Objective To investigate the influence of different pressures and duration of CO2 pneumoperitoneum on the adhesive and invasive ability of gastric cancer cells based on the expressions of adhesive and invasive molecules. Methods With an artificial CO2 pneumoperitoneum model in vitro, human gastric cancer cell lines including MKN-45, SGC-7901, and MKN-28 were exposed to CO2 in different environments: 0 mm Hg （1 mm Hg=0.133 kPa）, 9 mm Hg （2 h, 4 h）, and 15 mm Hg （2 h, 4 h）. The expressions of mRNA of E-cadherin, intercellular adhesion molecule-1 (ICAM-1), matrix metalloproteinase-2 (MMP-2), and vascular endothelial growth factor-A (VEGF-A) in the different environments were measured by RT-PCR. The expressions of protein of E-cadherin and ICAM-1 in the environments of 0 mm Hg and 15 mm Hg （4 h） were measured by FCM. Results With the increase of duration or pressure, RT-PCR showed that there was a downward trend in the expression of E-cadherin mRNA as well as there were upward trends in the expressions of ICAM-1, MMP-2, and VEGF-A mRNA; FCM showed that there was a downward trend in the expression of E-cadherin protein while the expression of ICAM-1 protein showed the opposite change. But there were no obvious differences under different environment (P＞0.05). Conclusions Under low pressure (≤15 mm Hg) and short time (≤4 h) of CO2 pneumoperitoneum, the adhesive and invasive ability of gastric cancer cells could not be affected, which means that under this environment, CO2 pneumoperitoneum will not increase the possibility of neoplasm metastasis.
Osteoarthritis is a common degenerative joint disease, which is often analyzed by X-ray images. However, if there is a lack of clinical experience when reading the films, it is easy to cause misdiagnosis. Although deep learning has made significant progress in the field of medical image processing, existing models still have limitations in capturing subtle lesion features such as joint spaces. This paper proposes an automatic diagnosis method for osteoarthritis based on the improved shifted windows Transformer (Swin Transformer) and graph convolutional network. By enhancing the modeling of joint space features and cross-layer feature fusion, it is expected to effectively improve the accuracy of early diagnosis of osteoarthritis. Firstly, this paper designs the shifted windows horizontal attention mechanism (SW-HAM), which can enhance the feature extraction ability in the horizontal direction. Secondly, the central-attention graphSAGE (CAG-SAGE) is introduced to conduct weighted aggregation of the feature information of the lesion area through the dynamic attention mechanism. Finally, cross-layer connection technology is utilized to achieve efficient fusion of multi-layer features. The experimental results show that the SW-HAM and CAG-SAGE modules and cross-layer connections significantly improve the model performance. The classification accuracy, recall rate, precision rate, F1 score, and area under the curve are 94.59%, 95.14%, 94.05%, 94.41%, and 96.30% respectively, all of which are superior to the classical network and existing methods. It provides a new and effective method for the classification and diagnosis of osteoarthritis.
Breast cancer is a malignancy caused by the abnormal proliferation of breast epithelial cells, predominantly affecting female patients, and it is commonly diagnosed using histopathological images. Currently, deep learning techniques have made significant breakthroughs in medical image processing, outperforming traditional detection methods in breast cancer pathology classification tasks. This paper first reviewed the advances in applying deep learning to breast pathology images, focusing on three key areas: multi-scale feature extraction, cellular feature analysis, and classification. Next, it summarized the advantages of multimodal data fusion methods for breast pathology images. Finally, the study discussed the challenges and future prospects of deep learning in breast cancer pathology image diagnosis, providing important guidance for advancing the use of deep learning in breast diagnosis.
Objective To review the advance of gene diagnosis and gene therapy on gastric cancer. Methods Literatures about the advance of gene diagnosis and therapy on gastric cancer were reviewed. Results Detection of tumor marker by gene technique is important for early diagnosis, follow-up and therapy evaluation of gastric cancer in clinic. But there are still many problems in gene therapy of gastric cancer. Conclusion Gene detection and gene therapy will become important supplementary means for diagnosis and treatment of gastric cancer.
