tbuckley/cabot-search huggingface dataset:
Generation of Distinct Patterns of Rheumatoid Arthritis Autoantigens by Peptidylarginine Deiminase Types 2 and 4 During Perforin‐Induced Cell Damage
Authors: Violeta Romero, Erika Darrah, Felipe Andrade
Journal: Arthritis & Rheumatology (2019)

To address the independent roles of peptidylarginine deiminase type 2 (PAD2) and PAD4 in generating rheumatoid arthritis (RA) autoantigens by using a system that mimics intracellular citrullination in the RA joint.PAD2- or PAD4-expressing 293T cells and mock-transfected cells were used as targets in cytotoxic assays using lymphokine-activated killer cells, cytotoxic YT cell granule contents, or purified human perforin. Protein citrullination and autoantigen production were determined by immunoblotting using the anti-modified citrulline-Senshu method and RA sera (n = 30), respectively.RA sera recognized at least 3 categories of autoantigens in PAD-expressing target cells killed by the cytotoxic lymphocyte granule-induced death pathway. These included: 1) autoantigens targeted in their native form, 2) citrullinated antigens, and 3) antigens cleaved by cytotoxic proteases (e.g., granzymes). Interestingly, although target cells expressing PAD2 or PAD4 showed prominent hypercitrullination of a broad range of proteins during cytotoxic granule-induced cell damage, autoantibodies in RA sera targeted only a very limited number of antigens in hypercitrullinated cells. Furthermore, RA sera showed distinct reactivities to autoantigens generated by PAD2 or PAD4.The cytotoxic granule-induced death pathway has the capacity to modify antigens by inducing hypercitrullination and antigen cleavage in target cells. Interestingly, among a large number of citrullinated proteins generated by PAD2 and PAD4 in cells, only a few are likely involved in the production of autoantibodies in RA.
Highlighting the Need for Action Regarding Persistent Sex Bias in Research
Authors: Kimberly E. Lind
Journal: JAMA Internal Medicine (2020)

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Deep learning–based detection and segmentation-assisted management of brain metastases
Authors: Jie Xue, Bao Wang, Yang Ming, Xuejun Liu, Zekun Jiang, Chengwei Wang, Xiyu Liu, Ligang Chen, Jianhua Qu, Shangchen Xu, Xuqun Tang, Ying Mao, Yingchao Liu, Dengwang Li
Journal: Neuro-Oncology (2019)

Abstract Background Three-dimensional T1 magnetization prepared rapid acquisition gradient echo (3D-T1-MPRAGE) is preferred in detecting brain metastases (BM) among MRI. We developed an automatic deep learning–based detection and segmentation method for BM (named BMDS net) on 3D-T1-MPRAGE images and evaluated its performance. Methods The BMDS net is a cascaded 3D fully convolution network (FCN) to automatically detect and segment BM. In total, 1652 patients with 3D-T1-MPRAGE images from 3 hospitals (n = 1201, 231, and 220, respectively) were retrospectively included. Manual segmentations were obtained by a neuroradiologist and a radiation oncologist in a consensus reading in 3D-T1-MPRAGE images. Sensitivity, specificity, and dice ratio of the segmentation were evaluated. Specificity and sensitivity measure the fractions of relevant segmented voxels. Dice ratio was used to quantitatively measure the overlap between automatic and manual segmentation results. Paired samples t-tests and analysis of variance were employed for statistical analysis. Results The BMDS net can detect all BM, providing a detection result with an accuracy of 100%. Automatic segmentations correlated strongly with manual segmentations through 4-fold cross-validation of the dataset with 1201 patients: the sensitivity was 0.96 ± 0.03 (range, 0.84–0.99), the specificity was 0.99 ± 0.0002 (range, 0.99–1.00), and the dice ratio was 0.85 ± 0.08 (range, 0.62–0.95) for total tumor volume. Similar performances on the other 2 datasets also demonstrate the robustness of BMDS net in correctly detecting and segmenting BM in various settings. Conclusions The BMDS net yields accurate detection and segmentation of BM automatically and could assist stereotactic radiotherapy management for diagnosis, therapy planning, and follow-up.
Variation in Bystander Cardiopulmonary Resuscitation Delivery and Subsequent Survival From Out-of-Hospital Cardiac Arrest Based on Neighborhood-Level Ethnic Characteristics
Authors: Audrey L. Blewer, Robert H. Schmicker, Laurie J. Morrison, Tom P. Aufderheide, Mohamud Daya, Monique A. Starks, Susanne May, Ahamed H. Idris, Clifton W. Callaway, Peter J. Kudenchuk, Gary M. Vilke, Benjamin S. Abella
Journal: Circulation (2019)

