Development and characterization of a new inbred transgenic rat strain expressing DsRed monomeric fluorescent protein

The inbred rat is a suitable model for studying human disease and because of its larger size is more amenable to complex surgical manipulation than the mouse. While the rodent fulfills many of the criteria for transplantation research, an important requirement is the ability to mark and track donors cells and assess organ viability. However, tracking ability is limited by the availability of transgenic (Tg) rats that express suitable luminescent or fluorescent proteins. Red fluorescent protein cloned from Discosoma coral (DsRed) has several advantages over other fluorescent proteins, including in vivo detection in the whole animal and ex vivo visualization in organs as there is no interference with autofluorescence. We generated and characterized a novel inbred Tg Lewis rat strain expressing DsRed monomeric (DsRed mono) fluorescent protein under the control of a ubiquitously expressed ROSA26 promoter. DsRed mono Tg rats ubiquitously expressed the marker gene as detected by RT-PCR but the protein was expressed at varying levels in different organs. Conventional skin grafting experiments showed acceptance of DsRed monomeric Tg rat skin on wild-type rats for more than 30 days. Cardiac transplantation of DsRed monomeric Tg rat hearts into wild-type recipients further showed graft acceptance and long-term organ viability (>6 months). The DsRed monomeric Tg rat provides marked cells and/or organs that can be followed for long periods without immune rejection and therefore is a suitable model to investigate cell tracking and organ transplantationFil: Montanari, Sonia. University Health Network. Toronto; Canadá. University of Toronto; Canadá. Princess Margaret Cancer Centre. Toronto; CanadáFil: Wang, Xing-Hua. University Health Network. Toronto; CanadáFil: Yannarelli, Gustavo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University Health Network. Toronto; CanadáFil: Dayan, Victor. University Health Network. Toronto; CanadáFil: Berger, Thorsten. University Health Network. Toronto; CanadáFil: Zocche, Larissa. University Health Network. Toronto; CanadáFil: Kobayashi, Eiji. Jichi Medical School. Tochigi; JapónFil: Viswanathan, Sowmya. University Health Network. Toronto; CanadáFil: Keating, Armand. University of Toronto; Canadá. University Health Network. Toronto; Canad

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

A Simplified Method for the Aspiration of Bone Marrow from Patients Undergoing Hip and Knee Joint Replacement for Isolating Mesenchymal Stem Cells and In Vitro Chondrogenesis

The procedure for aspiration of bone marrow from the femur of patients undergoing total knee arthroplasty (TKA) or total hip arthroplasty (THA) may vary from an OR (operating room) to OR based on the surgeon’s skill and may lead to varied extent of clotting of the marrow and this, in turn, presents difficulty in the isolation of mesenchymal stem cells (MSCs) from such clotted bone marrow. We present a simple detailed protocol for aspirating bone marrow from such patients, isolation, and characterization of MSCs from the aspirated bone marrow specimens and show that the bone marrow presented no clotting or exhibited minimal clotting. This represents an economical source and convenient source of MSCs from bone marrow for use in regenerative medicine. Also, we presented the detailed protocol and showed that the MSCs derived from such bone marrow specimens exhibited MSCs characteristics and generated micromass cartilages, the recipe for regenerative medicine for osteoarthritis. The protocols we presented can be used as standard operating procedures (SOPs) by researchers and clinicians.Peer Reviewe

A Systematic Study of the Effect of Different Molecular Weights of Hyaluronic Acid on Mesenchymal Stromal Cell-Mediated Immunomodulation

<div><p>Introduction</p><p>Osteoarthritis (OA) is associated with chronic inflammation, and mesenchymal stromal cells (MSCs) have been shown to provide pain relief and reparative effects in clinical investigations. MSCs are often delivered with hyaluronic acid (HA), although the combined mechanism of action is not fully understood; we thus investigated the immunomodulatory effects of combining MSCs with different molecular weights (MW) of HA.</p><p>Methods</p><p>HAs with MWs of 1.6 MDa (hHA), 150 kDa or 7.5 kDa, were added to MSCs alone or MSC-immune cell co-cultures. Gene expression analyses, flow cytometry and cytokine measurements were assessed to determine the effect of HAs on the MSC interactions with immune cells.</p><p>Results</p><p>MSCs in the presence of HAs, in both normal and lymphocyte-conditioned medium, showed negligible changes in gene expression. While addition of hHA resulted in increased proliferation of activated lymphocytes, both in the presence and absence of MSCs, the overall combined effect was a more regulated, homeostatic one; this was supported by higher ratios of secreted IL10/IFNγ and IL10/IL2, in lymphocyte cultures, than with lower MW HAs or no HA, both in the presence and absence of MSCs. In addition, examination of monocyte-derived macrophages showed an increased M2 macrophage frequency (CD14+CD163+CD206+) in the presence of hHA, both with and without MSCs.</p><p>Conclusions</p><p>hHA produces a less pro-inflammatory environment than lower MW HAs. Moreover, combining hHA with MSCs has an additive effect on the MSC-mediated immunomodulation, suggestive of a more potent combination treatment modality for OA.</p></div

Effect of different MWs of HA on the MSC-mediated inhibition of PBL proliferation.

<p>(A) and (C) representative histograms of carboxyfluorescein succinimidyl ester (CFSE) fluorescence. Lines: Black solid line, hHA; black dashed line, 150 kDa HA; black dotted line, 7.5 kDa HA; and gray solid line, no HA. Gray shaded histogram represents resting PBMC control. (B) and (D) PBL proliferation from the whole PBMC population. (A) and (B), normal conditions. (C) and (D), IFNγ-supplemented conditions. Solid filled bars stand for hHA; hatched bars, 150 kDa HA; dotted bars, 7.5 kDa HA and empty bars, no HA. Black color, normal conditions and gray color with red frame, IFNγ-supplemented conditions. All data shown is from one representative MSC donor; additional data from three other donors and at different PBMC:MSC ratios are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147868#pone.0147868.s005" target="_blank">S4 Fig</a>. Error bars represent 95% CI. Statistical differences in the presence of MSCs account for MSCs from 4 donors, each tested in triplicate. Statistical differences in the absence of MSCs account for PBMCs from one donor tested in quadruplicate. * p<0.05, ** p<0.01 and ***<0.001.</p

Effect of different MWs of HA on the MSC-mediated induction of Tregs.

<p>Frequency of Tregs (CD25+CD127-) within CD4+ T cells is shown (A, B). A) Effect of MSC donor-to-donor variability and different MWs of HA on Treg frequency. B) Effect of IFNγ-supplemented conditions on the Treg ratio from CD4+ T cells when MSCs and/or HAs are present. (A) and (B) show data from two separate experiments; normal conditions are shown in (B) for comparison purposes with IFNγ- supplemented conditions. Solid filled bars stand for hHA; hatched bars, 150 kDa HA; dotted bars, 7.5 kDa HA and empty bars, no HA. Black color, normal conditions and gray color with red frame, IFNγ-supplemented conditions. Each bar indicates the mean of triplicates replicates from MSCs or Th cell from one donor. Error bars represent 95% CI. * p<0.05, ** p<0.01 and ***<0.001.</p