Central role of Prominin-1 in lipid rafts during liver regeneration.

Prominin-1, a lipid raft protein, is required for maintaining cancer stem cell properties in hepatocarcinoma cell lines, but its physiological roles in the liver have not been well studied. Here, we investigate the role of Prominin-1 in lipid rafts during liver regeneration and show that expression of Prominin-1 increases after 2/3 partial hepatectomy or CCl4 injection. Hepatocyte proliferation and liver regeneration are attenuated in liver-specific Prominin-1 knockout mice compared to wild-type mice. Detailed mechanistic studies reveal that Prominin-1 interacts with the interleukin-6 signal transducer glycoprotein 130, confining it to lipid rafts so that STAT3 signaling by IL-6 is effectively activated. The overexpression of the glycosylphosphatidylinsositol-anchored first extracellular domain of Prominin-1, which is the domain that binds to GP130, rescued the proliferation of hepatocytes and liver regeneration in liver-specific Prominin-1 knockout mice. In summary, Prominin-1 is upregulated in hepatocytes during liver regeneration where it recruits GP130 into lipid rafts and activates the IL6-GP130-STAT3 axis, suggesting that Prominin-1 might be a promising target for therapeutic applications in liver transplantation.

Hepatocyte-specific Prominin-1 protects against liver injury-induced fibrosis by stabilizing SMAD7.

Prominin-1 (PROM1), also known as CD133, is expressed in hepatic progenitor cells (HPCs) and cholangiocytes of the fibrotic liver. In this study, we show that PROM1 is upregulated in the plasma membrane of fibrotic hepatocytes. Hepatocellular expression of PROM1 was also demonstrated in mice (Prom1CreER; R26TdTom) in which cells expressed TdTom under control of the Prom1 promoter. To understand the role of hepatocellular PROM1 in liver fibrosis, global and liver-specific Prom1-deficient mice were analyzed after bile duct ligation (BDL). BDL-induced liver fibrosis was aggravated with increased phosphorylation of SMAD2/3 and decreased levels of SMAD7 by global or liver-specific Prom1 deficiency but not by cholangiocyte-specific Prom1 deficiency. Indeed, PROM1 prevented SMURF2-induced SMAD7 ubiquitination and degradation by interfering with the molecular association of SMAD7 with SMURF2. We also demonstrated that hepatocyte-specific overexpression of SMAD7 ameliorated BDL-induced liver fibrosis in liver-specific Prom1-deficient mice. Thus, we conclude that PROM1 is necessary for the negative regulation of TGFß signaling during liver fibrosis.

Deep Learning Algorithm to Predict Need for Critical Care in Pediatric Emergency Departments.

BACKGROUND AND OBJECTIVES: Emergency department (ED) overcrowding is a national crisis in which pediatric patients are often prioritized at lower levels. Because the prediction of prognosis for pediatric patients is important but difficult, we developed and validated a deep learning algorithm to predict the need for critical care in pediatric EDs. METHODS: We conducted a retrospective observation cohort study using data from the Korean National Emergency Department Information System, which collected data in real time from 151 EDs. The study subjects were pediatric patients who visited EDs from 2014 to 2016. The data were divided by date into derivation and test data. The primary end point was critical care, and the secondary endpoint was hospitalization. We used age, sex, chief complaint, symptom onset to arrival time, arrival mode, trauma, and vital signs as predicted variables. RESULTS: The study subjects consisted of 2,937,078 pediatric patients of which 18,253 were critical care and 375,078 were hospitalizations. For critical care, the area under the receiver operating characteristics curve of the deep learning algorithm was 0.908 (95% confidence interval, 0.903-0.910). This result significantly outperformed that of the pediatric early warning score (0.812 [0.803-0.819]), conventional triage and acuity system (0.782 [0.773-0.790]), random forest (0.881 [0.874-0.890]), and logistic regression (0.851 [0.844-0.858]). For hospitalization, the deep-learning algorithm (0.782 [0.780-0.783]) significantly outperformed the other methods. CONCLUSIONS: The deep learning algorithm predicted the critical care and hospitalization of pediatric ED patients more accurately than the conventional early warning score, triage tool, and machine learning methods.

Selective Growth and Contact Gap-Fill of Low Resistivity Si via Microwave Plasma-Enhanced CVD.

Low resistivity polycrystalline Si could be selectively grown in the deep (~200 nm) and narrow patterns (~20 nm) of 20 nm pitch design rule DRAM (Dynamic Random Access Memory) by microwave plasma-enhanced chemical vapor deposition (MW-CVD). We were able to achieve the high phosphorus (CVD gap-fill in a large electrical contact area which does is affected by line pitch size) doping concentration (>2.5 × 1021 cm-3) and, thus, a low resistivity by adjusting source gas (SiH4, H2, PH3) decomposition through MW-CVD with a showerhead controlling the decomposition of source gases by using two different gas injection paths. In this study, a selective growth mechanism was applied by using the deposition/etch cyclic process to achieve the bottom-up process in the L-shaped contact, using H2 plasma that simultaneously promoted the deposition and the etch processes. Additionally, the cyclic selective growth technique was set up by controlling the SiH4 flow rate. The bottom-up process resulted in a uniform doping distribution, as well as an excellent filling capacity without seam and center void formation. Thus, low contact resistivity and higher transistor on-current could be achieved at a high and uniform phosphorus (P)-concentration. Compared to the conventional thermal, this method is expected to be a strong candidate for the complicated deep and narrow contact process.