Background: Bystander cardiopulmonary resuscitation (B-CPR) delivery and survival after out-of-hospital cardiac arrest vary at the neighborhood level, with lower survival seen in predominantly black neighborhoods. Although the Hispanic population is the fastest-growing minority population in the United States, few studies have assessed whether the proportion of Hispanic residents in a neighborhood is associated with B-CPR delivery and survival from out-of-hospital cardiac arrest. We assessed whether B-CPR rates and survival vary by neighborhood-level ethnicity. We hypothesized that neighborhoods with a higher proportion of Hispanic residents have lower B-CPR rates and lower survival. Methods: We conducted a retrospective cohort study using data from the Resuscitation Outcomes Consortium Epistry at US sites. Neighborhoods were classified by census tract based on percentage of Hispanic residents: &lt;25%, 25% to 50%, 51% to 75%, or &gt;75%. We independently modeled the likelihood of receipt of B-CPR and survival by neighborhood-level ethnicity controlling for site and patient-level confounding characteristics. Results: From 2011 to 2015, the Resuscitation Outcomes Consortium collected 27 481 US arrest events; after excluding pediatric arrests, emergency medical services–witnessed arrests, or arrests occurring in a healthcare or institutional facility, 18 927 were included. B-CPR was administered in 37% of events. In neighborhoods with &lt;25% Hispanic residents, B-CPR was administered in 39% of events, whereas it was administered in 27% of events in neighborhoods with &gt;75% Hispanic residents. Compared with &lt;25% Hispanic neighborhoods in a multivariable analysis, out-of-hospital cardiac arrest in predominantly Hispanic neighborhoods had lower B-CPR rates (51% to 75% Hispanic: odds ratio, 0.79 [CI, 0.65–0.95], P =0.014; &gt;75% Hispanic: odds ratio, 0.72 [CI, 0.55–0.96], P =0.025) and lower survival rates (global P value 0.029; &gt;75% Hispanic: odds ratio, 0.56 [CI, 0.34–0.93], P =0.023). Conclusions: Individuals with out-of-hospital cardiac arrest in predominantly Hispanic neighborhoods were less likely to receive B-CPR and had lower likelihood of survival. These findings suggest a need to understand the underlying disparities in cardiopulmonary resuscitationdelivery and an unmet cardiopulmonary resuscitationtraining need in Hispanic communities.
Participation in a Hospital Incentive Program for Follow-up Treatment for Opioid Use Disorder
Authors: Austin S. Kilaru, Jeanmarie Perrone, David Kelley, Sari Siegel, Su Fen Lubitz, Nandita Mitra, Zachary F. Meisel
Journal: JAMA Network Open (2020)

This cross-sectional study examines hospital participation in an incentive program that aims to improve the rate of opioid use disorder follow-up treatment among Medicaid recipients in Pennsylvania.
Abstract 10582: Comparative 5-year Outcomes in Non-ischemic Dilated Cardiomyopathy (NIDC) Patients With TITIN (TTN) Gene Truncating Variant (tv) Mutations
Authors: Jeffrey L Anderson, Victoria Jacobs, G B Christensen, Helaman Escobar, Benjamin D Horne, Kia Afshar, Virginia B Hebl, Kirk U Knowlton, Joseph B Muhlestein, John F Carlquist, Lincoln Nadauld
Journal: Circulation (2019)

Introduction: Genetic factors are known to play an important role in NIDC with a large number of pathogenic mutations in multiple genes reported. TTNtv mutations are of interest because of their co...
Therapeutic targeting of YY1/MZF1 axis by MZF1-uPEP inhibits aerobic glycolysis and neuroblastoma progression
Authors: Erhu Fang, Xiaojing Wang, Jianqun Wang, Anpei Hu, Huajie Song, Feng Yang, Dan Li, Wenjing Xiao, Yajun Chen, Yanhua Guo, Yang Liu, Hongjun Li, Kai Huang, Liduan Zheng, Qiangsong Tong
Journal: Theranostics (2020)

