Semiconductor photocatalysis to engineering deuterated N-alkyl pharmaceuticals enabled by synergistic activation of water and alkanols

Precisely controlled deuterium labeling at specific sites of N-alkyl drugs is crucial in drug-development as over 50% of the top-selling drugs contain N-alkyl groups, in which it is very challenging to selectively replace protons with deuterium atoms. With the goal of achieving controllable isotope-labeling in N-alkylated amines, we herein rationally design photocatalytic water-splitting to furnish [H] or [D] and isotope alkanol-oxidation by photoexcited electron-hole pairs on a polymeric semiconductor. The controlled installation of N-CH3, -CDH2, -CD2H, -CD3, and -13CH3 groups into pharmaceutical amines thus has been demonstrated by tuning isotopic water and methanol. More than 50 examples with a wide range of functionalities are presented, demonstrating the universal applicability and mildness of this strategy. Gram-scale production has been realized, paving the way for the practical photosynthesis of pharmaceuticals

The efficacy of fish oil supplements in the treatment of depression: food for thought.

A recent meta-analysis and meta-regression of 13 randomized clinical trials by Mocking et al.1 concluded that supplementation with omega-3 fatty acids, found naturally in fatty fish, has a beneficial effect in patients with major depressive disorder (MDD), especially for higher doses of the eicosapentaenoic acid (EPA) and in patients taking antidepressants. Novel treatments for MDD are certainly desired. However, in our view the evidence in this study does not solve the academic debate on the efficacy of omega-3 fatty acids for MDD. Some food for thought

Robust Facial Alignment for Face Recognition

© 2017, Springer International Publishing AG. This paper proposes a robust real-time face recognition system that utilizes regression tree based method to locate the facial feature points. The proposed system finds the face region which is suitable to perform the recognition task by geometrically analyses of the facial expression of the target face image. In real-world facial recognition systems, the face is often cropped based on the face detection techniques. The misalignment is inevitably occurred due to facial pose, noise, occlusion, and so on. However misalignment affects the recognition rate due to sensitive nature of the face classifier. The performance of the proposed approach is evaluated with four benchmark databases. The experiment results show the robustness of the proposed approach with significant improvement in the facial recognition system on the various size and resolution of given face images

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

A robust real-time facial alignment system with facial landmarks detection and rectification for multimedia applications

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Face detection often plays the first step in various visual applications. Large variants of facial deformations due to head movements and facial expression make it difficult to identify appropriate face region. In this paper, a robust real-time face alignment system, including facial landmarks detection and face rectification, is proposed. A facial landmarks detection model based on regression tree is utilized in the proposed system. In face rectification framework, 2-D geometrical analysis based on pitch, yaw and roll movements is designed to solve the misalignment problem in face detection. The experiments on the two datasets verify the performance significantly improved by the proposed method in the facial recognition task and outperform than those obtained by other alignment methods. Furthermore, the proposed method can achieve robust recognition results even if the amount of training images is not large

Molecular characterisation of virulence graded field isolates of myxoma virus

<p>Abstract</p> <p>Background</p> <p><it>Myxoma virus </it>(MV) has been endemic in Europe since shortly after its deliberate release in France in 1952. While the emergence of more resistant hosts and more transmissible and attenuated virus is well documented, there have been relatively few studies focused on the sequence changes incurred by the virus as it has adapted to its new host. In order to identify regions of variability within the MV genome to be used for phylogenetic studies and to try to investigate causes of MV strain attenuation we have molecularly characterised nine strains of MV isolated in Spain between the years 1992 and 1995 from wide ranging geographic locations and which had been previously graded for virulence by experimental infection of rabbits.</p> <p>Results</p> <p>The findings reported here show the analysis of 16 genomic regions accounting for approximately 10% of the viral genomes. Of the 20 genes analysed 5 (M034L, M069L, M071L, M130R and M135R) were identical in all strains and 1 (M122R) contained only a single point mutation in an individual strain. Four genes (M002L/R, M009L, M036L and M017L) showed insertions or deletions that led to disruption of the ORFs.</p> <p>Conclusions</p> <p>The findings presented here provide valuable tools for strain differentiation and phylogenetic studies of MV isolates and some clues as to the reasons for virus attenuation in the field.</p

The Galactic Center Black Hole Laboratory

The super-massive 4 million solar mass black hole Sagittarius~A* (SgrA*) shows flare emission from the millimeter to the X-ray domain. A detailed analysis of the infrared light curves allows us to address the accretion phenomenon in a statistical way. The analysis shows that the near-infrared flare amplitudes are dominated by a single state power law, with the low states in SgrA* limited by confusion through the unresolved stellar background. There are several dusty objects in the immediate vicinity of SgrA*. The source G2/DSO is one of them. Its nature is unclear. It may be comparable to similar stellar dusty sources in the region or may consist predominantly of gas and dust. In this case a particularly enhanced accretion activity onto SgrA* may be expected in the near future. Here the interpretation of recent data and ongoing observations are discussed.Comment: 30 pages - 7 figures - accepted for publication by Springer's "Fundamental Theories of Physics" series; summarizing GC contributions of 2 conferences: 'Equations of Motion in Relativistic Gravity' at the Physikzentrum Bad Honnef, Bad Honnef, Germany, (Feb. 17-23, 2013) and the COST MP0905 'The Galactic Center Black Hole Laboratory' Granada, Spain (Nov. 19 - 22, 2013

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci.

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies

Prediction of Liver-Related Events Using Fibroscan in Chronic Hepatitis B Patients Showing Advanced Liver Fibrosis

Liver stiffness measurement (LSM) using transient elastography (FibroScan®) can assess liver fibrosis noninvasively. This study investigated whether LSM can predict the development of liver-related events (LREs) in chronic hepatitis B (CHB) patients showing histologically advanced liver fibrosis.Between March 2006 and April 2010, 128 CHB patients with who underwent LSM and liver biopsy (LB) before starting nucleot(s)ide analogues and showed histologically advanced fibrosis (≥F3) with a high viral loads [HBV DNA ≥2,000 IU/mL] were enrolled. All patients were followed regularly to detect LRE development, including hepatic decompensation (variceal bleeding, ascites, hepatic encephalopathy, spontaneous bacterial peritonitis, hepatorenal syndrome) and hepatocellular carcinoma (HCC).The mean age of the patient (72 men, 56 women) was 52.2 years. During the median follow-up period [median 27.8 (12.6-61.6) months], LREs developed in 19 (14.8%) patients (five with hepatic decompensation, 13 with HCC, one with both). Together with age, multivariate analysis identified LSM as an independent predictor of LRE development [P<0.044; hazard ratio (HR), 1.038; 95% confidence interval (CI), 1.002-1.081]. When the study population was stratified into two groups using the optimal cutoff value (19 kPa), which maximized the sum of sensitivity (61.1%) and specificity (86.2%) from a time-dependent receiver operating characteristic curve, patients with LSM>19 kPa were at significantly greater risk than those with LSM≤19 kPa for LRE development (HR, 7.176; 95% CI, 2.257-22.812; P = 0.001).LSM can be a useful predictor of LRE development in CHB patients showing histologically advanced liver fibrosis