It can be concluded that the

It can be concluded that the predictions of impact velocity thresholds of different pairs of projectile-target in Table 4 are close to the numerical results in Table 3, which obtained by Rosenberg and Dekel [10]. In particular, the predictions of ogival ( = 3), spherical, and flat noses are a little less than the corresponding ranges in Table 3, while the predictions of conical nose are a little larger than those in Table 3. The deviations between Tables 3 and 4 are trusted to come from the implication of theoretical model and numerical simulation, but they all locate in the allowed range of 10%. Moreover, the prediction of the effect of nose shape on is completely consistent with the results in Ref. [10].
With re-check of Figs. 2–11, since the impact velocities of most cases are less than the impact velocity threshold , the assumption of constant resistive force is available. Exceptionally, regarding the cases of spherical and flat nose projectiles impacting aluminum and steel targets at  = 1500 m/s and  = 1000 m/s, respectively, as the impact velocities exceed the threshold (see Figs. 8, 9 and 11), the effect of the initial term is quite dominating during the penetration. Similarly, as in the concrete penetrations [7,8], almost all the decelerations are kept as constant, as shown in Figs. 12–16.
Thus, the rationality of above theoretical analysis and Eq. (18) are further validated, and the applicability of the predictions of on the other cases of Table 4 can also be confirmed.
According to above analysis, in the range of , Eq. (8) is reasonable for predicting DOP; and for , DOP should be calculated using Eq. (3). Due to the limit of experimental conditions, no test data of has been reported in published literatures regarding to the pairs of projectile-target in Table 4, and thus it 5-fluorocytosine is impossible to check the applicable range of Eqs. (3) and (8) by experimental results. However, Rosenberg and Dekel [10] also conducted some simulations under the condition of . Their simulations use two kinds of aspect ratios of projectile, i.e.  = 20, 10. Target materials are aluminum and steel with strength of 400 MPa, which are listed in Table 2. The DOPs predicted by theoretical analysis are further compared with the simulation results to check the applications of Eqs. (3) and (8). The comparative results are listed in Table 5, where the labels of -ns,-Eqs. (3) and (8). represent DOPs predicted by simulation, Eqs. (3) and (8), respectively.
It can be found from Table 5 that, for any kind of nose shape, the most values of ratio X-Eq. (3)/X-ns are close to 1, and the relative deviations mostly locate in the allowed range of 20%. In contrast, the most values of ratio -Eq. (8)/-ns are larger than 1 and the relative deviations are out of the allowed range of 20%. It indicates that Eq. (8) is indeed inappropriate and only Eq. (3) can be used to predict DOP accurately in the case of .

According to the dimensionless formulae of DOP of different targets penetrated by a rigid projectile, Postmeiotic segregation paper theoretically analyzed the resistive force exerting on the projectile during the penetration. According to the impulse equivalence, the impact velocity threshold was formulated, which is applicable for the assumption of constant resistive force. only depends on the nose shape of projectile and target material. The applicable ranges of various formulae of DOP were also checked up based on the test data in Refs. [7,8] and the simulation results in Ref. [10]. Especially, for , Eq. (8) formulated from the assumption of constant resistive force is no longer appropriate and only Eq. (3) is able to be employed to predict DOP.
The values of for different pairs of projectile-target in the present theoretical analysis are consistent with the simulation results in Ref. [10]. The relative test data also confirmed that the values of are correct and applicable. In particular, the impact velocity threshold are formulated out with combined the effects of projectile geometry and target material.