As a hallmark of metabolic reprogramming, aerobic glycolysis contributes to tumorigenesis and aggressiveness.However, the mechanisms and therapeutic strategies regulating aerobic glycolysis in neuroblastoma (NB), one of leading causes of cancer-related death in childhood, still remain elusive.Methods: Transcriptional regulators and their downstream glycolytic genes were identified by a comprehensive screening of publicly available datasets.Dual-luciferase, chromatin immunoprecipitation, real-time quantitative RT-PCR, western blot, gene over-expression or silencing, co-immunoprecipitation, mass spectrometry, peptide pull-down assay, sucrose gradient sedimentation, seahorse extracellular flux, MTT colorimetric, soft agar, matrigel invasion, and nude mice assays were undertaken to explore the biological effects and underlying mechanisms of transcriptional regulators in NB cells.Survival analysis was performed by using log-rank test and Cox regression assay.Results: Transcription factor myeloid zinc finger 1 (MZF1) was identified as an independent prognostic factor (hazard ratio=2.330,95% confidence interval=1.021 to 3.317), and facilitated glycolysis process through increasing expression of hexokinase 2 (HK2) and phosphoglycerate kinase 1 (PGK1).Meanwhile, a 21-amino acid peptide encoded by upstream open reading frame of MZF1, termed as MZF1-uPEP, bound to zinc finger domain of Yin Yang 1 (YY1), resulting in repressed transactivation of YY1 and decreased transcription of MZF1 and downstream genes HK2 and PGK1.Administration of a cell-penetrating MZF1-uPEP or lentivirus over-expressing MZF1-uPEP inhibited the aerobic glycolysis, tumorigenesis and aggressiveness of NB cells.In clinical NB cases, low expression of MZF1-uPEP or high expression of MZF1, YY1, HK2, or PGK1 was associated with poor survival of patients.Conclusions: These results indicate that therapeutic targeting of YY1/MZF1 axis by MZF1-uPEP inhibits aerobic glycolysis and NB progression.
Chemotherapy effectiveness in trial-underrepresented groups with early breast cancer: A retrospective cohort study
Authors: Ewan Gray, Joachim Marti, Jeremy C. Wyatt, David H. Brewster, Peter S. Hall
Journal: PLoS Medicine (2019)

Background Adjuvant chemotherapy in early stage breast cancer has been shown to reduce mortality in a large meta-analysis of over 100 randomised trials. However, these trials largely excluded patients aged 70 years and over or with higher levels of comorbidity. There is therefore uncertainty about whether the effectiveness of adjuvant chemotherapy generalises to these groups, hindering patient and clinician decision-making. This study utilises administrative healthcare data—real world data (RWD)—and econometric methods for causal analysis to estimate treatment effectiveness in these trial-underrepresented groups. Methods and findings Women with early breast cancer aged 70 years and over and those under 70 years with a high level of comorbidity were identified and their records extracted from Scottish Cancer Registry (2001–2015) data linked to other routine health records. A high level of comorbidity was defined as scoring 1 or more on the Charlson comorbidity index, being in the top decile of inpatient stays, and/or having 5 or more visits to specific outpatient clinics, all within the 5 years preceding breast cancer diagnosis. Propensity score matching (PSM) and instrumental variable (IV) analysis, previously identified as feasible and valid in this setting, were used in conjunction with Cox regression to estimate hazard ratios for death from breast cancer and death from all causes. The analysis adjusts for age, clinical prognostic factors, and socioeconomic deprivation; the IV method may also adjust for unmeasured confounding factors. Cohorts of 9,653 and 7,965 were identified for women aged 70 years and over and those with high comorbidity, respectively. In the ≥70/high comorbidity cohorts, median follow-up was 5.17/6.53 years and there were 1,935/740 deaths from breast cancer. For women aged 70 years and over, the PSM-estimated HR was 0.73 (95% CI 0.64–0.95), while for women with high comorbidity it was 0.67 (95% CI 0.51–0.86). This translates to a mean predicted benefit in terms of overall survival at 10 years of approximately3% (percentage points) and 4%, respectively. A limitation of this analysis is that use of observational data means uncertainty remains both from sampling uncertainty and from potential bias from residual confounding. Conclusions The results of this study, as RWD, should be interpreted with caution and in the context of existing and emerging randomised data. The relative effectiveness of adjuvant chemotherapy in reducing mortality in patients with early stage breast cancer appears to be generalisable to the selected trial-underrepresented groups.
18F-FDG PET/CT of Benign Tracheal Glomus Tumor
Authors: Dan Shao, Qiang Gao, Siyun Wang, You Cheng, Shuxia Wang
Journal: Clinical Nuclear Medicine (2019)

