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At least 217 records · Page 12Linked to original sources

The effectiveness of implementing the weight-based heparin nomogram as a practice guideline.

OBJECTIVE: To determine the effectiveness of the nomogram in a community hospital that implemented it as a practice guideline. DESIGN: A nonexperimental, retrospective time series. SETTING: A 600-bed community teaching hospital and regional referral center in Phoenix, Ariz. PATIENTS: The study population included 591 consecutive patients with venous thromboembolism, treated over a 5-year study period. METHODS: During this period, the weight-based heparin nomogram was adapted into a preprinted order sheet and distributed to the hospital wards. The main outcome variables were the time to achieve a therapeutic activated partial thromboplastin time and the rate of bleeding complications. RESULTS: Voluntary implementation of the nomogram steadily increased, reaching 94%. Comparison of the periods before and after 50% implementation demonstrated an increase in initial heparin dose (1185 vs 1420 U/h, P < .001), a decrease in time to achieve therapeutic activated partial thromboplastin time (19.6 vs 11.8 hours), a decrease in the variance of this parameter (25 vs 4 hours, P < .001), and no change in bleeding rates. The proportion of patients achieving a therapeutic activated partial thromboplastin time within 24 hours decreased from 97% to 86% when the results from our previous randomized controlled trial (efficacy) are compared with the present results (effectiveness). CONCLUSIONS: The weight-based heparin nomogram was well accepted by clinicians at our institution and led to more aggressive heparin dosing and improvements in intermediate outcomes, without increasing bleeding. Mitigation of benefit is likely to occur when practice guidelines are moved from the realm of efficacy research into clinical practice. Therefore, the effectiveness of such measures requires monitoring.

Drug Administration Schedule↗

Effective patient scheduling.

Patient appointments and scheduling of patients and physicians are the first step in any health-care delivery system. This paper deals with the conventional method usually found in preprinted appointment books, and the "wave" method. A method of testing this system is any practice environment is described, together with the comparative benefits of the wave method over the conventional method of scheduling. This paper also exemplifies one kind of research that can be accomplished in the private, ambulatory sector of medicine.

Appointments and Schedules↗

A cost-effective system for obtaining comprehensive cardiovascular information on the critically ill patient.

A relatively simple and inexpensive data management system is described with which comprehensive physiologic and cardiovascular profiles are produced. The system is comprised of a desk-top programmable calculator interfaced with an acoustic digitizer input, and an X-Y plotter, with alphanumeric printing output capability. Numerical clinical data such as intracardiac pressures and blood gas values are entered into the calculator via the keyboard, and graphical data such as dye-dilution curves or ventricular contours are digitized with a pen stylus on the acoustic tablet. The data are processed in the calculator and the results charted in familiar and readily interpreted bar-graph format on preprinted charts on the X-Y plotter. The entire system is inexpensive and compact enough to be applicable to small- and medium-size community hospitals.

Cardiovascular Physiological Phenomena↗

[The importance of hormone examinations in ovulation induction (author's transl)].

Those hormone-determination methods were reported by the authors which help to make the ovary response visible for the experts during the ovulation induction. They also dealt with the determination of basal temperature measuring, oestrogen, pregnandiol, progesterone, oestradiol-17beta, FSH, LH, epimestrol and clomiphen. After the routine determination of the above mentioned parameter a preprinted sheet was done, where every treated case was illustrated graphically. From these cases some of the typical ones were shown and analyzed. The determination of hormonal releasing curves characteristic of hyperstimulation, and the importance of these most dangerous complication was emphasized.

Adult↗

Patient information systems: unbiased information is key.

Successful patient information systems must have user-friendly services to transfer vast amounts of information. Whether it is preprinted discharge instructions for standard wound care, an algorithm-based triage discussion of one's chest pain, or simply a database to search out the current recommendations for flu shots or pediatric immunizations, the challenge for patient education in the communications revolution is high stakes indeed.

Humans↗

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)-Neanderthals and Denisovans-and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

Journal Article↗

A DUAL MTOR/NAD+ ACTING GEROTHERAPY.

