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This study compares the bias correction techniques of empirical quantile mapping (QM) and the Long Short-Term Memory (LSTM) machine learning model for summertime daily rainfall simulation focusing on precipitation-dependent bias and temporal variation. Numerical experiments using Weather Research and Forecasting (WRF) were conducted over South Korea with lateral boundary conditions of ERA5 reanalysis data. For the spatial distribution of mean summertime rainfall, the bias-uncorrected WRF simulation (WRF_RAW) showed dry bias for most of the region of South Korea. The WRF results corrected by QM and LSTM (WRF_QM and WRF_LSTM, respectively) were improved for the mean summer rainfall simulation with the root mean square error values of 0.17 and 0.69, respectively, which were smaller than those of the WRF_RAW (1.10). Although the WRF_QM performed better than the WRF_LSTM in terms of the summertime mean and monthly precipitation, the WRF_LSTM presented a closer interannual rainfall variation to the observation than the WRF_QM. The coefficient of determination for calendar-day mean rainfall was the highest in the following order: the WRF_LSTM (0.451), WRF_QM (0.230), and WRF_RAW (0.201). However, the WRF_LSTM had a limitation in reproducing extreme rainfall exceeding 50 mm/day due to the few cases of extreme precipitation in training data. Nevertheless, the WRF_LSTM better simulated the observed light-to-moderate precipitation (10–50 mm/day) than the others. [ABSTRACT FROM AUTHOR]

Simple Summary: This study describes a new machine-learning-based 28-day mortality prediction model in adult cancer patients admitted to the intensive care unit (ICU). A total of 6900 patients in three patient cohorts were used for the development, internal validation, and external validation, respectively, leading to the generation of a reliable model with high sensitivity and specificity. The CanICU uses nine variables that can be easily obtained in a practical ICU, with the potential benefit of critical care and avoiding unnecessary suffering. Furthermore, this is the largest patient cohort for developing a cancer patient-specific model. CanICU offers improved performance for predicting short- and long-term mortality in critically ill cancer patients admitted to the ICU. CanICU can help physicians determine how to allocate ICU care for patients with cancer according to objective mortality risk. Background: Although cancer patients are increasingly admitted to the intensive care unit (ICU) for cancer- or treatment-related complications, improved mortality prediction remains a big challenge. This study describes a new ML-based mortality prediction model for critically ill cancer patients admitted to ICU. Patients and Methods: We developed CanICU, a machine learning-based 28-day mortality prediction model for adult cancer patients admitted to ICU from Medical Information Mart for Intensive Care (MIMIC) database in the USA (n = 766), Yonsei Cancer Center (YCC, n = 3571), and Samsung Medical Center in Korea (SMC, n = 2563) from 2 January 2008 to 31 December 2017. The accuracy of CanICU was measured using sensitivity, specificity, and area under the receiver operating curve (AUROC). Results: A total of 6900 patients were included, with a 28-day mortality of 10.2%/12.7%/36.6% and a 1-year mortality of 30.0%/36.6%/58.5% in the YCC, SMC, and MIMIC-III cohort. Nine clinical and laboratory factors were used to construct the classifier using a random forest machine-learning algorithm. CanICU had 96% sensitivity/73% specificity with the area under the receiver operating characteristic (AUROC) of 0.94 for 28-day, showing better performance than current prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE) or Sequential Organ Failure Assessment (SOFA) score. Application of CanICU in two external data sets across the countries yielded 79–89% sensitivity, 58–59% specificity, and 0.75–0.78 AUROC for 28-day mortality. The CanICU score was also correlated with one-year mortality with 88–93% specificity. Conclusion: CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients. [ABSTRACT FROM AUTHOR]

