HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images.

BACKGROUND: Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. METHODS: In this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios. RESULTS: Our baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks. CONCLUSIONS: Comprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

Clinical Significance of a Novel Vasculogenic Mimicry-Based Prognostic Model in Hepatocellular Carcinoma.

BACKGROUND: Vasculogenic mimicry, a novel neovascularization pattern of aggressive tumors, is associated with poor clinical outcomes. OBJECTIVE: The aim of this research was to establish a new model, termed VC score, to predict the prognosis, Tumor Microenvironment (TME) components, and immunotherapeutic response in Hepatocellular Carcinoma (HCC). METHODS: The expression data of the public databases were used to develop the prognostic model. Consensus clustering was performed to confirm the molecular subtypes with ideal clustering efficacy. The high- and low-risk groups were stratified utilizing the VC score. Various methodologies, including survival analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Dysfunction and Exclusion scores (TIDE), Immunophenoscore (IPS), and nomogram, were utilized for verification of the model performance and to characterize the immune status of HCC tissues. GSEA was performed to mine functional pathway information. RESULTS: The survival and immune characteristics varied between the three molecular subtypes. A five-gene signature (TPX2, CDC20, CFHR4, SPP1, and NQO1) was verified to function as an independent predictive factor for the prognosis of patients with HCC. The high-risk group exhibited lower Overall Survival (OS) rates and higher mortality rates in comparison to the low-risk group. Patients in the low-risk group were predicted to benefit from immune checkpoint inhibitor therapy and exhibit increased sensitivity to immunotherapy. Enrichment analysis revealed that signaling pathways linked to the cell cycle and DNA replication processes exhibited enrichment in the high-risk group. CONCLUSIONS: The VC score holds the potential to establish individualized treatment plans and clinical management strategies for patients with HCC.

Does erectile dysfunction predict cardiovascular risk? A cross-sectional study of clinical characteristics in patients with erectile dysfunction combined with coronary heart disease.

Background: Erectile Dysfunction (ED) is a common sexual dysfunction in men who are unable to consistently obtain and maintain sufficient penile erection to accomplish a satisfactory sexual life. ED is currently considered to be a predictor of cardiovascular disease (CVD), but few studies have observed the association between ED and clinical features of coronary heart disease (CHD). An investigation of the association between ED and clinical characteristics of CHD was carried out using a cross-sectional study design. Methods: This cross-sectional single-center study was conducted in the Department of Cardiology and included 248 patients. Associations between patients' general information, underlying disease information, coronary heart disease information, and ED severity were statistically and analytically analyzed using SPSS 26.0 software. Patients with comparable clinical characteristics were grouped together using K-means clustering. Finally, ordered logistic regression analysis was performed for general and underlying disease information. Results: In the comparison of general data, age, education, and weekly exercise were associated with the distribution of ED severity. In the comparison of underlying disease information, the number of underlying diseases, hypertension, diabetes, hyperlipidemia, anxiety state, and depressive state were associated with the distribution of ED severity. In the comparison of CHD information, the degree of ED severity was associated with CHD subtypes, lesion sites, number of stenoses, degree of stenosis, and interventional interventions. The time from ED to CHD onset was associated with the subtypes of CHD and the number of stenoses. We clustered the main characteristics of low-risk and high-risk patients and ordered logistic regression analysis found that BMI, smoking, alcoholism, number of underlying diseases, diabetes, anxiety state, and depression state were all risk factors for CHD severity (P < 0.05); the higher the value of the above factors, the more severe the degree of CHD. Age was a protective factor for CHD severity; the younger the patient, the lower the likelihood of myocardial infarction. Conclusion: ED severity and the time from ED to CHD onset may be predictive of coronary heart disease severity. Reducing smoking and alcohol consumption, maintaining a healthy body weight, and regular physical activity are important in preventing CVD in ED patients.

[Comparative study of minimally invasive titanium elastic nail and steel plate on the treatment of fracture of tibiofibular fracture in adults].

