bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-Dimensional Iron Oxide Nanoparticle-Based Contrast-Enhanced Magnetic Resonance Imaging for Characterization of Cerebral Arteriogenesis in the Mouse Neocortex
Authors: de Bortoli Till , Boehm-Sturm Philipp , Koch Stefan P. , Nieminen-Kelhä Melina , Wessels Lars , Mueller Susanne , Ielacqua Giovanna D. , Klohs Jan , Vajkoczy Peter , Hecht Nils 
Published: December 2021

Purpose: Subsurface blood vessels in the cerebral cortex have been identified as a bottleneck in cerebral perfusion with the potential for collateral remodeling. However, valid techniques for non-invasive, longitudinal characterization of neocortical microvessels are still lacking. In this study, we validated contrast-enhanced magnetic resonance imaging (CE-MRI) for in vivo characterization of vascular changes in a model of spontaneous collateral outgrowth following chronic cerebral hypoperfusion.Methods: C57BL/6J mice were randomly assigned to unilateral internal carotid artery occlusion or sham surgery and after 21 days, CE-MRI based on T2*-weighted imaging was performed using ultra-small superparamagnetic iron oxide nanoparticles to obtain subtraction angiographies and steady-state cerebral blood volume (ss-CBV) maps. First pass dynamic susceptibility contrast MRI (DSC-MRI) was performed for internal validation of ss-CBV. Further validation at the histological level was provided by ex vivo serial two-photon tomography (STP).Results: Qualitatively, an increase in vessel density was observed on CE-MRI subtraction angiographies following occlusion; however, a quantitative vessel tracing analysis was prone to errors in our model. Measurements of ss-CBV reliably identified an increase in cortical vasculature, validated by DSC-MRI and STP.Conclusion: Iron oxide nanoparticle-based ss-CBV serves as a robust, non-invasive imaging surrogate marker for neocortical vessels, with the potential to reduce and refine preclinical models targeting the development and outgrowth of cerebral collateralization.
CNS GNPDA2 Does Not Control Appetite, but Regulates Glucose Homeostasis
Authors: Gutierrez-Aguilar Ruth , Grayson Bernadette E. , Kim Dong-Hoon , Yalamanchili Suma , Calcagno Mario L. , Woods Stephen C. , Seeley Randy J. 
Published: December 2021

GNPDA2 has been associated with human obesity and type-2 diabetes by using a GWAS approach. GNPDA2 is an enzyme involved in the hexosamine biosynthesis pathway, which is known to be important for nutrient sensing in various organism. Its counter enzyme, GFAT, has previously been shown to be important to the development of insulin resistance in diabetes. The implication of GNPDA2 and GFAT in metabolism is scarce and the effect of both enzymes over appetite and glucose homeostasis is unknown.Aim: Identify the role of GNPDA2 and GFAT in nutrient sensing circuits of the CNS that are important for the regulation of both appetite and glucose homeostasis.Methods: Using Long Evans rats, we administered either a GNPDA2 or GFAT antagonist or vehicle in i3vt.Key Findings:GNPDA2 is highly expressed in hypothalamus and adipose tissue, followed by muscle and liver. GNPDA2 is expressed in different hypothalamic nuclei (ARC, DMH, LHA, PVN). GNPDA2 is downregulated in hypothalamus under diet-induced obesity (as previously described), but GFAT expression does not change. Moreover, i3vt infusion of GNPDA2 or GFAT inhibitor resulted in increased c-Fos in areas related to appetite and glucose homeostasis control as PVN and DMH and to a lesser extent in the LHA and ARC. Central inhibition of GNPDA2 does not alter either acute food intake or body weight; however, GFAT inhibition diminished appetite and body weight due to visceral illness. In addition, central administration of the GNPDA2 antagonist, prior to an intraperitoneal glucose tolerance test, resulted in glucose intolerance in comparison to vehicle without altering insulin levels.Significance: These results suggest that central GNPDA2 does not control appetite, but regulates glucose homeostasis.
High Moesin Expression Is a Predictor of Poor Prognosis of Breast Cancer: Evidence From a Systematic Review With Meta-Analysis
Authors: Hu Xiaoli , Liu Yang , Bing Zhitong , Ye Qian , Li Chengcheng 
Published: December 2021

