Endoreplication Controls Cell Fate Maintenance

Cell-fate specification is typically thought to precede and determine cell-cycle regulation during differentiation. Here we show that endoreplication, also known as endoreduplication, a specialized cell-cycle variant often associated with cell differentiation but also frequently occurring in malignant cells, plays a role in maintaining cell fate. For our study we have used Arabidopsis trichomes as a model system and have manipulated endoreplication levels via mutants of cell-cycle regulators and overexpression of cell-cycle inhibitors under a trichome-specific promoter. Strikingly, a reduction of endoreplication resulted in reduced trichome numbers and caused trichomes to lose their identity. Live observations of young Arabidopsis leaves revealed that dedifferentiating trichomes re-entered mitosis and were re-integrated into the epidermal pavement-cell layer, acquiring the typical characteristics of the surrounding epidermal cells. Conversely, when we promoted endoreplication in glabrous patterning mutants, trichome fate could be restored, demonstrating that endoreplication is an important determinant of cell identity. Our data lead to a new model of cell-fate control and tissue integrity during development by revealing a cell-fate quality control system at the tissue level.     

Strain-rate dependent material properties of the porcine and human kidney capsule

This study was performed to characterize the mechanical properties of the kidney capsular membrane at strain-rates associated with blunt abdominal trauma. Uniaxial quasi-static and dynamic tensile experiments were performed on fresh, unfrozen porcine and human renal capsules at deformation rates ranging from 0.0001 to 7 m/s (strain-rates of 0.005-250 s(-1)). Single stroke, dynamic tests were performed on samples of porcine renal capsule at strain-rates of 0.005 s(-1) (n = 33), 0.05 s(-1) (n = 17), 0.5 s(-1) (n = 38), 2 s(-1) (n = 10), 4 s(-1) (n = 10), 50 s(-1) (n = 21), 100 s(-1) (n = 18), 150 s(-1) (n = 17), 200 s(-1) (n = 10), and 250 s(-1) (n = 17). Due to limited availability of human tissues, only quasi-static tests were performed (0.005 s(-1), n = 25). Porcine renal capsule properties were found to match the material properties of human capsular tissue sufficiently well such that porcine tissue material can be used as a human test surrogate. The apparent elastic modulus and breaking stress of the porcine renal capsule were observed to increase significantly with increasing strain-rate (p < 0.01). Breaking strain was inversely related to strain-rate (p < 0.01). The effect of increasing strain-rate on material properties diminished appreciably at rates exceeding 150 s(-1). Empirically derived mathematical models of constitutive behavior were developed using a hyperelastic/viscoelastic Ogden formulation, as well as a Cowper-Symonds law material curve multiplication.     

Remodeling of the uterine artery during and early after pregnancy in the mouse

Biomechanics and Modeling in Mechanobiology - Pregnancy associates with dramatic changes in maternal cardiovascular physiology that ensure that the utero-placental circulation can support the...     

Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment

Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate the feasibility of metabolites as temporal biomarkers of clinical outcomes. Serial serum specimens collected prospectively from lung cancer patients were analyzed using both nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography mass spectrometry (GC–MS). Multivariate statistical analysis consisted of unsupervised principal component analysis or orthogonal partial least squares discriminant analysis with significance assessed using a cross-validated ANOVA. The metabolite profiles were reflective of the temporal distinction between patient samples before during and after receiving therapy (¹H-NMR, p < 0.001: and GC–MS p < 0.01). Disease progression and survival were strongly correlative with the GC–MS metabolite data whereas stage and cancer type were associated with ¹H-NMR data. Metabolites such as hydroxylamine, tridecan-1-ol, octadecan-1-ol, were indicative of survival (GC–MS p < 0.05) and metabolites such as tagatose, hydroxylamine, glucopyranose, and threonine that were reflective of progression (GC–MS p < 0.05). Metabolite profiles have the potential to act as prognostic markers of clinical outcomes for lung cancer patients. Serial ¹H-NMR measurements appear to detect metabolites diagnostic of tumor pathology, while GC–MS provided data better related to prognostic clinical outcomes, possibility due to physiochemical bias related to specific biochemical pathways. These results warrant further study in a larger cohort and with various treatment options.     

A database and tool, IM Browser, for exploring and integrating emerging gene and protein interaction data forDrosophila

Background  

Biological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins or genes as nodes linked by interactions. Several programs have been developed for graphical representation and analysis of interaction data, yet there remains a need for alternative programs that can provide casual users with rapid easy access to many existing and emerging data sets.     

Functional Connectivity in the Brain Estimated by Analysis of Gamma Events

It is known that gamma activity is generated by local networks. In this paper we introduced a new approach for estimation of functional connectivity between neuronal networks by measuring temporal relations between peaks of gamma event amplitudes. We have shown in freely moving rats that gamma events recorded between electrodes 1.5 mm apart in the majority of cases, are generated by different neuronal modules interfering with each other. The map of functional connectivity between brain areas during the resting state, created based on gamma event temporal relationships is in agreement with anatomical connections and with maps described by fMRI methods during the resting state. The transition from the resting state to exploratory activity is accompanied by decreased functional connectivity between most brain areas. Our data suggest that functional connectivity between interhemispheric areas depends on GABAergic transmission, while intrahemispheric functional connectivity is kainate receptor dependent. This approach presents opportunities for merging electrographic and fMRI data on brain functional connectivity in normal and pathological conditions.     