The geroscience hypothesis states that a therapy that prevents the underlying aging process should prevent multiple aging related diseases. The mTOR (mechanistic target of rapamycin)/insulin and NAD+ (nicotinamide adenine dinucleotide) pathways are two of the most validated aging pathways. Yet, it's largely unclear how they might talk to each other in aging. In genome-wide CRISPRa screening with a novel class of N-O-Methyl-propanamide-containing compounds we named BIOIO-1001, we identified lipid metabolism centering on SIRT3 as a point of intersection of the mTOR/insulin and NAD+ pathways. In vivo testing indicated that BIOIO-1001 reduced high fat, high sugar diet-induced metabolic derangements, inflammation, and fibrosis, each being characteristic of non-alcoholic steatohepatitis (NASH). An unbiased screen of patient datasets suggested a potential link between the anti-inflammatory and anti-fibrotic effects of BIOIO-1001 in NASH models to those in amyotrophic lateral sclerosis (ALS). Directed experiments subsequently determined that BIOIO-1001 was protective in both sporadic and familial ALS models. Both NASH and ALS have no treatments and suffer from a lack of convenient biomarkers to monitor therapeutic efficacy. A potential strength in considering BIOIO-1001 as a therapy is that the blood biomarker that it modulates, namely plasma triglycerides, can be conveniently used to screen patients for responders. More conceptually, to our knowledge BIOIO-1001 is a first therapy that fits the geroscience hypothesis by acting on multiple core aging pathways and that can alleviate multiple conditions after they have set in.

Preprint↗

Diversity of ribosomes at the level of rRNA variation associated with human health and disease.

Ribosomal DNA and RNA (rDNA and rRNA) sequences are usually discarded from sequencing analyses. But with hundreds of copies of rDNA genes it is unknown whether they possess sequence variations that form different types of ribosomes that affect human physiology and disease. Here, we developed an algorithm for variant-calling between paralog genes (termed RGA) and compared rDNA variations found in short- and long-read sequencing data from the 1,000 Genomes Project (1KGP) and Genome In A Bottle (GIAB). We additionally developed a novel protocol for long-read sequencing full-length rRNA (RIBO-RT) from actively translating ribosomes. Our analyses identified hundreds of rDNA variants, most of which, surprisingly, are short insertion-deletions (indels) and dozens of highly abundant rRNA variants that are incorporated into translationally active ribosomes. To visualize variant ribosomes at the single cell level, we developed an in-situ rRNA sequencing method (SWITCH-seq) which revealed that variants are co-expressed within individual cells. Strikingly, by analyzing rDNA, we found that variants assemble into distinct ribosome subtypes. We discovered that these subtypes acquire different rRNA structures by successfully employing dimethyl sulfate (DMS) probing of full length rRNA. With this atlas we investigated rRNA variation changes across human tissues and cancer types. This revealed tissue-specific rRNA subtype expression in endoderm/ectoderm-derived tissues. In cancer, low abundant rRNA variants can become highly expressed, which suggests the presence of cancer-specific ribosomes. Together, this study identifies and comprehensively characterizes the diversity of ribosomes at the level of rRNA variants which is dominated by indel variants, their chromosomal location and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Journal Article↗

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK in female.

Alzheimer's disease, the most common age-related neurodegenerative disease, is closely associated with both amyloid-&#xdf; plaque and neuroinflammation. Two thirds of Alzheimer's disease patients are females and they have a higher disease risk. Moreover, women with Alzheimer's disease have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration. To identify how sex difference induces structural brain changes, we performed unbiased massively parallel single nucleus RNA sequencing on Alzheimer's disease and control brains focusing on the middle temporal gyrus, a brain region strongly affected by the disease but not previously studied with these methods. We identified a subpopulation of selectively vulnerable layer 2/3 excitatory neurons that that were RORB-negative and CDH9-expressing. This vulnerability differs from that reported for other brain regions, but there was no detectable difference between male and female patterns in middle temporal gyrus samples. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of diseased brains differed between males and females. Combining single cell transcriptomic data with results from genome-wide association studies (GWAS), we identified MERTK genetic variation as a risk factor for Alzheimer's disease selectively in females. Taken together, our single cell dataset revealed a unique cellular-level view of sex-specific transcriptional changes in Alzheimer's disease, illuminating GWAS identification of sex-specific Alzheimer's risk genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of Alzheimer's disease.

Journal Article↗

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗

Benchmarking large language models for genomic knowledge with GeneTuring.

Large language models (LLMs) show promise in biomedical research, but their effectiveness for genomic inquiry remains unclear. We developed GeneTuring, a benchmark consisting of 16 genomics tasks with 1,600 curated questions, and manually evaluated 48,000 answers from ten LLM configurations, including GPT-4o (via API, ChatGPT with web access, and a custom GPT setup), GPT-3.5, Claude 3.5, Gemini Advanced, GeneGPT (both slim and full), BioGPT, and BioMedLM. A custom GPT-4o configuration integrated with NCBI APIs, developed in this study as SeqSnap, achieved the best overall performance. GPT-4o with web access and GeneGPT demonstrated complementary strengths. Our findings highlight both the promise and current limitations of LLMs in genomics, and emphasize the value of combining LLMs with domain-specific tools for robust genomic intelligence. GeneTuring offers a key resource for benchmarking and improving LLMs in biomedical research.