Owing to metastases and drug resistance, the prognosis of breast cancer is still dismal. Therefore, it is necessary to find new prognostic markers to improve the efficacy of breast cancer treatment. Literature shows a controversy between moesin (MSN) expression and prognosis in breast cancer. Here, we aimed to conduct a systematic review and meta-analysis to evaluate the prognostic relationship between MSN and breast cancer. Literature retrieval was conducted in the following databases: PubMed, Web of Science, Embase, and Cochrane. Two reviewers independently performed the screening of studies and data extraction. The Gene Expression Omnibus (GEO) database including both breast cancer gene expression and follow-up datasets was selected to verify literature results. The R software was employed for the meta-analysis. A total of 9 articles with 3,039 patients and 16 datasets with 2,916 patients were ultimately included. Results indicated that there was a significant relationship between MSN and lymph node metastases (P&lt; 0.05), and high MSN expression was associated with poor outcome of breast cancer patients (HR = 1.99; 95% CI 1.73–2.24). In summary, there is available evidence to support that high MSN expression has valuable importance for the poor prognosis in breast cancer patients.Systematic Review Registrationhttps://inplasy.com/inplasy-2020-8-0039/.
Multi-Phase CT-Based Radiomics Nomogram for Discrimination Between Pancreatic Serous Cystic Neoplasm From Mucinous Cystic Neoplasm
Authors: Gao Jiahao , Han Fang , Wang Xiaoshuang , Duan Shaofeng , Zhang Jiawen 
Published: December 2021

PurposeThis study aimed to develop and verify a multi-phase (MP) computed tomography (CT)-based radiomics nomogram to differentiate pancreatic serous cystic neoplasms (SCNs) from mucinous cystic neoplasms (MCNs), and to compare the diagnostic efficacy of radiomics models for different phases of CT scans.Materials and MethodsA total of 170 patients who underwent surgical resection between January 2011 and December 2018, with pathologically confirmed pancreatic cystic neoplasms (SCN=115, MCN=55) were included in this single-center retrospective study. Radiomics features were extracted from plain scan (PS), arterial phase (AP), and venous phase (VP) CT scans. Algorithms were performed to identify the optimal features to build a radiomics signature (Radscore) for each phase. All features from these three phases were analyzed to develop the MP-Radscore. A combined model comprised the MP-Radscore and imaging features from which a nomogram was developed. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration tests, and decision curve analysis.ResultsFor each scan phase, 1218 features were extracted, and the optimal ones were selected to construct the PS-Radscore (11 features), AP-Radscore (11 features), and VP-Radscore (12 features). The MP-Radscore (14 features) achieved better performance based on ROC curve analysis than any single phase did [area under the curve (AUC), training cohort: MP-Radscore 0.89, PS-Radscore 0.78, AP-Radscore 0.83, VP-Radscore 0.85; validation cohort: MP-Radscore 0.88, PS-Radscore 0.77, AP-Radscore 0.83, VP-Radscore 0.84]. The combination nomogram performance was excellent, surpassing those of all other nomograms in both the training cohort (AUC, 0.91) and validation cohort (AUC, 0.90). The nomogram also performed well in the calibration and decision curve analyses.ConclusionsRadiomics for arterial and venous single-phase models outperformed the plain scan model. The combination nomogram that incorporated the MP-Radscore, tumor location, and cystic number had the best discriminatory performance and showed excellent accuracy for differentiating SCN from MCN.
A Clinical Scoring Model to Predict the Effect of Induction Chemotherapy With Definitive Concurrent Chemoradiotherapy on Esophageal Squamous Cell Carcinoma Prognosis
Authors: Li Yang , Du Qingwu , Wei Xiaoying , Guo Zhoubo , Lei Tongda , Li Yanqi , Han Dong , Wu Xiaoyue , Zhang Kunning , Zhang Tian , Chen Xi , Dong Jie , Zhang Baozhong , Wei Hui , Zhang Wencheng , Pang Qingsong , Wang Ping 
Published: December 2021

