Cancer Investigation最新文献

{"title":"Efficacy and Safety of Current Treatment Regimens for Acute Myeloid Leukemia in Elderly Patients.","authors":"Zinaida Stupakova, Oksana Karnabeda, Konstiantyn Isaiev, Ulyana Melnyk","doi":"10.1080/07357907.2025.2533279","DOIUrl":"https://doi.org/10.1080/07357907.2025.2533279","url":null,"abstract":"<p><p>The purpose of this study was to evaluate the efficacy and safety of Azacitidine, alone or in combination with Venetoclax, in the treatment of newly diagnosed acute myeloid leukemia in patients with significant comorbidities who are ineligible for intensive chemotherapy. Most patients in the cohort had high-risk acute myeloid leukemia based on clinical and cytogenetic characteristics and required low-intensity therapeutic regimens, such as Azacitidine with or without Venetoclax, due to their age and comorbidities. It was shown that 77% of patients treated with hypomethylating agents with the addition of Venetoclax achieved complete remission. In addition, the clinical case of a 61-year-old patient with severe comorbidity status is described in the end of the article. The diagnosis included a transient ischemic attack in the context of an unruptured cerebral aneurysm, for which the patient was not a candidate for thrombolytic therapy, alongside other conditions requiring comprehensive treatment. A limitation of this study was a small sample of patients with acute myeloid leukemia.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-14"},"PeriodicalIF":1.8,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Evaluation of Serum Irisin Levels in Cancer Patients and Healthy Individuals: A Systematic Review and Meta-Analysis of Diagnostic Evidence.","authors":"Rahul Mohandas, Supriya Kheur, Subhashree Mohapatra","doi":"10.1080/07357907.2025.2533267","DOIUrl":"https://doi.org/10.1080/07357907.2025.2533267","url":null,"abstract":"<p><strong>Background: </strong>Irisin influences key cancer-related processes such as cell proliferation, apoptosis, angiogenesis, and metastasis. This review aimed to evaluate serum irisin's potential in cancer diagnosis, prognosis, and treatment monitoring.</p><p><strong>Methods: </strong>Databases including Scopus, PubMed, Cochrane, and others were searched. Studies comparing serum irisin in cancer patients and healthy individuals were assessed using Joanna Briggs Institute criteria.</p><p><strong>Results: </strong>Nine studies showed significantly lower irisin levels in cancer patients (SMD: -1.16, <i>p</i> < 0.0001), especially in hepatocellular and bladder cancers.</p><p><strong>Conclusion: </strong>Reduced serum irisin may serve as a diagnostic cancer biomarker, though its utility varies by cancer type and requires further research.</p><p><strong>Prospero registration no: </strong>CRD420250650210.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-17"},"PeriodicalIF":1.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarker Potential of DNA Repair Genes <i>XRCC1, XRCC3</i> and <i>RAD51</i> Polymorphisms in Ovarian Cancer Patients.","authors":"Yanni A, Maria Afzal, Sidra Usman, Ayesha Akram, Hanan Nasir, Muhammad Umar, Anisa Iftikhar, Kashif Bashir","doi":"10.1080/07357907.2025.2524560","DOIUrl":"https://doi.org/10.1080/07357907.2025.2524560","url":null,"abstract":"<p><p>Ovarian cancer remains one of the most lethal gynecological malignancies, with a high mortality rate primarily due to late-stage diagnosis. Genetic predispositions play a significant role in its development, alongside environmental and lifestyle factors. The main objective of the study was to check the association of <i>XRCC1, XRCC3,</i> and <i>RAD51</i> gene polymorphism with ovarian cancer. In the present 300 ovarian cancer patients and 300 healthy controls blood samples collected. The results showed that the heterozygous (GA) genotype of rs25487 SNP shows significant correlation with ovarian cancer with decreased risk of disease (OR = 0.39; 95% CI = 0.17-0.88; <i>p</i> < 0.02), whereas the homozygous variant (AA) genotype of the same SNP exhibits a non-significant relation with ovarian cancer. The combined genotype model of this SNP indicated a highly significant association with increased risk of ovarian cancer by twofold (OR = 2.10;95% CI = 1.22-3.64; <i>p</i> < 0.007). In case of rs861539 heterozygous (CT) showed significant association by increasing the risk of disease almost threefold (OR = 2.73; 95% CI 1.68-4.41; <i>p</i> < 0.0001). while the mutant (TT) of the same SNP showed again significant association but with decreased risk of ovarian cancer (OR = 0.27; 95% CI 0.16-0.47; <i>p</i> < 0.0001). The genotype distribution of the <i>RAD51</i> gene's SNP (rs1801320) shows that heterozygous (GC) individuals exhibit a significant correlation and increased risk of ovarian cancer by twofold (OR = 2.81;95% CI = 1.72-4.60; <i>p</i> ≤ 0.0001). Conversely, the mutant (CC) of rs1801320 exhibits a significant correlation with a decrease in the risk of ovarian cancer (OR = 0.32; 95% CI = 0.19-0.55; <i>p</i> < 0.0001). In conclusion, the study's findings suggest that a higher chance of ovarian cancer is related to the gene <i>XRCC1, XRCC3,</i> and <i>RAD51</i> polymorphisms. In this study, SNPs were analyzed for their potential role as biomarkers for the diagnosis of ovarian cancer.