OBJECTIVE: To compare the clinical outcomes of using elastic intramedullary nail and plate to fix fibular fracture. METHODS: The 60 patients with tibiofibular fractures admitted from January 2015 to December 2022 were divided into two groups:intramedullary nail group and plate group, 30 cases each, intramedullary nail group was treated with elastic intramedullary nail fixation group, plate group was treated with steel plate and screw fixation group. Intramedullary nail group, there were 18 males and 12 females, aged from 22 to 75 years old with an average of (39.4±9.8) years old, including 24 cases of traffic accidents injury, 6 cases of falling injury, 23 cases of closed fractures, 7 cases of open fractures. Steel plate group, there were 15 males and 15 females, aged from 24 to 78 years old with an average of (38.6±10.2) years old. The 22 cases were injured by traffic accident, 8 cases were injured by falling. The 24 cases were closed fractures and 6 cases were open fractures. The operation time, intraoperative bleeding, American Orthopedic Foot and Ankle Society (AOFAS) ankle and hind foot scores, clinical healing time of fibula and the incidence of wound complications were compared between the two groups. RESULTS: The patients in both groups were followed up for 6 to 21 months, with an average of (14.0±2.8) months. Compared with plate group, intramedullary nail group had shorter operative time, less bleeding, shorter clinical healing time of fibula, and lower infection rate of incision, and the difference was statistically significant (P<0.05). There were 2 cases of delayed healing in intramedullary nail group, 1 case of nonunion in plate group, and 2 cases of delayed healing in plate group, and there was no statistically significant difference between the two groups (P>0.05). In the last follow-up, according to the AOFAS scoring standard, the ankle function in intramedullary nail group was excellent in 17 cases, good in 12 cases, fair in 1 case, with an average of (88.33±4.57) points, while in plate group, excellent in 16 cases, good in 10 cases, fair in 4 cases, with an average of (87.00±4.14) points;There was no statistical difference between the two groups (P>0.05). CONCLUSION: Elastic intramedullary nail has the advantages of short operation time, less intraoperative bleeding, short fracture healing time and less incision complications in the treatment of fibular fracture, which is worthy of clinical application.

Robotic-assisted total knee arthroplasty results in decreased incidence of anterior femoral notching compared to posterior referenced instrumented total knee arthroplasty.

OBJECTIVE: Periprosthetic fracture (PPF) is an uncommon but devastating complication after total knee arthroplasty (TKA). Anterior femoral notching (AFN) is one of a perioperative risk factor for PPF. The main purpose of this study was to compare between the rates of anterior femoral notching (AFN) and supracondylar periprosthetic femoral fracture (sPPF) of manual TKA and robotic arm-assisted TKA (RATKA). Meanwhile, blood loss, transfusion rates, inflammatory responses, complications, early clinical and radiological outcomes were also assessed. METHODS: This retrospective study included 330 patients (133 RATKA and 197 manual TKA). Differences in risks of inflammatory, blood loss, complications (periprosthetic fracture and periprosthetic joint infection), pre-operative and post-operative distal lateral femoral angle (LDFA), distal femoral width (DFW), prosthesis-distal femoral width (PDFW) ratio, AFN, femoral component flexion angle (FCFA), peri-operative and post-operative functional outcomes between the RATKA and manual TKA groups were compared. RESULTS: The operation time and postoperative CRP level in the RATKA group was significantly longer and higher than that in the manual TKA group (p < .001). However, there was no significant difference in postoperative WBC level (p = .217), hemoglobin loss (p = .362), postoperative drainage (p = .836), and periprosthetic fracture (p = 1.000). There was no significant difference in LDFA (p > .05), DFW(p = .834), PDFW ratio (p = .089) and FCFA (p = .315) between the two groups, but the rate of AFN in the RATKA group was significantly lower than that in the manual TKA group (p < .05). There was no significant difference in ROM between the two groups on POD3, POD 90 and 1 year (p < .05), but the FJS-12 score in the RATKA group was higher than that in the manual TKA group on 1 year (p = .001). CONCLUSION: Robotic-assisted total knee arthroplasty can decrease the incidence of anterior femoral notching compared to posterior referenced instrumented total knee arthroplasty.

Prognostic and immune predictive roles of a novel tricarboxylic acid cycle-based model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. Since the tricarboxylic acid cycle is widely involved in tumor metabolic reprogramming and cuproptosis, investigating related genes may help to identify prognostic signature of patients with HCC. Data on patients with HCC were sourced from public datasets, and were divided into train, test, and single-cell cohorts. A variety of machine learning algorithms were used to identify different molecular subtypes and determine the prognostic risk model. Our findings revealed that the risk score (TRscore), based on the genes OGDHL, CFHR4, and SPP1, showed excellent predictive performance in different datasets. Pathways related to cell cycle and immune inflammation were enriched in the high-risk group, whereas metabolism-related pathways were significantly enriched in the low-risk group. The high-risk group was associated with a greater number of mutations of detrimental biological behavior and higher levels of immune infiltration, immune checkpoint expression, and anti-cancer immunotherapy response. Low-risk patients demonstrated greater sensitivity to erlotinib and phenformin. SPP1 was mainly involved in the interaction among tumor-associated macrophages, T cells, and malignant cells via SPP1-CD44 and SPP1-(ITGA5 + ITGB1) ligand-receptor pairs. In summary, our study established a prognostic model, which may contribute to individualized treatment and clinical management of patients with HCC.