br Discussion Our patient s presentation with

Our patient\’s presentation with peculiar skin rashes combined with sensorimotor polyneuropathy and rheumatic manifestations, all evolving over 3–4 years, led to the skin biopsy that confirmed the diagnosis of leprosy. Although the coexistence of SLE and leprosy has been reported, SLE was not likely in this patient. First, immunosuppressive agents were ineffective, including on the skin and joint symptoms. Second, cutaneous manifestations gradually improved after using MDT alone. Third, the autoantibody profile, complement level, and direct immunofluorescence study result did not give good support to the diagnosis of lupus. Leprosy has a variable incubation aminoguanidine ranging from months to several years and may progress slowly. Although the Myanmar man had left the endemic area more than 25 years earlier, the disease may present long afterwards. It is not clear when our patient acquired his leprosy, but the most likely explanation is that his disease lay dormant for many years.
Rheumatic manifestations, observed in as many as 64–77% leprosy patients especially during reactional states, form the third most prevalent complication after dermatologic and neurologic abnormalities. In our patient, swollen hands syndrome, arthritis, Raynaud\’s phenomenon, and indurated facial rashes on malar eminence were noted during the disease course. One possible explanation for our patient having facial rashes reminiscent of malar rashes in lupus is that M. leprae grows best in cooler areas of the human body. Hence, the skin lesions tend to be localized to the chin, forehead, earlobes, and malar eminences.
It has been estimated that 6–75% of leprosy patients develop arthritis at some stage of the disease. In a retrospective review evaluating 1257 leprosy patients, Pereira et al found that the predominant type of leprosy in the patients with arthritis was lepromatous leprosy type (41.8%), followed by borderline tuberculoid type (23.6%), borderline (18.2%), and borderline lepromatous type (16.4%). Also, the review showed that the most common type of joint involvement was polyarticular, followed by oligoarticular and monoarticular. The wrist, ankle, proximal interphalangeal joint, and metacarpophalangeal joint were most frequently affected. Chauhan et al classify the arthritis in leprosy into the following groups: (1) Charcot\’s arthropathy secondary to peripheral sensory neuropathy; (2) swollen hands and feet syndrome; (3) acute polyarthritis of lepra reaction; and (4) chronic arthritis from direct infiltration of the synovium by lepra bacilli. Since our patient had a chronic course without a lepra reaction during diagnosis and responded to MDT and nonsteroidal anti-inflammatory drugs, the joint involvement in our patient seemed to be due to Charcot\’s arthropathy or chronic arthritis. Two commonly involved nerves in Charcot\’s arthropathy are the ulnar and median nerves. Early changes associated with ulnar neuropathy are flattening of the hypothenar muscles and ultimately result in claw-hand deformity, as observed in our patient.
Leprosy is invariably included in the list of diseases associated with positive ANA tests. The presence of ANA has been reported to vary from 3% to 34% usually in a low titer, and both speckled and homogeneous patterns were identified. The great variability probably reflects the heterogeneity of the sample, the duration, and the type of the disease. Patients with a longer duration of illness, an older age, multibacillary leprosy, and a history of repeated lepra reaction attacks have been reported to predispose to ANA production. Also, many other chronic infections such as malaria, tuberculosis, and fungal infection often coexist with leprosy in developing countries and they could augment the humoral immune stimulation and increase the titer and range of autoantibodies produced. It has been postulated that ANA presenting in leprosy patients results from weak cross-reactivity with complexed nucleic acids and nucleoproteins exposed after cell destruction in chronic inflammation. Newly exposed hidden antigens may provide antigenic determinants that stimulate adaptive immune response and polyclonal B cell activation.

Organization This paper is organized as follows

Organization. This paper is organized as follows: Section 2 discusses related work. In Section 3, background and definitions of data quality concepts are presented. Then, Section 4 highlights data cleaning in medical applications. Section 5 presents the proposed ICCFD_Miner, MICCFD_Miner, and T_Repair techniques. Section 6 discusses the experimental study and results conducted for different medical datasets. Finally, Section 7 concludes the proposed work and highlights the future trends.

Related work
Unfortunately, despite the urgent need for precise and dependable techniques for enhancing data quality and data cleaning problems, there is no vital solution up to now to these problems. There has been little discussion and analysis about enhancing data consistency. However, most of the recent work focus on record matching and duplicate detection [2].
Database and data quality researchers have discussed a variety of integrity constraints based on Functional Dependencies (FD) [5,12,20,35]. In Ref. [35], authors propose an FD_Mine algorithm that discovers functional dependency from given relation. A survey and comprehensive comparison of seven algorithms for discovering functional dependencies are discussed in Ref. [27]. Surveyed algorithms include TANE, FUN, FD_Mine, DFD, Dep-Miner, FastFDs, FDEP as indicated extensively in Ref. [27]. Nevertheless, traditional FDs are developed mainly for schema design but are often not able to detect the semantic values errors of data. Other researchers focus on the extension of FD, they Ketorolac tromethamine salt have proposed what is so-called Conditional Functional Dependencies (CFD) and Conditional Inclusion Dependencies (CID) for capturing errors in data. Algorithms that proposed for discovering CFDs rules from relation include: CFD Miner algorithm for discovering constant conditional functional dependencies, CTANE algorithm that extends TANE to discover general CFDs, and FastCFD for discovering general CFDs by employing a depth-first search strategy instead of the level-wise approach as used in CTANE algorithm [6].
Several data quality techniques are proposed to clean messy tuples from databases [9], as researchers aim to find critical information missing from databases. In Ref. [9], authors propose three models to specify relative information completeness of databases from which both tuples and values may be missing. Statistical inference approaches are studied in Ref. [24], which infer missing information and correct errors automatically. These approaches tackle missing values to enhance the quality of data. From technological part, several open source tools are developed for handling messy data. Open Refine and Data Wrangler are two open source tools for working with missing data for cleaning them as detailed in Ref. [18].
Moreover, there are a variety of data transformation methods such as commercial ETL (Extract, Transformation, and Loading) tools [31]. Extraction methods focus on extracting data from homogeneous and/or heterogeneous data sources. Transformation methods purpose is to store data in proper format or structure for querying and analysis purpose. Loading methods concern with load data into a single data source repository such data warehouse or other unified data source depending on the requirements of the organization. These tools are developed for data cleaning to support any changes in the structure, representation or content of data.
The usage of editing rules in combination with master data is discussed in Ref. [8]. Such rules can find certain fixes by updating input tuples with master data. According to constraints, editing rules have dynamic semantics and are relative to master data. Given an input tuple t that matches a pattern, editing rules tell us which attributes of given tuple t should be updated and what values from master data should be assigned to them. This approach requires defining editing rules manually for both relations, i.e., master relation and input relation, which is very expensive and time-consuming. Repairing use heuristic solution based on minimum cost function of two updates that not always provide with a deterministic fix. Editing rules require users to examine every tuple, which is expensive.

