TNF-α-1031T/C gene polymorphism as a predictor of malnutrition in patients with gastric cancer.

Introduction: Malnutrition is a complex clinical syndrome, the exact mechanism of which is yet not fully understood. Studies have found that malnutrition is associated with anorexia and inadequate intake, tumor depletion, leptin, tumor-induced metabolic abnormalities in the body, and catabolic factors produced by the tumor in the circulation and cytokines produced by the host immune system. Among these, single nucleotide polymorphisms (SNPs) are present in the gene encoding the pro-inflammatory cytokine TNF-α. Aim: The objective of this study was to investigate TNF-α -1,031 T/C gene polymorphism as an unfavorable predictor of malnutrition in patients with gastric cancer. Methods: The study group consisted of 220 gastric cancer patients treated at Affiliated Jinhua Hospital, Zhejiang University School of Medicine. Malnutrition was mainly assessed by the Global Consensus on Malnutrition Diagnostic Criteria (GLIM). DNA was extracted from peripheral leukocytes of whole blood samples using an animal DNA extraction kit. DNA was amplified using a 1.1× T3 Super PCR mixture and genotyped using SNP1 software. Results: There are three major genetic polymorphisms in TNF-α. Among the 220 patients with gastric cancer, there were 7 patients with the CC genotype, 61 with the CT genotype and 152 with the TT genotype. Compared to patients with the TT genotype, patients with the C allele had an approximately 2.5-fold higher risk of developing malnutrition (p = 0.003; OR = 0.406). On the basis of multivariate analysis, patients with the CC genotype had an approximately 20.1-fold higher risk of developing malnutrition (p = 0.013; OR = 20.114), while those with the CT genotype had an almost 3.7-fold higher risk of malnutrition (p = 0.002; OR = 3.218). Conclusion: SNP (-1,031 T/C) of the TNF-α may be a useful marker in the assessment of the risk of nutritional deficiencies in gastric cancer patients. Patients with gastric cancer carrying the C allele should be supported by early nutritional intervention, but more research is still needed to explore confirmation.

Comparison of the effects of Valsalva maneuver, EMLA cream, and the combination of both in relieving pain of needle insertion on totally implantable access port: A randomized controlled study.

BACKGROUND: Totally implantable access port (TIAP) is a subcutaneously implanted, long-term infusion device that is widely used in oncology patients. However, multiple needle insertions into TIAP may lead to pain, anxiety, and dread in patients. This study aimed to compare the effectiveness of Valsalva maneuver, eutectic mixture of local anesthetics (EMLA) cream, and the combination of both in relieving pain of cannulations on TIAP. METHODS: This was a prospective randomized controlled study. We included 223 patients treated with antineoplastic drugs and randomized them into four groups: EMLA Group (Group E), control Group (Group C), Valsalva maneuver Group (Group V), and EMLA cream combing with Valsalva maneuver Group (Group EV). Each group was given the corresponding intervention before non-coring needle insertion. The data on pain scores and overall comfort were collected by numerical pain rating scale (NPRS) and visual analog scale (VAS). RESULTS: Group E and Group EV experienced the least amount of pain scores in needle insertion, which was significantly lower than Group V and Group C (p < 0.05). Meanwhile, Group E and Group EV obtained the highest comfort level, which was significantly higher than group C (p < 0.05). Fifteen patients developed localized skin erythema after the application of medical Vaseline or EMLA cream and subsided within half an hour after rubbing. CONCLUSION: EMLA cream is a safe and effective way to alleviate pain during non-coring needle insertion in TIAP and enhance the overall comfort of patients. We recommend applying EMLA cream 1 h before needle insertion of TIAP, especially in patients having needle phobia or high pain scores from previous non-coring needle insertion.

A skeleton context-aware 3D fully convolutional network for abdominal artery segmentation.