Benchmark↗

Functional genomic analysis of non-canonical DNA regulatory elements of the aryl hydrocarbon receptor.

The aryl hydrocarbon receptor (AHR) is a ligand-dependent transcription factor activated by environmental toxicants like halogenated and polycyclic aromatic hydrocarbons, which then binds to DNA and regulates gene expression. AHR is implicated in numerous physiological processes, including liver and immune function, cell cycle control, oncogenesis, and metabolism. Traditionally, AHR binds a consensus DNA sequence (GCGTG), the xenobiotic response element (XRE), recruits coregulators, and modulates gene expression. Yet, recent evidence suggests AHR can also regulate gene expression via a non-consensus sequence (GGGA), termed the non-consensus XRE (NC-XRE). The prevalence and functional significance of NC-XRE motifs in the genome have remained unclear. While ChIP and reporter studies hinted at AHR-NC-XRE interactions, direct evidence for transcriptional regulation in a native context was lacking. In this study, we analyzed AHR binding to NC-XRE sequences genome-wide in mouse liver, integrating ChIP-seq and RNA-seq data to identify candidate AHR target genes containing NC-XRE motifs in their regulatory regions. We found NC-XRE motifs in 82% of AHR-bound DNA, significantly enriched compared to random regions, and present in promoters and enhancers of AHR targets. Functional genomics on the Serpine1 gene revealed that deleting NC-XRE motifs reduced TCDD-induced Serpine1 upregulation, demonstrating direct regulation. These findings provide the first direct evidence for AHR-mediated regulation via NC-XRE in a natural genomic context, advancing our understanding of AHR-bound DNA and its impact on gene expression and physiological relevance.

Journal Article↗

Beyond antibiotic resistance: the whiB7 transcription factor coordinates an adaptive response to alanine starvation in mycobacteria.

Pathogenic mycobacteria are a significant cause of morbidity and mortality worldwide. These bacteria are highly intrinsically drug resistant, making infections challenging to treat. The conserved whiB7 stress response is a key contributor to mycobacterial intrinsic drug resistance. Although we have a comprehensive structural and biochemical understanding of WhiB7, the complex set of signals that activate whiB7 expression remain less clear. It is believed that whiB7 expression is triggered by translational stalling in an upstream open reading frame (uORF) within the whiB7 5' leader, leading to antitermination and transcription into the downstream whiB7 ORF. To define the signals that activate whiB7, we employed a genome-wide CRISPRi epistasis screen and identified a diverse set of 150 mycobacterial genes whose inhibition results in constitutive whiB7 activation. Many of these genes encode amino acid biosynthetic enzymes, tRNAs, and tRNA synthetases, consistent with the proposed mechanism for whiB7 activation by translational stalling in the uORF. We show that the ability of the whiB7 5' regulatory region to sense amino acid starvation is determined by the coding sequence of the uORF. The uORF shows considerable sequence variation among different mycobacterial species, but it is universally and specifically enriched for alanine. Providing a potential rationalization for this enrichment, we find that while deprivation of many amino acids can activate whiB7 expression, whiB7 specifically coordinates an adaptive response to alanine starvation by engaging in a feedback loop with the alanine biosynthetic enzyme, aspC. Our results provide a holistic understanding of the biological pathways that influence whiB7 activation and reveal an extended role for the whiB7 pathway in mycobacterial physiology, beyond its canonical function in antibiotic resistance. These results have important implications for the design of combination drug treatments to avoid whiB7 activation, as well as help explain the conservation of this stress response across a wide range of pathogenic and environmental mycobacteria.

Preprint↗

Hybridization breaks species barriers in long-term coevolution of a cyanobacterial population.

Bacterial species often undergo rampant recombination yet maintain cohesive genomic identity. Ecological differences can generate recombination barriers between species and sustain genomic clusters in the short term. But can these forces prevent genomic mixing during long-term coevolution? Cyanobacteria in Yellowstone hot springs comprise several diverse species that have coevolved for hundreds of thousands of years, providing a rare natural experiment. By analyzing more than 300 single-cell genomes, we show that despite each species forming a distinct genomic cluster, much of the diversity within species is the result of hybridization driven by selection, which has mixed their ancestral genotypes. This widespread mixing is contrary to the prevailing view that ecological barriers can maintain cohesive bacterial species and highlights the importance of hybridization as a source of genomic diversity.

Journal Article↗

Quorum-sensing agr system of Staphylococcus aureus primes gene expression for protection from lethal oxidative stress.

