Single giant unilamellar vesicles (GUVs) rupture spontaneously from their salt-laden suspension onto solid surfaces. At hydrophobic surfaces, the GUVs rupture via a recurrent, bouncing ball rhythm. During each contact, the GUVs, rendered tense by the substrate interactions, porate, and spread a molecularly transformed motif of a monomolecular layer on the hydrophobic surface from the point of contact in a symmetric manner. The competition from pore closure, however, limits the spreading and produces a daughter vesicle, which re-engages with the substrate. At solid hydrophilic surfaces, by contrast, GUVs rupture via a distinctly different recurrent burst-heal dynamics; during burst, single pores nucleate at the contact boundary of the adhering vesicles, facilitating asymmetric spreading and producing a "heart"-shaped membrane patch. During the healing phase, the competing pore closure produces a daughter vesicle. In both cases, the pattern of burst-reseal events repeats multiple times, splashing and spreading the vesicular fragments as bilayer patches at the solid surface in a pulsatory manner. These remarkable recurrent dynamics arise, not because of the elastic properties of the solid surface, but because the competition between membrane spreading and pore healing, prompted by the surface-energy-dependent adhesion, determine the course of the topological transition.

In molecular biology, it is a general assumption that the ensemble of expressed molecules, their activities and interactions determine biological function, cellular states and phenotypes. Stable protein complexes-or macromolecular machines-are, in turn, the key functional entities mediating and modulating most biological processes. Although identifying protein complexes and their subunit composition can now be done inexpensively and at scale, determining their function remains challenging and labor intensive. This study describes Protein Complex Function predictor (PCfun), the first computational framework for the systematic annotation of protein complex functions using Gene Ontology (GO) terms. PCfun is built upon a word embedding using natural language processing techniques based on 1 million open access PubMed Central articles. Specifically, PCfun leverages two approaches for accurately identifying protein complex function, including: (i) an unsupervised approach that obtains the nearest neighbor (NN) GO term word vectors for a protein complex query vector and (ii) a supervised approach using Random Forest (RF) models trained specifically for recovering the GO terms of protein complex queries described in the CORUM protein complex database. PCfun consolidates both approaches by performing a hypergeometric statistical test to enrich the top NN GO terms within the child terms of the GO terms predicted by the RF models. The documentation and implementation of the PCfun package are available at https://github.com/sharmavaruns/PCfun. We anticipate that PCfun will serve as a useful tool and novel paradigm for the large-scale characterization of protein complex function.

We investigated the effects of transcranial alternating stimulation (tACS) in patients with insomnia. Nine patients with chronic insomnia underwent two in-laboratory polysomnography, 2 weeks apart, and were randomized to receive tACS either during the first or second study. The stimulation was applied simultaneously and bilaterally at F3/M1 and F4/M2 electrodes (0.75 mA, 0.75 Hz, 5-minute). Sleep onset latency and wake after sleep onset dropped on the stimulation night but they did not reach statistical significance; however, there were significant improvements in spontaneous and total arousals, sleep quality, quality of life, recall memory, sleep duration, sleep efficiency, and daytime sleepiness.

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.

The original online version of this article was revised: The additional reference [139] has been added. Tao Han’s ORICD ID has been incorrectly assigned to Chengcheng Han and Chengcheng Han’s ORCID ID to Tao Han. Yang Ma’s ORCID ID has been incorrectly assigned to Lianliang Ma, and Lianliang Ma’s ORCID ID to Yang Ma. The original article has been corrected.