PurposeThe aim of the study was to compare the clinical outcomes of induction chemotherapy (IC) followed by definitive concurrent chemoradiotherapy (dCCRT) versus chemoradiotherapy alone in patients with esophageal squamous cell carcinoma (ESCC) on the basis of a clinical scoring model.MethodsA retrospective review of 599 patients with ESCC treated with dCCRT at our institution from 2010 to 2019 was conducted. The patients were divided into two groups based on whether they received IC. A clinical scoring model was performed using the significant variables obtained from the multivariate analysis. The PFS and OS rates were estimated using the Kaplan–Meier method.ResultsDuring the study period, 182 patients receiving IC followed by dCCRT and 417 dCCRT alone were identified. No significant differences in the PFS and OS rates were observed between the IC group (P=0.532) and the non-IC group (P=0.078). A clinical scoring model was constructed based on independent prognostic factors with scores ranging from 0 to 10.4. The patients were divided into high- and low-risk groups by using the median score as the cutoff value. The PFS rate of patients receiving IC was higher than that of patients treated without IC (P=0.034), while there was no improvement in the OS rate (P=0.794) in the high-risk group. No significant differences in the PFS (P=0.207) or OS (P=0.997) rate were found between the two treatment groups in the low-risk group.ConclusionsThe addition of IC followed by dCCRT for patients with ESCC might be associated with better PFS rates based on a clinical scoring model but has no impact on OS rates. Further prospective studies are warranted for the validation of this model.
The Prognostic Role of Blood Inflammatory Biomarkers and EGFR Mutation Status in Stage IIIA/N2 Non-Small Cell Lung Cancer Patients Treated With Trimodality Therapy
Authors: Yang Hui , Wang Kunlun , Li Bingxu , Li Shenglei , Li Yan , Yuan Ling 
Published: December 2021

ObjectivesVarious blood inflammatory biomarkers were associated with treatment response and prognosis of non-small cell lung cancer (NSCLC) in previous studies. In this study, we retrospectively evaluated the prognostic role of pretreatment blood inflammatory biomarkers and epidermal growth factor receptor (EGFR) mutation status in stage IIIA/N2 NSCLC patients with trimodality therapy.MethodsCompletely resected stage IIIA/N2 NSCLC patients with adjuvant chemotherapy and postoperative radiotherapy (PORT) were assessed in this study. Cutoff values of blood inflammatory factors were calculated by the R package SurvivalROC of R software. SPSS Statistics software was used for survival analyses. Kaplan-Meier survival curve and log-rank test were used to compare the survival difference between every two groups. Univariate and multivariate analyses of predictive factors were performed by Cox proportional hazards regression model.ResultsThe univariate analysis showed that T stage (p=0.007), EGFR mutation status (p=0.043), lymphocyte-to-monocyte ratio (LMR) (p=0.067), and systemic immune-inflammation index (SII) (p=0.043) were significant prognostic factors of disease-free survival (DFS). In the multivariate analysis, T2 (HR=0. 885, 95% CI: 0.059-0.583, p=0.004), EGFR mutation-positive (HR=0.108, 95% CI: 0.023-0.498, p=0.004) and elevated pretreatment SII (HR=0.181, 95%CI: 0.046-0.709, p=0.014) were independently related to shorter DFS. High pretreatment neutrophil counts (HR=0.113, p=0.019) and high systemic inflammation response index (SIRI) (HR=0.123, p=0.025) were correlated with worse overall survival (OS) by the univariate analysis. In the multivariate analysis, only high pretreatment SIRI was an independent predictor for poorer OS (HR=0.025, 95% CI: 0.001-0.467, p=0.014).ConclusionsIn conclusion, we identified that high pretreatment SII and SIRI were unfavorable prognostic factors in stage IIIA/N2 NSCLC patients treated with surgery, adjuvant chemotherapy and PORT. Patients with high pretreatment SII, high pretreatment SIRI, T2, and EGFR mutation-positive may need more forceful adjuvant treatment. Further prospective studies with large-scale are needed to validate our results and identify the proper cut-off values and optimum adjuvant treatment for distinct patient population.
Immune-Related Adverse Events in PD-1 Treated Melanoma and Impact Upon Anti-Tumor Efficacy: A Real World Analysis
Authors: Bastacky Melissa L. , Wang Hong , Fortman Dylan , Rahman Zahra , Mascara Gerard P. , Brenner Timothy , Najjar Yana G. , Luke Jason J. , Kirkwood John M. , Zarour Hassane M. , Davar Diwakar 
Published: December 2021