Abstract Glomus tumors are tumors that arise from the glomus bodies, which can be found in sites of arteriovenous anastomosis. Glomus tumors can occur in all parts of the body but rarely occur in the trachea. The PET/CT findings of these tumors are similar to those of malignant tracheal tumors. We reported the PET/CT findings of a pathologically proven primary glomus tumor in the trachea of a 41-year-old man.
Can environmental determinants explain Nontuberculous Mycobacteria geographic incidence?
Authors: Diogo Rocha, Óscar Felgueiras, Raquel Duarte
Journal: Pulmonology (2019)

Nontuberculous mycobacteria (NTM) are opportunistic agents that have gained importance during the last decades due to their increasing incidence in high-risk populations. Their modes of transmission differ from person-toperson contact commonly described in Mycobacterium tuberculosis (MTB). In fact, NTM are frequently found in soil, natural waters and drinking-water distributions systems, emphasizing the contribution of environmental factors when discussing this disease's susceptibility. Our aim is to evaluate the incidence of NTM in Portugal and to identify the main environmental variables related to it. We performed a cross-sectional study centred on 2011 (date of the latest Portuguese census) from collected personal features and environmental data available in public databases. Environmental values when only known at the district level were interpolated using inverse distance weighting. A semiparametric poisson model was used to estimate NTM incidence. The non-parametric part of the model was obtained by using thin plate smoothing splines defined on the spatial component of the data. 359 new NTM cases were notified during a five-year period. None of the environmental determinants studied was strong enough to predict NTM geographical incidence in Portugal (p > 0.05), except for population density (p < 0.001). Personal characteristics such as female sex (p < 0.001), age (p < 0.001) and Human Immunodeficiency Virus infection and Acquired Immune Deficiency Syndrome (HIV/AIDS) incidence (p < 0.001) are associated with an increase of NTM disease incidence. NTM appears to be more common in elderly women, especially if they have HIV/AIDS disease or if they live in urban, highly populated areas. Overall, female sex seems to assume the most relevant role when discussing predisposition to NTM disease. However, further studies are needed to evaluate the impact on NTM geographical incidence by other environmental and personal variables not included in this one.
Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review
Authors: Ashley Spann, Angeline Yasodhara, Justin Kang, Kymberly Watt, Bo Wang, Anna Goldenberg, Mamatha Bhat
Journal: Hepatology (2020)

Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently and more effectively than conventional methods through detection of hidden patterns within large data sets. With this in mind, there are several areas within hepatology where these methods can be applied. In this review, we examine the literature pertaining to machine learning in hepatology and liver transplant medicine. We provide an overview of the strengths and limitations of ML tools and their potential applications to both clinical and molecular data in hepatology. ML has been applied to various types of data in liver disease research, including clinical, demographic, molecular, radiological, and pathological data. We anticipate that use of ML tools to generate predictive algorithms will change the face of clinical practice in hepatology and transplantation. This review will provide readers with the opportunity to learn about the ML tools available and potential applications to questions of interest in hepatology.
Reproducibility, performance, and clinical utility of a genetic risk prediction model for prostate cancer in Japanese patients.
Authors: Shusuke Akamatsu, Ryo Takata, Atsushi Takahashi, Takahiro Inoue, Michiaki Kubo, Naoyuki Kamatani, Johji Inazawa, Tomoaki Fujioka, Tomonori Habuchi, Osamu Ogawa, Yusuke Nakamura, Hidewaki Nakagawa
Journal: Journal of Clinical Oncology (2012)

