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A quantitative model of stasis-type of venous thrombosis in rats is described. The ligated bowel loop was used after provocation by an injection of kaolin. The mesenteric vessels of the loop were cut in a dish filled with distilled water and the extinction of escaped haemoglobin was measured photometrically. Heparin was highly effective in this model. Vessel wall lesion may be used or inducing thrombosis instead of kaolin.
Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.
A model for the partition of charged molecules in aqueous multiphase systems has been developed. The partition coefficient of one component, or the overall partition coefficient of a number of components, between two arbitrary phases is expressed in terms of the difference in electrical potential between the phases (due to electrolytes present in the system), the net charges of the partitioned components and their partition coefficients in a (sometimes hypothetical) uncharged state. The fraction of material in one phase has also been described as a function of the net charges of the partitioned components. The model fits well to experimental data for partition of chromate, pyridine, ribonuclease A, two types of CO-hemoglobin and an enzyme mixture (yeast lysate) in three-phase systems consisting of poly(ethylene glycol), dextran, Ficoll and water. Minor deviations from the model are construed to be a pH-dependent uptake of ions. The data have also been used to detect differences in solvation of similar proteins, as well as the presence of several forms of some glycolytic enzymes present in yeast lysate.
The knee joint in rabbits has been used as an arthritis model for the study of acute immunologic injury. Histologic examination of synovium plus a standardized procedure for irrigating inflammatory exudate from the joint allowed study of damage due to immune complexes, urate crystals, and Arthus type vascular lesions by multiple parameters. With this model Arthus lesions could be abolished with neutrophil depletion and reconstituted with intra-articular injection of neutrophil suspension. The rate and degree of injury could also be diminished by depletion of complement components.
A test model is presented which, in comparison with the conventional models of skin transplantation or graft-versus-host (GvH) reaction in mice, permits a more sensitive quantitative evaluation of T cell inhibition in vivo. Prospective donors (type AA) are immunized with prospective recipient material (type AB); the resulting T cell reaction of A versus B is inhibited by consecutive treatment. Extent of inhibition can be evaluated after transfer of the pretreated AA material onto AB recipients by calculation of remaining GvH reactivity, if compared to adequate control tranfers. In this model the target animal for T cell reactivity (the AB recipient) remains untouched from immunosuppressive regimen.
We describe a single-locus quantitative genetic model that incorporates effects due to DNA methylation. Extending Fisher's decomposition of the genotypic value, we distinguish two quantities to predict an individual's phenotypic or genetic values: the "basic genetic value" and the "expressed genetic value". We show how these quantities relate to the concept of breeding value and derive their corresponding formulas, along with those for phenotypic variance and covariance between relatives. The resulting parameters are influenced by several factors, including the population distribution of DNA methylation levels, the functional relationship between methylation and phenotype, the magnitudes of genetic and methylation effects, and allele frequencies. We show that under the conditions modeled, the presence of DNA methylation does not bias estimated breeding values.
