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The cyanobacterial circadian oscillator, consisting of KaiA, KaiB, and KaiC proteins, drives global rhythms of gene expression and compaction of the chromosome and regulates the timing of cell division and natural transformation. While the KaiABC posttranslational oscillator can be reconstituted in vitro, the Kai-based oscillator is subject to several layers of regulation in vivo. Specifically, the oscillator proteins undergo changes in their subcellular localization patterns, where KaiA and KaiC are diffuse throughout the cell during the day and localized as a focus at or near the pole of the cell at night. Here, we report that the CI domain of KaiC, when in a hexameric state, is sufficient to target KaiC to the pole. Moreover, increased ATPase activity of KaiC correlates with enhanced polar localization. We identified proteins associated with KaiC in either a localized or diffuse state. We found that loss of Rbp2, found to be associated with localized KaiC, results in decreased incidence of KaiC localization and long-period circadian phenotypes. Rbp2 is an RNA-binding protein, and it appears that RNA-binding activity of Rbp2 is required to execute clock functions. These findings uncover previously unrecognized roles for Rbp2 in regulating the circadian clock and suggest that the proper localization of KaiC is required for a fully functional clock in vivo.

Presentamos una versión divulgativa de nuestro artículo (Amster y Cid, 2022) en el que mostramos cómo la raíz cuadrada compleja nos permite demostrar de una forma muy sencilla diversos resultados topológicos en el plano, tan profundos como el Teorema de Brouwer y el Teorema de Invariancia del Dominio, así como del Teorema Fundamental del Álgebra.

Abstract In the present work, we used daily diary methodology to investigate the influence of awe on stress, somatic health (e.g., pain symptoms), and well-being during the COVID-19 pandemic in 2020. We recruited a sample of community adults (N = 269) and a sample of healthcare professionals (N = 145) in the United States. Across both samples, we found that awe and well-being increased, and stress and somatic health symptoms decreased over the 22-day diary period. In daily level analyses, we found that the more daily awe people experienced, the less stress, less somatic health symptoms, and greater well-being they felt. Daily experiences of awe can benefit individuals during times of acute and chronic stress—such as the COVID-19 pandemic.

Here, a proto-type Ermakov–Painlevé I equation is introduced and a homogeneous Dirichlet-type boundary value problem analysed. In addition, a novel Ermakov–Painlevé I system is set down which is reducible by an involutory transformation to the autonomous Ermakov–Ray–Reid system augmented by a single component Ermakov–Painlevé I equation. Hamiltonian such systems are delimited.

Global efforts to reduce Maternal Mortality Rates (MMR) have been significant, but researchers are exploring new approaches to address stalled progress and enduring health inequities. This scoping review offers an analytic synthesis of maternal and infant health (MIH) research in the low-middle income North African Islamic country of Morocco over 22 years, a mapping of the themes, research gaps, geographies, and methodologies, 2000-2022. Morocco is an official MIH success story with excellent health indicators, yet indicators do not address local contexts, gender issues, or health disparities. To understand how medical research has reflected social reality over the past 22 years, we explored not just what is known, but how it is known, where it is known, what remained unseen, and why. Four databases were searched: OVID: MEDLINE, Embase, APA PsycINFO, and EBSCO: CINAHL. 4590 abstracts were identified, 3131 abstracts screened, and 402 full MIH articles and 128 sub-group articles identified and subject to data extraction. The 402 full MIH articles were subject to qualitative thematic analysis, classified by 34 primary research themes and explored especially for gender, health equity, and methodology. Findings included significant geographic research disparities; four regions were the location of 75% of research and many regions remained virtually "unseen" by research. The best-equipped urban public hospitals in higher-income regions produced the most research, creating an urban, hospital-based research perspective. Maternal health articles predominated, often >50% more than articles published about infant health. Infants studied were mostly neonates. Socially marginalized women were often invisible to research, as were private healthcare, NGO care (non-governmental civic organizations), and healthcare in community. In articles, researchers recommended new policies, new laws, health system reform, and government actions to advocate for patients. Three solutions emerged to broaden the research perspective: increase geographic breadth, address missing topics and populations, and embrace interdisciplinary methods.

Background: As artificial intelligence (AI) continues to advance with breakthroughs in natural language processing (NLP) and machine learning (ML), such as the development of models like OpenAI’s ChatGPT, new opportunities are emerging for efficient curation of electronic health records (EHR) into real-world data (RWD) for evidence generation in oncology. Our objective is to describe the research and development of industry methods to promote transparency and explainability.Methods: We applied NLP with ML techniques to train, validate, and test the extraction of information from unstructured documents (e.g., clinician notes, radiology reports, lab reports, etc.) to output a set of structured variables required for RWD analysis. This research used a nationwide electronic health record (EHR)-derived database. Models were selected based on performance. Variables curated with an approach using ML extraction are those where the value is determined solely based on an ML model (i.e. not confirmed by abstraction), which identifies key information from visit notes and documents. These models do not predict future events or infer missing information.Results: We developed an approach using NLP and ML for extraction of clinically meaningful information from unstructured EHR documents and found high performance of output variables compared with variables curated by manually abstracted data. These extraction methods resulted in research-ready variables including initial cancer diagnosis with date, advanced/metastatic diagnosis with date, disease stage, histology, smoking status, surgery status with date, biomarker test results with dates, and oral treatments with dates.Conclusion: NLP and ML enable the extraction of retrospective clinical data in EHR with speed and scalability to help researchers learn from the experience of every person with cancer.

