Expression and clinical significance of interleukin-10, transforming growth factor-ß1, and CD4+CD25 cytokines in paediatric allergic rhinitis with allergic asthma.

Introduction: It was intended to research the level changes and clinical significance of interleukin (IL)-10, transforming growth factor ß1 (TGF-ß1), and CD4+CD25 cytokines in paediatric allergic rhinitis (AR) accompanied with allergic asthma (AA). Material and methods: Eighty children of AA with AR receiving immunotherapy indications were included as the experimental group (EG), while another 40 healthy children in the same period were selected as the control group (CG). IL-10, TGF-ß1, and CD4+CD25 levels in cells of the two groups before and after treatment were compared and analysed. Results: The serum TGF-ß1 level was determined as 1,045.7 ±44.7 pg/ml in the EG at admission, remarkably higher than that in the CG (p < 0.05). The IL-10 level was 21.4 ±2.8 pg/ml; CD4+CD25 cells accounted for 9.2 ±2.4%, CD4+CD25high cells accounted for 0.6 ±0.3%. These were all greatly lower than those in the CG (p < 0.05). At discharge, the serum TGF-ß1 level in the EG was 903.7 ±29.4 pg/ml, which was still memorably higher than that in the CG (p < 0.05). The IL-10 level changed to 32.8 ±3.7 pg/ml; the percentage of CD4+CD25 was 11.3 ±1.8, respectively, among CD4+T cells. These were also notably lower than those in the CG at discharge (p < 0.05). Conclusions: IL-10, TGF-ß1, and CD4+CD25 level changes in cells might be of reference value as therapeutic indicators for clinical treatment or evaluation of paediatric AR with AA.

[Dielectric properties of tidal volume changes in rabbit lung tissue in the 100 MHz~1 GHz band].

This paper investigates the variation of lung tissue dielectric properties with tidal volume under in vivo conditions to provide reliable and valid a priori information for techniques such as microwave imaging. In this study, the dielectric properties of the lung tissue of 30 rabbits were measured in vivo using the open-end coaxial probe method in the frequency band of 100 MHz to 1 GHz, and 6 different sets of tidal volumes (30, 40, 50, 60, 70, 80 mL) were set up to study the trends of the dielectric properties, and the data at 2 specific frequency points (433 and 915 MHz) were analyzed statistically. It was found that the dielectric coefficient and conductivity of lung tissue tended to decrease with increasing tidal volume in the frequency range of 100 MHz to 1 GHz, and the differences in the dielectric properties of lung tissue for the 6 groups of tidal volumes at 2 specific frequency points were statistically significant. This paper showed that the dielectric properties of lung tissue tend to vary non-linearly with increasing tidal volume. Based on this, more accurate biological tissue parameters can be provided for bioelectromagnetic imaging techniques such as microwave imaging, which could provide a scientific basis and experimental data support for the improvement of diagnostic methods and equipment for lung diseases.

Atomic-level polarization reversal in sliding ferroelectric semiconductors.

Intriguing "slidetronics" has been reported in van der Waals (vdW) layered non-centrosymmetric materials and newly-emerging artificially-tuned twisted moiré superlattices, but correlative experiments that spatially track the interlayer sliding dynamics at atomic-level remain elusive. Here, we address the decisive challenge to in-situ trace the atomic-level interlayer sliding and the induced polarization reversal in vdW-layered yttrium-doped γ-InSe, step by step and atom by atom. We directly observe the real-time interlayer sliding by a 1/3-unit cell along the armchair direction, corresponding to vertical polarization reversal. The sliding driven only by low energetic electron-beam illumination suggests rather low switching barriers. Additionally, we propose a new sliding mechanism that supports the observed reversal pathway, i.e., two bilayer units slide towards each other simultaneously. Our insights into the polarization reversal via the atomic-scale interlayer sliding provide a momentous initial progress for the ongoing and future research on sliding ferroelectrics towards non-volatile storages or ferroelectric field-effect transistors.

