Anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) show fatal outcomes, unlike DTCs. Here, we demonstrate mutational landscape of 27 ATCs and 86 advanced DTCs by ...massively-parallel DNA sequencing, and transcriptome of 13 ATCs and 12 advanced DTCs were profiled by RNA sequencing. TERT, AKT1, PIK3CA, and EIF1AX were frequently co-mutated with driver genes (BRAF
and RAS) in advanced DTCs as well as ATC, but tumor suppressors (e.g., TP53 and CDKN2A) were predominantly altered in ATC. CDKN2A loss was significantly associated with poor disease-specific survival in patients with ATC or advanced DTCs, and up-regulation of CD274 (PD-L1) and PDCD1LG2 (PD-L2). Transcriptome analysis revealed a fourth molecular subtype of thyroid cancer (TC), ATC-like, which hardly reflects the molecular signatures in DTC. Furthermore, the activation of JAK-STAT signaling pathway could be a potential druggable target in RAS-positive ATC. Our findings provide insights for precision medicine in patients with advanced TCs.
We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on ...mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune- and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.
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•Mutation-phosphorylation correlation suggests possible signaling interplays in EOGCs•mRNA-protein correlation suggests genes with high association with patient survival•Integrated analysis of mRNA and protein data identified four subtypes•Phosphorylation data provide cellular signaling pathways underlying the subtypes
Mun et al. perform proteogenomic analysis of diffuse gastric cancers (DGC) in a young population, identifying that correlations of mRNA-protein abundance associate with survival and defining four subtypes of DGC. The associations of some subtypes with related pathways are identified mainly by the proteomic data.
In this study, we propose a generative data augmentation technique to overcome the challenges of severely limited data when designing a deep learning-based automated strabismus diagnosis system. We ...implement a generative model based on the StyleGAN2-ADA model for system design and assess strabismus classification performance using two classifiers. We evaluate the capability of our proposed method against traditional data augmentation techniques and confirm a substantial enhancement in performance. Furthermore, we conduct experiments to explore the relationship between the diagnosis agreement among ophthalmologists and the generation performance of the generative model. Beyond FID, we validate the generative samples on the classifier to establish their practicality. Through these experiments, we demonstrate that the generative model-based data augmentation improves overall quantitative performance in scenarios of extreme data scarcity and effectively mitigates overfitting issues during deep learning model training.
Many malignant tumors initially appear benign but subsequently exhibit extensive metastases. Early identification of malignant pheochromocytomas and paragangliomas (PPGLs) before metastasis is ...important for improved prognosis. However, there are no robust prognostic indices of recurrence and malignancy. The aim of this study was to identify the clinical and histopathological factors that predict malignant PPGLs.
Retrospective follow-up study.
In this study, we included 223 patients with pathologically confirmed PPGLs who were treated between 2000 and 2015 at the Seoul National University Hospital in South Korea.
Of these patients, 29 were diagnosed with malignancy, 12 of whom presented with metastatic lesions at the initial diagnosis while 17 developed metastases during follow-up. Nineteen patients with recurrent PPGLs consisted of ones with malignant PPGLs (n = 17) and multifocal PPGLs (n = 2) who had VHL and RET mutations. The mean age at presentation for malignant PPGLs was significantly younger than that for benign PPGLs (43.0 vs. 49.0 years, respectively; p = 0.023). Tumor size was not a distinguishing factor between malignant and benign PPGLs (5.0 vs. 4.5 cm, respectively; p = 0.316) nor did it predict recurrence. Of 119 patients with available pheochromocytoma of adrenal gland scaled score (PASS) data, those with malignant PPGLs presented PASS values ≥4. Of 12 parameters of PASS, necrosis, capsular invasion, vascular invasion, cellular monotony, high mitosis, atypical mitotic figures, and nuclear hyperchromasia were significant predictors of malignancy.
Tumor size did not predict malignancy or recurrence of PPGLs. PPGL patients with characteristic pathologic findings and PASS ≥4 or germline mutations require close follow-up.
