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Using ball milled CNT catalysts, the electrocatalytic reductive amination of keto acids to amino acids was efficiently conducted. Moderate to high formation rates (up to 180.9 mmol g−1cat h−1) and Faradaic efficiencies (up to 90%) were achieved.

Spheronisation of cylindrical extrudates on a rotating friction plate involves breakage and rounding. Little attention has been given to the breakage stage and quantitative modelling of this process is scarce. Two simple models are compared with experimental data obtained for the early stages of spheronisation of microcrystalline cellulose/water extrudates. Tests were conducted for different times (t), rotational speeds (ω), initial loadings and on pyramidal friction plates with different dimensions. The first model, describing the number of pellets, validated ω3t as a characteristic time scale for the breakage stage. The kinetic parameters obtained by fitting showed a systematic dependence on plate dimensions expressed as a scaled gap width. The second model, a simple population balance, described the evolution of the number and length of pellets. The pseudo rate constants provided insights into the kinetics: extrudates tended to break near the middle, while breakage of smaller pellets was slowed down by more pellet‐pellet collisions.

The acceleration of Faradaic reactions by oscillating electric potentials has emerged as a viable tool to enhance electrocatalysis, but the non-Faradaic dynamic promotion of thermal catalytic processes remains to be proven. Here, we present experimental evidence showing that oscillating potentials are capable of enhancing the rate of ethylene hydrogenation despite no promotion effect being observed under static potentials. The non-Faradaic dynamic enhancement reaches up to 553% on a Pd/C electrode when cycling between -0.25 and 0.55 VNHE under optimized conditions with a frequency of around 0.1 Hz and a duty cycle of 99%. Under those conditions, the catalytic reaction rates were promoted beyond the rate of charge transfer to the electrode surface, confirming the non-Faradaic nature of the process. Experiments in different electrolytes reveal a good correlation between the catalytic enhancement and the double-layer capacitance, a measure for the interfacial electric field strength. Preliminary kinetic data is consistent with cyclic removal of adsorbates from the surface at negative potential and the subsequent adsorption of H2 and C2H4 and hydrogenation reaction at the positively polarized surface.

Establishing correlations between catalytic activity and dynamic surface properties of real catalysts, such as adsorbate coverage, is not straight-forward but crucial for the understanding of catalytic phenomena. The formic acid oxidation reaction comprises the non-Faradaic dehydration to CO when no potential is applied to the catalyst surface and the subsequent Faradaic oxidative desorption to form CO2. Here, we report a methodology based on applying oscillating potentials to various electrocatalytically active metal surfaces during the formic acid oxidation reaction. Moderate frequency oscillations (0.1–10 Hz) allow us to control the coverage of intermediates on the surface, thus enabling the quantification of the transient effects (on the time scale of up to 10−4 s) of coverage on the reaction rate. We determined different coverage-dependences of turnover frequencies for Pt metal plate and various carbon-supported metal nanoparticle catalysts (Pt/C, Pd/C and Rh/C). This method therefore constitutes a valuable and simple tool for the elucidation of adsorbate coverages on metal surfaces and their resulting catalytic performance. We also demonstrate that dynamic catalytic processes can be analysed semi-quantitatively with this new approach, allowing the design of catalytic processes under optimized conditions.

Objectives: This study aims to uncover variants of large effect size and allele frequency below 5% by sequencing all extant genes associated with rheumatoid arthritis (RA) in a homogeneous patient cohort. Patients and methods: This retrospective study was conducted between January 2001 and December 2017. We selected Chinese RA patients positive for anti-citrullinated peptide antibody (ACPA). All the 128 known candidate genes identified through genome-wide association studies were sequenced in 48 RA patients (15 males, 33 females; mean age 53.32±8.98 years; range, 32 to 75 years) and 45 controls (11 males, 34 females; mean age 32.18±9.54; range, 21 to 57 years). The exonic regions of these genes were sequenced. The resultant data were analyzed for association using single variant association and pathway-based association enrichment tests. The genetic burden due to low-frequency variants was assessed with the C-alpha test. The candidate variants that showed significant association were validated in a larger cohort of 500 RA cases (71 males, 429 females; mean age 48.6±12.2 years; range, 24 to 92 years) and 500 controls (66 males, 434 females; mean age 32.3±10.1 years; range, 21 to 73 years). Results: Thirty-nine variants in 21 genes were identified using single variant association analysis and C-alpha test, with stepwise filtering. Among these, the missense variant in interleukin-6 signal transducer (IL-6ST) 5:55260065 (p.Cys47Phe) was significantly associated with RA in Chinese patients in Singapore. Conclusion: Our results suggest that a mutation in IL-6ST (5:55260065) confers risk of RA in Chinese patients in Singapore.

