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Aim: An innovative method of digestive tract reconstruction following proximal gastrectomy, the uncut interposed jejunum pouch, esophagus and residual stomach double anastomosis(Uncut-D), was established in recent years. In order to fully clarify the superiority of the procedure, this study has conducted a systematic analysis and thorough discussion. Methods: 118 patients with adenocarcinoma of the esophagogastric junction who underwent proximal gastrectomy were enrolled in this study. According to the methods of digestive tract reconstruction, these patients were divided into three groups: Uncut-D(n = 43), esophagogastrostomy (EG, n = 36), jejunal interposition (JI, n = 39).The preoperative indicators, surgical complications and related indicators of postoperative quality of life were analyzed. Results: There were no significant differences in preoperative data among all groups (P > 0.05); The digestive tract reconstruction time in Uncut-D group was more than that in EG group, and less than that in JI group (P

Abstract The material loss caused by bubble collapse during the micro-nano bubbles auxiliary chemical mechanical polishing (CMP) process cannot be ignored. In this study, the material removal mechanism of cavitation in the polishing process was investigated in detail. Based on the mixed lubrication or thin film lubrication, bubble-wafer plastic deformation, spherical indentation theory, Johnson-Cook (J-C) constitutive model, and the assumption of periodic distribution of pad asperities, a new model suitable for micro-nano bubble auxiliary material removal in CMP was developed. The model integrates many parameters, including the reactant concentration, wafer hardness, polishing pad roughness, strain hardening, strain rate, micro-jet radius, and bubble radius. The model reflects the influence of active bubbles on material removal. A new and simple chemical reaction method was used to form a controllable number of micro-nano bubbles during the polishing process to assist in polishing silicon oxide wafers. The experimental results show that micro-nano bubbles can greatly increase the material removal rate (MRR) by about 400% and result in a lower surface roughness of 0.17 nm. The experimental results are consistent with the established model. In the process of verifying the model, a better understanding of the material removal mechanism involved in micro-nano bubbles in CMP was obtained.

Memristive nonlinear system has drawn much attention in recent years, due to its rich and complex dynamical characteristics. However, there are few studies focus on the analytical analysis of this significant system. In this paper, a novel analytical method for analyzing the chaotic trajectories of memristive circuit is proposed. This method combines Homotopy Analysis Method (HAM) and Multi-objective Optimization (MO), i.e., the convergence control parameter of traditional HAM is divided into lots of subintervals in the time domain and respectively optimized by MO, for accurately solving the Ordinary Differential Equations describing memristive circuits. Hence, this method is named by MO-based multi-interval HAM (MO-MIHAM). By using MO-MIHAM, we accurately tracked the chaotic trajectories of the classical Memristor-Capacitor-Inductor (MCL) circuit and current memristive Band Pass Filter (BPF) chaotic circuit. Furthermore, based on the comparisons of errors between analytical approximate solutions derived from MO-MIHAM and solutions solved by traditional homotopy-based analytical methods and by Runge-Kutta-Fehlberg Method (RKF45) based numerical analysis, we found that, MO-MIHAM is characterized by higher approximation accuracy and computational performance (comprehensively considering the accuracy, computational complexity and execution time by a proposed Quality Factor) among the homotopy-based analytical methods, due to the optimized convergence control parameters in subintervals. Besides this major advantage, MO-MIHAM enables both qualitative and quantitative analyses and high freedom to choose homotopy-related terms for simplicity, and it is insensitive to convergence issues. Therefore, it is a powerful tool for exploratory studies for analytically analyzing chaotic dynamics in memristive circuit.

Test vector coding and data transmission are the key technologies in the design-for-test of digital integrated circuits (IC). Existing parallel input methods of test stimuli can reduce test application times; however, they need to occupy multiple input ports. Thus, a novel method of test stimuli coding and data transmission was proposed to reduce the test application time of the test vectors and reduce the number of input ports required for the parallel input of test stimuli. This method was based on the segmentation of test stimuli. First, the test stimuli were evenly segmented into eight-bit wide. Second, the eight-bit data of each segment were encoded to the five-bit data according to the compatibility between the test data of each segment. The eight-bit test stimuli input can be completed in one or two clock cycles of automatic test equipment (ATE) by using the five input ports of the chip. The corresponding decoding circuit was added inside the netlist of the circuit to realize the rapid input of the test stimuli. Lastly, the ISCAS'89 benchmark circuit was used to conduct experiments, results of this coding method were then compared with those of the serial input method. Results show that the encoding method proposed in this study can save an average of 37% of the parallel input data width and 81.7% of the test stimuli input time. The proposed method in this study can also reduce the test application time and the cost of the IC test. The findings of this study can provide guidance for improving the scan testing method of digital IC.

Roll forming is an important processing method for the production of commercial vehicle anticollision beams, and edge buckling is one of the common defects in roll-forming process. In this paper, the “日” shape section of roll forming is studied, and first the b-shaped section is formed by roll forming, and the internal weld line is automatically welded while forming; then the long side of the b-shaped section is bent into the “U” shape, and the external weld line is welded while forming. The profile is cut off and then bent at both ends to form a commercial vehicle anticollision beam. The ABAQUS finite element software is used to model and analyze the factors affecting the “edge buckling” defect of roll-formed products. This paper uses three factors and three levels of orthogonal simulation experiments to study the problem. The results show that the effect of the factors of flange height, sheet thickness, and forming speed on the formation of edge buckling is in the order of sheet thickness > flange height > forming speed. The edge buckling size of the vertical edge of b-shaped tube decreases with the increase of sheet thickness and increases with the increase of flange height.

Springback is a common defect caused by elastic recovery in the plastic forming process, which can cause the formed workpiece to deviate from the target shape. The purpose of this paper is to grasp the influence law of process parameters on springback deviation so as to optimize process parameters to reduce springback. Taking the Y-profile as the research object, the influence of process parameters such as horizontal bending radius, vertical bending radius, transition zone length, radius of roller dies, and wall thickness of the profile on springback deviation is discussed by numerical simulation. Additionally, the validity of the numerical simulation is verified through experiments. The springback law obtained by numerical simulation is applied to practical production, and the large-scale production of the Y-profile is realized.

Abstract Glioblastoma (GBM) presents significant challenges due to its invasive nature and genetic heterogeneity. In this study, we investigated the impact of Small VCP/P97-Interacting Protein (SVIP) on GBM progression. Our results revealed elevated expression of Insulin-like Growth Factor Binding Protein 2 (IGFBP-2) and STIP1 homology and U-box containing protein 1 (STUB1), coupled with reduced SVIP levels in GBM samples. Notably, high IGFBP-2 expression correlated with poor prognosis. Mechanistically, SVIP competitively inhibited STUB1, selectively binding to VCP/p97, thereby reducing PTEN degradation. This SVIP-mediated regulation exerted influence on the PTEN/PI3K/AKT/mTOR pathway, leading to the suppression of GBM progression. Co-localization experiments demonstrated that SVIP hindered PTEN ubiquitination and degradation by outcompeting STUB1 for VCP/p97 binding. Moreover, SVIP overexpression resulted in reduced activation of AKT/mTOR signaling and facilitated autophagy. In vivo experiments using a GBM xenograft model substantiated the tumor-suppressive effects of SVIP, evident by suppressed tumor growth, decreased IGFBP-2 expression, and improved survival rates. Collectively, our findings underscore the functional significance of SVIP in GBM progression. By inhibiting STUB1 and stabilizing PTEN, SVIP modulates the expression of IGFBP-2 and attenuates the activation of the PI3K/AKT/mTOR pathway, thereby emerging as a promising therapeutic target for GBM treatment.