The agr quorum-sensing system links Staphylococcus aureus metabolism to virulence, in part by increasing bacterial survival during exposure to lethal concentrations of H2O2, a crucial host defense against S. aureus. We now report that protection by agr surprisingly extends beyond post-exponential growth to the exit from stationary phase when the agr system is no longer turned on. Thus, agr can be considered a constitutive protective factor. Deletion of agr increased both respiration and fermentation but decreased ATP levels and growth, suggesting that &#x394;agr cells assume a hyperactive metabolic state in response to reduced metabolic efficiency. As expected from increased respiratory gene expression, reactive oxygen species (ROS) accumulated more in the agr mutant than in wild-type cells, thereby explaining elevated susceptibility of &#x394;agr strains to lethal H2O2 doses. Increased survival of wild-type agr cells during H2O2 exposure required sodA, which detoxifies superoxide. Additionally, pretreatment of S. aureus with respiration-reducing menadione protected &#x394;agr cells from killing by H2O2. Thus, genetic deletion and pharmacologic experiments indicate that agr helps control endogenous ROS, thereby providing resilience against exogenous ROS. The long-lived "memory" of agr-mediated protection, which is uncoupled from agr activation kinetics, increased hematogenous dissemination to certain tissues during sepsis in ROS-producing, wild-type mice but not ROS-deficient (Nox2-/-) mice. These results demonstrate the importance of protection that anticipates impending ROS-mediated immune attack. The ubiquity of quorum sensing suggests that it protects many bacterial species from oxidative damage.

Staphylococcus aureus↗

Homologous chromosome recognition via nonspecific interactions.

In many organisms, most notably Drosophila, homologous chromosomes in somatic cells associate with each other, a phenomenon known as somatic homolog pairing. Unlike in meiosis, where homology is read out at the level of DNA sequence complementarity, somatic homolog pairing takes place without double strand breaks or strand invasion, thus requiring some other mechanism for homologs to recognize each other. Several studies have suggested a "specific button" model, in which a series of distinct regions in the genome, known as buttons, can associate with each other, presumably mediated by different proteins that bind to these different regions. Here we consider an alternative model, which we term the "button barcode" model, in which there is only one type of recognition site or adhesion button, present in many copies in the genome, each of which can associate with any of the others with equal affinity. An important component of this model is that the buttons are non-uniformly distributed, such that alignment of a chromosome with its correct homolog, compared with a non-homolog, is energetically favored; since to achieve nonhomologous alignment, chromosomes would be required to mechanically deform in order to bring their buttons into mutual register. We investigated several types of barcodes and examined their effect on pairing fidelity. We found that high fidelity homolog recognition can be achieved by arranging chromosome pairing buttons according to an actual industrial barcode used for warehouse sorting. By simulating randomly generated non-uniform button distributions, many highly effective button barcodes can be easily found, some of which achieve virtually perfect pairing fidelity. This model is consistent with existing literature on the effect of translocations of different sizes on homolog pairing. We conclude that a button barcode model can attain highly specific homolog recognition, comparable to that seen in actual cells undergoing somatic homolog pairing, without the need for specific interactions. This model may have implications for how meiotic pairing is achieved.

Preprint↗

Lanthanide-dependent isolation of phyllosphere methylotrophs selects for a phylogenetically conserved but metabolically diverse community.

Lanthanides have emerged as important metal cofactors for biological processes. Lanthanide-associated metabolisms are well-studied in leaf symbiont methylotrophic bacteria, which utilize reduced one-carbon compounds such as methanol for growth. Yet, the importance of lanthanides in plant-microbe interactions and on microbial physiology and colonization in plants remains poorly understood. To investigate this, 344 pink-pigmented facultative methylotrophs were isolated from soybean leaves by selecting for bacteria capable of methanol oxidation with lanthanide cofactors, but none were obligately lanthanide-dependent. Phylogenetic analyses revealed that all strains were nearly identical to each other and are part of the extorquens clade of Methylobacterium, despite variability in genome and plasmid sizes. Strain-specific identification was enabled by the higher resolution provided with rpoB compared to 16S rRNA as marker genes. Despite the low strain-level diversity, the metabolic capabilities of the collection diverged greatly. Strains encoding identical lanthanide-dependent alcohol dehydrogenases displayed significantly different growth rates and/or final ODs from each other on alcohols in the presence and absence of lanthanides. Several strains also lacked well-characterized lanthanide-associated genes thought to be important for phyllosphere colonization. Additionally, 3% of our isolates were capable of growth on sugars and 23% were capable of growth on aromatic acids, substantially expanding the range of substrates utilized by Methylobacterium extorquens in the phyllosphere. Our findings suggest that the expansion of metabolic capabilities, as well as differential usage of lanthanides and their influence on metabolism, among closely related strains point to evolution of niche partitioning strategies to promote colonization of the phyllosphere.

Journal Article↗

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank.

Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant () and 17 nominally significant () gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG-asthma () and USH2A-visual impairment (). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity.

Preprint↗