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Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API)., Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text., Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements., Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule., Materials and Methods: We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR., Results: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12 000 resources/min., Discussion: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases., Conclusion: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

We studied the physiological response to glucose limitation in batch and steady-state (chemostat) cultures of Saccharomyces cerevisiae by following global patterns of gene expression. Glucose-limited batch cultures of yeast go through two sequential exponential growth phases, beginning with a largely fermentative phase, followed by an essentially completely aerobic use of residual glucose and evolved ethanol. Judging from the patterns of gene expression, the state of the cells growing at steady state in glucose-limited chemostats corresponds most closely with the state of cells in batch cultures just before they undergo this "diauxic shift." Essentially the same pattern was found between chemostats having a fivefold difference in steady-state growth rate (the lower rate approximating that of the second phase respiratory growth rate in batch cultures). Although in both cases the cells in the chemostat consumed most of the glucose, in neither case did they seem to be metabolizing it primarily through respiration. Although there was some indication of a modest oxidative stress response, the chemostat cultures did not exhibit the massive environmental stress response associated with starvation that also is observed, at least in part, during the diauxic shift in batch cultures. We conclude that despite the theoretical possibility of a switch to fully aerobic metabolism of glucose in the chemostat under conditions of glucose scarcity, homeostatic mechanisms are able to carry out metabolic adjustment as if fermentation of the glucose is the preferred option until the glucose is entirely depleted. These results suggest that some aspect of actual starvation, possibly a component of the stress response, may be required for triggering the metabolic remodeling associated with the diauxic shift.

Intraspecies genetic diversity has been demonstrated to be important in the pathogenesis and epidemiology of several pathogens, such as HIV, influenza, Helicobacter and Salmonella. It is also important to consider strain-to-strain variation when identifying drug targets and vaccine antigens and developing tools for molecular diagnostics. Here, the authors present a description of the variability in gene expression patterns among ten clinical isolates of Mycobacterium tuberculosis, plus the laboratory strains H37Rv and H37Ra, growing in liquid culture. They identified 527 genes (15 % of those tested) that are variably expressed among the isolates studied. The remaining genes were divided into three categories based on their expression levels: unexpressed (38 %), low to undetectable expression (31 %) and consistently expressed (16 %). The expression categories were compared with functional categories and three biologically interesting gene lists: genes that are deleted among clinical isolates, T-cell antigens and essential genes. There were significant associations between expression variability and the classification of genes as T-cell antigens, involved in lipid metabolism, PE/PPE, insertion sequences and phages, and deleted among clinical isolates. This survey of mRNA expression among clinical isolates of M. tuberculosis demonstrates that genes with important functions can vary in their expression levels between strains grown under identical conditions.

Open source software encourages innovation by allowing users to extend the functionality of existing applications. Treeview is a popular application for the visualization of microarray data, but is closed-source and platform-specific, which limits both its current utility and suitability as a platform for further development. Java Treeview is an open-source, cross-platform rewrite that handles very large datasets well, and supports extensions to the file format that allow the results of additional analysis to be visualized and compared. The combination of a general file format and open source makes Java Treeview an attractive choice for solving a class of visualization problems. An applet version is also available that can be used on any website with no special server-side setup.

We studied the physiological response to limitation by diverse nutrients in batch and steady-state (chemostat) cultures of S. cerevisiae. We found that the global pattern of transcription in steady-state cultures in limiting phosphate or sulfate is essentially identical to that of batch cultures growing in the same medium just before the limiting nutrient is completely exhausted. The massive stress response and complete arrest of the cell cycle that occurs when nutrients are fully exhausted in batch cultures is not observed in the chemostat, indicating that the cells in the chemostat are "poor, not starving." Similar comparisons using leucine or uracil auxotrophs limited on leucine or uracil again showed patterns of gene expression in steady-state closely resembling those of corresponding batch cultures just before they exhaust the nutrient. Although there is also a strong stress response in the auxotrophic batch cultures, cell cycle arrest, if it occurs at all, is much less uniform. Many of the differences among the patterns of gene expression between the four nutrient limitations are interpretable in light of known involvement of the genes in stress responses or in the regulation or execution of particular metabolic pathways appropriate to the limiting nutrient. We conclude that cells adjust their growth rate to nutrient availability and maintain homeostasis in the same way in batch and steady state conditions; cells in steady-state cultures are in a physiological condition normally encountered in batch cultures.

Genomic and full-length cDNA sequences provide opportunities for understanding human gene structure and transcriptional regulatory elements. The simplest regulatory elements to identify are promoters, as their positions are dictated by the location of transcription start sites. We aligned full-length cDNA clones from the Mammalian Gene Collection to the human genome rough draft sequence to estimate the start sites of more than 10,000 human transcripts. We selected genomic sequence just upstream from the 5' end of these cDNA sequences and designated these as putative promoters. We assayed the functions of 152 of these DNA fragments, chosen at random from the entire set, in a luciferase-based transfection assay in four human cultured cell types. Ninety-one percent of these DNA fragments showed significant transcriptional activity in at least one of the cell lines, whereas 89% showed activity in at least two of the lines. We analyzed the distributions of strengths of these promoter fragments in the different cell types and identified likely alternative promoters in a large fraction of the genes. These data indicate that this approach is an effective method for predicting human promoters and provide the first set of functional data collected in parallel for a large set of human promoters.

The genome-wide program of gene expression during the cell division cycle in a human cancer cell line (HeLa) was characterized using cDNA microarrays. Transcripts of >850 genes showed periodic variation during the cell cycle. Hierarchical clustering of the expression patterns revealed coexpressed groups of previously well-characterized genes involved in essential cell cycle processes such as DNA replication, chromosome segregation, and cell adhesion along with genes of uncharacterized function. Most of the genes whose expression had previously been reported to correlate with the proliferative state of tumors were found herein also to be periodically expressed during the HeLa cell cycle. However, some of the genes periodically expressed in the HeLa cell cycle do not have a consistent correlation with tumor proliferation. Cell cycle-regulated transcripts of genes involved in fundamental processes such as DNA replication and chromosome segregation seem to be more highly expressed in proliferative tumors simply because they contain more cycling cells. The data in this report provide a comprehensive catalog of cell cycle regulated genes that can serve as a starting point for functional discovery. The full dataset is available at http://genome-www.stanford.edu/Human-CellCycle/HeLa/.

Microarray-based gene expression analysis identified genes showing ploidy-dependent expression in isogenic Saccharomyces cerevisiae strains that varied in ploidy from haploid to tetraploid. These genes were induced or repressed in proportion to the number of chromosome sets, regardless of the mating type. Ploidy-dependent repression of some G1 cyclins can explain the greater cell size associated with higher ploidies, and suggests ploidy-dependent modifications of cell cycle progression. Moreover, ploidy regulation of the FLO11 gene had direct consequences for yeast development.