Abstract Background In assessing the clinical utility and safety of 3.0 T intraoperative magnetic resonance imaging (iMRI) combined with multimodality functional MRI (fMRI) guidance in the resection of functional area gliomas, we conducted a study. Method Among 120 patients with newly diagnosed functional area gliomas who underwent surgical treatment, 60 were included in each group: the integrated group with iMRI and fMRI and the conventional navigation group. Between-group comparisons were made for the extent of resection (EOR), preoperative and postoperative activities of daily living based on the Karnofsky performance status, surgery duration, and postoperative intracranial infection rate. Results Compared to the conventional navigation group, the integrated navigation group with iMRI and fMRI exhibited significant improvements in tumor resection (complete resection rate: 85.0% vs. 60.0%, P = 0.006) and postoperative life self-care ability scores (Karnofsky score) (median ± interquartile range: 90 ± 25 vs. 80 ± 30, P = 0.013). Additionally, although the integrated navigation group with iMRI and fMRI required significantly longer surgeries than the conventional navigation group (mean ± standard deviation: 411.42 ± 126.4 min vs. 295.97 ± 96.48 min, P

Abstract Glioma is the most common malignant tumor of the central nervous system, with EZH2 playing a crucial regulatory role. This study further explores the abnormal expression of EZH2 and its mechanisms in regulating glioma progression. Additionally, it was found that IHMT-337 can potentially be a therapeutic agent for glioma. The prognosis, expression, and localization of EZH2 were determined using bioinformatics, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization. The effects of EZH2 on cell function were assessed using CCK-8 assays, Transwell assays, and wound healing assays. Public databases and RT-qPCR were utilized to identify downstream targets. The mechanisms regulating these downstream targets were elucidated using MS-PCR and WB analysis. The efficacy of IHMT-337 was demonstrated through IC50 measurements, WB analysis, and RT-qPCR. The effects of IHMT-337 on glioma cells in vitro were evaluated using Transwell assays, EdU incorporation assays, and flow cytometry. The potential of IHMT-337 as a treatment for glioma was assessed using a blood–brain barrier (BBB) model and an orthotopic glioma model. Our research confirms significantly elevated EZH2 expression in gliomas, correlating with patient prognosis. EZH2 facilitates glioma proliferation, migration, and invasion alongside promoting SLC12A5 DNA methylation. By regulating SLC12A5 expression, EZH2 activates the WNK1-OSR1-NKCC1 pathway, enhancing its interaction with ERM to promote glioma migration. IHMT-337 targets EZH2 in vitro to inhibit WNK1 activation, thereby suppressing glioma cell migration. Additionally, it inhibits cell proliferation and arrests the cell cycle. IHMT-337 has the potential to cross the BBB and has successfully inhibited glioma progression in vivo. This study expands our understanding of the EZH2-SLC12A5 axis in gliomas, laying a new foundation for the clinical translation of IHMT-337 and offering new insights for precision glioma therapy.

Abstract Background Calcifying pseudoneoplasm of the neuraxis (CAPNON) is indeed a rare central nervous system lesion that can occur in central nervous system (CNS). Due to its infrequency and limited literature reports, it is challenging to diagnose and manage CAPNON. Case presentation In this intriguing study, we embarked on a quest to uncover the story of a 16-year-old girl who experienced bothersome headaches. Through advanced imaging techniques like computed tomography (CT) and magnetic resonance imaging (MRI), we glimpsed a delicate calcified growth within the lateral ventricles’ posterior horn. Motivated by our unwavering commitment to solving mysteries, we embarked on a surgical journey that not only freed the young patient from her ailment but also shed light on the true nature of her puzzling adversary—a remarkable CAPNON. Conclusions For patients with CAPNON who have multiple or non-respectable lesions, the primary goal is to alleviate symptoms. After alleviating the symptoms with partial resection, close monitoring of any residual lesions is essential. If there is no evidence for disease progression, a strategy of continued close observation is appropriate.