BackgroundAnti-PD-1 immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of melanoma by producing durable long-term responses in a subset of patients. ICI-treated patients develop unique toxicities - immune related adverse events (irAEs) – that arise from unrestrained immune activation. The link between irAE development and clinical outcome in melanoma and other cancers is inconsistent; and little data exists on the occurrence of multiple irAEs. We sought to characterize development of single and multiple irAEs, and association of irAE(s) development with clinical variables and impact upon outcomes in advanced melanoma patients treated with anti-PD-1 ICIs.MethodsWe conducted a retrospective study of 190 patients with metastatic melanoma treated with single-agent anti-PD-1 ICI therapy between June 2014 and August 2020 at a large integrated network cancer center identified through retrospective review of pharmacy records. irAEs were graded based on the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0.Results190 patients were evaluated of whom 114 patients (60.0%) experienced ≥1 irAE, including 30 (15.8%) with grade 3/4 irAEs. The occurrence of any irAE was strongly associated with the development of investigator-assessed response to anti-PD-1 therapy (p &lt; 0.0001); whether evaluated by current (p=0.0082) or best (p=0.0001) response. In patients with ≥2 irAEs, distinct patterns were observed. Median progression-free survival (PFS) and overall survival (OS) were greater in those with any irAE compared to those without (PFS, 28 monthsvs. 5 months, p &lt; 0.0001; OS, not reachedvs. 9 months, p &lt; 0.0001). Development of ≥2 irAEs had a trend towards improved PFS and OS compared to those who developed a single irAE, although this did not reach statistical significance (p=0.2555, PFS; p=0.0583, OS). Obesity but not age or gender was distinctly associated with irAE development.ConclusionsIn this study, we demonstrated that irAE occurrence was significantly associated with response to anti-PD-1 therapy and improved PFS/OS. Those who developed multiple irAEs had a trend towards improved PFS and OS compared to those who developed only a single irAE. Increased BMI but neither age nor gender were associated with irAE development. Distinct patterns of irAEs observed suggest shared etiopathogenetic mechanisms.
GPI Is a Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma
Authors: Han Jiahui , Deng Xinzhou , Sun Renhuang , Luo Ming , Liang Meng , Gu Bing , Zhang Te , Peng Zhen , Lu Ying , Tian Chao , Yan Yutao , Luo Zhiguo 
Published: December 2021

BackgroundGlucose-6-phosphate isomerase (GPI) plays an important role in glycolysis and gluconeogenesis. However, the role of GPI in lung adenocarcinoma (LUAD) remains unclear.MethodsAll original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated via R 3.2.2. GPI expression was explored with TCGA, GEO, and Oncomine databases. Immunohistochemistry staining was used to analyze GPI expression in clinical specimens. The correlations between GPI and cancer immune characteristics were analyzed via the TIMER and TISIDB databases. GPI-specific siRNAs were used to verify the role of GPI expression on cell proliferation and cell cycle distribution.ResultsIn general, GPI is predominantly overexpressed and has reference value in the diagnosis and prognostic estimation of LUAD. Upregulated GPI was associated with poorer overall survival, clinical stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we identified a hub gene that included a total of 56 GPI-related genes, which were tightly associated with the cell cycle pathway in LUAD patients. Knockdown of GPI induced cell proliferation inhibition and cell cycle arrest. GPI expression was positively correlated with infiltrating levels of Th2 cells and regulatory T cells (Tregs); in contrast, GPI expression was negatively correlated with infiltrating levels of CD8+ T cells, central memory T cells, dendritic cells, macrophages, mast cells, and eosinophils. GPI was negatively correlated with the expression of immunostimulators, such as CD40L, IL6R, and TMEM173, in LUAD.ConclusionGPI may play an important role in the cell cycle and can be used as a prognostic biomarker for determining the prognosis and immune infiltration in LUAD.
Development of a Deep Learning Model to Assist With Diagnosis of Hepatocellular Carcinoma
Authors: Feng Shi , Yu Xiaotian , Liang Wenjie , Li Xuejie , Zhong Weixiang , Hu Wanwan , Zhang Han , Feng Zunlei , Song Mingli , Zhang Jing , Zhang Xiuming 
Published: December 2021

