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The impact of capsule imperfections is one of the challenges in achieving reproducible, high-gain ignition of inertial confinement fusion (ICF). The nonuniformities of capsule imperfections, which create instability seeds during the shock propagation, may cause significant performance degradation. A systematic study of the propagation of collisional shock wave in highly nonuniform plasmas is carried out using a hybrid fluid-PIC code, which enables the analysis of electromagnetic fields, ion mixing, and plasma viscosity self-consistently. During shock propagation, it interacts with multiple bubbles and significant material mixing in the nonuniform plasmas are observed. Consequently, the average viscosity of the post-shock plasma in the nonuniform case increases to $1\sim 2$ times that of the uniform case. These results provide a better understanding of the possible influence of capsule imperfections in ICF implosions.

The interaction and interpenetration of two counter-propagating plasma shocks are investigated via hybrid fluid-PIC (particle-in-cell) simulations. This study seeks to probe the kinetic effects and ion collisions on the structure of colliding plasma shocks in complex multi-ion-species plasma, in particular, the presence of the expansion of high- Z plasma bubbles against the low- Z filled gas inside an ICF hohlraum. The superposition of shock wave results in a wave-like electric field in the downstream region. The electric field can further reduce the kinetic energy of the incoming particles, and modulate the ion density profile. It finally generates a new downstream platform of high temperature and high density. However, on the hundred-ps time scale, cumulative ion collisions can still significantly alter the structure of the shock wave and the reflection of ions by the shock front. This study will help to improve the predictions of hohlraum plasma states and the understanding of the shock wave interactions.

Objective Publications on hidden blood loss (HBL) after posterior lumbar interbody fusion (PLIF) for lumbar spine stenosis syndrome (LSS) have been reported, but the modified HBL (mHBL) was different from HBL obtained by classical formula and there are few studies on lumbar spine hemorrhage with rheumatoid arthritis (RA). Therefore, the aim of our study is to respectively evaluate the importance of hidden blood loss (HBL) and modified HBL (mHBL) after posterior lumbar interbody fusion (PLIF) in patients diagnosed with LSS and RA, to explore the correlation between RA activity and HBL as well as mHBL. Methods A total of 61 patients (nine males and 52 females) diagnosed with LSS and RA who underwent PLIF were included. Data contained demographics, RA‐related parameters such as duration of RA, Steinbrocker classification (used to evaluated RA activity), the disease‐modifying anti‐rheumatic drugs (DMARDs), osteoporosis and total knee arthroplasty; operation and hemorrhage parameters. Then HBL and mHBL were calculated by Gross formula and modified formula, respectively. Subgroup analysis on HBL and mHBL was performed based on gender, age (≤60 years and ˃60 years), different number of surgical segments (single segment, double segment, and ≥3 segments), and taking DMARDs or not. ANOVA analysis was performed on HBL and mHBL in different surgery segment number and Steinbrocker classification of RA. Independent sample t‐test was used in comparison of gender and age, as well as in comparison between HBL and mHBL based on whether the patient took DMARDs or not. Furthermore, paired t‐test was used to compare the volume between HBL and mHBL. Results The mean age and duration of RA was 65.2 ± 9.3 years and 14.3 ± 10.7 years, respectively. There were 13 grade I cases, 34 grade II cases, and 14 grade III cases as assessed by Steinbrocker classification and the most common anti‐RA drugs were DMARDs (57.4%). The mean intraoperative bleeding, drainage, and blood loss in drainage (DBL) was 453.3 ± 377.8 mL, 489.1 ± 253.8 mL, and 304.6 ± 156.3 mL, respectively. There was no difference on HBL and mHBL in gender. HBL and mHBL was larger in patients over 60 years (P = 0.040 and P = 0.023). There were differences in intraoperative blood loss, drainage, and DBL based on different number of segments but not in HBL and mHBL, or on Steinbrocker classification. DBL was lower in DMARDs group than non‐drugged group (P = 0.03), while HBL and mHBL were both of no significance. The comparison of HBL and mHBL showed statistical difference (P

Objectives: The different etiology of HF has different prognostic risk factors. Prognosis assessment of ICM and NICM has important clinical value. This study is aimed to explore the predicting factors for ICM and NICM. Methods: 1082 HFrEF patients were retrospectively enrolled from Jan. 01, 2016 to Dec. 31, 2017. On Jan. 31, 2019, 873 patients were enrolled for analysis excluding incomplete, unfollowed, and unexplained data. The patients were divided into ischemic and non-ischemic group. The differences in clinical characteristics and long-term prognosis between the two groups were analyzed, and multivariate Cox analysis was used to predict the respective all-cause mortality, SCD and rehospitalization of CHF. Results: 873 patients aged 64(53,73) were divided into two groups: ICM (403, 46.16%) and NICM. At the end, 203 died (111 in ICM, 54.68%), of whom 87 had SCD (53 in ICM, 60.92%) and 269 had rehospitalization for HF(134 in ICM, 49.81%). Independent risk factors affecting all-cause mortality in ICM: DM, previous hospitalization of HF, age, eGFR, LVEF; for SCD: PVB, eGFR, Hb, revascularization; for readmission of HF: low T3 syndrome, PVB, DM, previous hospitalization of HF, eGFR. Otherwise; factors affecting all-cause mortality in NICM: NYHA III-IV, paroxysmal AF/AFL, previous hospitalization of HF, β-blocker; for SCD: low T3 syndrome, PVB, nitrates, sodium, β-blocker; for rehospitalization of HF: paroxysmal AF/AFL, previous admission of HF, LVEF. Conclusions: Both all-cause mortality and SCD in ICM is higher than that in NICM. Different etiologies of CHF have different risk factors affecting the prognosis.