Metformin Increases the Response of Cholangiocarcinoma Cells to Gemcitabine by Suppressing Pyruvate Kinase M2 to Activate Mitochondrial Apoptosis.

BACKGROUND: Cholangiocarcinoma (CCA) is a malignant tumor with a high mortality rate. Resistance to chemotherapy remains a major challenge related to cancer treatment, and increasing the sensitivity of cancer cells to therapeutic drugs is a major focus of cancer treatment. AIMS: We purposed to explore the role of Metformin in CCA involved in chemotherapeutic sensitivity and Pyruvate kinase M2 (PKM2) through regulating mitochondrial apoptosis in the present study. METHODS: CCA cell lines of HCC9810 and RBE were treated with Metformin companied with antagonists or agonists of PKM2, cells sensitivity to Gemcitabine, cell migration and invasion along with apoptosis, which is mediated by JC-1 and LDH were assayed. RESULTS: Our results indicated that Metformin and Gemcitabine exhibit synergistic effect on inhibition of cholangiocarcinoma cell viability, cell migration and invasion as well as promotion apoptosis of cholangiocarcinoma cells. In vivo, Metformin combined with Gemcitabine has cooperation in inhibiting the growth of cholangiocarcinoma cell-derived tumors. Moreover, Metformin and Gemcitabine inhibited expression of PKM2 and PDHB in HCC9810 and RBE. CONCLUSION: Our study suggested that Metformin may increase the response of cholangiocarcinoma cells to Gemcitabine by suppressing PKM2 to activate mitochondrial apoptosis.

The diagnosis and treatment of septic hip with osteonecrosis of the femoral head.

This article aims to provide clinical doctors with references for the diagnosis and treatment of osteonecrosis of the femoral head (ONFH) accompanied with septic hip by summarizing and analyzing clinical data and postoperative follow-up information of patients treated with two-stage arthroplasty. We retrospectively analyzed ten patients who underwent two-stage arthroplasty in our hospital due to ONFH accompanied with septic hip. The diagnosis of septic hip includes erythrocyte sedimentation rate (ESR) > 30 mm/h, C-reactive protein (CRP) > 10 mg/L, pus-like synovial fluid, positive microbiological culture, and the findings of septic arthritis on magnetic resonance imaging (MRI) scan. Patient's information was evaluated based on the review of medical records, including gender, age, symptoms, risk factor of ONFH and septic arthritis, blood test, radiograph, MRI scan, microbiological culture, treatment, follow-up period and outcome. A total of ten patients were diagnosed with ONFH accompanied with septic hip. The average follow-up period was 43.5 months. None of the patients experienced failure during the follow-up period. The risk factor of ONFH was alcohol-related (60%), steroid-related (20%) and idiopathic (20%). Nine patients (90%) have no risk factor of septic arthritis and one patient (10%) has nephrotic syndrome. All patients did not experience any fever symptoms before surgery, but all showed worsening symptoms of pain. There were three patients (30%) with abnormal WBC count > 10 × 109/L. All patients had elevated ESR and/or CPR. Nine patients (90%) had positive MRI findings, and seven patients (70%) had positive microbiological culture. When patients with ONFH experience worsening hip joint pain accompanied by unexplained elevated CRP and/or ESR, it should be suspected whether ONFH is accompanied with septic hip. In these cases, MRI scans should be performed to exclude septic hip. Patients with ONFH accompanied with septic hip showed satisfactory results after two-stage arthroplasty.

USBDAN: Unsupervised Scale-aware and Boundary-aware Domain Adaptive Network for Gastric Tumor Segmentation.

