Role of Baseline Albumin-Bilirubin Grade on Predict Overall Survival Among Sorafenib-Treated Patients With Hepatocellular Carcinoma in Vietnam.

INTRODUCTION: Albumin-bilirubin (ALBI) grade has been recently used in evaluation of liver function and prognosis of patients with hepatocellular carcinoma (HCC). However, in Vietnam, the utility of ALBI grade in clinical setting has not been adequately investigated. METHODS: This is a retrospective study of 110 patients with HCC treated with sorafenib from January 2010 to November 2018 at 2 tertiary hospitals in Vietnam. Prognostic value of ALBI grade was evaluated by Kaplan-Meier survival analysis and Cox proportional regression model. RESULTS: Results showed that the majority of ALBI grade 1 were Child-Pugh level A (97.5%); ALBI grade 2 was seen in all Child-Pugh score groups of 5, 6, 7, ≥8, whereas ALBI grade 3 was mostly reported in Child-Pugh score ≥8 group (83.3%). Compared with ALBI grade 3, ALBI grade 1 reduced 66.4% risk of death (hazards ratio [HR] = 0.336, 95% confidence interval [CI]: 0.115-0.981; P = .046). Compared with ALBI grade 3, ALBI grade 2 reduced 67.3% risk of death (HR = 0.327, 95% CI: 0.122-0.875; P = .026). Albumin-bilirubin grade was an independent predictor of survival outcome. CONCLUSION: Baseline ALBI grade is a simple and objective approach in assessing liver functions of patients with HCC. Baseline ALBI grade is an independent predictor of survival in patients treated with sorafenib.

Epidemiological Characteristics of Advanced Hepatocellular Carcinoma in the Northern Region of Vietnam.

Epidemiological characteristics of hepatocellular carcinoma (HCC) in Southern Vietnam has been well reported as in Globocan 2018 while data from the North has still not been fully presented. Therefore, we conducted this retrospective descriptive study on 198 advanced HCC patients treated at 3 major hospitals in Northern Vietnam to describe demographic features, HCC risk factors, and correlation among them in patients with advanced HCC. This information will lead to prevention efforts and provide information for allocating funds for treatment. The median age at diagnosis was 57 years (range: 19-86) and the male/female ratio was 8.9/1. The proportions of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection were 81.3% and 5.6%, respectively. Hepatitis C virus infection rate was significantly higher in patients <50 years old (12.5% vs 3.3%, P = .016). There was no significant difference in age or viral hepatitis infection status by gender. Only 7.6% of patients diagnosed with advanced HCC were asymptomatic. In conclusion, with the high rate of HBV infection among patients with advanced HCC, it is necessary for increasing prevention efforts in HBV screening. Furthermore, HCV infection should be noticed in patients with advanced HCC younger than 50 years old.

Multi-environment Genomic Selection in Rice Elite Breeding Lines.

BACKGROUND: Assessing the performance of elite lines in target environments is essential for breeding programs to select the most relevant genotypes. One of the main complexities in this task resides in accounting for the genotype by environment interactions. Genomic prediction models that integrate information from multi-environment trials and environmental covariates can be efficient tools in this context. The objective of this study was to assess the predictive ability of different genomic prediction models to optimize the use of multi-environment information. We used 111 elite breeding lines representing the diversity of the international rice research institute breeding program for irrigated ecosystems. The lines were evaluated for three traits (days to flowering, plant height, and grain yield) in 15 environments in Asia and Africa and genotyped with 882 SNP markers. We evaluated the efficiency of genomic prediction to predict untested environments using seven multi-environment models and three cross-validation scenarios. RESULTS: The elite lines were found to belong to the indica group and more specifically the indica-1B subgroup which gathered improved material originating from the Green Revolution. Phenotypic correlations between environments were high for days to flowering and plant height (33% and 54% of pairwise correlation greater than 0.5) but low for grain yield (lower than 0.2 in most cases). Clustering analyses based on environmental covariates separated Asia's and Africa's environments into different clusters or subclusters. The predictive abilities ranged from 0.06 to 0.79 for days to flowering, 0.25-0.88 for plant height, and - 0.29-0.62 for grain yield. We found that models integrating genotype-by-environment interaction effects did not perform significantly better than models integrating only main effects (genotypes and environment or environmental covariates). The different cross-validation scenarios showed that, in most cases, the use of all available environments gave better results than a subset. CONCLUSION: Multi-environment genomic prediction models with main effects were sufficient for accurate phenotypic prediction of elite lines in targeted environments. These results will help refine the testing strategy to update the genomic prediction models to improve predictive ability.