Increase in foreign direct investment

Increase in foreign direct investment (FDI) may decrease foreign portfolio investment volatility because it enhances the confidence of foreign investors and brings more investment in the home country (Gozgor & Erzurumlu, 2010). Similarly, Iyer, Rambaldi, and Tang (2003) found that FDI caused FPI while FPI did not cause FDI. Contrary to this, Ahmed and Malik (2012) concluded that direct investment found to granger cause by the portfolio investment in Pakistan only because its financial market is experiencing exponential progress (growth) and this factor will help in understanding the different investment environments. However, FPI was found to be non-consistent and non-persistent capital flow than FDI and other flows in crises times in some studies (Sarno & Taylor, 1999; Levchenko & Mauro, 2007). Thus, we expect significant relationship between FDI and foreign portfolio investment volatility.


Results and discussion
The results have been classified into tables. Table 1 reports descriptive statistics of our main variables and Table 2 presents GARCH results; it shows the effect of macroeconomic factors on FPI volatility. In Table 1, Pakistan has the highest inflation rate during the sample KPT-185 as compared to that of China, India and Srilanka. Pakistan has seen the highest interest rate on the average and it shows the severe problem of inflation On the other hand, China has the highest amount of foreign direct investment (131 billion dollars) and foreign portfolio investment (16.5 billion dollars, India has the second rank. China is the big economy and it has been able to attract more foreign investment. China has the highest economic growth, while India, Sri Lanka and Pakistan gets the second, third and fourth position in this regard. China has achieved tremendous industrial growth rate on the average, and Pakistan has obtained the second position.
In Table 2, the first equation is the mean equation and second is the variance equation of GARCH (1,1). The intercept of mean equation is negative and insignificant showing that there are no others factors influencing today׳s portfolio return. In mean equation, significant value of FPI(−1) implies that today׳s return is predicted by past return. The lag return value of FPI is significant at 1% level in case of all the countries; it means prior return of FPI predicts future return pattern of FPI. The residual term׳s coefficient is positively significant for all countries; it means that random term of previous day forecasts today׳s volatility. Therefore, we can say that there exists significant positive relationship between previous price behavior and current portfolio investment volatility.
The effect of foreign direct investment is negatively significant on volatility of FPI for three countries, namely, China, India and Pakistan. It implies that increase in FDI leads to reduction in FPI volatility. However, it has no effect in case of Srilanka because it has very lower level of FDI in the country. On the basis of these results, FDI has an important role to attract FPI in the country and it provides foundation for foreign portfolio investors to pursue FDI. Moreover, the significance of FDI for China, India and Pakistan shows that financial market is making progress and this would help understand different investment environments (Ahmed & Malik, 2012); insignificance of FDI in Srilanka implies that investors investing in Srilanka are facing liquidity problems (Gozgor & Erzurumlu, 2010).
In Table 2, the results of GDP growth rate are significant for China, Pakistan and Srilanka at 5%, 10% and 10% critical level. The results of China are more significant than those of Pakistan and Srilanka as China is growing rapidly; if we look at the average growth rate in Table 1, China has the highest average economic growth during the sample period. However, the results of Pakistan and Srilanka are moderately significant which indicate less attraction of GDP to foreign portfolio investors in these countries. Thus, Foreign portfolio flows are linked to higher GDP in China leading to reduction in volatility, and these results confirm to the results by Bekaert and Harvey (1998). Our result of GDPGR is against our expectation in case of Pakistan because GDP growth rate has no continuity and foreign investors are not attracted by the country׳s GDPGR.