Accurate segmentation of gastric tumors from computed tomography (CT) images provides useful image information for guiding the diagnosis and treatment of gastric cancer. Researchers typically collect datasets from multiple medical centers to increase sample size and representation, but this raises the issue of data heterogeneity. To this end, we propose a new cross-center 3D tumor segmentation method named unsupervised scale-aware and boundary-aware domain adaptive network (USBDAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale features from the CT images with anisotropic resolution, and a scale-aware and boundary-aware domain alignment (SaBaDA) module for adaptively aligning multi-scale features between two domains and enhancing tumor boundary drawing based on location-related information drawn from each sample across all domains. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers. Our results demonstrate that the proposed method outperforms several state-of-the-art methods.

DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer.

Background: The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC). Methods: We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm. Results: The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-ß, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed. Conclusions: An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.

The novel role of IFITM1-3 in myogenic differentiation of C2C12 cells.

Interferon-induced transmembrane proteins (IFITMs 1, 2, and 3) play a critical role in preventing pathogen infection in vertebrates. They are also involved in the occurrence and prognosis of cancer. Myogenesis is a complex process regulated by several factors. This study disclosed that Ifitm1-3 were upregulated in the process of myogenic differentiation of C2C12 myoblasts on days 3, 5, and 7. This positively correlated with the expression of differentiation factors MyoD, myogenin, Mrf5, and desmin. Furthermore, knockdown of Ifitm1-3 by their individual siRNAs inhibited myogenesis of C2C12 myoblasts, with relative downregulation of MyoD, myogenin, Mrf5, and desmin. Subsequently, myotube formation and fusion percentage decreased. Co-immunoprecipitation combined with LC-MS/MS analysis uncovered the interaction proteins of IFITM1 and IFITM3 in C2C12 myoblasts. A total of 84 overlapped interaction proteins of IFITM1 and IFITM3 were identified, and one of the clusters was engaged in cytoskeletal and sarcomere proteins, including desmin, myosin, actin, vimentin, nestin, ankycorbin, and nucleolin. Hence, we hypothesize that these interacting proteins may function as scaffolds for IFITM1-3, possibly through the interaction protein desmin to initiate further interaction with other proteins to participate in myogenesis; however, the molecular mechanisms remain unclear. Our study may contribute to the development of novel therapeutics for myopathic diseases.

Corrigendum to 'Modeling colorectal tumorigenesis using the organoids derived from conditionally immortalized mouse intestinal crypt cells (ciMICs)' [Genes Dis 8 (2021) 814-826].

[This corrects the article DOI: 10.1016/j.gendis.2021.01.004.].

Enhancing Bioactive Components of Euryale ferox with Lactobacillus curvatus to Reduce H2O2-Induced Oxidative Stress in Human Skin Fibroblasts.

This study investigated the effects of Lactobacillus curvatus fermentation on the oxidative stress attenuating effects of Euryale ferox on H2O2-induced human skin fibroblasts (HSF). The results showed that Lactobacillus curvatus fermentation (i) increases the content of the various bioactive components of Euryale ferox and is found to have smaller molecular weights of polysaccharides and polypeptides; (ii) increases the overall intracellular and extracellular antioxidant capacity of H2O2-induced HSF while reducing reactive oxygen species (ROS) levels. Superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) all showed simultaneous increases in activity. Aside from that, the Nrf2 and MAPK signaling pathways are activated to regulate downstream-associated proteins such as the Bax/Bcl-2 protein ratio, matrix metalloproteinase 1 (MMP-1) activity, and human type I collagen (COL-1). These results suggested that the fermentation of Euryale ferox with Lactobacillus curvatus enhances its antioxidant capacity and attenuates apoptosis and senescence caused by oxidative stress.

Unsupervised domain selective graph convolutional network for preoperative prediction of lymph node metastasis in gastric cancer.

Preoperative prediction of lymph node (LN) metastasis based on computed tomography (CT) scans is an important task in gastric cancer, but few machine learning-based techniques have been proposed. While multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. To tackle the above issue, we propose a novel multi-source domain adaptation framework for this diagnosis task, which not only considers domain-invariant and domain-specific features, but also achieves the imbalanced knowledge transfer and class-aware feature alignment across domains. First, we develop a 3D improved feature pyramidal network (i.e., 3D IFPN) to extract common multi-level features from the high-resolution 3D CT images, where a feature dynamic transfer (FDT) module can promote the network's ability to recognize the small target (i.e., LN). Then, we design an unsupervised domain selective graph convolutional network (i.e., UDS-GCN), which mainly includes three types of components: domain-specific feature extractor, domain selector and class-aware GCN classifier. Specifically, multiple domain-specific feature extractors are employed for learning domain-specific features from the common multi-level features generated by the 3D IFPN. A domain selector via the optimal transport (OT) theory is designed for controlling the amount of knowledge transferred from source domains to the target domain. A class-aware GCN classifier is developed to explicitly enhance/weaken the intra-class/inter-class similarity of all sample pairs across domains. To optimize UDS-GCN, the domain selector and the class-aware GCN classifier provide reliable target pseudo-labels to each other in the iterative process by collaborative learning. The extensive experiments are conducted on an in-house CT image dataset collected from four medical centers to demonstrate the efficacy of our proposed method. Experimental results verify that the proposed method boosts LN metastasis diagnosis performance and outperforms state-of-the-art methods. Our code is publically available at https://github.com/infinite-tao/LN_MSDA.