Trends in prevalence of chronic disease and multimorbidity in Ontario,Canada

BACKGROUND:New case-mix tools from the Canadian Institute for Health Information offer a novel way of exploring the prevalence of chronic disease and multimorbidity using diagnostic data. We took a comprehensive approach to determine whether the prevalence of chronic disease and multimorbidity has been rising in Ontario, Canada.METHODS:In this observational study, we applied case-mix methodology to a population-based cohort. We used 10 years of patient-level data (fiscal years 2008/09 to 2017/18) from multiple care settings to compute the rolling 5-year prevalence of 85 chronic diseases and multimorbidity (i.e., the co-occurrence of 2 or more diagnoses). Diseases were further classified based on type and severity. We report both crude and age- and sex-standardized trends.RESULTS:The number of patients with chronic disease increased by 11.0% over the 10-year study period to 9.8 million in 2017/18, and the number with multimorbidity increased 12.2% to 6.5 million. Overall increases from 2008/09 to 2017/18 in the crude prevalence of chronic conditions and multimorbidity were driven by population aging. After adjustments for age and sex, the prevalence of patients with ≥ 1 chronic conditions decreased from 70.2% to 69.1%, and the prevalence of multimorbidity decreased from 47.1% to 45.6%. This downward trend was concentrated in minor and moderate diseases, whereas the prevalence of many major chronic diseases rose, along with instances of extreme multimorbidity (≥ 8 conditions). Age- and sex-standardized resource intensity weights, which reflect relative expected costs associated with patient diagnostic profiles, increased 4.6%.INTERPRETATION:Evidence of an upward trend in the prevalence of chronic disease was mixed. However, the change in case mix toward more serious conditions, along with increasing patient resource intensity weights overall, may portend a future need for population health management and increased health system spending above that predicted by population aging.

Multimorbidity exists when a patient is diagnosed with 2 or more chronic diseases. Patients with multimorbidity present challenges for physicians managing their care and, as the proportion of these patients in the population increases, for health care system planning. The prevalence of multimorbidity and chronic disease has been strongly associated with primary care use, specialist consultations, number and intensity of inpatient hospital admissions and other types of care.^1–7 Among beneficiaries of fee-for-service Medicare in the United States, expenditures for those with 4 or more chronic diseases were reported to be 66 times higher than for those with none.⁸ One study found that most health spending growth (77.6%) in the US between 1987 and 2011 could be attributed to patients with 4 or more diseases.⁹Several recent studies have estimated the prevalence of chronic disease and multimorbidity in Canada.^3,10–13 Rates of multimorbidity ranged from 10% to 25%, owing to differences in classification systems used to identify chronic disease, including the choice of conditions, and variations in study population. Lack of standardization in measures of chronic disease prevalence and multimorbidity has hampered the evaluation of trends over time and across settings.Ontario provides an ideal setting to evaluate trends in the prevalence of chronic disease because patients have access to a comprehensive set of publicly funded services. The Canadian Institute for Health Information (CIHI) has created a system that maps patient diagnosis data from all health care settings to a set of 226 clinically meaningful health conditions, covering the full spectrum of acute and chronic morbidity (Jeffrey Hatcher, Canadian Institute for Health Information, Ottawa: personal communication, 2017). CIHI’s system has been independently compared with the Johns Hopkins ACG System; CIHI’s system was deemed to be more specific and less sensitive in classifying diagnoses, making it more conservative in identifying health conditions (S. Cheng, ICES, unpublished data, 2016). The purpose of this study was to evaluate trends in the prevalence of chronic disease and multimorbidity in Ontario using CIHI’s comprehensive disease classification system.     

Improvement of inflammatory and toxic stress biomarkers by silymarin in a murine model of type one diabetes mellitus

Type 1 diabetes mellitus (T1DM) is characterized by an impairment of the insulin-secreting beta cells with an immunologic base. Inflammatory cytokines such as tumor necrosis factor (TNF)-α and interleukin (IL)-1β, and free radicals are believed to play key roles in destruction of pancreatic β cells. The present study was designed to investigate the effect of Silybum marianum seed extract (silymarin), a combination of several flavonolignans with immunomodulatory, anti-oxidant, and anti-inflammatory potential on streptozotocin (STZ)-induced T1DM in mouse. Experimental T1DM was induced in male albino mice by IV injection of multiplelow- doses of STZ for 5 days. Seventy-two male mice in separate groups received various doses of silymarin (20, 40, and 80 mg/kg) concomitant or after induction of diabetes for 21 days. Blood glucose and pancreatic biomarkers of inflammation and toxic stress (IL-1β, TNF-α, myeloperoxidase, lipid peroxidation, protein oxidation, thiol molecules, and total antioxidant capacity) were determined. Silymarin treatment reduced levels of inflammatory cytokines such as TNF-α and IL-1β and oxidative stress mediators like myeloperoxidase activity, lipid peroxidation, carbonyl and thiol content of pancreatic tissue in an almost dose dependent manner. No marked difference between the prevention of T1DM and the reversion of this disease by silymarin was found. Use of silymarin seems to be helpful in T1DM when used as pretreatment or treatment. Benefit of silymarin in human T1DM remains to be elucidated by clinical trials.     

New water-soluble Fe3O4@SiO2 magnetic nanoparticles functionalized with levetiracetam drug for adsorption of essential biomolecules by case studies of DNA and HSA

Abstract

Communicated by Ramaswamy H. Sarma