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-13"},"PeriodicalIF":1.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemotherapy and Persistent Depression in Older Mexican Cancer Survivors: Secondary Analysis of the Mexican Health and Aging Study.","authors":"Diego Arriaga-Izabal, Francisco Morales-Lazcano, Adrián Canizalez-Román","doi":"10.1080/07357907.2025.2521693","DOIUrl":"https://doi.org/10.1080/07357907.2025.2521693","url":null,"abstract":"<p><strong>Introduction: </strong>Depressive symptoms (DS) are prevalent among cancer survivors and may be exacerbated by chemotherapy. However, longitudinal data on this relationship within the Mexican population are lacking. The current study aimed to analyze the relationship between chemotherapy and the persistence of depressive symptoms over time in cancer survivors.</p><p><strong>Methods: </strong>Retrospective observational study using Mexican Study of Health and Aging (MHAS) data (2012-2021). Participants aged 50+ included chemotherapy patients (n = 30) and healthy controls (n = 6,970). Depressive symptoms were assessed with a modified Center for Epidemiologic Studies Depression Scale. Mann-Whitney U, X² tests, and generalized estimating equations analyzed chemotherapy's impact on depressive symptoms over time.</p><p><strong>Results: </strong>Chemotherapy recipients showed significantly higher depressive symptoms at early follow-ups (2012, 2015, 2018; p < 0.05), with no significant difference by 2021. Adjusted analyses indicated chemotherapy was associated with a more than twofold increase in odds of depression (OR = 2.165; 95% CI: 1.220-3.810). Lower education and comorbidities such as diabetes and hypertension were also independently linked to increased depression risk.</p><p><strong>Conclusions: </strong>Chemotherapy is a significant predictor of persistent depressive symptoms among Mexican cancer survivors aged 50 and above. These findings highlight the critical need for integrated mental health screening and targeted psychosocial care within oncology settings.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-9"},"PeriodicalIF":1.8,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Lung Cancer Diagnosis: An Optimization-Driven Deep Learning Approach with CT Imaging.","authors":"Kasetty Lakshminarasimha, A T Priyeshkumar, M Karthikeyan, Rajalaxmi Sakthivel","doi":"10.1080/07357907.2025.2518404","DOIUrl":"10.1080/07357907.2025.2518404","url":null,"abstract":"<p><p>Lung cancer (LC) remains a leading cause of mortality worldwide, affecting individuals across all genders and age groups. Early and accurate diagnosis is critical for effective treatment and improved survival rates. Computed Tomography (CT) imaging is widely used for LC detection and classification. However, manual identification can be time-consuming and error-prone due to the visual similarities among various LC types. Deep learning (DL) has shown significant promise in medical image analysis. Although numerous studies have investigated LC detection using deep learning techniques, the effective extraction of highly correlated features remains a significant challenge, thereby limiting diagnostic accuracy. Furthermore, most existing models encounter substantial computational complexity and find it difficult to efficiently handle the high-dimensional nature of CT images. This study introduces an optimized CBAM-EfficientNet model to enhance feature extraction and improve LC classification. EfficientNet is utilized to reduce computational complexity, while the Convolutional Block Attention Module (CBAM) emphasizes essential spatial and channel features. Additionally, optimization algorithms including Gray Wolf Optimization (GWO), Whale Optimization (WO), and the Bat Algorithm (BA) are applied to fine-tune hyperparameters and boost predictive accuracy. The proposed model, integrated with different optimization strategies, is evaluated on two benchmark datasets. The GWO-based CBAM-EfficientNet achieves outstanding classification accuracies of 99.81% and 99.25% on the Lung-PET-CT-Dx and LIDC-IDRI datasets, respectively. Following GWO, the BA-based CBAM-EfficientNet achieves 99.44% and 98.75% accuracy on the same datasets. Comparative analysis highlights the superiority of the proposed model over existing approaches, demonstrating strong potential for reliable and automated LC diagnosis. Its lightweight architecture also supports real-time implementation, offering valuable assistance to radiologists in high-demand clinical environments.