Pan-cancer analysis of osteogenesis imperfecta causing gene SERPINF1.

Osteogenesis imperfecta (OI) type VI causative gene SERPINF1, encodes a member of the serpin family that does not display the serine protease inhibitory activity shown by many of the other serpin proteins. The encoded protein (pigment epithelium-derived factor, PEDF) has anti-tumor, anti-angiogenesis, anti-inflammation, nutrition and nerve protection functions, and participates in fat metabolism. In this paper, a series of bioinformatics analyses were conducted based on the regulation of SERPINF1 in the human. Pan-cancer analysis of SERPINF1 revealed it to play a role in the prognosis of tumors, especially in KIRC, and that high expression of SERPINF1 leads to a poor prognosis of the disease, the occurrence of which is largely related to the high expression of SERPINF1 leading to immune infiltration of cancer associated fibroblasts. Mutation analysis found that SERPINF1 had eight identical amino acids alterations sites with different in both cancer and OI patients. which hints the possible relationship between genotype and phenotype.

Reparative Effects of Dandelion Fermentation Broth on UVB-Induced Skin Inflammation.

Objective: To evaluate the efficacy of the dandelion fermentation broth in repairing UVB-induced skin inflammation. Methods: Detection of active ingredients in dandelion fermentation broth and water extract. The antioxidant capacity of dandelion fermentation broth was investigated by in vitro antioxidant experiments. The influence of the broth on the content of inflammatory factors interleukin-6 (IL-6), interleukin-8 (IL-8) and interleukin-1ß (IL-1ß), and tumor necrosis factor (TNF-α), in human immortalized epidermal cells (HaCaT) is discussed on the basis of a UVB-induced HaCaT damage model. The effects of the broth on the contents of skin barrier-related proteins kallikrein-7 (KLK-7), filaggrin (FLG) and aquaporin (AQP3) in the UVB-induced damage and repair of the HaCaT mechanism are also comprehensively discussed. The effect of DF on the activation of MAPK pathway proteins was detected by PCR. A chicken embryo chorioallantoic membrane test is used to explore the safety of the dandelion fermentation broth. Results: The results show that the dandelion fermentation broth is rich inTotal sugar, with good free radical scavenging ability and antioxidant effects; it can regulate the MAPK pathway, reduce the expression of inflammatory factors, adjust the skin barrier factors and good safety. Conclusion: Dandelion fermentation broth exhibits repairing effect on UVB-induced skin inflammation.

Protective effects of Lactobacillus reuteri SJ-47 strain exopolysaccharides on human skin fibroblasts damaged by UVA radiation.

Ultraviolet rays in sunlight can cause skin damage and premature aging. This study demonstrates that Lactobacillus reuteri SJ-47 strain exopolysaccharides (EPS) protect human skin fibroblasts (HSF) under UVA radiation. During the course of the experiments, we investigate the oxidative stress protection and antiaging effects of exopolysaccharides on HSF at the biochemical, cellular, and molecular levels. The results show that EPS can increase the antioxidant capacity of cells, decrease the amount of reactive-oxygen species (ROS) and malondialdehyde (MDA), while improve the expression of antioxidant enzymes. At the same time, EPS can increase collagen content, which can effectively regulate the expression of genes in the senescence and apoptosis pathways, and delay skin photoaging caused by UVA irradiation.

Integrative overview of IFITMs family based on Bioinformatics analysis.

