Challenges in Clinical Development of Mesenchymal Stromal/Stem Cells: Concise Review

Identified 50 years ago, mesenchymal stromal/stem cells (MSCs) immediately generated a substantial interest among the scientific community because of their differentiation plasticity and hematopoietic supportive function. Early investigations provided evidence of a relatively low engraftment rate and a transient benefit for challenging congenital and acquired diseases. The reasons for these poor therapeutic benefits forced the entire field to reconsider MSC mechanisms of action together with their ex vivo manipulation procedures. This phase resulted in advances in MSCs processing and the hypothesis that MSC-tissue supportive functions may be prevailing their differentiation plasticity, broadening the spectrum of MSCs therapeutic potential far beyond their lineage-restricted commitments. Consequently, an increasing number of studies have been conducted for a variety of clinical indications, revealing additional challenges and suggesting that MSCs are still lagging behind for a solid clinical translation. For this reason, our aim was to dissect the current challenges in the development of still promising cell types that, after more than half a century, still need to reach their maturity. Stem Cells Translational Medicine 2019;8:1135–1148

Impact of HOXB7 overexpression on human adipose-derived mesenchymal progenitors

Background: The ex vivo expansion potential of mesenchymal stromal/stem cells (MSC) together with their differentiation and secretion properties makes these cells an attractive tool for transplantation and tissue engineering. Although the use of MSC is currently being tested in a growing number of clinical trials, it is still desirable to identify molecular markers that may help improve their performance both in vitro and after transplantation. Methods: Recently, HOXB7 was identified as a master player driving the proliferation and differentiation of bone marrow mesenchymal progenitors. In this study, we investigated the effect of HOXB7 overexpression on the ex vivo features of adipose mesenchymal progenitors (AD-MSC). Results: HOXB7 increased AD-MSC proliferation potential, reduced senescence, and improved chondrogenesis together with a significant increase of basic fibroblast growth factor (bFGF) secretion. Conclusion: While further investigations and in vivo models shall be applied for better understanding, these data suggest that modulation of HOXB7 may be a strategy for innovative tissue regeneration applications

Laser Guide Stars for Extremely Large Telescopes: Efficient Shack-Hartmann Wavefront Sensor Design using Weighted center-of-gravity algorithm

Over the last few years increasing consideration has been given to the study of Laser Guide Stars (LGS) for the measurement of the disturbance introduced by the atmosphere in optical and near-infrared astronomical observations from the ground. A possible method for the generation of a LGS is the excitation of the Sodium layer in the upper atmosphere at approximately 90 km of altitude. Since the Sodium layer is approximately 10 km thick, the artificial reference source looks elongated, especially when observed from the edge of a large aperture. The spot elongation strongly limits the performance of the most common wavefront sensors. The centroiding accuracy in a Shack-Hartmann wavefront sensor, for instance, decreases proportionally to the elongation (in a photon noise dominated regime). To compensate for this effect a straightforward solution is to increase the laser power, i.e. to increase the number of detected photons per subaperture. The scope of the work presented in this paper is twofold: an analysis of the performance of the Weighted Center of Gravity algorithm for centroiding with elongated spots and the determination of the required number of photons to achieve a certain average wavefront error over the telescope aperture.Comment: 10 pages, 14 figure

A Novel 3D In Vitro Platform for Pre-Clinical Investigations in Drug Testing, Gene Therapy, and Immuno-oncology.

Tumors develop within complex cell-to-cell interactions, with accessory cells playing a relevant role starting in the early phases of cancer progression. This event occurs in a three-dimensional (3D) environment, which to date, has been difficult to reproduce in vitro due to its complexity. While bi-dimensional cultures have generated substantial data, there is a progressive awareness that 3D culture strategies may rapidly increase the understanding of tumor development and be used in anti-cancer compound screening and for predicting response to new drugs utilizing personalized approaches. However, simple systems capable of rapidly rebuilding cancer tissues ex-vivo in 3D are needed and could be used for a variety of applications. Therefore, we developed a flat, handheld and versatile 3D cell culture bioreactor that can be loaded with tumor and/or normal cells in combination which can be monitored using a variety of read-outs. This biocompatible device sustained 3D growth of tumor cell lines representative of various cancers, such as pancreatic and breast adenocarcinoma, sarcoma, and glioblastoma. The cells repopulated the thin matrix which was completely separated from the outer space by two gas-permeable membranes and was monitored in real-time using both microscopy and luminometry, even after transportation. The device was tested in 3D cytotoxicity assays to investigate the anti-cancer potential of chemotherapy, biologic agents, and cell-based therapy in co-cultures. The addition of luciferase in target cancer cells is suitable for comparative studies that may also involve parallel in vivo investigations. Notably, the system was challenged using primary tumor cells harvested from lung cancer patients as an innovative predictive functional assay for cancer responsiveness to checkpoint inhibitors, such as nivolumab. This bioreactor has several novel features in the 3D-culture field of research, representing a valid tool useful for cancer investigations, drug screenings, and other toxicology approaches