Abstract Understanding tumor heterogeneity and immune infiltrates within the tumor-immune microenvironment (TIME) is essential for the innovation of immunotherapies. Here, combining single-cell transcriptomics and chromatin accessibility sequencing, we profile the intratumor heterogeneity of malignant cells and immune properties of the TIME in primary central nervous system diffuse large B-cell lymphoma (PCNS DLBCL) patients. We demonstrate diverse malignant programs related to tumor-promoting pathways, cell cycle and B-cell immune response. By integrating data from independent systemic DLBCL and follicular lymphoma cohorts, we reveal a prosurvival program with aberrantly elevated RNA splicing activity that is uniquely associated with PCNS DLBCL. Moreover, a plasmablast-like program that recurs across PCNS/activated B-cell DLBCL predicts a worse prognosis. In addition, clonally expanded CD8 T cells in PCNS DLBCL undergo a transition from a pre-exhaustion-like state to exhaustion, and exhibit higher exhaustion signature scores than systemic DLBCL. Thus, our study sheds light on potential reasons for the poor prognosis of PCNS DLBCL patients, which will facilitate the development of targeted therapy.

Neuroblastoma is the most common extracranial neuroendocrine tumor in childhood. Although many studies have tried to find effective treatments, there are still numerous limitations in current clinical targeted therapy. So, it is important to find new therapeutic targets and strategies from a new perspective. Our previous study reported that the androgen receptor (AR) promotes the growth of neuroblastoma in vitro and in vivo. Based on documentary investigation, we postulated that the AR–SCAP–SREBPs-CYP17/HMGCR axis may regulate cholesterol and androgens synthesis and form a positive enhancement loop promoting NB progression. Clinical samples and Oncomine database analysis proved the activation of AR–SCAP–SREBPs-CYP17/HMGCR axis in neuroblastoma. The combination of inhibitors of HMGCR (statins) and CYP17A1 (abiraterone acetate) showed synergistic effect that significantly inhibited the proliferation and migration with decreased expression of related genes detected in vitro and in vivo suggesting the dual-targeted therapy had the potential to inhibit the progression of neuroblastoma in spite of its MYCN status. This study provides new ideas for clinical treatment of neuroblastoma with efficacy and reduced toxicity.

Aiming at the limitation of the convolution kernel with a fixed receptive field and unknown prior to optimal network width in U-Net, multi-scale U-Net (MSU-Net) is proposed by us for medical image segmentation. First, multiple convolution sequence is used to extract more semantic features from the images. Second, the convolution kernel with different receptive fields is used to make features more diverse. The problem of unknown network width is alleviated by efficient integration of convolution kernel with different receptive fields. In addition, the multi-scale block is extended to other variants of the original U-Net to verify its universality. Five different medical image segmentation datasets are used to evaluate MSU-Net. A variety of imaging modalities are included in these datasets, such as electron microscopy, dermoscope, ultrasound, etc. Intersection over Union (IoU) of MSU-Net on each dataset are 0.771, 0.867, 0.708, 0.900, and 0.702, respectively. Experimental results show that MSU-Net achieves the best performance on different datasets. Our implementation is available at https://github.com/CN-zdy/MSU_Net.

Multimodal medical images provide significant amounts of complementary semantic information. Therefore, multimodal medical imaging has been widely used in the segmentation of gliomas through computational neural networks. However, inputting images from different sources directly to the network does not achieve the best segmentation effect. This paper describes a convolutional neural network called F-S-Net that fuses the information from multimodal medical images and uses the semantic information contained within these images for glioma segmentation. The architecture of F-S-Net is formed by cascading two sub-networks. The first sub-network projects the multimodal medical images into the same semantic space, which ensures they have the same semantic metric. The second sub-network uses a dual encoder structure (DES) and a channel spatial attention block (CSAB) to extract more detailed information and focus on the lesion area. DES and CSAB are integrated into U-Net architectures. A multimodal glioma dataset collected by Yijishan Hospital of Wannan Medical College is used to train and evaluate the network. F-S-Net is found to achieve a dice coefficient of 0.9052 and Jaccard similarity of 0.8280, outperforming several previous segmentation methods.

Aiming at the problem that the target recognition algorithm based on deep learning has the characteristics of complex network structure, large amount of parameters and high computation delay, which is difficult to directly apply to the missile-borne task, the network lightweight method are summarized. The advantages and respective characteristics of existing compression methods and lightweight networks are introduced, and the excellent algorithms in va-rious aspects are selected for comparison. Finally, combined with the development of deep learning in the field of target detection, the lightweight missile borne image target recognition algorithm is prospected.