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Background: Diabetes is a major risk factor for the development of dementia, which has been proven to be associated with systemic inflammation. Acute pancreatitis, also a local and systemic inflammatory disease, is the most common gastrointestinal disease requiring acute hospitalization. Objective: The effect of acute pancreatitis on dementia was investigated in type 2 diabetic patients. Methods: Data was collected from the Korean National Health Insurance Service. The study sample included type 2 diabetes patients who received general health examination from 2009 to 2012. Cox proportional hazard regression analysis was used to evaluate the association between acute pancreatitis and dementia with adjustment of confounders. Stratified subgroup analysis by age, sex, smoking, alcohol consumption, hypertension, dyslipidemia, and body mass index was conducted. Results: Among the 2,328,671 participants in total, 4,463 patients had a history of acute pancreatitis before the health examination. During a median follow-up of 8.1 (IQR, 6.7–9.0) years, 194,023 participants (8.3%) developed all-cause dementia. Previous history of acute pancreatitis was a significant risk factor for dementia after adjustment of confounding variables (HR 1.39 [95% CI 1.26–1.53]). In the subgroup analysis, patient characteristics such as age under 65 years, male, current smoker, and alcohol consumption were significant risk factors for dementia in patients with a history of acute pancreatitis. Conclusion: The history of acute pancreatitis was associated with the development of dementia in patients with diabetes. Because the risk of dementia increases with alcohol consumption and smoking in diabetic patients with history of acute pancreatitis, abstinence from alcohol and smoking should be recommended.

PurposeThis study was to investigate the frequency of mismatch repair deficiency/high microsatellite instability (MMRd/MSI-H) in gynecologic malignancies and the efficacy of immune checkpoint inhibitors (ICIs) in patients with recurrent gynecologic cancers according to MMR/MSI status.Materials and MethodsWe conducted a multi-center retrospective review on the patients who were diagnosed with gynecologic cancers between 2015 and 2020. Their clinicopathologic information, results of immunohistochemistry staining for MLH1/MSH2/MSH6/PMS2 and MSI analysis, tumor response to treatment with ICIs were investigated.ResultsAmong 1,093 patients included in the analysis, MMRd/MSI-H was most frequent in endometrial/uterine cancers (34.8%, 164/471), followed by ovarian, tubal, and peritoneal cancers (12.8%, 54/422) and cervical cancer (11.3%, 21/186). When assessed by histology without regard for cancer types, the frequency of MMRd/MSI-H was 11.0% (38/345) in high-grade serous adenocarcinoma, 38.6% (117/303) in endometrioid adenocarcinoma, and 30.2% (16/53) in carcinosarcoma. A total of 114 patients were treated with ICIs at least once. The objective response rate (ORR) was 21.6% (8/37) in cervical cancer, 4.7% (2/43) in ovarian cancer, and 25.8% (8/31) in endometrial/uterine cancers. Univariate regression analysis identified MMRd/MSI-H as the only significant factor associated with the ORR (28.9% [11/38] vs. 11.8% [9/76]; odds ratio, 3.033; 95% confidence interval, 1.129–8.144; p=0.028).ConclusionThe frequency of MMRd/MSI-H is moderate to high in gynecologic cancers in the Korean population. MMRd/MSI-H could be effective predictive biomarkers in gynecologic cancers of any type.