Fluidized-bed based solar reactors for the gasification of biomass have been widely recognized as a promising approach to produce high-quality syngas due to the merits, e.g. continuous operation and superior heat and mass transport. In this work, a novel high-temperature solar reactor with a clapboard-type internally circulating configuration that can efficiently mitigate the overheating of the bed wall affected by non-uniform solar radiation, is designed, constructed, and experimentally investigated under Singapore’s first 28 kWe high-flux solar simulator. To investigate the flow dynamics in the high-temperature solar reactor, a transient 3D computational fluid dynamics multi-phase model is developed accordingly and validated by the experimental data. The simulated results can well clarify the flow and thermal behaviours in experiments. The effects of the gas flow rate and bed mass on the thermal performances of different Group-B particle materials are studied through experiments and simulation. The results indicate that increasing the bed mass in the solar reactor is capable of mitigating the overheating of the absorber surface caused by hot spots. The gas flow rate is dependent on the particle thermo-physical properties and shape as well as the clapboard geometric parameters. The highest solar-to-thermal conversion efficiency (defined as the ratio of the accumulated sensible heat of the particles to the solar power input) of 10.7 ± 0.4% is achieved by SiC due to its superior thermal conductivity.

Physical effects, such as electromagnetic waves, plasma, electric potential, electric/magnetic fields and mechanical strain, can efficiently promote heterogeneous catalysis beyond catalyst design., Despite the indisputable success of conventional approaches to manipulate the performance of heterogeneous catalysts by tuning the composition and structure of active sites, future research on catalysis engineering will likely go beyond the catalyst itself. Recently, several auxiliary promotion methods, either promoting the activity of reagents or enabling optimized adsorbate–catalyst interactions, have been proven as viable strategies to enhance catalytic reactions. Those auxiliary promotion methods range from electric/magnetic fields and electric potentials to mechanic stress, significantly altering the properties of reagent molecules and/or the surface characteristics of nanostructured catalysts. Apart from static enhancement effects, they in principle also allow for spatially and temporally variable modifications of catalyst surfaces. While some of those methods have been demonstrated, some are only theoretically predicted, opening exciting avenues for future experimental advances. Besides fundamental descriptions and comparisons of each activation method, in this perspective we plan to provide examples for the applications of those techniques for a variety of catalytic reactions as diverse as N2 and CO2 hydrogenation as well as electrochemical water splitting. Finally, we provide a unifying view and guidelines for future research into the use of promotion methods, generating deeper understanding of the complex dynamics on the nanoparticle surface under auxiliary promotion and the expansion of auxiliary techniques to different sustainability-related reactions.

Objective To evaluate the feasibility of detecting actionable gene mutations in circulating tumor DNA (ctDNA) in patients with advanced non-small-cell lung cancer (NSCLC) using targeted next-generation sequencing (NGS). Materials and methods In total 50 plasma samples from patients newly diagnosed with advanced NSCLC or resistant to first-line tyrosine kinase inhibitors (TKIs) were subjected to deep sequencing on a seven-gene panel (BRAF, EGFR, ERBB2, KRAS, NRAS, PIK3CA, PTEN) incorporated with molecular barcodes to improve accuracy in variant detection. When possible, results were compared with those from matched tissue samples. Results At least one alteration in the ctDNA was detected in 44 out of 50 patients (88%); EGFR was the most frequently mutated gene. Half the total number of patients (50%, 25 of 50) had at least one actionable genetic alteration with targeted therapies available for treatment. Our results showed a high concordance rate of 81% in detection of EGFR mutation between 26 matched tissue and plasma samples. For progressive patients, from whom tissue is mostly unavailable, the resistant EGFR T790 M mutation was validated using the droplet digital polymerase chain reaction (ddPCR), yielding a concordance of 92% between alternative platforms. Conclusion Our study demonstrated that therapeutically actionable mutations can be detected with high accuracy in ctDNA using NGS. This promising approach offers alternative and non-invasive diagnostic methods for treatment guidance and clinical monitoring.