The predictability of the wintertime Western Pacific (WP) pattern is evaluated based on seasonal predictions from five models participating in the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) multi-model ensemble (MME) for the winters from 1982/1983 to 2021/2022. The temporal correlation coefficient (TCC) between the observed and MME-predicted WP indices was 0.61 (0.37–0.54 for individual models) for the entire series. However, when only three Super El Niño (SEN) years (Niño3.4 ≥ 2.0) out of the 40-year series were excluded, the TCC dropped down to 0.54 (0.27–0.42). During the SEN years, the WP was strongly affected by the SEN-excited anomalies via the PNA. In observations from non-SEN years, the WP pattern was strongly related to the dipole pattern in Northwestern Pacific SST (TCC = 0.8), for the description of which we suggested a Northwestern Pacific (NWP) index, and it was significantly weakly related to the ENSO and IOD, whereas in the model simulations, the main role was played by the ENSO (TCC = 0.6). The NWP index was well predictable in MME (TCC = 0.73) and individual models (0.56–0.71). We showed that the prediction of the WP index polarity is reliable when both predicted WP and NWP anomalies are significant and indicate the same WP sign that has implications for the seasonal forecasting. [ABSTRACT FROM AUTHOR]

Simple Summary: The canonical mutations in gastrointestinal stromal tumors (GISTs) are typically activating mutations in KIT and platelet-derived growth factor receptor alpha (PDGFRA). Imatinib, the treatment of choice for GISTs, shows a lower response in KIT/PDGFRA wild-type GISTs. Neurotrophic tyrosine receptor kinase (NTRK) fusion, which can be treated with an NTRK target agent, has been reported in KIT/PDGFRA wild-type GISTs, and, therefore, the Yonsei Cancer Center analyzed NTRK fusion incidence in KIT/PDGFRA wild-type GISTs. At the Yonsei Cancer Center, NTRK fusion was confirmed in 16% of cases. Confirmation of NTRK fusion in KIT/PDGFRA wild-type GISTs provides important information for improving therapeutic outcomes. NTRK fusion was confirmed in 16% of KIT/PDGFRA wild-type GIST cases at the Yonsei Cancer Center. Confirmation of NTRK fusion in KIT/PDGFRA wild-type GISTs will improve therapeutic outcomes. The canonical mutations in gastrointestinal stromal tumors (GISTs) are typically activating mutations in KIT and platelet-derived growth factor receptor alpha (PDGFRA). GISTs with non-canonical mutations are a heterogeneous group. Here, we examined tropomyosin-related kinase (TRK) fusion in GIST cases without KIT/PDGFRA mutations (KIT/PDGFRA wild-type (WT) GISTs). We retrospectively analyzed patients who were diagnosed with GISTs at the Yonsei Cancer Center, Severance Hospital, between January 1998 and December 2016. Thirty-one patients with KIT/PDGFRA WT GISTs were included in the analysis. TRK expression in tumor samples was assessed by pan-TRK immunohistochemistry (IHC), and the neurotrophic tyrosine receptor kinase (NTRK: the gene encoding TRK) rearrangement was analyzed by fluorescence in situ hybridization (FISH). IHC analyses revealed that five cases in this cohort exhibited a weak to moderate TRK expression. NTRK1 fusions were detected in three tumor samples, and two samples harbored NTRK3 fusions. The remaining 26 samples did not harbor NTRK fusions. Two types of NTRK fusions were detected, and the overall NTRK fusion frequency in KIT/PDGFRA WT GIST cases was 16% (5/31). Our data provide insights into the molecular alterations underpinning KIT/PDGFRA WT GISTs. More effort should be devoted to improve methods to identify this distinct disease subtype within the KIT/PDGFRA WT GIST group. [ABSTRACT FROM AUTHOR]

The changes of agro-climate and heat extremes, and their impact on rice cultivation are assessed over South Korea in context of 2 and 3 °C global warming levels (GWL) compared to pre-industrial levels, with ensemble regional climate model projection produced under the Coordinated Regional Climate Downscaling Experiment–East Asia (CORDEX-EA) phase 2 protocols. It is found that the mean temperature increase under global warming has not only positive effects such as the extension of vegetable and crop periods and the widening of the cultivatable regions but also negative effects due to the shortening of the reproductive growth period. On the other hand, extreme heat changes in the future clearly show a negative effect on rice cultivation via the increase of hot days during heat-sensitive stages (27.16% under 2 °C GWL, 54.59% under 3 °C GWL) among rice phenology which determines the rice yield in tandem with rice flowering, ripening, and sterility problems. The major type of heat extreme is dominated by nationwide warm anomalies covering entire S. Korea, and the proportion of this type is projected to increase from 35.8% to 49.5% (57.4%) under 2 °C (3 °C) GWL in association with the thermal expansion of atmosphere which links to the favorable environment for occurring barotropic anti-cyclonic system. [ABSTRACT FROM AUTHOR]