Quantum dynamics of two-spin-qubit systems.

The aim of this topical review is a systematic and concise presentation of the results of a series of theoretical works on the quantum dynamics of two-spin-qubit systems towards the elaboration of a physical mechanism of the quantum information transfer between two spin-qubits. For this purpose the main attention is paid to exactly solvable models of two-spin-qubit systems, since the analytical expressions of the elements of their reduced density matrices explicitly exhibit the mutual dependence of the quantum information encoded into the spin-qubits. The treatment of their decoherence due to the interaction with the environment is performed in the Markovian approximation. Rate equations for axially symmetric systems of two coupled spin-qubits non-interacting, as well as interacting, with the environment are exactly solved. It is shown how the solutions of rate equations demonstrate the physical mechanism of the quantum information exchange between the spin-qubits. This mechanism holds also in all two-spin-qubit systems whose rate equations can be solved only by means of numerical calculations. Exact solutions of rate equations for two uncoupled spin-qubits interacting with two separate environments reveal an interesting physical phenomenon in the time evolution of the qubit-qubit entanglement generated by their interaction with the environments: the entanglement sudden death and revival. A two-spin-qubit system with an asymptotically decoherence free subspace was also explicitly constructed. The presented calculations and reasonings can be extended for application to the study of spin-qubit chains or networks.

Chlorine Gas Sensing Performance of On-Chip Grown ZnO, WO3, and SnO2 Nanowire Sensors.

Monitoring toxic chlorine (Cl2) at the parts-per-billion (ppb) level is crucial for safe usage of this gas. Herein, ZnO, WO3, and SnO2 nanowire sensors were fabricated using an on-chip growth technique with chemical vapor deposition. The Cl2 gas-sensing characteristics of the fabricated sensors were systematically investigated. Results demonstrated that SnO2 nanowires exhibited higher sensitivity to Cl2 gas than ZnO and WO3 nanowires. The response (RCl2/Rair) of the SnO2 nanowire sensor to 50 ppb Cl2 at 50 °C was about 57. Hence, SnO2 nanowires can be an excellent sensing material for detecting Cl2 gas at the ppb level under low temperatures. Abnormal sensing characteristics were observed in the WO3 and SnO2 nanowire sensors at certain temperatures; in particular, the response level of these sensors to 5 ppm of Cl2 was lower than that to 2.5 ppm of Cl2. The sensing mechanism of the SnO2 nanowire sensor was also elucidated by determining Cl2 responses under N2 and dry air as carrier gases. We proved that the Cl2 molecule was first directly adsorbed on the metal oxide surface and was then substituted for pre-adsorbed oxygen, followed by lattice oxygen.

Fabrication of highly sensitive and selective H2 gas sensor based on SnO2 thin film sensitized with microsized Pd islands.

Ultrasensitive and selective hydrogen gas sensor is vital component in safe use of hydrogen that requires a detection and alarm of leakage. Herein, we fabricated a H2 sensing devices by adopting a simple design of planar-type structure sensor in which the heater, electrode, and sensing layer were patterned on the front side of a silicon wafer. The SnO2 thin film-based sensors that were sensitized with microsized Pd islands were fabricated at a wafer-scale by using a sputtering system combined with micro-electronic techniques. The thicknesses of SnO2 thin film and microsized Pd islands were optimized to maximize the sensing performance of the devices. The optimized sensor could be used for monitoring hydrogen gas at low concentrations of 25-250 ppm, with a linear dependence to H2 concentration and a fast response and recovery time. The sensor also showed excellent selectivity for monitoring H2 among other gases, such as CO, NH3, and LPG, and satisfactory characteristics for ensuring safety in handling hydrogen. The hydrogen sensing characteristics of the sensors sensitized with Pt and Au islands were also studied to clarify the sensing mechanisms.