An Ensemble of 2.5D ResUnet Based Models for Segmentation for Kidney and Masses

The automatic segmentation of kidney, kidney tumor and kidney cyst on Computed Tomography (CT) scans is a challenging task due to the indistinct lesion boundaries and fuzzy texture. Considering the large range and unbalanced distribution of CT scans' thickness, 2.5D ResUnet are adopted to build an efficient coarse-to-fine semantic segmentation framework in this work. A set of 489 CT scans are used for training and validation, and an independent never-before-used CT scans for testing. Finally, we demonstrate the effectiveness of our proposed method. The dice values on test set are 0.954, 0.792, 0.691, the surface dice values are 0.897, 0.591, 0.541 for kidney, tumor and cyst, respectively. The average inference time of each CT scan is 20.65s and the max GPU memory is 3525MB. The results suggest that a better trade-off between model performance and efficiency.Comment: 7 pages, 2 figure

Factors related to the quality of life of family cancer caregivers

BackgroundCancer caregivers directly affect patient health outcomes. To maintain the function and health of caregivers so that patients can receive efficient care, we must pay more attention to caregivers’ quality of life in the process of caring for patients. However, the factors influencing caregivers’ quality of life are complex.AimTo assess caregivers’ quality of life in the process of caring for cancer patients and to explore the factors associated with it.DesignThis was a descriptive correlational study. A self-report questionnaire was used to anonymously collect data from one Chinese cancer hospital. The Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being (FACIT-Sp-12), General Self-efficacy Scale (GSES), Positive and Negative Affect Schedule (PANAS), Connor-Davidson Resilience Scale 10 (CD-RISC-10), 24-item Caregiver Burden Inventory (CBI) and Caregiver Evaluation Questionnaire were used to measure caregivers’ spiritual well-being, self-efficacy, affective well-being, resilience, caregiver burden and quality of life. One-way analysis of variance, the Kruskal–Wallis H test and multiple regression analysis were applied to measure the factors influencing caregivers’ situations.Setting and participantsA total of 315 caregivers of cancer patients were selected by convenience sampling. All participants were invited to complete the questionnaire through a one-on-one approach.ResultsThe mean score for caregiver quality of life was 204.62 ± 36.61. After controlling for demographic factors, self-efficacy (β’ = 0.265, p < 0.01), resilience (β’ = 0.287, p < 0.01) and positive affect (β’ = 0.103, p < 0.01) were protective factors for caregivers’ quality of life. Negative affect (β’ = −0.217, p < 0.01) and caregiver burden (β’ = −0.219, p < 0.01) were negative factors. Notably, not all of these predictors can predict all dimensions of quality of life.ConclusionCaregivers’ quality of life needs to be further improved. The results of this study may provide clues to help identify factors influencing caregivers’ quality of life and implement targeted strategies to improve their quality of life

Hard Sample Aware Network for Contrastive Deep Graph Clustering

Contrastive deep graph clustering, which aims to divide nodes into disjoint groups via contrastive mechanisms, is a challenging research spot. Among the recent works, hard sample mining-based algorithms have achieved great attention for their promising performance. However, we find that the existing hard sample mining methods have two problems as follows. 1) In the hardness measurement, the important structural information is overlooked for similarity calculation, degrading the representativeness of the selected hard negative samples. 2) Previous works merely focus on the hard negative sample pairs while neglecting the hard positive sample pairs. Nevertheless, samples within the same cluster but with low similarity should also be carefully learned. To solve the problems, we propose a novel contrastive deep graph clustering method dubbed Hard Sample Aware Network (HSAN) by introducing a comprehensive similarity measure criterion and a general dynamic sample weighing strategy. Concretely, in our algorithm, the similarities between samples are calculated by considering both the attribute embeddings and the structure embeddings, better revealing sample relationships and assisting hardness measurement. Moreover, under the guidance of the carefully collected high-confidence clustering information, our proposed weight modulating function will first recognize the positive and negative samples and then dynamically up-weight the hard sample pairs while down-weighting the easy ones. In this way, our method can mine not only the hard negative samples but also the hard positive sample, thus improving the discriminative capability of the samples further. Extensive experiments and analyses demonstrate the superiority and effectiveness of our proposed method.Comment: 9 pages, 6 figure

Dual-Stage Hybrid Learning Particle Swarm Optimization Algorithm for Global Optimization Problems