BackgroundAn accurate pathological diagnosis of hepatocellular carcinoma (HCC), one of the malignant tumors with the highest mortality rate, is time-consuming and heavily reliant on the experience of a pathologist. In this report, we proposed a deep learning model that required minimal noise reduction or manual annotation by an experienced pathologist for HCC diagnosis and classification.MethodsWe collected a whole-slide image of hematoxylin and eosin-stained pathological slides from 592 HCC patients at the First Affiliated Hospital, College of Medicine, Zhejiang University between 2015 and 2020. We propose a noise-specific deep learning model. The model was trained initially with 137 cases cropped into multiple-scaled datasets. Patch screening and dynamic label smoothing strategies are adopted to handle the histopathological liver image with noise annotation from the perspective of input and output. The model was then tested in an independent cohort of 455 cases with comparable tumor types and differentiations.ResultsExhaustive experiments demonstrated that our two-step method achieved 87.81% pixel-level accuracy and 98.77% slide-level accuracy in the test dataset. Furthermore, the generalization performance of our model was also verified using The Cancer Genome Atlas dataset, which contains 157 HCC pathological slides, and achieved an accuracy of 87.90%.ConclusionsThe noise-specific histopathological classification model of HCC based on deep learning is effective for the dataset with noisy annotation, and it significantly improved the pixel-level accuracy of the regular convolutional neural network (CNN) model. Moreover, the model also has an advantage in detecting well-differentiated HCC and microvascular invasion.
HPV Type Distribution in HIV Positive and Negative Women With or Without Cervical Dysplasia or Cancer in East Africa
Authors: Mcharo Ruby , Lennemann Tessa , France John , Torres Liseth , Garí Mercè , Mbuya Wilbert , Mwalongo Wolfram , Mahenge Anifrid , Bauer Asli , Mnkai Jonathan , Glasmeyer Laura , Judick Mona , Paul Matilda , Schroeder Nicolas , Msomba Bareke , Sembo Magreth , Chiwerengo Nhamo , Hoelscher Michael , Geisenberger Otto , Lelle Ralph J. , Saathoff Elmar , Maboko Leonard , Chachage Mkunde , Kroidl Arne , Geldmacher Christof 
Published: December 2021

BackgroundWomen living with HIV in sub-Saharan Africa are at increased risk to develop cervical cancer (CC), which is caused by persistent infection with 13 oncogenic human papilloma viruses (HR-HPVs). It is important to accurately identify and target HIV-positive women at highest risk to develop CC for early therapeutic intervention.MethodsA total of 2,134 HIV+ and HIV− women from South-West Tanzania were prospectively screened for cervical cancer and precancerous lesions. Women with cervical cancer (n=236), high- and low-grade squamous intraepithelial lesions (HSIL: n=68, LSIL: n=74), and without lesion (n=426) underwent high-resolution HPV genotyping.ResultsEighty percent of women who were diagnosed with HSIL or LSIL were living with HIV. Any lesion, young age, HIV status, and depleted CD4 T cell counts were independent risk factors for HPV infections, which were predominantly caused by HR-HPV types. While multiple HR-HPV type infections were predominant in HIV+ women with HSIL, single-type infections predominated in HIV+ CC cases (p=0.0006). HPV16, 18, and 45 accounted for 85% (68/80) and 75% (82/110) of HIV+ and HIV− CC cases, respectively. Of note, HPV35, the most frequent HPV type in HSIL-positive women living with HIV, was rarely detected as a single-type infection in HSIL and cancer cases.ConclusionHPV16, 18, and 45 should receive special attention for molecular diagnostic algorithms during CC prevention programs for HIV+ women from sub-Saharan Africa. HPV35 may have a high potential to induce HSIL in women living with HIV, but less potential to cause cervical cancer in single-type infections.