PURPOSE: This paper aims to propose a deep learning-based method for abdominal artery segmentation. Blood vessel structure information is essential to diagnosis and treatment. Accurate blood vessel segmentation is critical to preoperative planning. Although deep learning-based methods perform well on large organs, segmenting small organs such as blood vessels is challenging due to complicated branching structures and positions. We propose a 3D deep learning network from a skeleton context-aware perspective to improve segmentation accuracy. In addition, we propose a novel 3D patch generation method which could strengthen the structural diversity of a training data set. METHOD: The proposed method segments abdominal arteries from an abdominal computed tomography (CT) volume using a 3D fully convolutional network (FCN). We add two auxiliary tasks to the network to extract the skeleton context of abdominal arteries. In addition, our skeleton-based patch generation (SBPG) method further enables the FCN to segment small arteries. SBPG generates a 3D patch from a CT volume by leveraging artery skeleton information. These methods improve the segmentation accuracies of small arteries. RESULTS: We used 20 cases of abdominal CT volumes to evaluate the proposed method. The experimental results showed that our method outperformed previous segmentation accuracies. The averaged precision rate, recall rate, and F-measure were 95.5%, 91.0%, and 93.2%, respectively. Compared to a baseline method, our method improved 1.5% the averaged recall rate and 0.7% the averaged F-measure. CONCLUSIONS: We present a skeleton context-aware 3D FCN to segment abdominal arteries from an abdominal CT volume. In addition, we propose a 3D patch generation method. Our fully automated method segmented most of the abdominal artery regions. The method produced competitive segmentation performance compared to previous methods.

Financial toxicity in patients with lung cancer: a scoping review protocol.

INTRODUCTION: Lung cancer has the second-ranked morbidity rate and the first-ranked mortality rate worldwide. With the progression of the cancer condition and the advancement of new treatments, the corresponding medical expenses have risen sharply. Nowadays, financial toxicity has become one of the most common concerns in patients with cancer. However, by far, the full landscape of studies on financial toxicity is unclear in patients with lung cancer. Thus, this scoping review aims to summarise the degree, affecting factors, outcomes and intervention strategies of financial toxicity in patients with lung cancer. METHODS AND ANALYSIS: This scoping review will be developed following the methodology described in the Joanna Briggs Institute Manual for Evidence Synthesis on scoping review protocol, which was based on Arksey and O'Malley's methodological framework, Levac et al's recommendations for applying this framework and Peters et al's enhancements of the framework. From the day of database building to 31 December 2021, 10 English databases will be searched in the 'Abstract' field with three key search terms: "Lung", "Cancer" and "Financial toxicity". The studies' screening and data extraction will be independently performed by two reviewers (MZ and RZ). Any disagreements between the two reviewers (MZ and RZ) will be resolved by consensus, and a third reviewer (BW) will be invited if necessary. The results will be analysed and presented using tables and figures. This scoping review will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. ETHICS AND DISSEMINATION: An ethical approval is not required for this scoping review protocol, nor for the scoping review. The results of this scoping review will be disseminated through publication in a peer-reviewed journal or presentation at conferences. REGISTRATION: This scoping review protocol has been registered in the Open Science Framework (https://osf.io/ub45n/?view_only=bb93eb94e1434a0f8196b3b61cffcec2).

Myocardial ischemia analysis based on electrocardiogram QRS complex.

Electrocardiogram (ECG) is an economic, convenient, and non-invasive detecting tool in myocardial ischemia (MI), and its clinical appearance is mainly exhibited by the changes in ST-T complex. Recently, QRS complex characters were proposed to analyze MI by more and more researchers. In this paper, various QRS complex characters were extracted in ECG signals, and their relationship was analyzed systematically. As a result, these characters were divided into two groups, and there existed good relationship among them for each group, while the poor relationship between the groups. Then these QRS complex characters were applied for statistical analysis on MI, and five characters had significant differences after ECG recording verification, which were: QRS upward and downward slopes, transient heart rate, angle R and angle Q. On the other hand, these QRS complex characters were analyzed in frequency domain. Experimental results showed that the frequency features of RR interval series (Heart Rate Variability, HRV), and QRS barycenter sequence had significant differences between MI states and normal states. Moreover, QRS barycenter sequence performed better.