Physics Behind Precision

This document provides a writeup of contributions to the FCC-ee mini-workshop on "Physics behind precision" held at CERN, on 2-3 February 2016.Comment: https://indico.cern.ch/event/469561

Predictive fat mass equations for spinal muscular atrophy type I children: Development and internal validation

BACKGROUND: Body composition assessment is paramount for spinal muscular atrophy type I (SMA I) patients, as weight and BMI have proven to be misleading for these patients. Despite its importance, no disease-specific field method is currently available, and the assessment of body composition of SMA I patients requires reference methods available only in specialized settings. OBJECTIVE: To develop predictive fat mass equations for SMA I children based on simple measurements, and compare existing equations to the new disease-specific equations. DESIGN: Demographic, clinical and anthropometric data were examined as potential predictors of the best candidate response variable and non-linear relations were taken into account by transforming continuous predictors with restricted cubic splines. Alternative models were fitted including all the dimensions revealed by cluster analysis of the predictors. The best models were then internally validated, quantifying optimism of the obtained performance measures. The contribution of nusinersen treatment to the unexplained variability of the final models was also tested. RESULTS: A total of 153 SMA I patients were included in the study, as part of a longitudinal observational study in SMA children conducted at the International Center for the Assessment of Nutritional Status (ICANS), University of Milan. The sample equally represented both sexes (56% females) and a wide age range (from 3 months to 12 years, median 1.2 years). Four alternative models performed equally in predicting fat mass fraction (fat mass/body weight). The most convenient was selected and further presented. The selected model uses as predictors sex, age, calf circumference and the sum of triceps, suprailiac and calf skinfold thicknesses. The model showed high predictive ability (optimism corrected coefficient of determination, R2 = 0.72) and internal validation indicated little optimism both in performance measures and model calibration. The addition of nusinersen as a predictor variable did not improve the prediction. The disease-specific equation was more accurate than the available fat mass equations. CONCLUSIONS: The developed prediction model allows the assessment of body composition in SMA I children with simple and widely available measures and with reasonable accuracy

Growth patterns in children with spinal muscular atrophy

Background: Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by muscle atrophy and weakness. SMA type 1 (SMA1) is the most severe form: affected infants are unable to sit unaided; SMA type 2 (SMA2) children can sit, but are not able to walk independently. The Standards of Care has improved quality of life and the increasing availability of disease-modifying treatments is progressively changing the natural history; so, the clinical assessment of nutritional status has become even more crucial. Aims of this multicenter study were to present the growth pattern of treatment-naïve SMA1 and SMA2, and to compare it with the general growth standards. Results: Body Weight (BW, kg) and Supine Length (SL, cm) were collected using a published standardized procedure. SMA-specific growth percentiles curves were developed and compared to the WHO reference data. We recruited 133 SMA1 and 82 SMA2 (48.8% females). Mean ages were 0.6 (0.4–1.6) and 4.1 (2.1–6.7) years, respectively. We present here a set of disease-specific percentiles curves of BW, SL, and BMI-for-age for girls and boys with SMA1 and SMA2. These curves show that BW is significantly lower in SMA than healthy peers, while SL is more variable. BMI is also typically lower in both sexes and at all ages. Conclusions: These data on treatment-naïve patients point toward a better understanding of growth in SMA and could be useful to improve the clinical management and to assess the efficacy of the available and forthcoming therapies not only on motor function, but also on growth

Predictive energy equations for spinal muscular atrophy type I children

BACKGROUND: Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status. OBJECTIVE: To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations. METHODS: Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients. RESULTS: In na\uefve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009).In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949).Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error. CONCLUSIONS: We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations