Here, we report the generation of MeV alpha-particles from H-11B fusion initiated by laser-accelerated boron ions. Boron ions with maximum energy of 6 MeV and fluence of 109/MeV/sr@5 MeV were generated from 60 nm-thick self-supporting boron nanofoils irradiated by 1 J femtosecond pulses at an intensity of 1019 W/cm2. By bombarding secondary hydrogenous targets with the boron ions, 3 × 105/sr alpha-particles from H-11B fusion were registered, which is consistent with the theoretical yield calculated from the measured boron energy spectra. Our results demonstrated an alternative way toward ultrashort MeV alpha-particle sources employing compact femtosecond lasers. The ion acceleration and product measurement scheme are referential for the studies on the ion stopping power and cross section of the H-11B reaction in solid or plasma.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent liver disorder, affecting approximately 25 % of the population. Coffee-drinking obese smokers exhibit lower body weights and decreased NAFLD rates, but the reasons behind this remain unclear. Additionally, the effect of nicotine, the main component of tobacco, on the development of NAFLD is still controversial. Our study aimed to explore the possible reasons that drinking coffee could alleviate NAFLD and gain weight and identify the real role of nicotine in NAFLD of obese smokers. A NAFLD model in mice was induced by administering nicotine and a high-fat diet (HFD). We recorded changes in body weight and daily food intake, measured the weights of the liver and visceral fat, and observed liver and adipose tissue histopathology. Lipid levels, liver function, liver malondialdehyde (MDA), superoxide dismutase (SOD), serum inflammatory cytokine levels and the expression of hepatic genes involved in lipid metabolism were determined. Our results demonstrated that nicotine exacerbated the development of NAFLD and caffeine had a hepatoprotective effect on NAFLD. The administration of caffeine could ameliorate nicotine-plus-HFD-induced NAFLD by reducing lipid accumulation, regulating hepatic lipid metabolism, alleviating oxidative stress, attenuating inflammatory response and restoring hepatic functions. These results might explain why obese smokers with high coffee consumption exhibit the lower incidence rate of NAFLD and tend to be leaner. It is essential to emphasise that the detrimental impact of smoking on health is multifaceted. Smoking cessation remains the sole practical and effective strategy for averting the tobacco-related complications and reducing the risk of mortality.

The single largest contributor to human mortality is cardiovascular disease, the top risk factor for which is hypertension (HTN). The last two decades have placed much emphasis on the identification of genetic factors contributing to HTN. As a result, over 1,500 genetic alleles have been associated with human HTN. Mapping studies using genetic models of HTN have yielded hundreds of blood pressure (BP) loci but their individual effects on BP are minor, which limits opportunities to target them in the clinic. The value of collecting genome-wide association data is evident in ongoing research, which is beginning to utilize these data at individual-level genetic disparities combined with artificial intelligence (AI) strategies to develop a polygenic risk score (PRS) for the prediction of HTN. However, PRS alone may or may not be sufficient to account for the incidence and progression of HTN because genetics is responsible for <30% of the risk factors influencing the etiology of HTN pathogenesis. Therefore, integrating data from other nongenetic factors influencing BP regulation will be important to enhance the power of PRS. One such factor is the composition of gut microbiota, which constitute a more recently discovered important contributor to HTN. Studies to-date have clearly demonstrated that the transition from normal BP homeostasis to a state of elevated BP is linked to compositional changes in gut microbiota and its interaction with the host. Here, we first document evidence from studies on gut dysbiosis in animal models and patients with HTN followed by a discussion on the prospects of using microbiota data to develop a metagenomic risk score (MRS) for HTN to be combined with PRS and a clinical risk score (CRS). Finally, we propose that integrating AI to learn from the combined PRS, MRS and CRS may further enhance predictive power for the susceptibility and progression of HTN.

