Reversible disulfide bond crosslinks as tunable levers of phase separation in designer biomolecular condensates.

Biomolecular condensates (BCs) are membraneless hubs enriched in proteins and nucleic acids that have become important players in many cellular functions. Uncovering the sequence determinants of proteins for phase separation is important in understanding the biophysical and biochemical properties of BCs. Despite significant discoveries in the last decade, the role of cysteine residues in BC formation and dissolution has remained unknown. Here, to determine the involvement of disulfide crosslinks and their redox sensitivity in BCs, we designed a 'stickers and spacers' model of phase-separating peptides interspersed with cysteines. Through biophysical investigations, we learned that cysteines promote liquid-liquid phase separation in oxidizing conditions and perpetuate liquid condensates through disulfide crosslinks, which can be reversibly tuned with redox chemistry. By varying the composition of cysteines, subtle but distinct changes in the viscoelastic behavior of the condensates were observed. Empirically, we conclude that cysteines are neither stickers nor spacers but function as covalent nodes to lower the effective concentrations for sticker interactions and inhibit system-spanning percolation networks. Together, we unmask the role of cysteines in protein phase behavior and the potential to develop tunable, redox-sensitive viscoelastic materials.

A Perspective on the History and Current Opportunities of Aqueous RAFT Polymerization.

Reversible addition-fragmentation chain transfer (RAFT) polymerization has proven itself as a powerful polymerization technique affording facile control of molecular weight, molecular weight distribution, architecture, and chain end groups - while maintaining a high level of tolerance for solvent and monomer functional groups. RAFT is highly suited to water as a polymerization solvent, with aqueous RAFT now utilized for applications such as controlled synthesis of ultra-high molecular weight polymers, polymerization induced self-assembly, and biocompatible polymerizations, among others. Water as a solvent represents a non-toxic, cheap, and environmentally friendly alternative to organic solvents traditionally utilized for polymerizations. This, coupled with the benefits of RAFT polymerization, makes for a powerful combination in polymer science. This perspective provides a historical account of the initial developments of aqueous RAFT polymerization at the University of Southern Mississippi from the McCormick Research Group, details practical considerations for conducting aqueous RAFT polymerizations, and highlights some of the recent advances aqueous RAFT polymerization can provide. Finally, some of the future opportunities that this versatile polymerization technique in an aqueous environment can offer are discussed, and it is anticipated that the aqueous RAFT polymerization field will continue to realize these, and other exciting opportunities into the future.

Machine learning makes magnificent macromolecules for medicine.

At the University of Minnesota, scientists explore the application of machine learning to screen a multiparametric library of polymers to investigate the relationship between polymer attributes, payload type, and biological outcomes to optimize polymeric vector development for delivery of nucleic acid payloads.

Acceptability of Using a Robotic Nursing Assistant in Health Care Environments: Experimental Pilot Study.

BACKGROUND: According to the US Bureau of Labor Statistics, nurses will be the largest labor pool in the United States by 2022, and more than 1.1 million nursing positions have to be filled by then in order to avoid a nursing shortage. In addition, the incidence rate of musculoskeletal disorders in nurses is above average in comparison with other occupations. Robot-assisted health care has the potential to alleviate the nursing shortage by automating mundane and routine nursing tasks. Furthermore, robots in health care environments may assist with safe patient mobility and handling and may thereby reduce the likelihood of musculoskeletal disorders. OBJECTIVE: This pilot study investigates the perceived ease of use and perceived usefulness (acceptability) of a customized service robot as determined by nursing students (as proxies for nursing staff in health care environments). This service robot, referred to as the Adaptive Robotic Nurse Assistant (ARNA), was developed to enhance the productivity of nurses through cooperation during physical tasks (eg, patient walking, item fetching, object delivery) as well as nonphysical tasks (eg, patient observation and feedback). This pilot study evaluated the acceptability of ARNA to provide ambulatory assistance to patients. METHODS: We conducted a trial with 24 participants to collect data and address the following research question: Is the use of ARNA as an ambulatory assistive device for patients acceptable to nurses? The experiments were conducted in a simulated hospital environment. Nursing students (as proxies for nursing staff) were grouped in dyads, with one participant serving as a nurse and the other acting as a patient. Two questionnaires were developed and administrated to the participants based on the Technology Acceptance Model with respect to the two subscales of perceived usefulness and perceived ease of use metrics. In order to evaluate the internal consistency/reliability of the questionnaires, we calculated Cronbach alpha coefficients. Furthermore, statistical analyses were conducted to evaluate the relation of each variable in the questionnaires with the overall perceived usefulness and perceived ease of use metrics. RESULTS: Both Cronbach alpha values were acceptably high (.93 and .82 for perceived usefulness and perceived ease of use questionnaires, respectively), indicating high internal consistency of the questionnaires. The correlation between the variables and the overall perceived usefulness and perceived ease of use metrics was moderate. The average perceived usefulness and perceived ease of use metrics among the participants were 4.13 and 5.42, respectively, out of possible score of 7, indicating a higher-than-average acceptability of this service robot. CONCLUSIONS: The results served to identify factors that could affect nurses' acceptance of ARNA and aspects needing improvement (eg, flexibility, ease of operation, and autonomy level).