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1. Full Text Papillary tumor of the pineal region with synchronous suprasellar focus and novel cytogenetic features
by Mobley, Bret C., MD and Kumar, Manoj, MD and Sanger, Warren G., PhD and Nelson, Marilu, MS and Nickols, Hilary H., MD, PhD and Chambless, Lola B., MD and Gokden, Murat, MD
Human pathology, ISSN 0046-8177, 2015, Volume 46, Issue 8, pp. 1232 - 1236
Pathology | Cytogenetics | Suprasellar | Multifocal | Papillary tumor of the pineal region | Circumventricular organs | Life Sciences & Biomedicine | Science & Technology | Neurosurgical Procedures | Carcinoma, Papillary - genetics | Humans | Pinealoma - pathology | Pinealoma - therapy | Adult | Male | Combined Modality Therapy | Cytogenetic Analysis | Radiotherapy | Carcinoma, Papillary - pathology | Pinealoma - genetics | Development and progression | Chromosomes | Tumors | Studies | Medical imaging | Nuclear magnetic resonance--NMR | Cloning | Metastasis | Gene expression | Hemorrhage | Index Medicus
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2. Full Text Type 2 Diabetes is an Independent Negative Prognostic Factor in Patients Undergoing Surgical Resection of a WHO Grade I Meningioma
by Nayeri, Arash, MD and Chotai, Silky, MD and Prablek, Marc A., BS and Brinson, Philip R, MPH and Douleh, Diana G, BS and Weaver, Kyle D, MD and Thompson, Reid C, MD and Chambless, Lola, MD
Clinical neurology and neurosurgery, ISSN 0303-8467, 2016, Volume 149, pp. 6 - 10
Neurology | Neurosurgery | Obesity | WHO grade I | Diabetes | Survival | Mortality | Meningioma | Clinical Neurology | Neurosciences & Neurology | Life Sciences & Biomedicine | Surgery | Science & Technology | Meningeal Neoplasms - epidemiology | Prognosis | Outcome Assessment (Health Care) | Comorbidity | Humans | Meningioma - surgery | Middle Aged | Male | Diabetes Mellitus, Type 2 - epidemiology | Meningeal Neoplasms - mortality | Neoplasm Grading | Meningioma - epidemiology | Meningeal Neoplasms - surgery | Adult | Female | Aged | Retrospective Studies | Meningioma - mortality | Type 2 diabetes | Diabetics | Medical research | Analysis | Medicine, Experimental | Medical records | Statistical analysis | Nuclear magnetic resonance--NMR | Glucose | Gender | Radiation therapy | Multivariate analysis | Patients | Confidence intervals | Variables | Body mass index | Survival analysis | Weight control | Medical prognosis | Age | Index Medicus
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3. Full Text Heterogeneity within the PF-EPN-B ependymoma subgroup
by Cavalli, Florence M. G and Hübner, Jens-Martin and Sharma, Tanvi and Luu, Betty and Sill, Martin and Zapotocky, Michal and Mack, Stephen C and Witt, Hendrik and Lin, Tong and Shih, David J. H and Ho, Ben and Santi, Mariarita and Emery, Lyndsey and Hukin, Juliette and Dunham, Christopher and McLendon, Roger E and Lipp, Eric S and Gururangan, Sridharan and Grossbach, Andrew and French, Pim and Kros, Johan M and van Veelen, Marie-Lise C and Rao, Amulya A. Nageswara and Giannini, Caterina and Leary, Sarah and Jung, Shin and Faria, Claudia C and Mora, Jaume and Schüller, Ulrich and Alonso, Marta M and Chan, Jennifer A and Klekner, Almos and Chambless, Lola B and Hwang, Eugene I and Massimino, Maura and Eberhart, Charles G and Karajannis, Matthias A and Lu, Benjamin and Liau, Linda M and Zollo, Massimo and Ferrucci, Veronica and Carlotti, Carlos and Tirapelli, Daniela P. C and Tabori, Uri and Bouffet, Eric and Ryzhova, Marina and Ellison, David W and Merchant, Thomas E and Gilbert, Mark R and Armstrong, Terri S and Korshunov, Andrey and Pfister, Stefan M and Taylor, Michael D and Aldape, Kenneth and Pajtler, Kristian W and Kool, Marcel and Ramaswamy, Vijay
Acta neuropathologica, ISSN 0001-6322, 8/2018, Volume 136, Issue 2, pp. 227 - 237