Follicular thyroid carcinoma (FTC) and benign follicular adenoma (FA) are indistinguishable by preoperative diagnosis due to their similar histological features. Here we report the first RNA ...sequencing study of these tumors, with data for 30 minimally invasive FTCs (miFTCs) and 25 FAs. We also compared 77 classical papillary thyroid carcinomas (cPTCs) and 48 follicular variant of PTCs (FVPTCs) to observe the differences in their molecular properties. Mutations in H/K/NRAS, DICER1, EIF1AX, IDH1, PTEN, SOS1, and SPOP were identified in miFTC or FA. We identified a low frequency of fusion genes in miFTC (only one, PAX8-PPARG), but a high frequency of that in PTC (17.60%). The frequencies of BRAFV600E and H/K/NRAS mutations were substantially different in miFTC and cPTC, and those of FVPTC were intermediate between miFTC and cPTC. Gene expression analysis demonstrated three molecular subtypes regardless of their histological features, including Non-BRAF-Non-RAS (NBNR), as well as BRAF-like and RAS-like. The novel molecular subtype, NBNR, was associated with DICER1, EIF1AX, IDH1, PTEN, SOS1, SPOP, and PAX8-PPARG. The transcriptome of miFTC or encapsulated FVPTC was indistinguishable from that of FA, providing a molecular explanation for the similarly indolent behavior of these tumors. We identified upregulation of genes that are related to mitochondrial biogenesis including ESRRA and PPARGC1A in oncocytic follicular thyroid neoplasm. Arm-level copy number variations were correlated to histological and molecular characteristics. These results expanded the current molecular understanding of thyroid cancer and may lead to new diagnostic and therapeutic approaches to the disease.
Coronavirus Disease-19 (COVID-19) is a respiratory infection characterized by the main symptoms of pneumonia and fever. It is caused by the novel coronavirus severe acute respiratory syndrome ...Coronavirus-2 (SARS-CoV-2), which is known to spread via respiratory droplets. We aimed to determine the rate and likelihood of SARS-CoV-2 transmission from COVID-19 patients through non-respiratory routes.
Serum, urine, and stool samples were collected from 74 hospitalized patients diagnosed with COVID-19 based on the detection of SARS-CoV-2 in respiratory samples. The SARS-CoV-2 RNA genome was extracted from each specimen and real-time reverse transcription polymerase chain reaction performed. CaCo-2 cells were inoculated with the specimens containing the SARS-COV-2 genome, and subcultured for virus isolation. After culturing, viral replication in the cell supernatant was assessed.
Of the samples collected from 74 COVID-19 patients, SARS-CoV-2 was detected in 15 serum, urine, or stool samples. The virus detection rate in the serum, urine, and stool samples were 2.8% (9/323), 0.8% (2/247), and 10.1% (13/129), and the mean viral load was 1,210 ± 1,861, 79 ± 30, and 3,176 ± 7,208 copy/μL, respectively. However, the SARS-CoV-2 was not isolated by the culture method from the samples that tested positive for the SARS-CoV-2 gene.
While the virus remained detectable in the respiratory samples of COVID-19 patients for several days after hospitalization, its detection in the serum, urine, and stool samples was intermittent. Since the virus could not be isolated from the SARS-COV-2-positive samples, the risk of viral transmission via stool and urine is expected to be low.
This article proposes a multimedia emotion-prediction approach using movie scripts and spectrograms with speech information. First, a variety of information is extracted from textual dialogues in ...scripts for emotion prediction. In addition, spectrograms transformed from speech information help to identify subtle representations of difficult-to-predict emotions from scripts. Accent helps predict emotions because it is an important means of expressing emotion states in speech. These are to analyze emotion words with a similar tendency on the basis of the emotion keywords in scripts and spectrograms. Emotion candidate keywords are extracted from text data using morphological analysis, and representative emotion keywords are extracted through Word2Vec_ARSP. Emotion keywords and speech data from the last part of the dialogue are extracted and converted into images. This multimedia information is used for the input layer in a convolutional neural network. In this paper, we propose a multi-modal method for more efficiently extracting and predicting emotions by mixing and learning integrated multimedia information through the character’s speech and background sounds, as well as dialogue that can directly express the emotional situation of the context. In order to improve the accuracy of emotion prediction using multimedia information in movies, we propose a system with a CNN for learning, testing, and prediction using a multi-modal method. The proposed multi-modal system compensates for unpredictable emotions from certain parts of the text through the spectrogram. The prediction accuracy is improved by 20.9% and 6.7%, compared to using only text information and only voice information, respectively.