10520 Background: Prostate specific antigen (PSA) is widely used as a diagnostic biomarker for prostate cancer (PC). However, due to its low predictive performance, many patients without PC suffer from the harms of unnecessary prostate needle biopsies. The present study aims to evaluate the reproducibility and performance of a genetic risk prediction model and estimate its utility as a diagnostic biomarker in a clinical scenario. Methods: We created a logistic regression model incorporating 16 SNPs that were significantly associated with PC in a genome-wide association study of the Japanese. The model was validated by two independent sets of samples comprising 3,294 cases and 6,281 controls. Various cut offs were evaluated to be used in a clinical scenario. Results: The area under a curve (AUC) of the model was 0.679, 0.655, and 0.661 for the samples used to create the model and those used for validation respectively. The AUC of the model was not significantly altered in samples with PSA 1-10 ng/ml. 24.2% and 9.7% of the patients had odds ratio &lt;0.5 (low risk) or &gt;2 (high risk) in the model, and assuming the overall positive rate of prostate needle biopsies to be 20% in PSA gray zone (PSA 2-10 ng/ml), the positive biopsy rates were 10.7% and 42.4% respectively for the two genetic risk groups. Conclusions: The genetic risk prediction model was highly reproducible, and its predictive performance was not influenced by PSA. The model could have a potential to affect clinical decision when it is applied to patients with gray-zone PSA, which should be confirmed in future clinical studies.
Cytology- versus histology-based diagnosis in small cell lung cancer: Is there any clinical implication?
Authors: Alexios S Strimpakos, Vassilios Ramfidis, Charilaos Maragkos, Meropi Panagiotarakou, Ioannis Gkiozos, Kostas N Syrigos
Journal: Journal of Clinical Oncology (2012)

e17557 Background: Small cell lung cancer (SCLC) is a common disease representing around 15% of all lung cancer patients. Unlike other solid tumours, SCLC is staged as limited or extensive depending on whether the disease can be confined to a radiation field or not. Diagnosis is confirmed either on histology (H) or cytological (C) examination, but it has not been studied yet whether there is a clinically significant difference between them. This study aimed to highlight possible differences and clinical significance of SCLC diagnosis made by H or C. Methods: Medical records of 422 patients (pts) diagnosed with SCLC between 2000 and 2011 were screened. Complete demographic, clinical and treatment data were available for 414 patients. Results: 274/414 pts (66,2%) were diagnosed by histology and 140/414 (33,8%) by cytology. Male:female ratio was 224:50 and 122:18 in H and C groups whereas median age 64 years in both. Limited:extensive stage was established in 89:185 pts in the H group and 41:99 in the C group. Chemotherapy was received by most patients in both groups but radiotherapy only in 110/274 pts (40%) in H and 59/140 pts (42%) in the C group. Median survival (OS) for the H and C groups were 7,7 and 7,3 months respectively. Conclusions: SCLC is a common and aggressive disease with poor prognosis. Early diagnosis offers the best chances for a longer survival and treatment should be commenced promptly. Diagnosis based on histology or cytology shares similar demographic and clinical characteristics without difference in treatment outcomes and survival.
68Ga–Prostate-Specific Membrane Antigen 11 PET/CT Detects Residual Glioblastoma After Radical Surgery in a Patient With Synchronous Recurrent Prostate Cancer
Authors: Emanuela Pilati, Daniele Giovanni Nicolotti, Francesco Ceci, Monica Finessi, Ivan Cerio, Beatrice Dionisi, Michela Zotta, Marilena Bellò, Désirée Deandreis
Journal: Clinical Nuclear Medicine (2019)

Abstract Prostate-specific membrane antigen (PSMA) is a transmembrane enzyme also known as folate hydrolase 1 highly expressed by prostate cancer (PCa) cells. However, PSMA overexpression by tumor-associated neovasculature of a variety of solid tumors, including glioblastoma (GBM), has also been proven. This clinical case reports about a 67-year-old man with a history of PCa who underwent radical surgery for GBM and performed a 68 Ga-PSMA-11 PET/CT to restage PCa. PET imaging showed PSMA uptake in GBM residual disease after surgery. This finding suggests a possible role of PSMA inhibitors as diagnostic and therapeutic agents in patients affected by GBM.
The functions and regulation of Smurfs in cancers
Authors: Lin Fu, Chun-Ping Cui, Xueli Zhang, Lingqiang Zhang
Journal: Seminars in Cancer Biology (2019)

Smad ubiquitination regulatory factor 1 (Smurf1) and Smurf2 are HECT-type E3 ubiquitin ligases, and both Smurfs were initially identified to regulate Smad protein stability in the TGF-β/BMP signaling pathway. In recent years, Smurfs have exhibited E3 ligase-dependent and -independent activities in various kinds of cells. Smurfs act as either potent tumor promoters or tumor suppressors in different tumors by regulating biological processes, including metastasis, apoptosis, cell cycle, senescence and genomic stability. The regulation of Smurfs activity and expression has therefore emerged as a hot spot in tumor biology research. Further, the Smurf1- or Smurf2-deficient mice provide more in vivo clues for the functional study of Smurfs in tumorigenesis and development. In this review, we summarize these milestone findings and, in turn, reveal new avenues for the prevention and treatment of cancer by regulating Smurfs.