Regarding JNK phosphorylation levels were either moderately for JNK

Regarding JNK, phosphorylation levels were either moderately (for JNK 1) or significantly increased (for JNK 2/3) at 5μM SB203580 compared to DMSO controls; these effects were further pronounced at 30μM (Figs. 5 A–B, schema in Figs. 6 C–D). This suggests a concentration-dependent activation of JNK by SB203580, which has been described to be a MAPK3K-regulated process as shown for various human cell types (Henklova et al., 2008; Muniyappa and Das, 2008). In the literature, it has been suggested that TAK1, a MAPK3K member, is the intermediary that activates both, p38 and JNK. Activation of p38 in turn leads to inhibition of TAK1 via TAB1 (TAK1-binding protein 1). This negative feedback loop is disrupted upon addition of SB203580, which subsequently results in a higher TAK1 activity and consequently JNK phosphorylation as well (Fig. 6 C) (Heinrichsdorff et al., 2008; Cheung et al., 2003; Hall and Davis, 2002; Gaestel et al., 2009). To what extent this compensatory mechanism contributes to SB203580-enhanced cardiomyogenesis in hESC needs further investigation. However, given that even minor modification in MAPK activity might result in profound changes in cell fate, it is plausible to assume that the moderate up regulation of JNK phosphorylation at 5μM SB203580 might be causative for increased cardiomyogenesis. This was confirmed by applying the JNK inhibitor, SP600125. Results showed abrogation of cardiac differentiation after single treatment with SP600125, which was not rescued by SB203580, in transketolase to anisomycin treatment. These findings suggest that JNK activity is necessary for cardiomyocyte formation in line with previous findings from mESC which described an essential role of the JNK pathway in mesoderm and cardiac differentiation (Xu and Davis, 2010; Sato et al., 2005).
In contrast to JNK, ERK phosphorylation was apparently not affected at a 5μM SB203580 concentration (Figs. 5 C–D, 6 C) but remained at a relatively high level in EBs, which might support cell viability and some degree of proliferation. However, at 30μM, ERK phosphorylation was significantly reduced (Figs. 5 C–D, 6 D). According to in vitro studies, SB203580 can affect the ERK pathway by direct inhibition of c-Raf upstream of ERK (Hall-Jackson et al., 1999). As cell proliferation is correlated with high phosphorylation levels of ERK (Geest et al., 2009; Wang et al., 2009), inhibition of this pathway might explain the significant drop in cell count which we have observed at 30μM SB203580 (Fig. 2D). The pronounced ERK inhibition at the high inhibitor concentrations might also directly be related to suppressed cardiomyogenic differentiation, as the importance of ERK activity in mesoderm i.e. T-bra induction in hESC was recently pointed out by Yu et al., in line with our observation (Yu et al., 2011). It is also worth noting that in mice, ERK pathway activity was shown to be necessary for mesoderm differentiation (Yao, 2003).
Also in mice, activity of HSP25, the mouse homolog of the human HSP27 downstream of p38, is necessary for functional cardiac differentiation (Davidson and Morange, 2000). Another study showed that expression of HSP27 is essential for preventing differentiating mouse ESC from undergoing apoptosis (Mehlen et al., 1997). The transcription factor MEF2C, a downstream target of p38, is essential for early embryonic cardiovascular development (Yang et al., 2000) and the expression of the cardiac-specific gene TNNI3K (Wang et al., 2008). In addition, ATF-2, a third downstream target of p38, was reported to play a critical role in cardiomyocyte differentiation (Monzen et al., 2001). Thus, at least in the mouse system, direct links between MAPKs pathways regulation and cardiomyogenic differentiation are well established.
However, in contrast to hESC, it is reported that activation rather than inhibition of MAPK signaling cascades results in cardiovascular commitment in mouse ESC, including a crucial role for ROS (reactive oxygen species)-induced p38 activation (Schmelter et al., 2006). Furthermore, p38 activity was required in mouse-derived P19 embryonal carcinoma cells for cardiomyocyte differentiation (Yang et al., 2000; Eriksson, 2002). In both studies, administration of different MAPK inhibitors (SB203580, UO126 and SP600125) disrupted cardiomyogenesis in mESC. Also, ERK phosphorylation is low in undifferentiated mESC in contrast to hESC (Dvorak et al., 2005). Instead of inducing differentiation as described for hESC, inhibition of the ERK pathway by small molecules helps to maintain the cells in an undifferentiated state. These observations suggest that species-specific differences exist, requiring careful assessment of a given system.