BACKGROUND: Pseudomonas aeruginosa has an extraordinary capacity for resistance emergence during treatment, even with newer antipseudomonals. There is a gap in understanding how resistance mechanisms affect the time-course of bacterial response to these newer agents. Traditional approaches for predicting pathogen response to an antibiotic do not apply to combination therapy. We aimed to develop a modelling framework to predict treatment response based on resistome information, using isolates of the worldwide-disseminated high-risk clone sequence type (ST) 235 and β-lactam antibiotics as the example. METHODS: In this hollow-fibre in-vitro infection study, we used three extensively drug-resistant ST235 clinical isolates from the national collection of the Clinical Microbiology Department of the Hospital Son Espases (Palma de Mallorca, Spain) that were hospital-acquired, were isolated following routine microbiological procedures from different patients between 2017 and 2022, were susceptible to ceftolozane-tazobactam, and had different levels of meropenem resistance. The selected isolates (ST235-05, ST235-09, and ST235-10) showed classical β-lactam resistance mechanisms pre-treatment. The isolates were investigated in 240-h dynamic hollow-fibre in-vitro infection models (HFIMs). The studies exposed the isolates to pharmacokinetic profiles of ceftolozane-tazobactam (simulating 1 g of ceftolozane and 0·5 g of tazobactam as a 3-h infusion every 8 h) and meropenem (simulating 6 g per day continuous infusion) as observed in hospitalised patients, as monotherapy and in combination. Treatment response was assessed through the quantification of the time-courses of viable total and resistant bacteria. Whole-genome sequencing identified the mechanisms of emerging resistance. A quantitative systems pharmacology (QSP) approach was used to model total and resistant bacterial counts and corresponding pharmacokinetic data from the HFIM. Monte Carlo simulations were used to predict treatment responses in 1000 virtual infected patients treated with ceftolozane-tazobactam and meropenem as monotherapies or in combination over 10 days. FINDINGS: In the HFIMs, each antibiotic alone amplified resistance by approximately 48 h for all isolates; that is, monotherapies resulted in a higher concentration of resistant bacteria compared with the control treatment at the respective time, except ceftolozane-tazobactam against ST235-10. Combination of ceftolozane-tazobactam and meropenem was synergistic (bacterial counts ≥2 log10 colony forming units [CFU] per mL lower than the best performing monotherapy and initial inoculum) against all isolates and suppressed resistance. Against ST235-10, ceftolozane-tazobactam monotherapy reduced counts to less than 1 log10 CFU per mL from 192 h onwards, whereas the combination reached less than 1 log10 CFU per mL by 24 h. Across strains, population genomics confirmed monotherapy failures were associated with emerging resistance mechanisms (ceftolozane-tazobactam: ampC Ω-loop mutations; meropenem: ftsl mutation). The developed QSP model incorporated baseline resistance mechanisms and those emerging in resistant mutant subpopulations. The model explained and predicted the monotherapy failures involving amplification of these subpopulations, and synergistic killing and resistance suppression by the combination. Simulations using the model predicted bacterial regrowth above the initial inoculum for more than 90% of patients after 0 to approximately 3 days for meropenem monotherapy across all strains and for ceftolozane-tazobactam monotherapy against ST235-05 and ST235-09. For ceftolozane-tazobactam monotherapy against ST235-10, regrowth was predicted for approximately 30% of patients. In contrast, the simulations predicted sustained bacterial killing of at least 2 log10 CFU per mL compared with the initial inoculum by the combination for more than 89% of patients across all strains. INTERPRETATION: To our knowledge, this model is the first to characterise and predict the time-course of responses of clinical isolates to antibiotics only by the resistance mechanisms present and their complex interplay, representing a step towards pathogen-specific, personalised medicine. FUNDING: Australian National Health and Medical Research Council.
A simple immunoprecipitation--dissociation technique for large scale purification of antibodies is described, which comprises selective denaturation of the antigen and recovery of the antibody fraction by exclusion chromatography at low pH. Its use is illustrated by the purification of antibodies to pregnancy zone protein. A purification factor of about 60 was achieved. An antigen consumption electroimmunoassay was also developed which permits quantitative determination of the antigen binding activity of antibodies with a given specificity. The methods have general application.
Hematopoietic stem and progenitor cells (HSPCs) respond to infections, inflammation, and regenerative challenges using emergency myelopoiesis (EM) pathways to amplify myeloid cell production. However, it remains unclear how various EM inducers regulate HSPCs using shared or distinct molecular mechanisms. Here, we generate a comprehensive and generalizable cell annotation method (HemaScribe) and a refined quantitative model of hematopoietic differentiation (HemaScape) using single-cell RNA sequencing (scRNA-seq) of murine HSPCs, which we apply to a broad range of EM modalities. We uncover multiple strategies for enhancing myelopoiesis that act at different levels of the HSPC hierarchy and are associated with both unique and shared transcriptional response modules. In particular, we identify a myeloid progenitor-based EM activation module across diverse inflammatory challenges that is conserved in humans and informs outcomes in adult and pediatric acute myeloid leukemia. Our work illuminates fundamental regulatory mechanisms in hematopoietic regeneration that have direct translational applications in disease contexts.