Deciphering the tumor immune microenvironment of imatinib-resistance in advanced gastrointestinal stromal tumors at single-cell resolution.

The heterogeneous nature of tumors presents a considerable obstacle in addressing imatinib resistance in advanced cases of gastrointestinal stromal tumors (GIST). To address this issue, we conducted single-cell RNA-sequencing in primary tumors as well as peritoneal and liver metastases from patients diagnosed with locally advanced or advanced GIST. Single-cell transcriptomic signatures of tumor microenvironment (TME) were analyzed. Immunohistochemistry and multiplex immunofluorescence staining were used to further validate it. This analysis revealed unique tumor evolutionary patterns, transcriptome features, dynamic cell-state changes, and different metabolic reprogramming. The findings indicate that in imatinib-resistant TME, tumor cells with activated immune and cytokine-mediated immune responses interacted with a higher proportion of Treg cells via the TIGIT-NECTIN2 axis. Future immunotherapeutic strategies targeting Treg may provide new directions for the treatment of imatinib-resistant patients. In addition, IDO1+ dendritic cells (DC) were highly enriched in imatinib-resistant TME, interacting with various myeloid cells via the BTLA-TNFRSF14 axis, while the interaction was not significant in imatinib-sensitive TME. Our study highlights the transcriptional heterogeneity and distinct immunosuppressive microenvironment of advanced GIST, which provides novel therapeutic strategies and innovative immunotherapeutic agents for imatinib resistance.

Multi-Path Fusion in SFCF-Net for Enhanced Multi-Frequency Electrical Impedance Tomography.

Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.

A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma treatment.

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

Early detection of acute ischemic stroke using Contrast-enhanced electrical impedance tomography perfusion.

A cerebral contrast-enhanced electrical impedance tomography perfusion method is developed for acute ischemic stroke during intravenous thrombolytic therapy. Several clinical contrast agents with stable impedance characteristics and high-conductivity contrast were screened experimentally as electrical impedance contrast agent candidates. The electrical impedance tomography perfusion method was tested on rabbits with focal cerebral infarction, and its capability for early detection was verified based on perfusion images. The experimental results showed that ioversol 350 performed significantly better as an electrical impedance contrast agent than other contrast agents (p < 0.01). Additionally, perfusion images of focal cerebral infarction in rabbits confirmed that the electrical impedance tomography perfusion method could accurately detect the location and area of different cerebral infarction lesions (p < 0.001). Therefore, the cerebral contrast-enhanced electrical impedance tomography perfusion method proposed herein combines traditional, dynamic continuous imaging with rapid detection and could be applied as an early, rapid-detection, auxiliary, bedside imaging method for patients after a suspected ischemic stroke in both prehospital and in-hospital settings.

Development and validation of nomograms for predicting overall survival and cancer-specific survival in elderly patients with locally advanced gastric cancer: a population-based study.

OBJECTIVE: To evaluate the multiple factors influencing the survival of elderly patients with locally advanced gastric cancer (LAGC) and develop and validate the novel nomograms for predicting the survival. METHODS: The clinical features of patients treated between 2000 and 2018 were collected and collated from the Surveillance, Epidemiology, and End Results (SEER) database and three medical centres in China, and the patients were randomly divided into a training cohort (3494), internal validation cohort (1497) and external validation cohort (841). Univariate and multivariate analyses of the prognostic values were performed to identify independent prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS), and two nomogram models were developed. Harrell's concordance index (C-index) and calibration curves were employed to assess discrimination and calibration. Decision curve analysis (DCA) and receiver-operating characteristic (ROC) curves were utilized to investigate the clinical usefulness. RESULTS: In the SEER database, the 5-year OS of the patients was 31.08%, while the 5-year CSS of the patients was 44.09%. Furthermore, in the external validation set, the 5-year OS of the patients was 49.58%, and the 5-year CSS of these patients was 53.51%. After statistical analysis, nine independent prognostic factors of OS and CSS were identified, including age, race, tumour size, differentiation, TNM stage, gastrectomy type, lymph node metastasis (LNM), lymph node ratio (LNR) and chemotherapy. The C-index (approximately 0.7) and calibration curve (close to the optimal calibration line) indicated satisfactory discrimination and calibration of the nomogram. DCA and ROC curves showed that the developed nomogram was superior to TNM stage. CONCLUSION: The novel validated nomogram could accurately predict the prognosis of individual elderly patients with LAGC and guide the selection of clinical treatment measures.