E7080 Compared to the adherent monolayer culture an alternative method

Compared to the adherent monolayer culture, an alternative method using suspension culture has been shown to be more effective in obtaining and maintaining the early neural E7080 emerged during multi-staged differentiation process. Using serum-free medium supplemented with epidermal growth factor (EGF) and FGF, which selectively favor the maintenance of NSCs isolated from CNS (Gage, 2000), ESCs have been successfully induced into NSCs that could be maintained in culture and retained the ability to further differentiate into functional neurons and glial cells (Nakayama et al., 2004). These EGF/FGF-dependent NSCs largely resembled CNS-NSCs, which were termed definitive NSCs due to their defined neural identity and robust capability of generating neurons and glia cells (Hitoshi et al., 2004; Smukler et al., 2006; Rowland et al., 2011). The emergence of definitive type of NSC also suggested that earlier stages of neural induction were possibly bypassed in the EGF and FGF directed neural induction. Interestingly, an earlier type of neural cells, named primitive NSCs, has been established in the absence of differentiation-inducing cues using suspension culture (Tropepe et al., 2001; Smukler et al., 2006). These primitive NSCs resembled early stage neural cells isolated from E5.5–E7.5 embryonic neuroectoderm (Hitoshi et al., 2004), a stage before CNS formation and emergence of definitive NSCs. These primitive NSCs grew in a leukemia inhibitory factor (LIF)-dependent manner, and expressed pluripotency genes Oct4 and Nanog as well as early neural markers Sox1 and Hes1 (Hitoshi et al., 2004), but not conventional markers found in more committed CNS-NSCs, such as Nestin and Pax6 (Rowland et al., 2011). Further induction in culture medium supplemented with FGF and EGF could direct these primitive NSCs to definitive type of NSCs (Tropepe et al., 2001; Hitoshi et al., 2004; Rowland et al., 2011), suggesting that primitive NSCs obtained using this method define an early stage of neural induction. Further study on this cell type may facilitate unveiling of the molecular regulations underlying initial neural commitment, which still remains obscure due to the complex and fast-changing nature of early neural induction process.
In this study, we took one step forward to further investigate the LIF-dependent primitive NSCs. For the first time we analyzed global gene expression profiles in mouse ESC-derived primitive NSCs and identified groups of genes which were specifically up- or down-regulated in these cells using Affymetrix DNA microarray. Our data illustrated that primitive NSCs retained the expression of many pluripotency genes while exhibiting gene expression changes associated with ESC differentiation. Cell cycle analysis further supported that primitive NSCs exhibited intermediate features between mouse ESCs and CNS-derived definitive NSCs. By re-plating primitive NSCs back to ESC culture conditions, these cells could be reverted back to ESC stage from early neural committed stage, which was further supported by the reversible regulation of early neural genes and cell cycle profiles changes. Importantly, our loss-of-function analysis identified Hes1 and Ccdc141 as potential regulators in early neural induction. Thus our study clarified features of primitive NSCs as early neural cells and shed light on the mechanism underlying the early neural commitment from ESCs.

Materials and methods


Definitive NSCs, including CNS-derived NSC and their in vitro counterparts derived from ESC, can give rise to various neuronal cell types. Thus it has raised the possibility of treating injuries and neurodegenerative conditions of CNS through cell replacement therapy (Martino and Pluchino, 2006). However, although these NSCs can be maintained in culture, they exist in a form of heterogeneous population comprising of multipotent NSCs and committed neural precursor cells (Temple, 1989; Tropepe et al., 1999). Moreover, properties of CNS-NSCs depend on their origins in the brain and their stages of development (Temple, 2001); characteristics of ESC-derived NSCs vary according to the induction procedures. As there is no available method to further purify these diverse subtypes efficiently, application of NSCs in clinical therapies is greatly hindered. p-NSCs, a kind of earlier stage NSCs, have been obtained from neuroectoderm prior to CNS formation (Hitoshi et al., 2004), and their equivalent cell type can be derived from mouse ESCs in suspension culture condition (Tropepe et al., 2001; Hitoshi et al., 2004; Smukler et al., 2006; Rowland et al., 2011). Compared to CNS-NSCs, p-NSCs represent early stage neural cells. Thus they have opened up a new area in NSC study, which may facilitate unraveling of the mechanism that leads to heterogeneity and diversity among NSCs.

HSCs reside in functional niches within the bone

HSCs reside in functional niches within the bone marrow microenvironment, where their asymmetric division and differentiation give rise to all blood cell lineages throughout life (for review, see (Wang and Wagers, 2011)). Coordinate signals from other cellular components of the hematopoietic microenvironment modulate HSC proliferation and differentiation through the elaboration of soluble factors and cell adhesion molecules (Chitteti et al., 2010; Chen et al., 2013; Nakamura-Ishizu and Suda, 2013). Endothelial nvp-aew541 (ECs) are microenvironmental components that modulate the proliferation, self-renewal, and differentiation of HSCs at the vascular niche (Kopp et al., 2005; Kobayashi et al., 2010). Our group and others have shown that ECs effectively restore hematopoiesis by regenerating irradiated HSCs both in vitro and in vivo (Chute et al., 2004; Muramoto et al., 2006; Hooper et al., 2009; Li et al., 2010). However, the mechanisms and practicality of EC-mediated hematopoietic regeneration are still largely unexplored.
In this study, we used a co-culture system to evaluate the regeneration of functional murine HSCs by human aortic ECs (HAECs) following whole body irradiation (WBI). We report that HAECs rescue hematopoiesis by reversing DNA damage in primitive hematopoietic cells and expanding long-term HSCs. Furthermore, we demonstrate that HAECs can rescue functional HSCs up to 48h following HSC radiation injury, whereas G-CSF cannot. Our results show that HAECs robustly support HSC regeneration following radiation injury, and that in vitro, their radiation mitigation is superior to G-CSF.