Human interferon-induced transmembrane proteins (IFITMs) family is a multi-functional biomacromolecule family playing a critical role in various physiological processes, such as, antiviral immunity, tumor suppression, and bone formation. Although there are many studies proving that a subset of tumors strongly links to the changes of IFITMs, the link between different IFITMs mutant types and diverse tumors has not been studied thoroughly. To investigate the law of expression among IFITMs internal members and the linking of IFITMs mutant types and cancers, online databases were used to pool together relevant data for bioinformatics analysis. Here, we summarize mutations, expression, and functions of human IFITMs, analyze diverse expression levels of IFITMs in physiological and pathological tissues, predict protein-protein interaction (PPI) networks, and target miRNAs and relevant signaling pathways of IFITMs. The results show that IFITM1, IFITM2, and IFITM3 have similar motif pattern constructions and physiological functions, while IFITM5 and IFITM10 show far diversity from them. Particularly, IFITM1-3, in conjunction with interacting proteins, is strongly related to development and overall survival rates of a portion of cancers, including renal cancer and uveal melanoma (UVM). This trait may make IFITM1-3 become a prognostic marker of cancers. Meanwhile, hsa_circ_0116375 has been found as the common circRNA for IFITM2, IFITM3, IFITM5, and IFITM10.

Modeling colorectal tumorigenesis using the organoids derived from conditionally immortalized mouse intestinal crypt cells (ciMICs).

Intestinal cancers are developed from intestinal epithelial stem cells (ISCs) in intestinal crypts through a multi-step process involved in genetic mutations of oncogenes and tumor suppressor genes. ISCs play a key role in maintaining the homeostasis of gut epithelium. In 2009, Sato et al established a three-dimensional culture system, which mimicked the niche microenvironment by employing the niche factors, and successfully grew crypt ISCs into organoids or Mini-guts in vitro. Since then, the intestinal organoid technology has been used to delineate cellular signaling in ISC biology. However, the cultured organoids consist of heterogeneous cell populations, and it was technically challenging to introduce genomic changes into three-dimensional organoids. Thus, there was a technical necessity to develop a two-dimensional ISC culture system for effective genomic manipulations. In this study, we established a conditionally immortalized mouse intestinal crypt (ciMIC) cell line by using a piggyBac transposon-based SV40 T antigen expression system. We showed that the ciMICs maintained long-term proliferative activity under two-dimensional niche factor-containing culture condition, retained the biological characteristics of intestinal epithelial stem cells, and could form intestinal organoids in three-dimensional culture. While in vivo cell implantation tests indicated that the ciMICs were non-tumorigenic, the ciMICs overexpressing oncogenic ß-catenin and/or KRAS exhibited high proliferative activity and developed intestinal adenoma-like pathological features in vivo. Collectively, these findings strongly suggested that the engineered ciMICs should be used as a valuable tool cell line to dissect the genetic and/or epigenetic underpinnings of intestinal tumorigenesis.

3D IFPN: Improved Feature Pyramid Network for Automatic Segmentation of Gastric Tumor.

Automatic segmentation of gastric tumor not only provides image-guided clinical diagnosis but also assists radiologists to read images and improve the diagnostic accuracy. However, due to the inhomogeneous intensity distribution of gastric tumors in CT scans, the ambiguous/missing boundaries, and the highly variable shapes of gastric tumors, it is quite challenging to develop an automatic solution. This study designs a novel 3D improved feature pyramidal network (3D IFPN) to automatically segment gastric tumors in computed tomography (CT) images. To meet the challenges of this extremely difficult task, the proposed 3D IFPN makes full use of the complementary information within the low and high layers of deep convolutional neural networks, which is equipped with three types of feature enhancement modules: 3D adaptive spatial feature fusion (ASFF) module, single-level feature refinement (SLFR) module, and multi-level feature refinement (MLFR) module. The 3D ASFF module adaptively suppresses the feature inconsistency in different levels and hence obtains the multi-level features with high feature invariance. Then, the SLFR module combines the adaptive features and previous multi-level features at each level to generate the multi-level refined features by skip connection and attention mechanism. The MLFR module adaptively recalibrates the channel-wise and spatial-wise responses by adding the attention operation, which improves the prediction capability of the network. Furthermore, a stage-wise deep supervision (SDS) mechanism and a hybrid loss function are also embedded to enhance the feature learning ability of the network. CT volumes dataset collected in three Chinese medical centers was used to evaluate the segmentation performance of the proposed 3D IFPN model. Experimental results indicate that our method outperforms state-of-the-art segmentation networks in gastric tumor segmentation. Moreover, to explore the generalization for other segmentation tasks, we also extend the proposed network to liver tumor segmentation in CT images of the MICCAI 2017 Liver Tumor Segmentation Challenge.