Trematodes of the genus Ogmocotyle are intestinal flukes that can infect a variety of definitive hosts, resulting in significant economic losses worldwide. However, there are few studies on molecular data of these trematodes. In this study, the mitochondrial (mt) genome of Ogmocotyle ailuri isolated from red panda (Ailurus fulgens) was determined and compared with those from Pronocephalata to investigate the mt genome content, genetic distance, gene rearrangements and phylogeny. The complete mt genome of O. ailuri is a typical closed circular molecule of 14 642 base pairs, comprising 12 protein-coding genes (PCGs), 22 transfer RNA genes, 2 ribosomal RNA genes and 2 non-coding regions. All genes are transcribed in the same direction. In addition, 23 intergenic spacers and 2 locations with gene overlaps were determined. Sequence identities and sliding window analysis indicated that cox1 is the most conserved gene among 12 PCGs in O. ailuri mt genome. The sequenced mt genomes of the 48 Plagiorchiida trematodes showed 5 types of gene arrangement based on all mt genome genes, with the gene arrangement of O. ailuri being type I. Phylogenetic analysis using concatenated amino acid sequences of 12 PCGs revealed that O. ailuri was closer to Ogmocotyle sikae than to Notocotylus intestinalis. These data enhance the Ogmocotyle mt genome database and provide molecular resources for further studies of Pronocephalata taxonomy, population genetics and systematics.

A detailed electron backscatter diffraction (EBSD) characterization was utilized to investigate abnormal grain growth behavior of nanocrystalline (NC) Au films constrained by a flexible substrate under cyclic loading. Abnormally grown grains (AGGs) in front of about 15 fatigue cracks were picked out to investigate the grain reorientation behavior during abnormal grain growth in the fatigue crack tip in the cyclically deformed thin films. It shows that the AGGs exhibited 〈001〉 orientation along the loading direction, whereas grains grown far away from fatigue cracks had no significant texture change. The cyclic cumulative shear strain was found to play a key role in grain reorientation. A lattice rotation model was proposed to elucidate the grain reorientation mechanism during abnormal grain growth. Such grain reorientation behavior of NC metals was found to provide an intrinsic resistance of the NC metals to fatigue damage.

l-Carnitine is essential for mitochondrial β-oxidation and has been used as a lipid-lowering feed additive in humans and farmed animals. d-Carnitine is an optical isomer of l-carnitine and dl-carnitine has been widely used in animal feeds. However, the functional differences between l- and d-carnitine are difficult to study because of the endogenous l-carnitine background. In the present study, we developed a low-carnitine Nile tilapia model by treating fish with a carnitine synthesis inhibitor, and used this model to investigate the functional differences between l- and d-carnitine in nutrient metabolism in fish. l- or d-carnitine (0·4 g/kg diet) was fed to the low-carnitine tilapia for 6 weeks. l-Carnitine feeding increased the acyl-carnitine concentration from 3522 to 10 822 ng/g and alleviated the lipid deposition from 15·89 to 11·97 % in the liver of low-carnitine tilapia. However, as compared with l-carnitine group, d-carnitine feeding reduced the acyl-carnitine concentration from 10 822 to 5482 ng/g, and increased lipid deposition from 11·97 to 20·21 % and the mRNA expression of the genes involved in β-oxidation and detoxification in the liver. d-Carnitine feeding also induced hepatic inflammation, oxidative stress and apoptosis. A metabolomic investigation further showed that d-carnitine feeding increased glycolysis, protein metabolism and activity of the tricarboxylic acid cycle and oxidative phosphorylation. Thus, l-carnitine can be physiologically utilised in fish, whereas d-carnitine is metabolised as a xenobiotic and induces lipotoxicity. d-Carnitine-fed fish demonstrates increases in peroxisomal β-oxidation, glycolysis and amino acid degradation to maintain energy homeostasis. Therefore, d-carnitine is not recommended for use in farmed animals.

In order to reveal the quantitative relationship between fatigue crack deflection path and cross-sectional grain boundary (GB) arrangement of metallic nanolayered composites (NLCs), a stochastic model was established based on the interface-dominant fatigue damage for the ultrafine-scale NLCs. The model indicates that the crack deflection length decreases with decreasing GB arrangement deviation and grain size of constituent layers. The observation and quantitative analysis of fatigue cracking behavior of the Cu/W multilayers with a layer thickness of 5 and 20 nm was conducted to verify the model.