We aimed to assess the survival benefits of primary tumor resection (PTR) followed by chemotherapy in patients with asymptomatic stage IV colorectal cancer with asymptomatic, synchronous, unresectable metastases compared to those of upfront chemotherapy alone. This was an open-label, prospective, randomized controlled trial (ClnicalTrials.gov Identifier: NCT01978249). From May 2013 to April 2016, 48 patients (PTR, n = 26; upfront chemotherapy, n = 22) diagnosed with asymptomatic colorectal cancer with unresectable metastases in 12 tertiary hospitals were randomized (1:1). The primary endpoint was two-year overall survival. The secondary endpoints were primary tumor-related complications, PTR-related complications, and rate of conversion to resectable status. The two-year cancer-specific survival was significantly higher in the PTR group than in the upfront chemotherapy group (72.3% vs. 47.1%; p = 0.049). However, the two-year overall survival rate was not significantly different between the PTR and upfront chemotherapy groups (69.5% vs. 44.8%, p = 0.058). The primary tumor-related complication rate was 22.7%. The PTR-related complication rate was 19.2%, with a major complication rate of 3.8%. The rates of conversion to resectable status were 15.3% and 18.2% in the PTR and upfront chemotherapy groups. While PTR followed by chemotherapy resulted in better two-year cancer-specific survival than upfront chemotherapy, the improvement in the two-year overall survival was not significant. [ABSTRACT FROM AUTHOR]

Reanalysis data are known to have relatively large uncertainties in the polar region than at lower latitudes. In this study, we used a single sea-ice model (Los Alamos' CICE5) and three sets of reanalysis data to quantify the sensitivities of simulated Arctic sea ice area and volume to perturbed atmospheric forcings. The simulated sea ice area and thickness thus volume were clearly sensitive to the selection of atmospheric reanalysis data. Among the forcing variables, changes in radiative and sensible/latent heat fluxes caused significant amounts of sensitivities. Differences in sea-ice concentration and thickness were primarily caused by differences in downward shortwave and longwave radiations. 2-m air temperature also has a significant influence on year-to-year variability of the sea ice volume. Differences in precipitation affected the sea ice volume by causing changes in the insulation effect of snow-cover on sea ice. The diversity of sea ice extent and thickness responses due to uncertainties in atmospheric variables highlights the need to carefully evaluate reanalysis data over the Arctic region. [ABSTRACT FROM AUTHOR]

Paclitaxel (PTX) is commonly used to treat urothelial carcinoma (UC) after platinum-based chemotherapy has failed. However, single-agent taxane therapy is not sufficient to inhibit tumor progression and drug resistance in advanced UC. Epithelial-to-mesenchymal transition (EMT) induced by fibroblast growth factor receptor (FGFR)1 signaling has been proposed as a mechanism of PTX resistance, but it is unclear whether this can be overcome by FGFR1 inhibition. The present study investigated whether FGFR1 overexpression contributes to PTX resistance and whether FGFR inhibition can enhance PTX efficacy in UC. The effects of PTX combined with the FGFR inhibitor BGJ398 were evaluated in UC cell lines by flow cytometry; Western blot analysis; cell viability, migration, and colony forming assays; and RNA interference. PTX+BGJ398 induced cell cycle arrest and apoptosis in UC cells with mesenchymal characteristics was accompanied by downregulation of cyclin D1 protein and upregulation of gamma-histone 2A family member X and cleaved poly(ADP-ribose) polymerase. Additionally, PTX+BGJ398 synergistically suppressed UC cell migration and colony formation via regulation of EMT-associated factors, while FGFR1 knockdown enhanced the antitumor effect of PTX. These findings provide a basis for development of effective strategies for overcoming PTX resistance in UC through inhibition of FGFR1 signaling. [ABSTRACT FROM AUTHOR]