PURPOSE: Biallelic HPDL variants have been identified as the cause of a progressive childhood-onset movement disorder, with a broad clinical spectrum from severe neurodevelopmental disorder to juvenile-onset pure hereditary spastic paraplegia type 83. This study aims at delineating the geno- and phenotypic spectra of patients with HPDL-related disease, quantitatively modeling the natural history, and uncovering genotype-phenotype associations. METHODS: A cross-sectional analysis of 90 published and 1 novel case was performed, using a Human-Phenotype-Ontology-based approach. Unsupervised phenotypic clustering was used alongside in silico analyses to identify distinct patient subgroups. RESULTS: The study models the natural history of the HPDL-related disease in a global cohort, clarifying the molecular and phenotypic spectrum and identifying 3 distinct subgroups characterized by differences in onset, clinical trajectories, and survival. It establishes genotype-phenotype associations, showing that the presence of moderately pathogenic missense variants in 1 allele leads to a milder, spastic paraplegic phenotype with later disease onset, whereas biallelic, highly pathogenic missense or truncating variants are associated with a more severe phenotype and reduced life span. CONCLUSION: Quantitative and unbiased natural history modeling in HPDL-related disease reveals significant genotype-phenotype associations, providing a foundation for variant interpretation, anticipatory guidance, and choice of outcome measures in future prospective and functional studies.
Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. These frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit-host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.
A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.
1. The kinetic properties of mitochondrial creatine phosphokinase (Km for all substrates and maximal rates of the forward and reverse reaction) have been studied. Since (a) Km value for MgADP- (0.05 mM) and creatine phosphate (0.5 mM) are significantly lower than Km for MgATP2- (0.7 mM) and creatine (5.0 mM) and (b) maximal rate of the reverse reaction (creatine phosphate + ADP leads to ATP + creatine) equal to 3.5 mumol times min-1 times mg-1 is essentially higher than maximal rate of the forward reaction (0.8 mumol times min-1 times mg-1), ATP synthesis from ADP and creatine phosphate is kinetically preferable over the forward reaction. 2. A possible regulatory role of Mg2+ ions in the creatine phosphokinase reaction has been tested. It has been shown that in the presence of all substrates and products of the reaction the ratio of the rates of forward and reverse reactions can be effectively regulated by the concentration of Mg2+ ions. At limited Mg2+ concentrations creatine phosphate is preferably synthesized while at high Mg2+ concentrations (more ATP in the reaction medium) ATP synthesis takes place. 3. The kinetic (mathematical) model of the mitochondrial creatine phosphokinase reaction has been developed. This model accounts for the existence of a variety of molecular forms of adenine nucleotides in solution and the formation of their complexes with magnesium. It is based on the assumption that the mitochondrial creatine phosphokinase reactions mechanism is analogous to that for soluble isoenzymes. 4. The dependence of the overall rate of the creatine phosphokinase reaction on the concentration of total Mg2+ ions calculated from the kinetic model quantitatively correlates with the experimentally determined dependence through a wide range of substrates (ATP, ADP, creatine and creatine phosphate) concentration. The analysis of the kinetic model demonstrates that the observed regulatory effect of Mg2+ on the overall reaction rate can be expained by (a) the sigmoidal variation in the concentration of the MgADP- complex resulting from the competition between ATP AND ADP for Mg2+ and (b) the high affinity of the enzyme to MgADP-. 5. The results predicted by the model for the behavior of mitochondrial creatine phosphokinase under conditions of oxidative phosphorylation point to an intimate functional interaction of mitochondrial creatine phosphokinase and ATP-ADP translocase.
PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.