Background Lipid storage myopathy (LSM) is a diverse group of lipid metabolic disorders with great variations in the clinical phenotype and age of onset. Classical multiple acyl-CoA dehydrogenase deficiency (MADD) is known to occur secondary to mutations in electron transfer flavoprotein dehydrogenase (ETFDH) gene. Whole exome sequencing (WES) with clinical correlations can be useful in identifying genomic alterations for targeted therapy. Case presentation We report a patient presented with severe muscle weakness and exercise intolerance, suggestive of LSM. Diagnostic testing demonstrated lipid accumulation in muscle fibres and elevated plasma acyl carnitine levels. Exome sequencing of the proband and two of his unaffected siblings revealed compound heterozygous mutations, c.250G > A (p.Ala84Thr) and c.770A > G (p.Tyr257Cys) in the ETFDH gene as the probable causative mutations. In addition, a previously unreported variant c.1042C > T (p.Arg348Trp) in ACOT11 gene was found. This missense variant was predicted to be deleterious but its association with lipid storage in muscle is unclear. The diagnosis of MADD was established and the patient was treated with riboflavin which resulted in rapid clinical and biochemical improvement. Conclusions Our findings support the role of WES as an effective tool in the diagnosis of highly heterogeneous disease and this has important implications in the therapeutic strategy of LSM treatment. Electronic supplementary material The online version of this article (10.1186/s12920-018-0356-8) contains supplementary material, which is available to authorized users.

Background Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories. Methods We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow. Results We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population. Conclusion Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.

To estimate the increased channel parameters in large-scale multiple-input-single-output (MISO) systems, a structured compressive channel estimation scheme based on preamble signals is proposed. The channel estimation scheme exploits the sparse common support of different channel impulse responses (CIRs), leading to a block-structured compressive sensing model for the MISO system. Using this model, an optimization criteria characterizing the unique block sparsity is formulated, and accordingly a block-based orthogonal matching pursuit algorithm is developed which effectively recovers the channel parameters. Simulation results validate the efficacy of the proposed scheme in estimating many sparse CIRs, showing its performance advantage in the emerging large-scale antenna systems.

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).

The theory of Compressive Sensing (CS) has enabled the efficient acquisition of high-bandwidth (but sparse) signals via nonuniform low-rate sampling protocols. While most work in CS has focused on reconstructing the high-bandwidth signals from nonuniform low-rate samples, in this work, we consider the task of inferring the modulation of a communications signal directly in the compressed domain, without requiring signal reconstruction. We show that the Nth power nonlinear features used for Automatic Modulation Recognition (AMR) are compressible in the Fourier domain, and hence, that AMR of M-ary Phase-Shift-Keying (MPSK) modulated signals is possible by applying the same nonlinear transformation on nonuniform compressive samples. We provide analytical support for the accurate approximation of AMR features from nonuniform samples, present practical rules for classification of modulation type using these samples, and validate our proposed rules on simulated data.

The framework of computing Higher Order Cyclostationary Statistics (HOCS) from an incoming signal has proven useful in a variety of applications over the past half century, from Automatic Modulation Recognition (AMR) to Time Dierence of Arrival (TDOA) estimation. Much more recently, a theory known as Compressive Sensing (CS) has emerged that enables the ecient acquisition of high-bandwidth (but sparse) signals via nonuni- form low-rate sampling protocols. While most work in CS has focused on reconstructing the high-bandwidth signals from nonuniform low-rate samples, in this work, we consider the task of inferring the modulation of a communications signal directly in the compressed domain, without requiring signal reconstruction. We show that the HOCS features used for AMR are compressible in the Fourier domain, and hence, that AMR of various linearly modulated signals is possible by estimating the same HOCS features from nonuniform compressive sam- ples. We provide analytical support for the accurate approximation of HOCS features from nonuniform samples and derive practical rules for classication of modulation type using these samples based on simulated data.