Multimodal Learning for Non-small Cell Lung Cancer Prognosis

This paper focuses on the task of survival time analysis for lung cancer. Although much progress has been made in this problem in recent years, the performance of existing methods is still far from satisfactory. Traditional and some deep learning-based survival time analyses for lung cancer are mostly based on textual clinical information such as staging, age, histology, etc. Unlike existing methods that predicting on the single modality, we observe that a human clinician usually takes multimodal data such as text clinical data and visual scans to estimate survival time. Motivated by this, in this work, we contribute a smart cross-modality network for survival analysis network named Lite-ProSENet that simulates a human's manner of decision making. Extensive experiments were conducted using data from 422 NSCLC patients from The Cancer Imaging Archive (TCIA). The results show that our Lite-ProSENet outperforms favorably again all comparison methods and achieves the new state of the art with the 89.3% on concordance. The code will be made publicly available.Comment: 11 pages, 6 figures, Multimodal learning, NSCLC, Survival analysis, Transforme

Age-Heterogeneity in Marine Sediments Revealed by Three-Dimensional High-Resolution Radiocarbon Measurements

Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from. However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions. To shed light on 1) the age-depth relationship and its full uncertainty, 2) the magnitude of mixing processes affecting the downcore proxy variations, and 3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle. Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( ∼ 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 × 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth. Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met. Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples. We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records

Fever Screening at Airports and Imported Dengue

Airport fever screening in Taiwan, July 2003–June 2004, identified 40 confirmed dengue cases. Results obtained by capture immunoglobulin (Ig) M and IgG enzyme-linked immunoassay, real time 1-step polymerase chain reaction, and virus isolation showed that 33 (82.5%) of 40 patients were viremic. Airport fever screening can thus quickly identify imported dengue cases

Massive haemorrhagic pericardial effusion as the cardiac manifestation of Salmonella enteritidis infection in a severely immunocompromised patient

A 41-years-old gentleman was admitted for reduced effort tolerance with non-specific symptoms of weight loss and generalised body weakness. Chest X-ray (CXR) showed cardiomegaly. Echocardiography showed a large pericardial effusion with septation. Emergency pericardiocentesis was performed and pericardial fluid culture grew Salmonella enteritidis (S. enteritidis). He tested positive for the retroviral disease, with a CD4 count of 10 cells/µL. Intravenous (IV) ceftriaxone was administered. A pericardial drain was inserted due to the rapid re-accumulation of pericardial fluid after the initial pericardiocentesis. He also had drainage of his left pleural effusion. He had a guidewire exchange of pericardial drain around 2 weeks after admission, with flushing performed whenever the flow was poor. A repeat echocardiogram showed early signs of constrictive pericarditis with residual pericardial effusion in which intrapericardial fibrinolysis was considered. He was started on antiretroviral therapy (ART) and his condition remained stable. The pericardial drain was kept throughout his admission. Unfortunately, he developed severe sepsis and succumbed to it about a month post-admission

SIRT1 Activation by a c-MYC Oncogenic Network Promotes the Maintenance and Drug Resistance of Human FLT3-ITD Acute Myeloid Leukemia Stem Cells

SummaryThe FLT3-ITD mutation is frequently observed in acute myeloid leukemia (AML) and is associated with poor prognosis. In such patients, FLT3 tyrosine kinase inhibitors (TKIs) are only partially effective and do not eliminate the leukemia stem cells (LSCs) that are assumed to be the source of treatment failure. Here, we show that the NAD-dependent SIRT1 deacetylase is selectively overexpressed in primary human FLT3-ITD AML LSCs. This SIRT1 overexpression is related to enhanced expression of the USP22 deubiquitinase induced by c-MYC, leading to reduced SIRT1 ubiquitination and enhanced stability. Inhibition of SIRT1 expression or activity reduced the growth of FLT3-ITD AML LSCs and significantly enhanced TKI-mediated killing of the cells. Therefore, these results identify a c-MYC-related network that enhances SIRT1 protein expression in human FLT3-ITD AML LSCs and contributes to their maintenance. Inhibition of this oncogenic network could be an attractive approach for targeting FLT3-ITD AML LSCs to improve treatment outcomes