Materials and methods


We have shown that HAECs mediate the recovery of hematopoietic function following radiation injury by promoting the proliferation of functional HSCs and reducing DNA damage. Relative to control culture conditions, HAEC co-culture regenerated significantly more CD150+LSK cells from irradiated bone marrow; furthermore, HAEC-rescued BMC had increased long-term hematopoietic reconstitution potential and contained self-renewing, multilineage-reconstituting HSCs. For phenotypic identification of HSCs we included the SLAM family member CD150, which has been shown to enrich for long-term HSCs within LSK populations (Kiel et al., 2005; Chen et al., 2008). HAECs expanded the proportion of CD150+LSK cells in culture by 24-fold (Fig. 1D), and this increase correlated with a log-fold engraftment advantage for HAEC-treated BMC relative to control (Fig. 2C).
A remarkable finding from our study is the long window of opportunity during which irradiated HSCs can be rescued. Despite the persistence of substantial amounts of DNA damage in LSK cells (Fig. 3D), a subpopulation of these cells survive for up to 48h and are responsive to HAEC-derived factors that promote HSC regeneration. In the case of unanticipated exposure to ionizing radiation, the possibility that healthcare intervention may not be immediate is clinically important. Our results show that in the absence of HAEC-derived signals, irradiated HSCs completely lose their ability to repopulate the blood of radiation-conditioned recipients after a 48h culture delay (Fig. 4D). Notably, the degree to which irradiated BMC remained capable of producing CD150+LSK cells and active progenitors was inversely proportional to the length of the post-irradiation delay. Although we recovered fewer absolute CD150+LSK cells from BMC cultures that were delayed 48h prior to co-culture with HAECs, the percentage of CD150+LSK cells in day 7 cultures did not change significantly when compared to BMC cultured immediately on HAECs (data not shown). Thus, our functional studies show that HSCs regenerated by HAECs immediately after irradiation (Fig. 2C) have comparable engraftment potential on a per-cell basis as HSCs regenerated by HAECs after a post-irradiation delay of 48h (Fig. 4D). These results suggest that HSC death, rather than an intrinsic alteration to the quality and engraftment potential of HSCs, is limiting for the delayed rescue of HSCs through HAEC co-culture.

Induced pluripotent stem iPS cells derived from human

Induced pluripotent stem (iPS) GSK212 Supplier derived from human somatic cells by expression of defined transcription factors represent a powerful novel system for disease modeling (Park et al., 2008; Takahashi et al., 2007). Moreover, the recent development of highly efficient genome editing tools has greatly facilitated the use of corrected iPS cell-derived products for autologous tissue replacement (Mali and Cheng, 2012). Most relevant to A-T, preclinical studies have started to define sets of transcription factors that promote differentiation of mouse ES cells (Muguruma et al., 2010; Tao et al., 2010) and human ES and iPS cells (Muguruma et al., 2015; Wang et al., 2015) to Purkinje neurons. Furthermore, these cells have some engraftment capability (Muguruma et al., 2010; Wang et al., 2015), suggesting that A-T iPS cells could similarly represent a source of neuronal cells for disease modeling and ultimately for regenerative therapy.
Previous work has shown that A-T iPS cells generated by expression of Yamanaka factors in A-T fibroblasts (Fukawatase et al., 2014; Lee et al., 2013; Nayler et al., 2012) or T cells (Lin et al., 2015) are viable. However, all fibroblast-based protocols employed integrating viral vectors and feeder layers (Fukawatase et al., 2014; Lee et al., 2013; Nayler et al., 2012). Moreover, consistent with impaired reprogramming in fibroblasts deficient for other DSB repair factors (Gonzalez et al., 2013; Tilgner et al., 2013), the efficiency of reprogramming from A-T fibroblasts was decreased about 100-fold relative to control fibroblasts from healthy individuals (Fukawatase et al., 2014; Lee et al., 2013; Nayler et al., 2012). Furthermore, the efficiency of reprogramming from A-T carrier fibroblasts was also markedly decreased in one study (Nayler et al., 2012), suggesting a gene dose effect. Patient-derived circulating T lymphocytes were recently shown to represent an alternative to fibroblasts (Lin et al., 2015). However, the fact that they often harbor clonal pre-leukemic rearrangements involving antigen receptor loci (Taylor et al., 1996) complicates their use for disease modeling and therapy. In this context, reprogramming of nonlymphoid mononuclear cells (Chou et al., 2015; Dowey et al., 2012; Hu et al., 2011) could provide a robust yet safe approach for A-T patients and carriers. More specifically, the erythroid compartment is no or minimally affected in A-T (Boder and Sedgwick, 1958).