ObjectiveTo assess the outcomes of laparoscopy-assisted surgery for treatment of advanced gastric cancer.MethodsA total of 115 patients with advanced gastric cancer were included between January 2014 and December 2018 were analyzed retroprospectively, the patients were divided into two groups: open surgery group (OS group, n=63) and laparoscopy-assisted surgery group (LAS group, n=52). Baseline characteristics, intraoperative parameters and postoperative items, and long-term efficacy were compared between the two groups.ResultsThere was no significant difference in preoperative baseline data including gender, age and preoperative serum parameters between the two groups (P>0.05). Intraoperative blood loss in the LAS group was significantly less than that in the OS group (P<0.05). In addition, the first feeding time after operation and postoperative hospital stay in the LAS group were significantly shorter than the OS group (P<0.05). Furthermore, numbers of white blood cells and neutrophils in the LAS group were fewer than that in the OS group at postoperative 2 days (P<0.05); the level of serum albumin in the LAS group was higher than that OS group (P<0.05). The number of lymph nodes detected during operation in the LAS group was more than that in the OS group (P<0.05). Operative time and occurrence of postoperative complications were not statistically significant between the two groups (P>0.05). One hundred and ten of 115 patients were followed- up, the follow-up rate was 95.7%. The follow-up time ranged from 6 to 48 months, with a median follow-up time of 12.4 months. The disease-free survival time of the OS group was 12.2±6.5 months, while that of the LAS group was 13.5±7.4 months. There was no significant difference between the two groups (P>0.05).ConclusionsLaparoscopic technique in treatment of advanced gastric cancer has the minimally invasive advantage, less intraoperative blood loss, less surgical trauma, and faster postoperative recovery in comparing to the traditional open surgery. Also the lymph node dissection is superior to open surgery. The curative effect is comparable to that of open surgery.
【Abstract】ObjectiveTo evaluate the role of MRA, IPVG and DUS in the hemodynamics studies of portal hypertension. MethodsThirtyeight patients with portal hypertension were examined with Philips Gyroscan 1.0 Tesla MR imaging system. 3DDCE MRA and 2DPC MR were used for study of portal venous anatomy and its hemodynamics. The results were compared with those obtained from IPVG and DUS. Results3DDCE MRA could clearly display the anatomical imaging of portal venous system and its imaging quality was better than that of IPVG. The data of hemodynamics from 2DPC MR including diameter, blood velocity and blood flow were closely correlated to those from DUS. ConclusionAs a noninvasive technique, MRA can display the anatomy of portal venous system and measure its hemodynamics exactly. It should be applied as the first choice in hemodynamics evaluation for portal hypertension.
In recent years, wearable devices grew up gradually and developed increasingly. Aiming at the problems of skin sensibility and the change of electrode impedance of Ag/AgCl electrode in the process of long-term electrocardiogram (ECG) signal monitoring and acquisition, this paper discussed in detail a new sensor technology–fabric electrode, which is used for ECG signal acquisition. First, the concept and advantages of fabric electrode were introduced, and then the common substrate materials and conductive materials for fabric electrode were discussed and evaluated. Next, we analyzed the advantages and disadvantages from the aspect of textile structure, putting forward the evaluation system of fabric electrode. Finally, the deficiencies of fabric electrode were analyzed, and the development prospects and directions were prospected.