Effective Electrical Impedance Tomography Based on Enhanced Encoder-Decoder Using Atrous Spatial Pyramid Pooling Module.

Electrical impedance tomography (EIT) is a noninvasive and radiation-free imaging method. As a "soft-field" imaging technique, in EIT, the target signal in the center of the measured field is frequently swamped by the target signal at the edge, which restricts its further application. To alleviate this problem, this study presents an enhanced encoder-decoder (EED) method with an atrous spatial pyramid pooling (ASPP) module. The proposed method enhances the ability to detect central weak targets by constructing an ASPP module that integrates multiscale information in the encoder. The multilevel semantic features are fused in the decoder to improve the boundary reconstruction accuracy of the center target. The average absolute error of the imaging results by the EED method reduced by 82.0%, 83.6%, and 36.5% in simulation experiments and 83.0%, 83.2%, and 36.1% in physical experiments compared with the errors of the damped least-squares algorithm, Kalman filtering method, and U-Net-based imaging method, respectively. The average structural similarity improved by 37.3%, 42.9%, and 3.6%, and 39.2%, 45.2%, and 3.8% in the simulation and physical experiments, respectively. The proposed method provides a practical and reliable means of extending the application of EIT by solving the problem of weak central target reconstruction under the effect of strong edge targets in EIT.

Inertial migration of spherical and oblate particles in a triangular microchannel.

The. inertial migration of both spherical and oblate particles within an equilateral triangular channel is studied numerically. Our study primarily focuses on the effects of fluid inertia, quantified by the Reynolds number (Re) and particle size (ß). Our observations reveal two distinct equilibrium positions: the corner equilibrium position (CEP) is situated along the angle bisector near the corner, while the face equilibrium position (FEP) is located on a segment of the line perpendicular from the triangle's center to one of its sides. Spherical particles with varying initial positions predominantly reach the FEP. For oblate particles initially positioned along the angle bisector with a specific orientation, meaning the particle's evolution axis is inside the plane bisecting the angle, they will migrate along the angle bisector to reach the CEP while rotating in the tumbling mode. Conversely, for particles with different initial orientations and positions, they will employ the log-rolling mode to reach the FEP. Notably, we identify a dual-stage particle migration process to the FEP, with trajectories converging to an equilibrium manifold, which bears a resemblance to the cross section of the channel. To further illustrate the transition between FEP and CEP under general initial conditions, except for those along the angle bisector, we construct a phase diagram in the (Re, ß) parameter space. This transition is often triggered by the size of larger particles (as the FEP cannot accommodate them) or the influence of inertia for smaller particles. For the FEP, especially for medium- or small-size particles, we notice an initial outward movement of the FEP from the center of the cross section as Re increases, followed by a return towards the center. This behavior results from the interplay of three forces acting on the particle. This research holds potential implications for the design of microfluidic devices, offering insights into the behavior of particles within equilateral triangular channels.

Fast Iterative Shrinkage-Thresholding Algorithm with Continuation for Brain Injury Monitoring Imaging Based on Electrical Impedance Tomography.

Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring by EIT imaging suffers from image noise (IN) and resolution problems, causing blurred reconstructions. To address these problems, a least absolute shrinkage and selection operator model is built, and a fast iterative shrinkage-thresholding algorithm with continuation (FISTA-C) is proposed. Results of numerical simulations and head phantom experiments indicate that FISTA-C reduces IN by 63.2%, 47.2%, and 29.9% and 54.4%, 44.7%, and 22.7%, respectively, when compared with the damped least-squares algorithm, the split Bergman, and the FISTA algorithms. When the signal-to-noise ratio of the measurements is 80-50 dB, FISTA-C can reduce IN by 83.3%, 72.3%, and 68.7% on average when compared with the three algorithms, respectively. Both simulation and phantom experiments suggest that FISTA-C produces the best image resolution and can identify the two closest targets. Moreover, FISTA-C is more practical for clinical application because it does not require excessive parameter adjustments. This technology can provide better reconstruction performance and significantly outperforms the traditional algorithms in terms of IN and resolution and is expected to offer a general algorithm for brain injury monitoring imaging via EIT.

Collective behavior and hydrodynamic advantage of side-by-side self-propelled flapping foils.

Fish schools and their potential hydrodynamic advantages are intriguing problems and many underlying mechanisms are unclear due to the complexity of the system, especially for large schools. Here large schools containing four, six, and eight self-propelled foils in a side-by-side configuration are numerically studied. The effect of different combinations out of phase and in phase between two neighboring foils is studied. The results show that the multiple abreast self-propelled foils driven by synchronized harmonic flapping motions can spontaneously form stable side-by-side configurations. When compared with a single foil flapping alone, for cases in which any two neighboring foils are in an out-of-phase state, foils consume more energy with a specific cruising speed. For cases where any two neighboring foils are in an in-phase state, foils propel at a lower speed for a specific flapping frequency. Interestingly, the foils in hybrid states in which both out of phase and in phase coexist are preferred to enhance speed and save power. Further analysis indicates that the stability of the configuration and the lower cost of transport are attributed to the synchronized collaborative wake vortex structure and bow configuration formed by any three neighboring foils in a hybrid state. The collaborative vortices in the wake help the foils move forward alternatively during one flapping cycle. The bow configuration prevents the wake from spreading laterally and enhances the performance. Our paper sheds some light on understanding the self-organized collective behavior and hydrodynamic advantages of large schools.

PIM2 Expression Induced by Proinflammatory Macrophages Suppresses Immunotherapy Efficacy in Hepatocellular Carcinoma.

Cancer immunotherapy restores or enhances the effector function of T cells in the tumor microenvironment, but the efficacy of immunotherapy has been hindered by therapeutic resistance. Here, we identify the proto-oncogene serine/threonine protein kinase PIM2 as a novel negative feedback regulator of IFNγ-elicited tumor inflammation, thus endowing cancer cells with aggressive features. Mechanistically, IL1ß derived from IFNγ-polarized tumor macrophages triggered PIM2 expression in cancer cells via the p38 MAPK/Erk and NF-κB signaling pathways. PIM2+ cancer cells generated by proinflammatory macrophages acquired the capability to survive, metastasize, and resist T-cell cytotoxicity and immunotherapy. A therapeutic strategy combining immune checkpoint blockade (ICB) with IL1ß blockade or PIM2 kinase inhibition in vivo effectively and successfully elicited tumor regression. These results provide insight into the regulatory and functional features of PIM2+ tumors and suggest that strategies to influence the functional activities of inflammatory cells or PIM2 kinase may improve the efficacy of immunotherapy. SIGNIFICANCE: Cross-talk between T cells and macrophages regulates cancer cell PIM2 expression to promote cancer aggressiveness, revealing translational approaches to improve response to ICB in hepatocellular carcinoma.

Integrative Analysis of the Genomic and Immune Microenvironment Characteristics Associated With Clear Cell Renal Cell Carcinoma Progression: Implications for Prognosis and Immunotherapy.