Fatigue performance of metallic nanolayered composites (NLCs) has been gaining more and more attention due to the rapid development in the field of both micro-electro-mechanical systems and high-performance engineering structure materials and the increasing demand for long-term fatigue reliability. Metallic NLCs have exhibited different damage behaviors due to the effect of high-density heterogeneous interface compared with bulk materials and thin metal films. In this review paper, the cyclic deformation damage behavior, fatigue cracking feature, and fatigue properties of some metallic NLCs are reviewed. Effects of length scales, including layer thickness and grain size, on fatigue damage behaviors of the NLCs are revealed, and the transition of the fatigue cracking behavior and the corresponding damage mechanism are discussed. Then, the fatigue properties of some typical metallic NLCs are presented and compared with that of bulk materials and metal thin films. The effect of interface type and grain boundary alignment is also discussed to correlate with fatigue cracking resistance of the NLCs. Finally, some prospective research topics on fatigue performance of metallic NLCs are addressed.

Fatigue properties of Mo/W multilayers with individual layer thickness (λ) of 5, 20, 50 and 100 nm on flexible polyimide substrates were investigated. The experimental results show that the fatigue resistance increases with decreasing λ from 100 nm to 20 nm, and reaches the maximum at λ=20 nm, and then decreases when further decreasing λ. Fatigue cracks of Mo/W multilayers with different λ were found to propagate along columnar grain boundary in the out-of-plane direction and along the boundary of cluster structures. The enhanced fatigue resistance is attributed to the larger cluster inclination angles and the more tortuous in-plane cracking paths.

Stretchability of polyimide-supported nanocrystalline Au films with a thickness ranging from 930 to 20 nm was evaluated by uniaxial tensile testing. The results show that the fracture strain gradually decreased with decreasing the film thickness. Such degraded stretchability depends on plastic deformation mechanisms associated with the length scales. As the film thickness is larger than 90 nm, local thinning in the grown grains contributed to the high stretchability. Full dislocation behaviors including dislocation pileup in the 930 nm-thick film, the activation of Frank–Read dislocation source in the 170 nm-thick film and the grain boundary dislocation source in the 90 nm-thick film were dominated plastic deformation. As the film thickness is less than 40 nm, low stretchability of thin films resulted from intergranular fracture, and partial dislocation behaviors became prevailed. Evident grain growth happened in the films studied except for the 20 nm-thick film, which is expected to be involved in the stretchability of the nanocrystalline metal films on flexible substrates.

We examined the in vitro developmental competence of parthenogenetic activation (PA) oocytes activated by an electric pulse (EP) and treated with various concentrations of AZD5438 for 4 h. Treatment with 10 µM AZD5438 for 4 h significantly improved the blastocyst formation rate of PA oocytes in comparison with 0, 20, or 50 µM AZD5438 treatment (46.4% vs. 34.5%, 32.3%, and 24.0%, respectively; P < 0.05). The blastocyst formation rate was higher in the group treated with AZD5438 for 4 h than in the groups treated with AZD5438 for 2 or 6 h (42.8% vs. 38.6% and 37.2%, respectively; P > 0.05). Furthermore, 66.67% of blastocysts derived from these AZD5438-treated PA oocytes had a diploid karyotype. The blastocyst formation rate of PA and somatic cell nuclear transfer (SCNT) embryos was similar between oocytes activated by an EP and treated with 2 mM 6-dimethylaminopurine for 4 h and those activated by an EP and treated with 10 µM AZD5438 for 4 h (11.11% vs. 13.40%, P > 0.05). In addition, the level of maturation-promoting factor (MPF) was significantly decreased in oocytes activated by an EP and treated with 10 µM AZD5438 for 4 h. Finally, the mRNA expression levels of apoptosis-related genes (Bax and Bcl-2) and pluripotency-related genes (Oct4, Nanog, and Sox2) were checked by RT-PCR; however, there were no differences between the AZD5438-treated and non-treated control groups. Our results demonstrate that porcine oocyte activation via an EP in combination with AZD5438 treatment can lead to a high blastocyst formation rate in PA and SCNT experiments.

Selecting important variables and estimating coordinate covariation have received considerable attention in the current big data deluge. Previous work shows that the gradient of the regression function, the objective function in regression and classification problems, can provide both types of information. In this paper, an algorithm to learn this gradient function is proposed for nonidentical data. Under some mild assumptions on data distribution and the model parameters, a result on its learning rate is established which provides a theoretical guarantee for using this method in dynamical gene selection and in network security for recognition of malicious online attacks.