ObjectiveTo evaluate the effect of glutamineenhanced enteral nutritional support on elder patients after total gastrectomy. MethodsA total of eightyfour cases of elder patients receiving total gastrectomy were included in this study from February 2008 to August 2010. The patients were randomly divided into three groups: glutamineenhanced enteral nutrition (Gln) group, enteral nutrition (EN) group and parenteral nutrition (PN) group. The complications and hospital stay after operation were compared, and the levels of serum total protein, albumin, proalbumin， and transferrin of patients were measured before operation, on 2 d and 10 d after operation, respectively. Furthermore, the percentage of CD4 and CD8 T cells, CD4/CD8 ratio， and the levels of serum IgM and IgG of patients in peripheral blood before and after operation were detected. ResultsNutritional therapy was successfully performed in patients of three groups. The anal exhaust time and hospital stay after operation of patients in Gln group and EN group were significantly lower than those in PN group (Plt;0.05). The difference of postoperative complications and digestive tract symptoms of patients in three groups was not obvious (Plt;0.05). Anastomotic fistula occurred in one patient of PN group on 6 d after operation and was cured by conservative treatment for 54 d. The difference of total protein, albumin, proalbumin, and transferrin levels of patients in three groups before operation was not significant (Pgt;0.05), and these indexes fell dramatically on 2 d after operation and lower than before operation (Plt;0.05), although the intergroup difference was not statistically significant (Pgt;0.05). On 10 d after operation, all indexes recovered in different extent, while those data in Gln group and EN group were significantly higher than those on 2 d after operation (Plt;0.05). The levels of total protein, albumin, and proalbumin of patients in Gln group and EN group were markedly higher than those in PN group (Plt;0.05), although there was no difference between the former groups (Pgt;0.05). The difference of several immunological parameters of patients in three groups before operation was not significant (Pgt;0.05). On 10 d after operation, the percentage of CD4 and CD8 T cells, CD4/CD8 ratio, and the levels of serum IgM and IgG of patients in Gln group returned and even exceeded the preoperative results, which were significantly higher than those in EN group and PN group other than IgM (Plt;0.05). The postoperative results of all parameters except IgG in EN group were significantly lower than preoperative results in patients of EN group and PN group (Plt;0.05). ConclusionsIt is safe and feasible to elder patients who had received total gastrectomy and perioperative glutamine-enhanced nutritional support, which can improve nutrition and immune status, promote the recovery and reduce the duration of hospital stay, and nutritiional support after total gastrectomy is one of the optimal choices for these patients.
Breast whole slide image (WSI) serves as an essential basis for breast cancer diagnosis and subtype classification. However, its high resolution, multi-scale structural characteristics, and arbitrary orientation pose substantial challenges for automated analysis. Existing deep learning methods typically rely on large amounts of annotated data and struggle to handle the rotational variability and scale differences inherent in pathological images, which limits their generalization ability in cross-center settings. To address these issues, this study proposes a self-supervised learning model, IAM-BYOL, which incorporated geometric priors into the representation learning process. Building upon the BYOL framework, the model introduced an isotropic attention module (IAM). By employing discrete rotation group convolution, IAM enabled weight sharing across different rotated versions of the convolutional kernels, endowing the encoder with structural rotation equivariance. A subsequent group pooling operation converted the equivariant features into rotation-invariant isotropic representations. In addition, a multi-scale attention mechanism adjusted feature weights adaptively according to responses from different receptive fields, allowing the model to capture informative patterns ranging from nuclear-level details to tissue-level organization. Experimental results demonstrated that IAM-BYOL achieved classification accuracies of 98.74%, 99.04%, 99.01%, and 98.63% on the BreakHis dataset at 40×, 100×, 200×, and 400× magnifications, respectively, while attaining an accuracy of 93.02% on the cross-center private clinical dataset BCD. These findings indicate that introducing geometric inductive biases into pathological image representation learning can effectively enhance model robustness and generalization capability.
As an intermediate phenotype for multiple cardiovascular diseases, left ventricular hypertrophy (LVH) benefits from early diagnosis, which allows for timely intervention to prevent worsening of the condition, mitigate severe complications like heart failure and arrhythmias, and consequently improve patient outcomes. Preliminary advances have been made using deep learning for the early diagnosis and identification of etiology in LVH. This paper reviews the pathophysiology, causes, and diagnostic standards for LVH, discusses the strengths and weaknesses of applying deep learning to diagnostic tools such as echocardiography, cardiac magnetic resonance imaging, and electrocardiogram, examines its use in prognostic evaluation, and concludes by summarizing current achievements and suggesting future research avenues.