How do myofibroblast sources compare between bone marrow and

How do myofibroblast sources compare between bone marrow and other organs? Perivascular R406 australia with MSC properties significantly contribute to fibrosis in muscle, fat, skin, heart, kidney, lung, and liver (reviewed in Iwayama et al., 2015) and activate Gli1 in many of these organs (Kramann et al., 2015). Non-perivascular myofibroblast sources have also been identified, such as in the lung and in the skin. Many lung myofibroblasts originate from lipofibroblasts, a type of lipid droplet-rich stromal cell, and upon spontaneous resolution of fibrosis, contractile cells de-differentiate back into lipofibroblasts (El Agha et al., 2017). Although skin wound myofibroblasts are typically non-adipogenic, they can regenerate new adipocytes in response to signals produced by hair follicles (Plikus et al., 2017), suggesting cell fate reprogramming as the basis for fat regeneration. Additional tracing studies are necessary to define the lineage history of regeneration-competent myofibroblasts and reveal common themes for myofibroblast plasticity across different organs and fibrosis models. Regeneration from myofibroblasts, either spontaneously or induced, is highly attractive as an anti-fibrotic strategy that can restore organ functions. Indeed, two recent papers in Cell Stem Cell on liver fibrosis (Rezvani et al., 2016, Song et al., 2016) show that viral vectors expressing hepatic transcription factors can directly reprogram myofibroblasts into new hepatocytes in vivo. In the future, bone marrow fibrosis can likely be treated by the reprogramming of myofibroblasts toward their original identities, efficiently restoring depleted hematopoietic stem cell niches.
Introduction The new predicted values of TL,CO by the working group of the Global Lung Function Initiative (GLI) [1] are available since September 2017. The GLI was undertaken since the 2005 ATS-ERS Task Force had concluded that the use of the ERS ‘93-reference values [2] are not appropriate. However, an alternative set of reference equations for spirometry for the use in European lung function laboratories was not suggested [3]. This activated Prof. Em. Quanjer in 2006 to start collecting normal data provided by authors of publications in international journals. After the publication of Stanejovic et al. on extended, complex models to describe spirometry data [4], the GLI working group was formed which became an ERS Task Force in 2010. Their final GLI collection of more than 74.000 spirometric data, resulted in an ERJ-publication on global, multi-ethnic reference values for forced expiratory maneuvers in 2012 [5]. It confirmed previously published data by Roca et al. [6] who observed that the former ERS '93 predicted values on FEV1 and VC were too low compared to their measured values on a general population (the ECHRS-study) by about 10–15%. Clinically, this means that when ERS ’93 predicted values are used for spirometry, the disease severity is always underestimated and that restrictive lung disorders might be “overlooked” based on apparently normal spirometric results [7]. Recently, the work of the GLI working group has advanced to the publication of new global reference values on the transfer factor (TL,CO) for Caucasians [1]. Compared with earlier published reference TL,CO-values for children, the GLI values are not that different, however, for adults, the GLI reference values are noticeably lower [1]. To our disappointment, the authors omitted to compare them with the ERS-‘93 prediction equations [8], which are still in use throughout Europe today. For the clinician confronted with the switch from old to new reference equations, it is crucial to understand the potential clinical impact of that switch, which may eventually lead to changes in diagnostic and therapeutic cut-off values, as has recently been demonstrated when screening patients with systemic sclerosis for pulmonary hypertension and interstitial lung disease [9].