Materials and Methods


A-T, a monogenic disease presenting with multi-organ dysfunction early in childhood, is a candidate for regenerative medicine after gene defect correction. However, previous strategies to generate iPS cells from patient-derived somatic cells were hampered by very low reprogramming efficiency (fibroblasts) or possible contamination of the source with premalignant cells (T cells). Here, we show that circulating erythroid cells provide a robust and safe alternative for the generation of A-T iPS cells. Moreover, we find that reprogramming corrects defects in chromosomal integrity and telomere length observed in A-T somatic cells, suggesting that patient-derived iPS cells rather than somatic cells represent the best substrate for gene defect correction. This observation is not unique to A-T because a previous report demonstrated that the abnormal ring chromosome 17 causing Miller Dieker Syndrome (MDS) is also corrected by reprogramming (Bershteyn et al., 2014).
The use of patient peripheral blood for reprogramming has several advantages. First, the small volume of blood (30cm3 or less) employed here can be obtained from virtually any patient by venipuncture, obviating the need for specialized medical care and the discomfort associated to skin biopsies. Indeed, frozen material stored at a blood bank can be used. Secondly, the addition of BCl-xL to Yamanaka factors markedly increases the efficiency of reprogramming over previous findings using Yamanaka factors alone and fibroblasts (Fukawatase et al., 2014; Lee et al., 2013; Nayler et al., 2012). Importantly, the A-T line generated here has a normal karyotype, indicating that improved reprogramming efficiency does not result from unchecked proliferation of cells harboring chromosomal aberrations. Thirdly, our protocol takes advantage of the fact that, unlike the lymphoid compartment, the erythroid compartment is no or minimally affected in A-T, minimizing potential carry-over of abnormalities from parental cells. Finally, unlike most previous studies that employed feeder layers and/or viral vectors (Fukawatase et al., 2014; Lee et al., 2013; Lin et al., 2015; Nayler et al., 2012), our experiments were conducted using our previously described xeno-free episomal-based protocol (Chou et al., 2015), further supporting their clinical applicability.

The most commonly used trophoblast markers reported in

The most commonly used “trophoblast” markers reported in the literature are cytokeratin 7 (KRT7), HLA-G, and human chorionic gonadotropin (hCG), but these are either not specific to all trophoblast Wortmannin or are expressed in other cell types. Several of the transcription factors (TF) that define the transcriptional network of mouse TSC have also been used (e.g. CDX2 and EOMES) (Senner and Hemberger, 2010). However, it is not known whether the same network operates in humans or what the pattern of expression is in normal first-trimester trophoblast populations (Table S1).
ELF5 is a TF that is expressed in mouse TSC to sustain their potential for self-renewal and commitment to the extraembryonic lineage (Donnison et al., 2005; Ng et al., 2008). In mice, the promoter of Elf5 is hypermethylated in ESC and hypomethylated in TSC (Ng et al., 2008). In human early placental tissue, the ELF5 promoter is mostly hypomethylated (Hemberger et al., 2010). Thus, the lack of methylation of the ELF5 promoter could potentially be an additional marker to define trophoblast, although it is still unknown whether ELF5 hypomethylation is present specifically in trophoblast or in other placental cell types.
Another possible candidate for defining trophoblast is the expression of specific non-protein-coding microRNAs (miRNAs), in particular the chromosome 19 miRNA cluster (C19MC) that is located in the leukocyte receptor complex on chromosome 19q13.41 (Bentwich et al., 2005). C19MC miRNAs are primate specific and maternally imprinted, with expression normally restricted only to the placenta and hESC (Bentwich et al., 2005; Laurent et al., 2008; Bortolin-Cavaillé et al., 2009; Noguer-Dance et al., 2010). C19MC is the largest cluster of miRNAs in humans and is highly expressed in human trophoblast cells (Bortolin-Cavaillé et al., 2009; Donker et al., 2012).
In this study we test these four criteria, which include both protein and non-protein-coding markers, using primary human trophoblast. We focused on the first trimester, as this is when placental development occurs. We show that, by using these criteria in combination, reliable identification of genuine trophoblast is possible. As proof of principle, we then tested these four diverse characteristics (expression of trophoblast protein markers and C19MC miRNAs, HLA class I profile, and methylation status of ELF5 promoter) on two cell types: 2102Ep, an embryonal carcinoma (EC) cell line, and trophoblast-like cells induced from BMP4-treated hESC. Here, we show that both cell types show some properties typical of trophoblast, but neither displays all four characteristics. We propose that this classification system will provide a stringent method to define human trophoblast cells in vitro.


The main obstacle in defining trophoblast cell fate in cell lines in vitro has been that there is no marker exclusive to trophoblast cells that could serve as an unambiguous readout of cell lineage allocation. Therefore, our aim in this study was to identify a set of criteria that would allow cells to be rigorously assigned to the trophoblast lineage. These criteria have been defined using first-trimester primary trophoblast, the period of gestation when exuberant trophoblast proliferation and development of the placenta occurs. Furthermore, obstetric outcome is affected by placental dysfunction before 10 weeks’ gestational age (Smith, 2010). In future, analysis of trophectoderm and trophoblast later in gestation can be done to confirm that these criteria define trophoblast throughout pregnancy.
Our tables illustrate that many of the markers currently in use are either only present in some trophoblast subtypes (e.g. CDX2, ELF5, HLA-G), and/or are not specific to trophoblast (e.g. KRT7, CDX2, EOMES). Therefore, using information from our previous microarray data of fluorescence-activated cell-sorted trophoblast cells, we selected genes involved in the transcriptional network that drive murine TSC, and show that TFAP2C and GATA3 are expressed in all mononuclear trophoblast cells, providing useful additional markers (Biadasiewicz et al., 2011; Kuckenberg et al., 2012).