Low-dose radiation therapy (LDRT) can suppress intractable inflammation, such as that in rheumatoid arthritis, and is used for treating more than 10,000 rheumatoid arthritis patients annually in Europe. Several recent clinical trials have reported that LDRT can effectively reduce the severity of coronavirus disease (COVID-19) and other cases of viral pneumonia. However, the therapeutic mechanism of LDRT remains unelucidated. Therefore, in the current study, we aimed to investigate the molecular mechanism underlying immunological alterations in influenza pneumonia after LDRT. Mice were irradiated to the whole lung 1 day post-infection. The changes in levels of inflammatory mediators (cytokines and chemokines) and immune cell populations in the bronchoalveolar lavage (BALF), lungs, and serum were examined. LDRT-treated mice displayed markedly increased survival rates and reduced lung edema and airway and vascular inflammation in the lung; however, the viral titers in the lungs were unaffected. Levels of primary inflammatory cytokines were reduced after LDRT, and transforming growth factor-β (TGF-β) levels increased significantly on day 1 following LDRT. Levels of chemokines increased from day 3 following LDRT. Additionally, M2 macrophage polarization or recruitment was increased following LDRT. We found that LDRT-induced TGF-β reduced the levels of cytokines and polarized M2 cells and blocked immune cell infiltration, including neutrophils, in BALF. LDRT-induced early TGF-β production was shown to be a key regulator involved in broad-spectrum anti-inflammatory activity in virus-infected lungs. Therefore, LDRT or TGF-β may be an alternative therapy for viral pneumonia.

In this study, basic research was conducted regarding the era of autonomous vessels and artificial intelligence (deep learning, big data, etc.). When a vessel is navigating autonomously, it must determine the optimal route by itself and accurately follow the designated route using route-following control technology. First, the optimal route should be generated in a manner that ensures safety and reduces fuel consumption by the vessel. To satisfy safety requirements, sea depth, under-keel clearance, and navigation charts are used; algorithms capable of determining and shortening the distance of travel and removing unnecessary waypoints are used to satisfy the requirements for reducing fuel consumption. In this study, a reinforcement-learning algorithm-based machine learning technique was used to generate an optimal route while satisfying these two sets of requirements. Second, when an optimal route is generated, the vessel must have a route-following controller that can accurately follow the set route without deviation. To accurately follow the route, a velocity-type fuzzy proportional–integral–derivative (PID) controller was established. This controller can prevent deviation from the route because overshoot rarely occurs, compared with a proportional derivative (PD) controller. Additionally, because the change in rudder angle is smooth, energy loss by the vessel can be reduced. Here, a method for determining the presence of environmental disturbance using the characteristics of the Kalman filter innovation process and estimating environmental disturbance with a fuzzy disturbance estimator is presented, which allows the route to be accurately maintained even under conditions involving environmental disturbance. The proposed approach can automatically set the vessel’s optimal route and accurately follow the route without human intervention, which is useful and can contribute to maritime safety and efficiency improvement.

The recent seismic events that occurred in South Korea have increased the interest in the re-evaluation of the seismic capacity of nuclear power plant (NPP) equipment, which is often conservatively estimated. To date, various approaches—including the Bayesian method proposed by the United States (US) Electric Power Research Institute —have been developed to quantify the seismic capacity of NPP equipment. Among these, the Bayesian approach has advantages in accounting for both prior knowledge and new information to update the probabilistic distribution of seismic capacity. However, data availability and region-specific issues exist in applying this Bayesian approach to Korean NPP equipment. Therefore, this paper proposes to construct an earthquake experience database by combining available earthquake records at Korean NPP sites and the general location of equipment within NPPs. Also, for the better representation of the seismic demand of Korean earthquake datasets, which have distinct seismic characteristics from those of the US at a high-frequency range, a broadband frequency range optimization is suggested. The proposed data construction and seismic demand optimization method for seismic capacity re-evaluation are demonstrated and tested on a 480 V motor control center of a South Korea NPP.

Phosphorylation state-dependent interactions of the phosphoenolpyruvate (PEP):carbohydrate phosphotransferase system (PTS) components with transcription factors play a key role in carbon catabolite repression (CCR) by glucose in bacteria. Glucose inhibits the PTS-dependent transport of fructose and is preferred over fructose in Vibrio cholerae, but the mechanism is unknown. We have recently shown that, contrary to Escherichia coli, the fructose-dependent transcriptional regulator FruR acts as an activator of the fru operon in V. cholerae and binding of the FruR–fructose 1-phosphate (F1P) complex to an operator facilitates RNA polymerase (RNAP) binding to the fru promoter. Here we show that, in the presence of glucose, dephosphorylated HPr, a general PTS component, binds to FruR. Whereas HPr does not affect DNA-binding affinity of FruR, regardless of the presence of F1P, it prevents the FruR–F1P complex from facilitating the binding of RNAP to the fru promoter. Structural and biochemical analyses of the FruR–HPr complex identify key residues responsible for the V. cholerae-specific FruR–HPr interaction not observed in E. coli. Finally, we reveal how the dephosphorylated HPr interacts with FruR in V. cholerae, whereas the phosphorylated HPr binds to CcpA, which is a global regulator of CCR in Bacillus subtilis and shows structural similarity to FruR.

