The rockefeller university

Nanodiscs, small discoidal membrane patches stabilized by membrane-scaffold proteins (MSPs), are popular tools to stabilize integral membrane proteins (IMPs) for structural studies by cryogenic electron microscopy (cryo-EM). While nanodiscs provide a near-native membrane environment for the incorporated IMPs, they do not reproduce all characteristics of a native membrane. Also, IMPs must first be purified in detergent before they can be reconstituted into MSP-based nanodiscs, a problem that has been overcome by newer approaches, such as copolymer-based native nanodiscs and cell-derived vesicles. In this review, we argue that despite these advances, MSP-based nanodiscs remain a unique tool for the structural interrogation of IMPs.

Despite waning of virus-neutralizing antibodies, protection against severe SARS-CoV-2 in the majority of immune individuals remains high, but the underlying immune mechanisms are incompletely understood. Here, rhesus macaques with pre-existing immunity from Novavax WA-1 and/or P.1 vaccines and WA-1 or P.1 infection are immunized with a bivalent WA-1/Omicron BA.5 Novavax vaccine ten months after the last exposure. The boost vaccination primarily increases the frequency of cross-reactive spike (S)-specific antibodies and B cells instead of inducing de novo BA.5-specific responses. Reinfection with heterologous Omicron XBB.1.5 six months after the boost vaccination results in low levels of virus replication in the respiratory tract compared with virus-na & iuml;ve results from other studies. Whereas systemic S-specific immunity remains largely unchanged in all animals, the animals with complete protection from infection exhibit a stronger influx of S-specific IgG, monocytes, B cells and T cells into the bronchioalveolar space combined with expansion of CD69+CD103+ lung tissue-resident, S-specific CD8 T cells compared to actively infected animals. Our results underscore the importance of localized respiratory immune responses in mediating protection from Omicron reinfection and provide guidance for future vaccine development.

Defining viral proteomes is crucial to understanding viral life cycles and immune recognition but the landscape of translated regions remains unknown for most viruses. We have developed massively parallel ribosome profiling (MPRP) to determine open reading frames (ORFs) across tens of thousands of designed oligonucleotides. MPRP identified 4208 unannotated ORFs in 679 human-associated viral genomes. We found viral peptides originating from detected noncanonical ORFs presented on class-I human leukocyte antigen in infected cells and hundreds of upstream ORFs that likely modulate translation initiation of viral proteins. The discovery of viral ORFs across a wide range of viral families-including highly pathogenic viruses-expands the repertoire of vaccine targets and reveals potential cis-regulatory sequences.

Changes in gene expression are a key driver of phenotypic evolution, leading to a persistent interest in the evolution of transcriptomes. Traditionally, gene expression is modeled as a continuous trait, leaving qualitative transitions largely unexplored. In this paper, we detail the development of new Bayesian inference techniques to study the evolutionary turnover of organ-specific transcriptomes, which we define as instances where orthologous genes gain or lose expression in a particular organ. To test these techniques, we analyze the transcriptomes of 2 male reproductive organs, testes and accessory glands, across 11 species of the Drosophila melanogaster species group. We first discretize gene expression states by estimating the probability that each gene is expressed in each organ and species. We then define a phylogenetic model of correlated transcriptome evolution in 2 or more organs and fit it to the expression state data. Inferences under this model imply that many genes have gained and lost expression in each organ, and that the 2 organs experienced accelerated transcriptome turnover on different branches of the Drosophila phylogeny.

Coherent anti-Stokes Raman scattering (CARS) is a powerful nonlinear spectroscopic technique widely used in biological imaging, chemical analysis, and combustion and flame diagnostics. The adoption of pulse shapers in CARS has emerged as a useful approach, offering precise control of optical waveforms. By tailoring the phase, amplitude, and polarization of laser pulses, the pulse shaping approach enables selective excitation, spectral resolution improvement, and non-resonant background suppression in CARS. This paper presents a comprehensive review of applying pulse shaping techniques in CARS spectroscopy for biophotonics. There are two different pulse shaping strategies: passive pulse shaping and active pulse shaping. Two passive pulse shaping techniques, hybrid CARS and spectral focusing CARS, are reviewed. Active pulse shaping using a programmable pulse shaper such as spatial light modulator (SLM) is discussed for CARS spectroscopy. Combining active pulse shaping and passive shaping, optimizing CARS with acousto-optic programmable dispersive filters (AOPDFs) is discussed and illustrated with experimental examples conducted in the authors' laboratory. These results underscore pulse shapers in advancing CARS technology, enabling improved sensitivity, specificity, and broader applications across diverse scientific fields.

In Cancer Cell, two studies unveil mechanisms by which co-option of the protein synthesis machinery promotes cancer progression and potential therapeutic interventions. Kuzuoglu-Ozturk et al. show that eIF4A-mediated enhancement of oncogenic transcript translation initiation drives cancer progression, while Weller et al. demonstrate how aberrant transfer RNA (tRNA) modification disrupts translational fidelity to produce neoantigens.

Background: This paper describes an innovative cluster randomized controlled trial design to evaluate the comparative effectiveness of two approaches to preventing significant destabilization, leading to unplanned hospitalization and increased disability for patients with high comorbidity, that is, multiple chronic diseases defined by an enhanced Charlson Comorbidity Index >= 4. Methods: A total of 1974 patients were randomized in four waves at each of the sixteen Federally Qualified Health Centers (FQHCs) in four health systems -two in New York and two in Chicago. The two interventions compared 1) Patient-Centered Medical Home (PCMH) as implemented by the FQHCs (usual care control); or 2) PCMH plus a coaching intervention delivered by Health Coaches (experimental) helping patients identify life goals to encourage self-management enhanced by a positive affect/self-affirmation strategy. The two primary patient-centered clinical outcomes are 1) Unplanned hospitalizations; and 2) Within-patient changes in quality of life and disability, as measured by the World Health Organization Disability Assessment Scale 2 (WHODAS 2.0). The hypotheses are: 1) intervention patients will have a 5 % relative reduction in unplanned hospitalizations as compared to control patients; and 2) reduced disability measured by WHODAS2.0; 3) destabilization or 'tipping points' leading to hospitalization will be more often triggered by psychosocial issues than by medical Issues. Conclusion: This cluster RCT has the potential to transform the care for patients with high comorbidity by helping motivate patients to engage in self-management and to successfully navigate the barriers, challenges, and stresses leading to destabilization, hospitalization, and increased disability. ClinicalTrials.gov registration number: NCT04176510

Holistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical workforce. Artificial intelligence (AI) is a rapidly emerging technology already having an impact on the medical school and residency application process as students and faculty alike increasingly turn to AI tools to automate some steps in the preparation and evaluation of application materials. While AI may have the potential to improve the holistic admissions process by increasing efficiency and adding some measure of standardization among reviewers, the authors caution that this promise does not come without certain pitfalls. AI models may introduce new sources of bias and amplify existing ones, which, when combined with a lack of transparency regarding their use in the admissions process, may perpetuate the very inequities that holistic review seeks to minimize. The authors call for the medical education community to establish clear regulations to govern the acceptable use of AI in the admissions process and for a principled adoption of AI tools in a way that is sustainable for applicants and reviewers in the future.