Accurate seizure prediction will transform epilepsy management by offering warnings to patients or triggering interventions. However, state-of-the-art algorithm design relies on accessing adequate long-term data. Crowd-sourcing ecosystems leverage quality data to enable cost-effective, rapid development of predictive algorithms. A crowd-sourcing ecosystem for seizure prediction is presented involving an international competition, a follow-up held-out data evaluation, and an online platform, Epilepsyecosystem.org, for yielding further improvements in prediction performance. Crowd-sourced algorithms were obtained via the 'Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge' conducted at kaggle.com. Long-term continuous intracranial electroencephalography (iEEG) data (442 days of recordings and 211 lead seizures per patient) from prediction-resistant patients who had the lowest seizure prediction performances from the NeuroVista Seizure Advisory System clinical trial were analysed. Contestants (646 individuals in 478 teams) from around the world developed algorithms to distinguish between 10-min inter-seizure versus pre-seizure data clips. Over 10 000 algorithms were submitted. The top algorithms as determined by using the contest data were evaluated on a much larger held-out dataset. The data and top algorithms are available online for further investigation and development. The top performing contest entry scored 0.81 area under the classification curve. The performance reduced by only 6.7% on held-out data. Many other teams also showed high prediction reproducibility. Pseudo-prospective evaluation demonstrated that many algorithms, when used alone or weighted by circadian information, performed better than the benchmarks, including an average increase in sensitivity of 1.9 times the original clinical trial sensitivity for matched time in warning. These results indicate that clinically-relevant seizure prediction is possible in a wider range of patients than previously thought possible. Moreover, different algorithms performed best for different patients, supporting the use of patient-specific algorithms and long-term monitoring. The crowd-sourcing ecosystem for seizure prediction will enable further worldwide community study of the data to yield greater improvements in prediction performance by way of competition, collaboration and synergism.10.1093/brain/awy210_video1awy210media15817489051001.

Nucleoid-associated proteins (NAPs) facilitate chromosome organization in bacteria, but the precise mechanism remains elusive. H-NS is a NAP that also plays a major role in silencing pathogen genes. We used genetics, single-particle tracking in live cells, superresolution microscopy, atomic force microscopy, and molecular dynamics simulations to examine H-NS/DNA interactions in single cells. We discovered a role for the unstructured linker region connecting the N-terminal oligomerization and C-terminal DNA binding domains. In the present work we demonstrate that linker amino acids promote engagement with DNA. In the absence of linker contacts, H-NS binding is significantly reduced, although no change in chromosome compaction is observed. H-NS is not localized to two distinct foci; rather, it is scattered all around the nucleoid. The linker makes DNA contacts that are required for gene silencing, while chromosome compaction does not appear to be an important H-NS function.

The differential structural–elastic properties of molecules between their transition and initial (native or denatured) states determine force-dependent transition rates.

Edited by Joel M. Gottesfeld The G-rich Pu39 region of the P1 promoter of the oncogene BCL-2, an apoptosis regulator, can fold into multiple G-quadruplex (G4) structures. Bcl2-2345 and Bcl2-1245 are two major G4 species forming with high thermal stability and distinct topologies in the Pu39 region, but their folding/unfolding kinetics have not yet been investigated. Here, we used magnetic tweezers to measure the mechanical stability and the folding/unfolding kinetics of the Bcl2-2345 and Bcl2-1245 G4 structures. We report that the hybrid-stranded Bcl2-2345 G4 had a lower mechanical stability than the parallel-stranded Bcl2-1245 G4. We observed that the Bcl2-2345 G4 is a kinetically favored structure, whereas the Bcl2-1245 G4, with a slow unfolding rate, may function as a kinetic barrier for transcription. We also determined that in addition to the Bcl2-2345 and Bcl2-1245 G4s, other stable DNA secondary structures, such as a hybrid-stranded Bcl2-1234 G4, can also form in the Pu39 sequence. The characterization of the folding/unfolding kinetics of specific G4s reported here sheds light on the participation of G4s during gene transcription and provides information for designing G4-targeting small molecules that could modulate BCL-2 gene expression.

Unfolded protein, a disordered structure found before folding of newly synthesized protein or after protein denaturation, is a substrate for binding by many cellular factors such as heat-stable proteins, chaperones, and many small molecules. However, it is challenging to directly probe such interactions in physiological solution conditions because proteins are largely in their folded state. In this work we probed small molecule binding to mechanically unfolded polyprotein using sodium dodecyl sulfate (SDS) as an example. The effect of binding is quantified based on changes in the elasticity and refolding of the unfolded polyprotein in the presence of SDS. We show that this single-molecule mechanical detection of binding to unfolded polyprotein can serve, to our knowledge, as a novel label-free assay with a great potential to study many factors that interact with unfolded protein domains, which underlie many important biological processes.