Osteoarthritis (OA) is the most common joint disease type and is accompanied by varying degrees of functional limitation. Both hyaluronic acid (HA) joint injections and pain relievers are efficient treatments for early-stage osteoarthritis. However, for the decomposition by hyaluronidase and free radicals in the knee joint, HA injection treatment has limited effect time. The cerium oxide nanoparticles (CeO2) is a long time free radical scavenger. CeO2 combined with HA expected, may extend the HA decomposition time and have a positive effect on osteoarthritis therapy. In this study, CeO2 was successfully synthesized using the hydrothermal method with a particle size of about 120 nm, which possessed excellent dispersibility in the culture medium. The in vitro OA model was established by cell treated with H2O2 for 30 min. Our study found that the inhibition of chondrocyte proliferation dose-dependently increased with H2O2 concentration but was significantly decreased by supplementation of cerium oxide nanoparticles. COL2a1 and ACAN gene expression in chondrocytes was significantly decreased after H2O2 treatment; however, the tendency was changed after cerium oxide nanoparticles treatment, which suggested that damaged chondrocytes were protected against oxidative stress. These findings suggest that cerium oxide nanoparticles are potential therapeutic applications in the early stage of OA.

HepG2 cell death with magnetic hyperthermia (MHT) using hydroxyapatite nanoparticles (mHAPs) and alternating magnetic fields (AMF) was investigated in vitro. The mHAPs were synthesized as thermo-seeds by co-precipitation with the addition of Fe2+. The grain size of the HAPs and iron oxide magnetic were 39.1 and 19.5 nm and were calculated by the Scherrer formula. The HepG2 cells were cultured with mHAPs and exposed to an AMF for 30 min yielding maximum temperatures of 43 ± 0.5 °C. After heating, the cell viability was reduced by 50% relative to controls, lactate dehydrogenase (LDH) concentrations measured in media were three-fold greater than those measured in all control groups. Readouts of toxicity by live/dead staining were consistent with cell viability and LDH assay results. Measured reactive oxygen species (ROS) in cells exposed to MHT were two-fold greater than in control groups. Results of cDNA microarray and Western blotting revealed tantalizing evidence of ATM and GADD45 downregulation with possible MKK3/MKK6 and ATF-2 of p38 MAPK inhibition upon exposure to mHAPs and AMF combinations. These results suggest that the combination of mHAPs and AMF can increase intracellular concentrations of ROS to cause DNA damage, which leads to cell death that complement heat stress related biological effects. [ABSTRACT FROM AUTHOR]

Abstract Background Colon adenocarcinoma (COAD) patients who develop recurrence have poor prognosis. Our study aimed to establish effective prognosis prediction model based on competing endogenous RNAs (ceRNAs) for recurrence of COAD. Methods COAD expression profilings downloaded from The Cancer Genome Atlas (TCGA) were used as training dataset, and expression profilings of GSE29623 retrieved from Gene Expression Omnibus (GEO) were set as validation dataset. Differentially expressed RNAs (DERs) between non-recurrent and recurrent specimens in training dataset were screened, and optimum prognostic signature DERs were revealed to establish prognostic score (PS) model. Kaplan-Meier survival analysis was conducted for PS model, and GEO dataset was used for validation. Prognosis prediction efficiencies were evaluated by area under curve (AUC) and C-index. Meanwhile, ceRNA regulatory network was constructed by using signature mRNAs, lncRNAs and miRNAs. Results We identified 562 DERs including 42 lncRNAs, 36 miRNAs, and 484 mRNAs. PS prediction model, consisting of 17 optimum prognostic signature DERs, showed that high risk group had significantly poorer prognosis (5-year AUC = 0.951, C-index = 0.788), which also validated in GSE29623. Prognosis prediction model incorporating multi-RNAs with pathologic distant metastasis (M) and pathologic primary tumor (T) (5-year AUC = 0.969, C-index = 0.812) had better efficiency than clinical prognosis prediction model (5-year AUC = 0.712, C-index = 0.680). In the constructed ceRNA regulatory network, lncRNA NCBP2-AS1 could interact with hsa-miR-34c and hsa-miR-363, and lncRNA LINC00115 could interact with hsa-miR-363 and hsa-miR-4709. SIX4, GRAP, NKAIN4, MMAA, and ERVMER34–1 are regulated by hsa-miR-4709. Conclusion Prognosis prediction model incorporating multi-RNAs with pathologic M and pathologic T may have great value in COAD prognosis prediction.