Particle swarm optimization (PSO) is a type of swarm intelligence algorithm that is frequently used to resolve specific global optimization problems due to its rapid convergence and ease of operation. However, PSO still has certain deficiencies, such as a poor trade-off between exploration and exploitation and premature convergence. Hence, this paper proposes a dual-stage hybrid learning particle swarm optimization (DHLPSO). In the algorithm, the iterative process is partitioned into two stages. The learning strategy used at each stage emphasizes exploration and exploitation, respectively. In the first stage, to increase population variety, a Manhattan distance based learning strategy is proposed. In this strategy, each particle chooses the furthest Manhattan distance particle and a better particle for learning. In the second stage, an excellent example learning strategy is adopted to perform local optimization operations on the population, in which each particle learns from the global optimal particle and a better particle. Utilizing the Gaussian mutation strategy, the algorithm’s searchability in particular multimodal functions is significantly enhanced. On benchmark functions from CEC 2013, DHLPSO is evaluated alongside other PSO variants already in existence. The comparison results clearly demonstrate that, compared to other cutting-edge PSO variations, DHLPSO implements highly competitive performance in handling global optimization problems

The relationship between resilience and quality of life in advanced cancer survivors: multiple mediating effects of social support and spirituality

BackgroundWhile previous studies have revealed a positive association between resilience and quality of life in advanced cancer survivors, the mechanisms of the relationship is still unclear. This study aimed to explore the relationships between resilience, social support, spirituality, and quality of life and determine the multiple mediation effects of social support and spirituality on the relationship between resilience and quality of life.MethodsWith 286 advanced cancer survivors, a cross-sectional, correlational survey was adopted using convenience sampling. Resilience, social support, spirituality, and quality of life were evaluated by self-report questionnaires. The PROCESS macro for SPSS was used to test the multiple mediation model.ResultsThe scores for resilience, social support, spirituality and quality of life were positively correlated with one another. Resilience was found to be directly impact quality of life. Meanwhile, the relationship between resilience and quality of life was mediated by social support (effect = 0.067, 95% CI [0.019, 0.120]) and by spirituality (effect = 0.221, 95% CI [0.134, 0.332]), respectively, and by these two serially (effect = 0.036, 95% CI [0.015, 0.067]).ConclusionSocial support and spirituality played multiple mediating roles in the relationship between resilience and quality of life. Interventions aimed at increasing resilience, and then boosting social support and spirituality may be beneficial for promoting quality of life of advanced cancer survivors

Preventive Effects of the Intestine Function Recovery Decoction, a Traditional Chinese Medicine, on Postoperative Intra-Abdominal Adhesion Formation in a Rat Model

The intestine function recovery decoction (IFRD) is a traditional Chinese medicine that has been used for the treatment of adhesive intestinal obstruction. In this study, the preventative effects and probable mechanism of the IFRD were investigated in a rat model. We randomly assigned rats to five groups: normal, model, control, low dose IFRD, and high dose IFRD. In the animal model, the caecum wall and parietal peritoneum were abraded to induce intra-abdominal adhesion formation. Seven days after surgery, adhesion scores were assessed using a visual scoring system, and histopathological samples were examined. The levels of serum interleukin-6 (IL-6) and transforming growth factor beta-1 (TGF-β1) were analysed by an enzyme-linked immunosorbent assay (ELISA). The results showed that a high dose of IFRD reduced the grade of intra-abdominal adhesion in rats. Furthermore, the grades of inflammation, fibrosis, and neovascularization in the high dose IFRD group were significantly lower than those in the control group. The results indicate that the IFRD can prevent intra-abdominal adhesion formation in a rat model. These data suggest that the IFRD may be an effective antiadhesion agent

Activation of Nrf2 by Sulforaphane Inhibits High Glucose-Induced Progression of Pancreatic Cancer via AMPK Dependent Signaling