Pathology | Neurosciences | Medicine & Public Health | Subgrouping | PFA | Posterior fossa | Clustering | PFB | Ependymoma | Clinical Neurology | Neurosciences & Neurology | Life Sciences & Biomedicine | Science & Technology | Infratentorial Neoplasms - genetics | Infratentorial Neoplasms - classification | Age Factors | Humans | Middle Aged | Kaplan-Meier Estimate | Ependymoma - classification | Male | DNA Copy Number Variations - genetics | DNA Methylation - genetics | Gene Expression Profiling | Ependymoma - genetics | Infratentorial Neoplasms - pathology | Young Adult | Ependymoma - surgery | Microarray Analysis | Adolescent | Infratentorial Neoplasms - surgery | Adult | Ependymoma - pathology | Female | Child | Cohort Studies | Medical colleges | Genomes | Methylation | Gene expression | Analysis | Genomics | Demography | DNA methylation | Chromosome 13 | DNA fingerprinting | Chromosome 2 | Tumors | Index Medicus | ependymoma | clustering | subgrouping | posterior fossa
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4. Full Text Recurrent noncoding U1 snRNA mutations drive cryptic splicing in SHH medulloblastoma
by Suzuki, Hiromichi and Kumar, Sachin A and Shuai, Shimin and Diaz-Navarro, Ander and Gutierrez-Fernandez, Ana and De Antonellis, Pasqualino and Cavalli, Florence M. G and Juraschka, Kyle and Farooq, Hamza and Shibahara, Ichiyo and Vladoiu, Maria C and Zhang, Jiao and Abeysundara, Namal and Przelicki, David and Skowron, Patryk and Gauer, Nicole and Luu, Betty and Daniels, Craig and Wu, Xiaochong and Forget, Antoine and Momin, Ali and Wang, Jun and Dong, Weifan and Kim, Seung-Ki and Grajkowska, Wieslawa A and Jouvet, Anne and Fèvre-Montange, Michelle and Garrè, Maria Luisa and Nageswara Rao, Amulya A and Giannini, Caterina and Kros, Johan M and French, Pim J and Jabado, Nada and Ng, Ho-Keung and Poon, Wai Sang and Eberhart, Charles G and Pollack, Ian F and Olson, James M and Weiss, William A and Kumabe, Toshihiro and López-Aguilar, Enrique and Lach, Boleslaw and Massimino, Maura and Van Meir, Erwin G and Rubin, Joshua B and Vibhakar, Rajeev and Chambless, Lola B and Kijima, Noriyuki and Klekner, Almos and Bognár, László and Chan, Jennifer A and Faria, Claudia C and Ragoussis, Jiannis and Pfister, Stefan M and Goldenberg, Anna and Wechsler-Reya, Robert J and Bailey, Swneke D and Garzia, Livia and Morrissy, A. Sorana and Marra, Marco A and Huang, Xi and Malkin, David and Ayrault, Olivier and Ramaswamy, Vijay and Puente, Xose S and Calarco, John A and Stein, Lincoln and Taylor, Michael D
Nature (London), ISSN 0028-0836, 10/2019, Volume 574, Issue 7780, pp. 707 - 711
Science & Technology - Other Topics | Multidisciplinary Sciences | Science & Technology | RNA Splicing | RNA Splice Sites | Alternative Splicing | Hedgehog Proteins - genetics | RNA, Small Nuclear - genetics | Humans | Adolescent | Hedgehog Proteins - metabolism | Adult | Cerebellar Neoplasms - genetics | Mutation | Medulloblastoma - genetics | Sonic hedgehog | Gene mutations | Medulloblastoma | Analysis | Genetic aspects | Small nuclear ribonucleoproteins | Methods | RNA splicing | Alternative splicing | Splicing | Genes | Hot spots | Genomics | Infants | Genomes | Nucleotides | snRNA | Subgroups | Confidence intervals | Proteins | Acids | Hedgehog protein | Medical prognosis | Adolescents | Bioinformatics | Cancer | Tumors | Index Medicus
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5. Full Text 115 Neurosurgical Resident Attrition
by White, Michael D and Agarwal, Nitin and Pannullo, Susan C and Chambless, Lola B
Neurosurgery, ISSN 0148-396X, 09/2018, Volume 65, Issue CN_suppl_1, pp. 85 - 85
Clinical medicine | Neurosurgery
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6. Full Text Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells
by Leelatian, Nalin and Sinnaeve, Justine and Mistry, Akshitkumar M and Barone, Sierra M and Brockman, Asa A and Diggins, Kirsten E and Greenplate, Allison R and Weaver, Kyle D and Thompson, Reid C and Chambless, Lola B and Mobley, Bret C and Ihrie, Rebecca A and Irish, Jonathan M
eLife, ISSN 2050-084X, 06/2020, Volume 9
Biology | Life Sciences & Biomedicine - Other Topics | Life Sciences & Biomedicine | Science & Technology | Unsupervised Machine Learning | Pilot Projects | Algorithms | Tumor Cells, Cultured | Glioblastoma - physiopathology | Humans | Immunohistochemistry | Statistical analysis | Tumor cells | Glioblastoma | Kinases | Patients | Datasets | Variables | Design | Proteins | Learning algorithms | Cytometry | Brain research | Medical prognosis | Risk assessment | Machine learning | Stochasticity | Cancer | Tumors | Index Medicus
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7. Full Text Implementation and Impact of Patient Lay Navigator-Led Advance Care Planning Conversations