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-20"},"PeriodicalIF":1.8,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modified Le-Net Model with Multiple Image Features for Skin Cancer Detection.","authors":"Vinay Kumar Y B, Vimala H S, Shreyas J","doi":"10.1080/07357907.2025.2518400","DOIUrl":"https://doi.org/10.1080/07357907.2025.2518400","url":null,"abstract":"<p><p>Computer-based technologies significantly improve melanoma and non-melanoma skin cancer detection by providing non-invasive, cost-effective, and rapid diagnostic solutions. In this context, the study proposes a novel Deep Learning (DL)-based skin cancer detection approach that leverages an advanced segmentation technique called Improved DeepJoint Segmentation (IDJS). This method is designed to enhance the accuracy and precision of the detection process. Initially, the proposed Modified LeNet (MLeNet)-based model applies a Gaussian filter during preprocessing to reduce speckle noise in the input skin images effectively. Following this, the preprocessed images undergo the IDJS segmentation process, which effectively partitions the cancerous regions with high accuracy. Subsequently, three types of features are extracted from the segmented images and they are Multi-Texton Histogram (MTH)-based features, Improved Pyramid Histogram of Oriented Gradient (IPHOG)-based features, and Median Binary Pattern (MBP). These extracted features serve as the input to the MLeNet model for the final skin cancer detection. The datasets used in this work are the HAM10000 dataset and the ISIC 2019 dataset. With a positive metric value of 0.952, the MLeNet model outperforms the traditional models, with LeNet achieving the highest score of 0.932.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-30"},"PeriodicalIF":1.8,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144324573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overexpression FARSB Reveals Poor Prognosis in Breast Cancer and is Correlated with Immunity.","authors":"Yueming Hu, Ting Liu, Li Tian, Bohai Cao, Jinheng Xu","doi":"10.1080/07357907.2025.2512379","DOIUrl":"10.1080/07357907.2025.2512379","url":null,"abstract":"<p><strong>Background: </strong>FARSB is a β-regulatory subunit of phenylalanine tRNA synthetase. It is reported that FARSB was involved in cancer progression. However, the molecular function of FARSB in breast cancer was unclear. This study aimed to investigate the prognostic significance of FARSB expression and its relationship with immunity in breast cancer.</p><p><strong>Methods: </strong>Several databases, including TCGA, HPA, and UALCAN database, were applied to study FARSB mRNA and protein expression and its association with aggressiveness in breast cancer. We used immunohistochemical staining (IHC) to study FARSB expression in breast cancer and normal tissues. Chi square test was explored to study the correlation between FARSB expression and clinical features in breast cancer. Kaplan-Meier analysis and Cox regression were utilized to discuss the prognosis of breast cancer. Spearman analysis was applied to analyze the association between FARSB expression and immunity. We studied the correlation of FARSB with common breast cancer chemotherapeutic drugs. We conducted GO, KEGG, and GSEA enrichment analysis to study the molecular function of FARSB in breast cancer.</p><p><strong>Results: </strong>The TCGA database suggested that FARSB was increased in several cancers, including breast cancer. HPA and UALCAN databases suggested that FARSB protein expression was higher in breast cancer than normal tissues. IHC analysis also confirmed the higher expression of FARSB in breast cancer. FARSB expression had correlation with ER status and PR status. In TCGA database, FARSB expression was related to ER status, PR status, and PAM50. Overexpression FARSB had adverse prognosis, and Cox regression considered FARSB as a prognostic marker. Immunological analysis demonstrated that FARSB was linked with immune cell infiltration and immune checkpoints. High FARSB expression had low TIDE score. In addition, FARSB was linked to drugs, such as 5-fluorouracil, doxorubicin, gemcitabine, and paclitaxel. GSEA analysis suggested that FARSB was involved in the pathways, including cell cycle, aminoacyl TRNA biosynthesis, DNA replication, spliceosome, and mismatch repair.</p><p><strong>Conclusion: </strong>FARSB was highly expression at mRNA and protein level in breast cancer. Overexpression of FARSB had a poor prognosis in breast cancer. FARSB expression was associated with immunity and acted as a new target for cancer immunological therapy.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"326-336"},"PeriodicalIF":1.8,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association Between Vulnerability and Taste Changes in Older Cancer Patients Undergoing Chemotherapy.","authors":"Yajun Dong, Jiajia Lu, Danhui Wang, Min Zhu, Liping Teng","doi":"10.1080/07357907.2025.2500495","DOIUrl":"10.1080/07357907.2025.2500495","url":null,"abstract":"<p><p>This study aimed to examine the association between taste changes and vulnerability in elderly cancer patients undergoing chemotherapy. A cross-sectional study was conducted among older cancer patients undergoing chemotherapy in Wuxi, China. The Chemotherapy-induced Taste Alteration Scale (CiTAS) was used to measure taste alteration. The Vulnerable Elders Survey (VES) was