Thermomagnetic Convection of Ferrofluid in an Enclosure Channel with an Internal Magnetic Field.

Ferrofluid is a colloidal liquid in which magnetic nanoparticles such as Fe3O4 are dispersed in a nonconductive solution, and the average diameter of the nanoparticles is 10 nm. When a magnetic field is applied, the ferrofluid generates magnetization, which changes the physical properties of the fluid itself. In this study, characteristics of the thermomagnetic convection of ferrofluid (Fe3O4) by the permanent magnet in the enclosure channel were studied. To effectively mix the ferrofluid (Fe3O4) and disturb the boundary layer, the heat dissipation of the heat source depending on the strength of the magnetic field and the shape of the enclosure channel was numerically studied. In particular, four different enclosure channels were considered: Square, separated square, circle, and separated circle. The hot temperature was set at the center of the enclosure channel. The ferrofluid was affected by the permanent magnet in the center of the channel. The magnetic field strength in the region close to the permanent magnet was enhanced. The magnetophoretic (MAP) force increased with increasing magnetic field strength. The MAP force generated a vortex in the enclosure channel, disturbing the thermal boundary. The vortex occurs differently, depending on the shape of the enclosure channel and affects the thermomagnetic convection. The temperature and velocity fields for thermomagnetic convection were described and the convective heat flux was calculated and compared. Results show that when the magnetic field strength was 4000 kA/m and the shape of the enclosure channel was a circle, the maximum convective heat flux of 4.86 × 105 W/m2 was obtained.

In situ analysis of chemical components induced by steaming between fresh ginseng, steamed ginseng, and red ginseng.

BACKGROUND: The chemical constituents of Panax ginseng are changed by processing methods such as steaming or sun drying. In the present study, the chemical change of Panax ginseng induced by steaming was monitored in situ. METHODS: Samples were separated from the same ginseng root by incision during the steaming process, for in situ monitoring. Sampling was sequentially performed in three stages; FG (fresh ginseng) → SG (steamed ginseng) → RG (red ginseng) and 60 samples were prepared and freeze dried. The samples were then analyzed to determine 43 constituents among three stages of P. ginseng. RESULTS: The results showed that six malonyl-ginsenoside (Rg1, Rb1, Rb3, Rc, Rd, Rb2) and 15 amino acids were decreased in concentration during the steaming process. In contrast, ginsenoside-Rh1, 20(S)-Rg2, 20(S, R)-Rg3 and Maillard reaction product such as AF (arginine-fructose), AFG (arginine-fructose-glucose), and maltol were newly generated or their concentrations were increased. CONCLUSION: This study elucidates the dynamic changes in the chemical components of P. ginseng when the steaming process was induced. These results are thought to be helpful for quality control and standardization of herbal drugs using P. ginseng and they also provide a scientific basis for pharmacological research of processed ginseng (Red ginseng).

Simultaneous determination of 30 ginsenosides in Panax ginseng preparations using ultra performance liquid chromatography.

A quick and simple method for simultaneous determination of the 30 ginsenosides (ginsenoside Ro, Rb1, Rb2, Rc, Rd, Re, Rf, Rg1, 20(S)-Rg2, 20(R)-Rg2, 20(S)-Rg3, 20(R)-Rg3, 20(S)-Rh1, 20(S)-Rh2, 20(R)-Rh2, F1, F2, F4, Ra1, Rg6, Rh4, Rk3, Rg5, Rk1, Rb3, Rk2, Rh3, compound Y, compound K, and notoginsenoside R1) in Panax ginseng preparations was developed and validated by an ultra performance liquid chromatography photo diode array detector. The separation of the 30 ginsenosides was efficiently undertaken on the Acquity BEH C-18 column with gradient elution with phosphoric acids. Especially the chromatogram of the ginsenoside Ro was dramatically enhanced by adding phosphoric acid. Under optimized conditions, the detection limits were 0.4 to 1.7 mg/L and the calibration curves of the peak areas for the 30 ginsenosides were linear over three orders of magnitude with a correlation coefficients greater than 0.999. The accuracy of the method was tested by a recovery measurement of the spiked samples which yielded good results of 89% to 118%. From these overall results, the proposed method may be helpful in the development and quality of P. ginseng preparations because of its wide range of applications due to the simultaneous analysis of many kinds of ginsenosides.