One-Electron Quantum Cyclotron as a Milli-eV Dark-Photon Detector.

We propose using trapped electrons as high-Q resonators for detecting meV dark photon dark matter. When the rest energy of the dark photon matches the energy splitting of the two lowest cyclotron levels, the first excited state of the electron cyclotron will be resonantly excited. A proof-of-principle measurement, carried out with one electron, demonstrates that the method is background free over a 7.4 day search. It sets a limit on dark photon dark matter at 148 GHz (0.6 meV) that is around 75 times better than previous constraints. Dark photon dark matter in the 0.1-1 meV mass range (20-200 GHz) could likely be detected at a similar sensitivity in an apparatus designed for dark photon detection.

Biological characteristics associated with virulence in Clostridioides difficile ribotype 002 in Hong Kong.

Clostridioides difficile infection (CDI) is a common cause of nosocomial diarrhea and can sometimes lead to pseudo-membranous colitis and toxic megacolon. We previously reported that the PCR ribotype 002 was a common C. difficile ribotype in Hong Kong that was associated with increased mortality. In this study, we assessed in vitro bacteriological characteristics and in vivo virulence of ribotype 002 compared to other common ribotypes, including ribotypes 012, 014 and 046. We observed significantly higher toxin A (p < 0.05) and toxin B (p < 0.05) production, sporulation (p < 0.001) and germination rates (p < 0.0001) in ribotype 002 than other common ribotypes. In a murine model of C. difficile infection, ribotype 002 caused significantly more weight loss (p < 0.001) and histological damage (p < 0.001) than other common ribotypes. These findings may have contributed to the higher prevalence and mortality observed, and provided mechanistic insights that can help public surveillance and develop novel therapeutics to combat against this infection.

Meditation-induced neuroplastic changes in amygdala activity during negative affective processing.

Recent evidence suggests that the effects of meditation practice on affective processing and resilience have the potential to induce neuroplastic changes within the amygdala. Notably, literature speculates that meditation training may reduce amygdala activity during negative affective processing. Nonetheless, studies have thus far not verified this speculation. In this longitudinal study, participants (N = 21, 9 men) were trained in awareness-based compassion meditation (ABCM) or matched relaxation training. The effects of meditation training on amygdala activity were examined during passive viewing of affective and neutral stimuli in a non-meditative state. We found that the ABCM group exhibited significantly reduced anxiety and right amygdala activity during negative emotion processing than the relaxation group. Furthermore, ABCM participants who performed more compassion practice had stronger right amygdala activity reduction during negative emotion processing. The lower right amygdala activity after ABCM training may be associated with a general reduction in reactivity and distress. As all participants performed the emotion processing task in a non-meditative state, it appears likely that the changes in right amygdala activity are carried over from the meditation practice into the non-meditative state. These findings suggest that the distress-reducing effects of meditation practice on affective processing may transfer to ordinary states, which have important implications on stress management.

Can the neural-cortisol association be moderated by experience-induced changes in awareness?

Cortisol homeostasis is important for cognitive and affective functions that depend on cortisol-sensitive brain regions including the hippocampus and prefrontal cortex. Recent studies have shown that training induces changes in the brain. We report the findings of a longitudinal study that verified the moderation effect of experience-induced changes in awareness on the neural-cortisol association in cortisol-sensitive brain regions. These findings provide the first piece of evidence that planned behavioral experience can moderate the neural-cortisol association. A range of changes in awareness was achieved in a sample of 21 Chinese participants, divided into two groups: Awareness-based compassion meditation (ABCM) (n = 10) and relaxation (n = 11). We observed that changes in awareness were significant moderators of hippocampal-cortisol changes. Furthermore, a significant negative association between changes in plasma cortisol level and the resting-state synchrony of the right hippocampal and insular-frontal-operculum regions was observed. These novel findings shed light on the inter-relationships between changes in hippocampal-cortisol levels and changes in awareness and preliminarily identify the neural underpinnings of interventions for cortisol-related abnormal functioning for further study.

EvoMD: an algorithm for evolutionary molecular design.

Traditionally, Computer-Aided Molecular Design (CAMD) uses heuristic search and mathematical programming to tackle the molecular design problem. But these techniques do not handle large and nonlinear search space very well. To overcome these drawbacks, graph-based evolutionary algorithms (EAs) have been proposed to evolve molecular design by mimicking chemical reactions on the exchange of chemical bonds and components between molecules. For these EAs to perform their tasks, known molecular components, which can serve as building blocks for the molecules to be designed, and known chemical rules, which govern chemical combination between different components, have to be introduced before the evolutionary process can take place. To automate molecular design without these constraints, this paper proposes an EA called Evolutionary Algorithm for Molecular Design (EvoMD). EvoMD encodes molecular designs in graphs. It uses a novel crossover operator which does not require known chemistry rules known in advanced and it uses a set of novel mutation operators. EvoMD uses atomics-based and fragment-based approaches to handle different size of molecule, and the value of the fitness function it uses is made to depend on the property descriptors of the design encoded in a molecular graph. It has been tested with different data sets and has been shown to be very promising.