Protection of endothelial integrity has been recognized as a frontline approach to alleviating sepsis progression, yet no effective agent for preserving endothelial integrity is available. Using an ...unusual anti-angiopoietin 2 (ANG2) antibody, ABTAA (ANG2-binding and TIE2-activating antibody), we show that activation of the endothelial receptor TIE2 protects the vasculature from septic damage and provides survival benefit in three sepsis mouse models. Upon binding to ANG2, ABTAA triggers clustering of ANG2, assembling an ABTAA/ANG2 complex that can subsequently bind and activate TIE2. Compared with a conventional ANG2-blocking antibody, ABTAA was highly effective in augmenting survival from sepsis by strengthening the endothelial glycocalyx, reducing cytokine storms, vascular leakage, and rarefaction, and mitigating organ damage. Together, our data advance the role of TIE2 activation in ameliorating sepsis progression and open a potential therapeutic avenue for sepsis to address the lack of sepsis-specific treatment.
This letter introduces the impact of behind-the-meter generation (BTMG) trip on primary frequency response through recent operational experience in Korea, and examines whether this impact can be ...appropriately modeled in power system analysis. The most influential parameter for properly modeling BTMG trip is discussed in the case studies, demonstrating that simulation-based studies can reproduce the interesting observation of instantaneous load increase (i.e., the impact of BTMG trip). The outcome of this letter highlights the necessity for modeling BTMG trip in frequency stability analysis, especially for power systems with high penetration of BTMG.
Satellite-based vegetation monitoring provides important insights regarding spatiotemporal variations in vegetation growth from a regional to continental scale. Most current vegetation monitoring ...methodologies rely on spectral vegetation indices (VIs) observed by polar-orbiting satellites, which provide one or a few observations per day. This study proposes a new methodology based on diurnal changes in land surface temperatures (LSTs) using Japan's geostationary satellite, Himawari-8/Advanced Himawari Imager (AHI). AHI thermal infrared observation provides LSTs at 10-min frequencies and ∼ 2 km spatial resolution. The DTC parameters that summarize the diurnal cycle waveform were obtained by fitting a diurnal temperature cycle (DTC) model to the time-series LST information for each day. To clarify the applicability of DTC parameters in detecting vegetation drying under humid climates, DTC parameters from in situ LSTs observed at vegetation sites, as well as those from Himawari-8 LSTs, were evaluated for East Asia. Utilizing the record-breaking heat wave that occurred in East Asia in 2018 as a case study, the anomalies of DTC parameters from the Himawari-8 LSTs were compared with the drying signals indicated by VIs, latent heat fluxes (LE), and surface soil moisture (SM). The results of site-based and satellite-based analyses revealed that DTR (diurnal temperature range) correlates with the evaporative fraction (EF) and SM, whereas Tmax (daily maximum LST) correlates with LE and VIs. Regarding other temperature-related parameters, T0 (LST around sunrise), Ta (temperature rise during daytime), and δT (temperature fall during nighttime) are unstable in quantification by DTC model. Moreover, time-related parameters, such as tm (time reaching Tmax), are more sensitive to topographic slope and geometric conditions than surface thermal properties at humid sites in East Asia, although they correlate with EF and SM at a semi-arid site in Australia. Additionally, the spatial distribution of the DTR anomaly during the 2018 heat wave corresponds with the drying signals indicated as negative SM anomalies. Regions with large positive anomalies in Tmax and DTR correspond to area with visible damage to vegetation, as indicated by negative VI anomalies. Hence, combined Tmax and DTR potentially detects vegetation drying indetectable by VIs, thereby providing earlier and more detailed vegetation monitoring in both humid and semi-arid climates.
•Himawari-8 satellite was used to measure diurnal changes in land surface temperature.•Anomalies in diurnal changes correlated with decreases in surface soil moisture.•Himawari-8 diurnal temperature range indicates drying/heat stress in plants.•This monitoring strategy may be used for drying detection even in humid climates.
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