Surprisingly few studies on human fetal livers have

Surprisingly, few studies on human fetal livers have reported that the hematopoietic progenitor markers CD34, CD117, CD90, CD133, and CD44 are also expressed on a subset of human hepatoblasts and/or precursors of hepatoblasts depending on the embryonic stage examined (Table S1). Most of the EpCAM+ hepatoblasts express CD133 and CD44 in the second trimester of gestation (Schmelzer et al., 2007). Co-expressions of CD117 and AFP or CD117 and ALB in hepatoblasts are detected at around 14 weeks and represent about 2% and 1% of total cells, respectively (Nava et al., 2005). A subset of CD117+ Anisomycin cost that co-express CD34 can turn on the hepatic markers ALB and CK19 when further cultured in vitro suggesting the presence of CD177+CD34+ precursors of hepatoblasts (Nava et al., 2005; Nowak et al., 2005). Similarly, human fetal liver multipotent progenitor cells have been identified from fetal livers from first and second trimesters (Lazaro et al., 2003); they express CD34 and CD44 and differentiate into ALB+glycogen+ hepatoblasts, CK7+GGT+CK19+ biliary cells, and mesenchymal cells (Dan et al., 2006). These studies indicate that some hematopoietic progenitor markers are surprisingly also expressed on developing hepatoblasts and/or precursors of hepatoblasts in human fetal livers.
Our previous work has established an efficient protocol to generate functional hepatoblast-like cells (referred to as hepatic cells or Hep cells) from human embryonic stem cell (hESC) differentiation cultures that express endoderm and hepatic markers including FOXA2, HNF4α, AFP, ALB, CK18, and EpCAM (Goldman et al., 2013). Here, we characterize expression kinetics of hematopoietic progenitor markers in Hep cells as they specify from the endoderm. We demonstrate dynamic expression patterns for the hematopoietic progenitor markers CD34, CD133, and GATA2 in developing Hep cells, and confirm these findings in vivo with analyses of human fetal livers collected in the first and second trimesters of gestation. Knockdown of CD34, CD133, and GATA2 revealed their impact on hepatic specification of Hep cells mostly in a cell-autonomous fashion. This study highlights the powerful utility of the hESC differentiation system to recapitulate early human hepatic specification and has uncovered the functional impact on hepatic specification and maturation of hematopoietic progenitor markers expressed in human hepatoblasts.

Results and Discussion

Experimental Procedures

This work was supported by the Black Family Stem Cell Institute, NIH/NIDDK (R01DK087867-01) and the March of Dimes to V.G.E. (FY113-969). The authors are grateful to Drs Georges Uzan and Vanina Jodon de Villenoche for providing us with FT human fetal livers.

Human embryonic stem cells (hESCs) are pluripotent stem cells that exhibit epithelial-like features resembling the epiblast epithelium of the post-implantation embryo (Nichols and Smith, 2009). Similarly to epithelial cells, hESCs are dependent on E-cadherin-mediated cell-cell contacts and anchorage to the extracellular matrix (ECM) via integrin receptors (Ohgushi et al., 2010; Braam et al., 2008). Various studies have established the efficacy of integrin engagement with ECM substrates in supporting hESC self-renewal and pluripotency (Braam et al., 2008; Baxter et al., 2009; Miyazaki et al., 2012; Soteriou et al., 2013; Rodin et al., 2014). However, the specific nature and role of downstream signaling from integrins in hESCs remains largely unexplored.
One of the key functions of the ECM in epithelial cells is to prevent a common form of apoptosis, anoikis, or “homelessness” of cells that have lost contact with the matrix (Frisch and Francis, 1994). Anoikis is executed via the mitochondrion and results in activation of caspase downstream of integrin-associated pathways (Gilmore et al., 2000). ECM-integrin interaction initiates signaling, promoting the assembly of cytoplasmic scaffold and kinase proteins at focal adhesions near active integrin clusters (Giancotti and Ruoslahti, 1999). Focal adhesion kinase (FAK), a protein tyrosine kinase, is one of the principal integrin signaling regulators, containing three domains: the protein 4.1, ezrin, radixin, moesin (FERM) domain, the kinase domain, and the focal adhesion targeting domain (Frame et al., 2010). Upon integrin activation FAK localizes at the adhesion site where structural changes displace the inhibitory FERM, allowing autophosphorylation of the Tyr397 (Y397) site, leading to the activation of its intrinsic kinase function and the formation of docking sites for multiple downstream signaling molecules (Frame et al., 2010). Several signaling players directly interact with the Y397 site, e.g., Src, which in turn phosphorylates FAK, promoting further activation, or p130Cas, Grb2, and phosphatidylinositol 3-kinase (PI3K), involved in controlling cytoskeletal rearrangements, cell cycle, and survival (Parsons, 2003). FAK is crucial in preventing anoikis through direct activation of PI3K, via the Y397 site, in turn promoting the pro-survival AKT cascade (Gilmore et al., 2000; Xia et al., 2004). FAK can also leave focal adhesions and act in a kinase-independent manner by localizing in the nucleus where the FERM scaffolds the AKT target MDM2 for ubiquitination of pro-apoptotic p53, leading to its protein degradation (Lim et al., 2008).