Neurosurgical interventions for patients with nasopharyngeal carcinoma: a single institution experience

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a frequent head and neck cancer in southern China and Southeast Asia. The majority of NPC patients are managed by radiation oncologists, medical oncologists and head and neck surgeons. Actually, neurosurgical interventions are warranted under specific circumstances. In this article, we described our experience as neurosurgeons in the management of NPC patients. METHODS: Medical records of NPC patients who received neurosurgical procedure at Sun Yat-sen University Cancer Center were reviewed. RESULTS: Twenty-seven patients were identified. Among 27 cases, neurosurgical procedures were performed in 18 (66.7%) with radiation-induced temporal necrosis, 2 (7.4%) with radiation-induced sarcoma, 4 (14.8%) with synchronous NPC with primary brain tumors, 2 (7.4%) with recurrent NPC involving skull base, and 1 (3.7%) with metachronous skull eosinophilic granuloma, respectively. The diagnosis is challenging in specific cases and initial misdiagnoses were found in 6 (22.2%) patients. CONCLUSIONS: For NPC patients with intracranial or skull lesions, the initial diagnosis can be occasionally difficult because of the presence or a history of NPC and related treatment. Unawareness of these entities can result in misdiagnosis and subsequent improper treatment. Neurosurgical interventions are necessary for the diagnosis and treatment for these patients

Brain metastases from hepatocellular carcinoma: clinical features and prognostic factors

<p>Abstract</p> <p>Background</p> <p>Brain metastases (BM) from hepatocellular carcinoma (HCC) are extremely rare and are associated with a poor prognosis. The aim of this study was to define clinical outcome and prognostic determinants in patients with BM from HCC.</p> <p>Methods</p> <p>Between January 1994 and December 2009, all patients with HCC and BM treated in Sun Yat-sen University Cancer Center were retrospectively reviewed. Univariate and multivariate survival analyses were performed to identify possible prognostic factors.</p> <p>Results</p> <p>Forty-one patients were diagnosed with BM from HCC, an incidence of 0.47%. The median age at diagnosis of BM was 48.5 years. Thirty-three patients (80.5%) developed extracranial metastases at diagnosis of BM, and 30 patients (73.2%) had hepatitis B. Intracranial hemorrhage occurred in 19 patients (46.3%). BM were treated primarily either with whole brain radiation therapy (WBRT; 5 patients), stereotactic radiosurgery (SRS; 7 patients), or surgical resection (6 patients). The cause of death was systemic disease in 17 patients and neurological disease in 23. Patients in a high RPA (recursive partitioning analysis) class, treated with conservatively and without lung metastases, tended to die from neurological disease. Median survival after the diagnosis of BM was 3 months (95% confidence interval: 2.2-3.8 months). In multivariate analysis, the presence of extracranial metastases, a low RPA class and aggressive treatment, were positively associated with improved survival.</p> <p>Conclusions</p> <p>BM from HCC is rare and associated with an extremely poor prognosis. However, patients with a low RPA class may benefit from aggressive treatment. The clinical implication of extracranial metastases in HCC patients with BM needs further assessment.</p

A Randomly-Controlled Study on the Cardiac Function at the Early Stage of Return to the Plains after Short-Term Exposure to High Altitude

High altitude acclimatization and adaptation mechanisms have been well clarified, however, high altitude de-adaptation mechanism remains unclear. In this study, we conducted a controlled study on cardiac functions in 96 healthy young male who rapidly entered the high altitude (3700 m) and returned to the plains (1500 m) after 50 days. Ninety eight healthy male who remained at low altitude were recruited as control group. The mean pulmonary arterial pressure (mPAP), left ventricular ejection fraction (LVEF), left ventricular fraction shortening (LVFS), cardiac function index (Tei index) were tested. Levels of serum creatine kinase isoform MB (CK-MB), lactate dehydrogenase isoenzyme-1 (LDH-1), endothelin-1 (ET-1), nitrogen oxide (NO), serum hypoxia-inducible factor-1α (HIF-1α), 8-iso-prostaglandin F2α (8-iso PGF2α), superoxide dismutase (SOD) and malonaldehyde (MDA) were measured at an altitude of 3700 m and 1500 m respectively. The results showed that after short-term exposure to high altitude mPAP and Tei index increased significantly, while LVEF and LVFS decreased significantly. These changes were positively correlated with altitude. On the 15th day after the subjects returned to low altitude, mPAP, LVEF and LVFS levels returned to the same level as those of the control subjects, but the Tei index in the returned subjects was still significantly higher than that in the control subjects (P<0.01). We also found that changes in Tei index was positively correlated with mPAP, ET-1, HIF-1α and 8-iso PGF2α levels, and negatively correlated with the level of NO, LVEF, LVFS, CK-MB and LDH-1. These findings suggest that cardiac function de-adapts when returning to the plains after short-term exposure to high altitude and the function recovery takes a relatively long time

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License