Background/Aims: Sulforaphane (SFN) is known for its potent bioactive properties, such as anti-inflammatory and anti-tumor effects. However, its anti-tumor effect on pancreatic cancer is still poorly understood. In the present study, we explored the therapeutic potential of SFN for pancreatic cancer and disclosed the underlying mechanism. Methods: Panc-1 and MiaPaca-2 cell lines were used in vitro. The biological function of SFN in pancreatic cancer was measured using EdU staining, colony formation, apoptosis, migration and invasion assays. Reactive oxygen species (ROS) production was measured using 2’-7’-Dichlorofluorescein diacetate (DCF-DA) fluorometric analysis. Western blotting and immunofluorescence were used to measure the protein levels of p-AMPK and epithelial-mesenchymal transition (EMT) pathway-related proteins, and cellular translocation of nuclear factor erythroid 2-related factor 2 (Nrf2). Nude mice and transgenic pancreatic cancer mouse model were used to measure the therapeutic potential of SFN on pancreatic cancer. Results: SFN can inhibit pancreatic cancer cell growth， promote apoptosis, curb colony formation and temper the migratory and invasion ability of pancreatic cancer cells. Mechanistically, excessive ROS production induced by SFN activated AMPK signaling and promoted the translocation of Nrf2, resulting in cell viability inhibition of pancreatic cancer. Pretreatment with compound C, a small molecular inhibitor of AMPK signaling, reversed the subcellular translocation of Nrf2 and rescued cell invasion ability. With nude mice and pancreatic cancer transgenic mouse, we identified SFN could inhibit tumor progression, with smaller tumor size and slower tumor progression in SFN treatment group. Conclusion: Our study not only elucidates the mechanism of SFN-induced inhibition of pancreatic cancer in both normal and high glucose condition, but also testifies the dual-role of ROS in pancreatic cancer progression. Collectively, our research suggests that SFN may serve as a potential therapeutic choice for pancreatic cancer

Exposure to violence, chronic stress, nasal DNA methylation, and atopic asthma in children

BACKGROUND: Exposure to violence (ETV) or chronic stress may influence asthma through unclear mechanisms. METHODS: Epigenome-wide association study (EWAS) of ETV or chronic stress measures and DNA methylation in nasal epithelium from 487 Puerto Ricans aged 9-20 years who participated in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study [EVA-PR]). We assessed four measures of ETV and chronic stress in children (ETV scale, gun violence, and perceived stress) and their mothers (perceived stress). Each EWAS was conducted using linear regression, with CpGs as dependent variables and the stress/violence measure as a predictor, adjusting for age, sex, the top five principal components, and SVA latent factors. We then selected the top 100 CpGs (by p value) associated with each stress/violence measure in EVA-PR and conducted a meta-analysis of the selected CpGs and atopic asthma using data from EVA-PR and two additional cohorts (Project Viva and PIAMA). RESULTS: Three CpGs (in SNN, PTPRN2, and LINC01164) were associated with maternal perceived stress or gun violence (p = 1.28-3.36 × 10-7 ), but not with atopic asthma, in EVA-PR. In a meta-analysis of three cohorts, which included the top CpGs associated with stress/violence measures in EVA-PR, 12 CpGs (in STARD3NL, SLC35F4, TSR3, CDC42SE2, KLHL25, PLCB1, BUD13, OR2B3, GALR1, TMEM196, TEAD4, and ANAPC13) were associated with atopic asthma at FDR-p < .05. CONCLUSIONS: Pending confirmation in longitudinal studies, our findings suggest that nasal epithelial methylation markers associated with measures of ETV and chronic stress may be linked to atopic asthma in children and adolescents

Inhibition of CDC25B With WG-391D Impedes the Tumorigenesis of Ovarian Cancer

Novel inhibitors are urgently needed for use as targeted therapies to improve the overall survival (OS) of patients with ovarian cancer. Here, we show that cell division cycle 25B (CDC25B) is over-expressed in ovarian tumors and associated with poor patient prognosis. All previously reported CDC25B inhibitors have been identified by their ability to reversibly inhibit the catalytic dephosphorylation activity of CDC25B in vitro; however, none of these compounds have entered clinical trials for ovarian cancer therapy. In this study, we synthesized a novel small molecule compound, WG-391D, that potently down-regulates CDC25B expression without affecting its catalytic dephosphorylation activity. The inhibition of CDC25B by WG-391D is irreversible, and WG-391D should therefore exhibit potent antitumor activity against ovarian cancer. WG-391D induces cell cycle progression arrest at the G2/M phase. Half maximal inhibitory concentration (IC50) values of WG-391D for inhibition of the proliferation and migration of eight representative ovarian cancer cell lines (SKOV3, ES2, OVCAR8, OVTOKO, A2780, IGROV1, HO8910PM, and MCAS) and five primary ovarian tumor cell lines (GFY004, GFY005, CZ001, CZ006, and CZ008) were lower than 10 and 1 μM, respectively. WG-391D inhibited tumor growth in nude mice inoculated with SKOV3 cells or a patient-derived xenograft (PDX). The underlying mechanisms were associated with the down-regulation of CDC25B and subsequent inactivation of cell division cycle 2 (CDC2) and the serine/threonine kinase, AKT. In conclusion, this study demonstrates that WG-391D exhibits strong antitumor activity against ovarian cancer and indicates that the down-regulation of CDC25B by inhibitors could provide a rationale for ovarian cancer therapy