A heterologous protein expression platform in a culturable methanogen Methanococcus maripaludis is developed to study the methyl-coenzyme M reductase from uncultured archaea.

Abstract Human roundabout 1 (hRobo1) is an extracellular receptor glycoprotein that plays important roles in angiogenesis, organ development, and tumor progression. Interaction between hRobo1 and heparan sulfate (HS) has been shown to be essential for its biological activity. To better understand the effect of HS binding we engineered a lanthanide-binding peptide sequence (Loop) into the Ig2 domain of hRobo1. Native mass spectrometry was used to verify that loop introduction did not inhibit HS binding or conformational changes previously suggested by gas phase ion mobility measurements. NMR experiments measuring long-range pseudocontact shifts were then performed on 13C-methyl labeled hRobo1-Ig1-2-Loop in HS-bound and unbound forms. The magnitude of most PCSs for methyl groups in the Ig1 domain increase in the bound state confirming a change in the distribution of interdomain geometries. A grid search over Ig1 orientations to optimize the fit of data to a single conformer for both forms produced two similar structures, both of which differ from existing X-ray crystal structures and structures inferred from gas-phase ion mobility measurements. The structures and degree of fit suggest that the hRobo1-Ig1-2 structure changes slightly and becomes more rigid on HS binding. This may have implications for Robo-Slit signaling.

Proliferative forms of glomerulonephritis are characterized by the influx of leukocytes, albuminuria, and loss of kidney function. The glomerular endothelial glycocalyx is a thick carbohydrate layer that covers the endothelium and is comprised of heparan sulfate (HS), which plays a pivotal role in glomerular inflammation by facilitating endothelial-leukocyte trafficking. We hypothesize that the exogenous glomerular glycocalyx may reduce the glomerular influx of inflammatory cells during glomerulonephritis. Indeed, administration of mouse glomerular endothelial cell (mGEnC)-derived glycocalyx constituents, or the low-molecular-weight heparin enoxaparin, reduced proteinuria in mice with experimental glomerulonephritis. Glomerular influx of granulocytes and macrophages, as well as glomerular fibrin deposition, was reduced by the administration of mGEnC-derived glycocalyx constituents, thereby explaining the improved clinical outcome. HSglx also inhibited granulocyte adhesion to human glomerular endothelial cells in vitro. Notably, a specific HSglx fraction inhibited both CD11b and L-selectin binding to activated mGEnCs. Mass spectrometry analysis of this specific fraction revealed six HS oligosaccharides, ranging from tetra- to hexasaccharides with 2–7 sulfates. In summary, we demonstrate that exogenous HSglx reduces albuminuria during glomerulonephritis, which is possibly mediated via multiple mechanisms. Our results justify the further development of structurally defined HS-based therapeutics for patients with (acute) inflammatory glomerular diseases, which may be applicable to non-renal inflammatory diseases as well.

Table of Contents Introduction I. The Technology Behind a Geofence Request A. The Sensor Vault B. Warrant Execution 1. Initial data dump 2. Selective expansion 3. Unmasking II. Geofences and [...], Law enforcement is increasingly relying on a new tool when investigating crimes with no suspects: geofence warrants. Geofence warrants take advantage of geofence technology, which constructs a virtually bounded geographic area and identifies all users present within that area during a given time window. Google, the primary recipient of geofence warrants, has adopted a policy of objecting to any geofence request that is not a probable-cause warrant. So far, law enforcement has complied. This has caused courts and litigators to defer the question of whether, under Carpenter v. United States, a probable-cause warrant is necessary. Instead, these parties have located the legality of geofence warrants in less explored regions of the Fourth Amendment as applied to new technologies: probable-cause and particularity requirements, the few exceptions to those requirements, and the proper execution of a warrant. This Note fills an analytical void by providing a comprehensive examination of these less explored regions. The Note first provides a technology primer, detailing the three steps involved in geofence warrants: the initial data dump, selective expansion, and unmasking. It then provides background on relevant Fourth Amendment law, explaining why the familiar "reasonable expectation of privacy" test has not yet proven dispositive in geofence-warrant litigation. After cataloguing burgeoning geofence litigation, the Note examines the initial data dump, identifying the difficulty of meeting probable-cause and particularity requirements due to the inherent breadth of the search. Here the Note answers the question of whether probable cause must be shown for each device included in a digital search, based in part on jurisprudence regarding checkpoints, area warrants, and searches of many people in a commercial location. The Note next examines the selective expansion and unmasking steps, arguing (1) that geofence warrants are unconstitutional general warrants because of the discretion given to law-enforcement officials in warrant execution; and (2) that these steps may impermissibly increase a warrant's scope or constitute multiple searches under one warrant. The Note concludes by considering the broader implications of corporate policy shaping Fourth Amendment guardrails.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.