by Rocque, Gabrielle B., MD and Dionne-Odom, J. Nicholas, PhD, RN and Sylvia Huang, Chao-Hui, PhD and Niranjan, Soumya J., BPharm, MS and Williams, Courtney P., MPH and Jackson, Bradford E., PhD and Halilova, Karina I., MD, MPH and Kenzik, Kelly M., PhD and Bevis, Kerri S., MD and Wallace, Audrey S., MD, MSN and Lisovicz, Nedra, PhD, MPH, CHES and Taylor, Richard A., DNP, CRNP, ANP-BC and Pisu, Maria, PhD and Partridge, Edward E., MD and Butler, Thomas W., MD and Briggs, Linda A., MSN, MA, RN and Kvale, Elizabeth A., MD and Patient Care Connect Group and Patient Care Connect Grp
Journal of pain and symptom management, ISSN 0885-3924, 2017, Volume 53, Issue 4, pp. 682 - 692
Anesthesia & Perioperative Care | Pain Medicine | end of life | Advance care planning | lay navigation | lay navigator | Clinical Neurology | Life Sciences & Biomedicine | Health Care Sciences & Services | Medicine, General & Internal | Neurosciences & Neurology | General & Internal Medicine | Science & Technology | Advance Care Planning | Self Efficacy | Follow-Up Studies | Humans | Health Personnel - psychology | Male | Antineoplastic Agents - therapeutic use | Patient Navigation | Patient Preference | Feasibility Studies | Neoplasms - therapy | Terminal Care - statistics & numerical data | Health Personnel - education | Education, Medical | Female | Interviews as Topic | Surveys and Questionnaires | Aged | Qualitative Research | Neoplasms - epidemiology | Communication | Care plans | Discomfort | Navigation | Advance directives | African Americans | Patients | Clinical outcomes | Studies | Training | Treatment preferences | Chemotherapy | Readiness | Self-efficacy | Palliative care | Facilitators | End of life decisions | Life sustaining treatment | Cancer | Index Medicus
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8. Full Text Predicting Inpatient Length of Stay After Brain Tumor Surgery: Developing Machine Learning Ensembles to Improve Predictive Performance
by Muhlestein, Whitney E and Akagi, Dallin S and Davies, Jason M and Chambless, Lola B
Neurosurgery, ISSN 0148-396X, 09/2019, Volume 85, Issue 3, pp. 384 - 393
Clinical Neurology | Neurosciences & Neurology | Life Sciences & Biomedicine | Surgery | Science & Technology | Length of Stay | Inpatients | Regression Analysis | Algorithms | Prognosis | Humans | Middle Aged | Female | Male | Clinical Decision Rules | Machine Learning | Brain Neoplasms - surgery | Brain | Brain tumors | Machine learning | Neurosurgery | Brain cancer | Clinical outcomes | Index Medicus | Research—Human—Clinical Studies | Predictive modeling | Outcomes | Length of stay
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9. Full Text Bone morphogenetic protein signaling promotes tumorigenesis in a murine model of high-grade glioma
by Hover, Laura D and Owens, Philip and Munden, Alexander L and Wang, Jialiang and Chambless, Lola B and Hopkins, Corey R and Hong, Charles C and Moses, Harold L and Abel, Ty W
Neuro-oncology (Charlottesville, Va.), ISSN 1522-8517, 07/2016, Volume 18, Issue 7, pp. 928 - 938
DMH1 | BMP | high-grade glioma | BMPR1a | genetically engineered mice | Oncology | Clinical Neurology | Neurosciences & Neurology | Life Sciences & Biomedicine | Science & Technology | Glioma - genetics | Bone Morphogenetic Proteins - metabolism | Animals | Cell Proliferation | Signal Transduction | Cell Transformation, Neoplastic | Gene Expression Regulation - genetics | Carcinogenesis - genetics | Bone Morphogenetic Protein Receptors, Type I - genetics | Mice, Transgenic | Astrocytes - metabolism | Glioma - metabolism | Index Medicus | Basic and Translational Investigations
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10. Full Text Cancer Dissemination, Hydrocephalus, and Survival After Cerebral Ventricular Entry During High-Grade Glioma Surgery: A Meta-Analysis
by Mistry, Akshitkumar M and Kelly, Patrick D and Thompson, Reid C and Chambless, Lola B
Neurosurgery, ISSN 0148-396X, 12/2018, Volume 83, Issue 6, pp. 1119 - 1127
Glioma | Hydrocephalus | Dissemination | Glioblastoma | Ventricle | Lateral ventricle | Survival | Clinical Neurology | Neurosciences & Neurology | Life Sciences & Biomedicine | Surgery | Science & Technology | Neurosurgery | Meta-analysis
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