Unlike early clear cell renal cell carcinoma (ccRCC), locally advanced and metastatic ccRCC present poor treatment outcomes and prognosis. As immune checkpoint inhibitors have achieved favorable results in the adjuvant treatment of metastatic ccRCC, we aimed to investigate the immunogenomic landscape during ccRCC progression and its potential impact on immunotherapy and prognosis. Using multi-omics and immunotherapy ccRCC datasets, an integrated analysis was performed to identify genomic alterations, immune microenvironment features, and related biological processes during ccRCC progression and evaluate their relevance to immunotherapy response and prognosis. We found that aggressive and metastatic ccRCC had higher proportions of genomic alterations, including SETD2 mutations, Del(14q), Del(9p), and higher immunosuppressive cellular and molecular infiltration levels. Of these, the Del(14q) might mediate immune escape in ccRCC via the VEGFA-VEGFR2 signaling pathway. Furthermore, immune-related pathways associated with ccRCC progression did not affect the immunotherapeutic response to ccRCC. Conversely, cell cycle pathways not only affected ccRCC progression and prognosis, but also were related to ccRCC immunotherapeutic response resistance. Overall, we described the immunogenomic characteristics of ccRCC progression and their correlations with immunotherapeutic response and prognosis, providing new insights into their prediction and the development of novel therapeutic strategies.

Deep-reinforcement-learning-based self-organization of freely undulatory swimmers.

It is fascinating that fish groups spontaneously form different formations. The collective locomotions of two and multiple undulatory self-propelled foils swimming in a fluid are numerically studied and the deep reinforcement learning (DRL) is applied to control the locomotion. We explored whether typical patterns emerge spontaneously under the driven two DRL strategies. One strategy is that only the following fish gets hydrodynamic advantages. The other is that all individuals in the group take advantage of the interaction. In the DRL strategy, we use swimming efficiency as the reward function, and the visual information is included. We also investigated the effect of involving hydrodynamic force information, which is an analogy to that detected by the lateral line of fish. Each fish can adjust its undulatory phase to achieve the goal. Under the two strategies, collective patterns with different characteristics, i.e., the staggered-following, tandem-following phalanx and compact modes emerge. They are consistent with the results in the literature. The hydrodynamic mechanism of the above high-efficiency collective traveling modes is analyzed by the vortex-body interaction and thrust. We also found that the time sequence feature and hydrodynamic information in the DRL are essential to improve the performance of collective swimming. Our research can reasonably explain the controversial issue observed in the relevant experiments. The paper may be helpful for the design of bionic fish.

Postoperative Adjuvant Imatinib Therapy-Associated Nomogram to Predict Overall Survival of Gastrointestinal Stromal Tumor.

Background: Adjuvant imatinib therapy has been shown to improve overall survival (OS) of gastrointestinal stromal tumor (GIST) significantly. Few nomograms combining the use of adjuvant imatinib and clinicopathological characteristics estimate the outcome of patients. We aimed to establish a more comprehensive nomogram for predicting OS in patients with GIST. Methods: In total, 1310 GIST patients undergoing curative resection at four high-volume medical centers between 2001 and 2015 were enrolled. Independent prognostic factors were identified by multivariate Cox analysis. Eligible patients were randomly assigned in a ratio of 7:3 into a training set (916 cases) and a validation set (394 cases). A nomogram was established by R software and its predictive power compared with that of the modified National Institutes of Health (NIH) classification using time-dependent receiver operating characteristic (ROC) curves and calibration plot. Results: Age, tumor site, tumor size, mitotic index, postoperative imatinib and diagnostic delay were identified as independent prognostic parameters and used to construct a nomogram. Of note, diagnostic delay was for the first time included in a prognostic model for GIST. The calibrated nomogram resulted in predicted survival rates consistent with observed ones. And the decision curve analysis suggested that the nomogram prognostic model was clinically useful. Furthermore, time-dependent ROC curves showed the nomogram exhibited greater discrimination power than the modified NIH classification in 3- and 5-year survival predictions for both training and validation sets (all P < 0.05). Conclusions: Postoperative adjuvant imatinib therapy improved the survival of GIST patients. We developed and validated a more comprehensive prognostic nomogram for GIST patients, and it could have important clinical utility in improving individualized predictions of survival risks and treatment decision-making.

