.5% with RSDs ≤ 8.3%. The developed method demonstrated an excellent practicability for sensitive analysis of the BUs. [ABSTRACT FROM AUTHOR]

• A novel magnetic porous organic polymer (named Rut-MOP) was prepared. • The Rut-MOP showed excellent extraction capability to neonicotinoid insecticides. • A sensitive method was developed to analyze neonicotinoids in lemon juice and honey. • H-bonding, π-π stacking and Lewis acid-base interactions involved in the extraction. • Rut-MOP displayed good application prospect for analysis of some other compounds. Natural rutin with abundant hydroxyl groups was used as a green monomer to synthesize hydroxyl-functional magnetic porous organic polymer (named Rut-MOP) through environmentally-benign diazo-coupling reaction for the first time. The Rut-MOP displayed high extraction capability for neonicotinoid insecticides (thiamethoxam, imidacloprid, acetamiprid and thiacloprid). Thus, a Rut-MOP based magnetic solid-phase extraction method combined with high performance liquid chromatography was established for sensitive determination of neonicotinoid insecticides in lemon juice and honey samples. Under optimized conditions, the linear response of neonicotinoids was 0.1–100.0 ng mL−1 for lemon juice and 8.0–1000.0 ng g−1 for honey. The limits of detection (S/N = 3) were 0.03–0.04 ng mL−1 and 2.5–3.0 ng g−1 for lemon juice and honey, respectively. The method recoveries were 82–118% with the relative standard deviations of 1.9–7.6%. The results demonstrate that the Rut-MOP based method can be served as a good alternative for the sensitive analysis of neonicotinoid insecticides in lemon juice and honey. [ABSTRACT FROM AUTHOR]

• Novel magnetic nanoporous polymer (PA-MOP) with hydroxyl moieties was synthesized. • The hydrophilic PA-MOP showed high extraction capacity to neonicotinoid insecticides. • PA-MOP was applied to detect neonicotinoid insecticides in water and juice samples. • Hydrogen bonding, π-π stacking and electrostatic interactions contribute to adsorption. • PA-MOP exhibited good application prospect for determination of other compounds. In this work, a natural proanthocyanidin (PA) based magnetic nanoporous organic polymer (named as PA-MOP) was successfully synthesized for the first time. The PA-MOP possessed high hydrophilic-surface, good magnetic responsiveness and high affinity for neonicotinoid insecticides. It was applied as an advanced magnetic sorbent for extraction of four neonicotinoids (thiamethoxam, imidacloprid, acetamiprid and thiacloprid) from environmental water, peach juice and honey samples prior to HPLC analysis. Under optimal conditions, the limits of detection for the analytes at S/N = 3 were 0.02–0.08 ng mL−1 for water, 0.03–0.10 ng mL−1 for peach juice and 0.05–0.16 ng g−1 for honey sample. The method recoveries were 80.0%-114.8%, with the relative standard deviations below 6.8%. The values of matrix effect were from −1.5% to −9.3%. Based on theory calculation, the extraction mechanism can be attributed to multiple interactions between the PA-MOP and the neonicotinoids, in which hydrogen bonding, π-π stacking and electrostatic interactions are the major interactions. [ABSTRACT FROM AUTHOR]