Bacterial operons often contain intergenic transcription terminators that terminate some, but not all, RNA polymerase molecules. In these operons, the level of terminator readthrough determines downstream gene expression and helps establish protein ratios among co-regulated genes. Despite its critical role in maintaining stoichiometric gene expression, terminator strength remains difficult to predict from DNA sequence. The necessary features of a major class of bacterial terminators - intrinsic terminators - have been known for half a century, but a strong sequence-function model has yet to be developed. Here, we summarize high-throughput approaches for probing the sequence determinants of intrinsic termination efficiency and discuss the impact of trans-acting factors on this sequence-function relationship. Building on the main lessons from these studies, we map out the experimental challenges that must be circumvented to establish a quantitative model for termination efficiency.
DNA-protien crosslinks produced in mouse leukemia L1210 cells by trans-Pt(II)diamminedichloride were quantitated using the technique of DNA alkaline elution. DNA single-strand segments that were or were not linked to protein were separable into distinct components by alkaline elution after exposure of the cells to 2--15 kR of X-ray. Protein-linked DNA strands were separated on the basis of their retention of filters at pH 12 while free DNA strands of the size generated by 2--15 kR of X-ray passed rapidly through the filters. The retention of protein-linked DNA strands was attributable to adsorption of protein to the filter under the conditions of alkaline elution. The results obeyed a simple quantitative model according to which the frequency of DNA-protein crosslinks could be calculated.
A lambda light chain, isolated from an immunoglobulin G molecule, was found to reversibly precipitate at low temperatures. This cryoprecipitation was a function of pH, ionic strength, protein concentration, and time as well as temperature. The lambda chain underwent a cooperative conformational change as the temperature was lowered from 26 to 0 degrees C as judged by ultraviolet difference spectroscopy and circular dichroism. Normal lambda chains showed no conformational change. By difference spectroscopy it was possible to calculate the equilibrium constant governing the conformational change. The change was strongly exothermic (delta H approximately -80 kcal mol-1) and accompanied by a large decrease in entropy (delta S approximately -280 eu). The midpoint of the transition was dependent on the initial protein concentration, suggesting that only the noncovalent dimer of the lambda chain exhibited the conformational change. The existence of a monomer-dimer eqiulibrium (KA approximately 4 X 10(5) M-1) was confirmed by sedimentation velocity. No conformational change was observed by circular dichroism at concentrations where greater than 95% of lambda chain was in the form of a monomer. Although high ionic strength inhibited cryoprecipitation, it had no effect on the conformational change. Stabilization of the dimer by forming an interchain disulfide bond between two monomers abolished both the conformational change and cryoprecipitation. A fragment corresponding to the constant region was isolated from both peptic and tryptic digests of the lambda chain. This fragment neither cryoprecipitated nor showed temperature dependence conformational changes. It proved impossible to isolate a fragment corresponding to the variable region. Both qualitative and quantitative models are presented to account for the behavior of the lambda chain at low temperatures.
Human leukocyte antigen (HLA) disparity between donors and recipients is a key determinant triggering intense alloreactivity, leading to a lethal complication, namely, acute graft-versus-host disease (aGVHD), after allogeneic transplantation. Moreover, aGVHD remains a cause of mortality after HLA-matched allogeneic transplantation. Protocols for HLA-haploidentical hematopoietic cell transplantation (haploHCT) have been established successfully and widely applied, further highlighting the urgency of performing panoramic screening of non-HLA variations correlated with aGVHD. On the basis of our time-consecutive large haploHCT cohort (with a homogenous discovery set and an extended confirmatory set), we first delineated the genetic landscape of 1366 samples to quantitatively model aGVHD risk by assessing the contributions of HLA and non-HLA genes together with clinical factors. In addition to identifying multiple loss-of-function (LoF) risk variations in non-HLA coding genes, our data-driven study revealed that non-HLA genetic variations, independent of HLA disparity, contributed the most to the occurrence of aGVHD. This unexpected major effect was verified in an independent cohort that received HLA-identical sibling HCT. Subsequent functional experiments further revealed the roles of a representative non-HLA LoF gene and LoF gene pair in regulating the alloreactivity of primary human T cells. Our findings highlight the importance of non-HLA genetic risk in the new era of transplantation and propose a new direction to explore the immunogenetic mechanism of alloreactivity and to optimize donor selection strategies for allogeneic transplantation.