Clinical outcomes of proximal gastrectomy with gastric tubular reconstruction and total gastrectomy for proximal gastric cancer: A matched cohort study.

Background: Proximal gastrectomy with gastric tubular reconstruction is a surgical procedure that can preserve function in patients with proximal gastric cancer. However, whether gastric tubular reconstruction with proximal gastrectomy has certain advantage in some aspects over total gastrectomy is controversial. To evaluate the benefit of gastric tubular reconstruction after proximal gastrectomy, we compared gastric tubular reconstruction with total gastrectomy for proximal gastric cancer. Method: A total of 351 patients were enrolled. Concurrent total gastrectomy patients matched with the Proximal gastrectomy group in age, sex, body mass index, clinical stage, and ASA score were selected by propensity score matching. Preoperative basic information, perioperative indicators, histopathological features, postoperative complications and nutritional status, reflux were compared between the two groups. Results: There was no significant difference in the incidence of reflux between two groups (14.8% and 6.5% respectively, P = 0.085). There were significant differences between the two groups in bowel function recovery (2.29 ± 1.16 vs. 3.01 ± 1.22; P = 0.039) and start of soft diet (4.06 ± 1.81 vs. 4.76 ± 1.69; P = 0.047). There were no significant differences between the two groups in nutritional status one year after surgery. However, the decrease in serum hemoglobin in the TG group at 3 and 6 months after surgery was significantly higher than that in the PG group (P = 0.032 and 0.046, respectively). One month after surgery, %BW loss in TG group was significantly lower than that in the PG group (P = 0.024). Conclusion: The Proximal gastrectomy group has better clinical outcome and gastric tubular reconstruction is simple, similar complications and reflux rates, gastric tubular reconstruction may be more suitable for proximal gastric cancer.

Effects of robotic and laparoscopic-assisted surgery on lymph node dissection and quality of life in the upper third of gastric cancer: A retrospective cohort study based on propensity score matching.

Objective: The objective of this study was compare the effects of robot-assisted and laparoscopic-assisted surgery on lymph node dissection and quality of life in upper third gastric cancer patients undergoing radical total gastrectomy. Methods: The clinical and follow-up data of 409 patients with upper third gastric cancer who underwent total gastrectomy from July 2016 to May 2021 were enrolled. The patients were divided into a robotic group (n = 106) and a laparoscopic group (n = 303). Age, sex, body mass index, American Society of Anesthesiologists score, tumor size and location, pathological type, cT, cN, and cTNM were adjusted to offset selection bias. The patient characteristics, operative procedures, surgical outcomes, oncologic and pathologic outcomes, number of lymph node dissections, quality of life assessment, and nutritional status were compared between the two groups. Results: After propensity score matching, 61 cases were included in the robotic group and 122 cases were included in the laparoscopic group. The number of dissected lymph nodes (37.3 ± 13.5 vs. 32.8 ± 11.8, P = 0.022) significantly differed between the two groups. The number of lower mediastinal and subphrenic lymph nodes in the robotic group was greater than that in the laparoscopic group, and the difference was statistically significant (P < 0.001). Compared with the laparoscopic group, the total score of physical symptoms in the robotic group was significantly lower at 6 and 12 months after surgery (P = 0.03 and P = 0.001, respectively). The total social function score at 6 and 12 months after surgery was higher in the robotic group (P = 0.006 and P = 0.022). The quality of life scores were statistically significant only at 3 months after the operation (P = 0.047). A higher patient-generated subjective global assessment (PG-SGA) score is when the score significantly correlated (P < 0.001) with a higher related physical symptoms score, lower social function score, and lower quality of life score. Conclusion: Compared with laparoscopic radical gastrectomy, robotic radical gastrectomy is safe and feasible. Compared with laparoscopic radical gastrectomy, robotic radical gastrectomy was more refined, was associated with less surgical bleeding, and increased the quality of lymph node dissection. In addition, patients in the robotic group showed better postoperative quality of life.

Advances of deep learning in electrical impedance tomography image reconstruction.

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future.