The current study suggests that intravenous injection of MSCs into rabbits with chemotherapy-induced ovarian damage improved ovarian function. MSCs accomplish this function by direct differentiation into specific cellular phenotypes and by secretion of VEGF, which influence the regeneration of the ovary.

Mass spectrometry (MS) has become an integral tool in life sciences. The first step in MS analysis is ion formation (ionization). Many ionization methods currently exist; electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI) are the most commonly used. ESI relies on the formation of charged droplets releasing ions from the surface (ion evaporation model) or via complete solvent evaporation (charge residual model). MALDI ionization, however, is facilitated via laser energy and the use of a matrix. Despite wide use, ESI cannot efficiently ionize nonpolar compounds. Atmospheric pressure chemical ionization (APCI) and atmospheric pressure photo ionization (APPI) are better suited for such tasks. APPI requires photon energy and a dopant, whereas APCI is similar to chemical ionization. In 2004, ambient MS was introduced in which ionization occurs at the sample in its native form. Desorption electrospray ionization (DESI) and direct analysis in real time (DART) are the most widely used methods. In this mini-review, we provide an overview of the main ionization methods and the mechanisms of ion formation. This article is educational and intended for students/researchers who are not very familiar with MS and would like to learn the basics; it is not for MS experts.

With the fast growing market of pure enantiomer drugs and bioactive molecules, new chiral-selective analytical tools have been instigated including the use of mass spectrometry (MS). Even though MS is one of the best analytical tools that has efficiently been used in several pharmaceutical and biological applications, traditionally MS is considered as a "chiral-blind" technique. This limitation is due to the MS inability to differentiate between two enantiomers of a chiral molecule based merely on their masses. Several approaches have been explored to assess the potential role of MS in chiral analysis. The first approach depends on the use of MS-hyphenated techniques utilizing fast and sensitive chiral separation tools such as liquid chromatography (LC), gas chromatography (GC), and capillary electrophoresis (CE) coupled to MS detector. More recently, several alternative separation techniques have been evaluated such as supercritical fluid chromatography (SFC) and capillary electrochromatography (CEC); the latter being a hybrid technique that combines the efficiency of CE with the selectivity of LC. The second approach is based on using the MS instrument solely for the chiral recognition. This method depends on the behavioral differences between enantiomers towards a foreign molecule and the ability of MS to monitor such differences. These behavioral differences can be divided into three types: (i) differences in the enantiomeric affinity for association with the chiral selector, (ii) differences of the enantiomeric exchange rate with a foreign reagent, and (iii) differences in the complex MS dissociation behaviors of the enantiomers. Most recently, ion mobility spectrometry was introduced to qualitatively and quantitatively evaluate chiral compounds. This article provides an overview of MS role in chiral analysis by discussing MS based methodologies and presenting the challenges and promises associated with each approach.

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Introduction Urine is an ideal matrix for metabolomics investigation due to its non-invasive nature of collection and its rich metabolite content. Despite the advancements in mass spectrometry and 1 H-NMR platforms in urine metabolomics, the statistical analysis of the generated data is challenged with the need to adjust for the hydration status of the person. Normalization to creatinine or osmolality values are the most adopted strategies, however, each technique has its challenges that can hinder its wide application. Objective Assessment of whether the statistical model established using a targeted urine metabolomics dataset for the differential diagnosis of asthma and chronic obstructive pulmonary disease (COPD) would be improved by normalization to osmolality instead of creatinine. Methods A metabolomics dataset from 51 patient urine samples previously analyzed using two liquid chromatography-tandem mass spectrometry methods was used. The data was normalized to creatinine and osmolality. The statistical analysis was achieved using partial least square discriminant analysis and models of separation were generated and compared. Results Creatinine and osmolality values in asthma and COPD patients were strongly correlated. Using the same metabolites, we found that normalization to osmolality did not significantly change the results. The metabolites of importance in separation remained the same for both methods. The statistical strength of the creatinine model was somewhat better than the osmolality normalized model (R 2 Q 2 =0.919, 0.705 vs R 2 Q 2 =0.929, 0.671). Conclusion Our findings suggest that targeted urine metabolomics data can be normalized to creatinine or osmolality with no significant impact on the diagnostic accuracy of the model.