used to measure vulnerability status. The univariate, correlation, and hierarchical regression analyses were applied to assess the association between taste changes and vulnerability. Of 200 older cancer patients, 123 (61.5%) participants were non-vulnerable. The univariate analysis revealed significant distribution differences of vulnerability in education level, smell abnormalities, drinking history, chemotherapy cycle, and taste changes. The level of taste changes was positively correlated with vulnerability (<i>r</i> = 0.401, <i>p</i> < 0.01). Results of the regression analysis indicated that vulnerability in older cancer patients was significantly associated with higher odds of \"phantogeusia and parageusia\" (OR = 4.505, <i>p</i> < 0.001). Taste changes may be an important influencing factor of vulnerability in older cancer patients.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"283-292"},"PeriodicalIF":1.8,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143966562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Malignant Melanoma Detection Using Ensemble Model and Improved BIRCH Clustering-Based Segmentation.","authors":"Pavithra G, Palanisamy C","doi":"10.1080/07357907.2025.2502052","DOIUrl":"10.1080/07357907.2025.2502052","url":null,"abstract":"<p><strong>Background: </strong>The most deadly disease in skin cancers family is melanoma. The color resemblance among melanoma-affected and healthy areas pose significant challenges in early detection.</p><p><strong>Objective: </strong>An automated localization and segmentation of skin lesions at earlier stages remains challenging. To tackle these issues, a new method is proposed in this research for detecting malignant melanoma.</p><p><strong>Method: </strong>This proposed strategy comprises five stages namely augmentation, preprocessing, segmentation, feature extraction, and classification. Initially, data augmentation is performed, then median filtering and image enhancement are applied to input image during preprocessing. Subsequently, IBIRCH algorithm is employed for segmentation. Furthermore, color and shape features, statistical features and improved local texton XOR pattern are extracted. Finally, ensemble model (proposed Bi-LSTM, CNN and DBN) is proposed which receives features and intermediate score obtained from each model undergoes improved score level fusion and yields final classification output.</p><p><strong>Results: </strong>The proposed model is evaluated against traditional models and the suggested model achieved superior accuracy of 97.59% and 95.32% on datasets 1 and 2, respectively.</p><p><strong>Conclusion: </strong>The improved performance of proposed model not only outperforms traditional approaches but also paves way for reliable automated early-stage melanoma diagnosis and so reduces life risk of patients due to this early detection.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"355-390"},"PeriodicalIF":1.8,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144246613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Characteristics and Impact on Prognosis of Melanoma Accompanied by Multiple Primary Malignancies: A Retrospective Analysis.","authors":"Huichun Tian, Jiaran Zhang, Lili Mao, Caili Li, Xiaoting Wei, Junjie Gu, Li Zhou, Chuanliang Cui, Zhihong Chi, Xinan Sheng, Jun Guo, Lu Si","doi":"10.1080/07357907.2025.2507113","DOIUrl":"10.1080/07357907.2025.2507113","url":null,"abstract":"<p><strong>Introduction: </strong>This study aims to explore the clinical characteristics and prognosis of patients with melanoma (MM), which are composed mainly of acral and mucosal MM accompanied by multiple primary tumors.</p><p><strong>Methods: </strong>A total of 87 patients diagnosed with single primary MM and 87 patients diagnosed with multiple primary malignant tumors were included. Nonmelanoma malignancy tumor type, genetic testing, and the survival data were collected. Pearson's chi-square test, Fisher's exact test, log-rank test, univariate and multivariate Cox's regression analysis were applied.</p><p><strong>Results: </strong>The most common nonmelanoma malignancies in all patients involved the digestive system; breast cancer, thyroid cancer, lung cancer, and prostate cancer; and breast cancer was more common in patients with acral MM. Mutations in <i>BRAF</i> V600, <i>NRAS</i>, <i>KIT</i>, and <i>TP53</i> were the most common. Univariate analysis revealed that mutations in <i>KIT</i> and elevated levels of lactate dehydrogenase (LDH) were potential factors that influenced OS. Multivariate analysis revealed that mutations in <i>NRAS</i> and increased LDH levels were related to worse survival and that survival was prolonged in patients with MM as the first primary tumor.</p><p><strong>Conclusion: </strong>This study preliminarily describes the clinical features and prognosis of patients with melanomas, while the further study with larger sample size is needed.</p>","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"305-314"},"PeriodicalIF":1.8,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}