Hardware-based neural networks (NNs) can provide a significant breakthrough in artificial intelligence applications due to their ability to extract features from unstructured data and learn from them. However, realizing complex NN models remains challenging because different tasks, such as feature extraction and classification, should be performed at different memory elements and arrays. This further increases the required number of memory arrays and chip size. Here, we propose a three-dimensional ferroelectric NAND (3D FeNAND) array for the area-efficient hardware implementation of NNs. Vector-matrix multiplication is successfully demonstrated using the integrated 3D FeNAND arrays, and excellent pattern classification is achieved. By allocating each array of vertical layers in 3D FeNAND as the hidden layer of NN, each layer can be used to perform different tasks, and the classification of color-mixed patterns is achieved. This work provides a practical strategy to realize high-performance and highly efficient NN systems by stacking computation components vertically.

The association between acute pancreatitis (AP) and gastrointestinal cancers in diabetic patients is currently not well understood. The study aim was to investigate the association between AP and gastrointestinal cancers in diabetic patients. Data from the Korean National Health Insurance Service database were analyzed. Participants with diabetes who underwent a health examination between 2009 and 2012 were followed up till December 2018. The primary outcome was the occurrence of gastrointestinal cancer. A total of 2,263,184 patients were included in the final analysis. Patients with a history of AP (n = 2390) were found to have a significantly higher risk of gastrointestinal cancer, except for esophageal cancer, as follows: gastric cancer (aHR = 1.637, 95% CI: 1.323–2.025), colorectal cancer (aHR = 2.183, 95% CI: 1.899–2.51), liver cancer (aHR = 2.216, 95% CI: 1.874–2.621), pancreatic cancer (aHR = 4.558, 95% CI: 4.078–5.095), bile duct cancer (aHR = 3.996, 95% CI: 3.091–5.269), and gallbladder cancer (aHR = 2.445, 95% CI: 1.459–4.099). The history of AP is associated with the increased risk of gastrointestinal cancer in diabetic patients. It is necessary to investigate the history of AP and more actively recommend screening for gastrointestinal cancers in such patients.

The 4-α-glucanotransferase (4-α-GTase or amylomaltase) is an essential enzyme in maltodextrin metabolism. Generally, most bacterial 4-α-GTase is classified into glycoside hydrolase (GH) family 77. However, hyperthermophiles have unique 4-α-GTases belonging to GH family 57. These enzymes are the main amylolytic protein in hyperthermophiles, but their mode of action in maltooligosaccharide utilization is poorly understood. In the present study, we investigated the catalytic properties of 4-α-GTase from the hyperthermophile Pyrococcus sp. ST04 (PSGT) in the presence of maltooligosaccharides of various lengths. Unlike 4-α-GTases in GH family 77, GH family 57 PSGT produced maltotriose in the early stage of reaction and preferred maltose and maltotriose over glucose as the acceptor. The kinetic analysis showed that maltotriose had the lowest KM value, which increased amylose degradation activity by 18.3-fold. Structural models of PSGT based on molecular dynamic simulation revealed two aromatic amino acids interacting with the substrate at the +2 and +3 binding sites, and the mutational study demonstrated they play a critical role in maltotriose binding. These results clarify the mode of action in carbohydrate utilization and explain acceptor binding mechanism of GH57 family 4-α-GTases in hyperthermophilic archaea.