Summary Aging is characterized by a progressive loss of muscle mass and impaired contractility (e.g., decline in force, velocity, and power). Although the slowing of contraction speed in aging muscle is well described, the underlying molecular mechanisms responsible for the decrement in speed are unknown. Myosin heavy chain (MHC) isoforms are the primary molecules determining contractile velocity; however, the contraction speed of single fibers within a given MHC isoform type is variable. Recent evidence proposes that the decline in shortening velocity (Vo) with aging is associated with a decrease in the relative content of essential myosin light chain 3f (MLC3f) isoform. In the current study, we first evaluated the relative content of MLC3f isoform and Vo in adult and old rats. We then used recombinant adenovirus (rAd) gene transfer technology to increase MLC3f protein content in the MHC type II semimembranosus muscle (SM). We hypothesized that (i) aging would decrease the relative MLC3f content and Vo in type II fibers, and (ii) increasing the MLC3f content would restore the age-induced decline in Vo. We found that there was an age-related decrement in relative MLC3f content and Vo in MHC type II fibers. Increasing MLC3f content, as indicated by greater % MLC3f and MLC3f/MLC2f ratio, provided significant protection against age-induced decline in Vo without influencing fiber diameter, force generation, MHC isoform distribution, or causing cellular damage. To the best of our knowledge, these are the first data to demonstrate positive effects of MLC3f against slowing of contractile function in aged skeletal muscle.

Background Etiopathogenesis of preterm birth (PTB) is multifactorial, with a universe of risk factors interplaying between the mother and the environment. It is of utmost importance to identify the most informative factors in order to estimate the degree of PTB risk and trace an individualized profile. The aims of the present study were: 1) to identify all acknowledged risk factors for PTB and to select the most informative ones for defining an accurate model of risk prediction; 2) to verify predictive accuracy of the model and 3) to identify group profiles according to the degree of PTB risk based on the most informative factors. Methods The Maternal Frailty Inventory (MaFra) was created based on a systematic review of the literature including 174 identified intrauterine (IU) and extrauterine (EU) factors. A sample of 111 pregnant women previously categorized in low or high risk for PTB below 37 weeks, according to ACOG guidelines, underwent the MaFra Inventory. First, univariate logistic regression enabled p-value ordering and the Akaike Information Criterion (AIC) selected the model including the most informative MaFra factors. Second, random forest classifier verified the overall predictive accuracy of the model. Third, fuzzy c-means clustering assigned group membership based on the most informative MaFra factors. Results The most informative and parsimonious model selected through AIC included Placenta Previa, Pregnancy Induced Hypertension, Antibiotics, Cervix Length, Physical Exercise, Fetal Growth, Maternal Anxiety, Preeclampsia, Antihypertensives. The random forest classifier including only the most informative IU and EU factors achieved an overall accuracy of 81.08% and an AUC of 0.8122. The cluster analysis identified three groups of typical pregnant women, profiled on the basis of the most informative IU and EU risk factors from a lower to a higher degree of PTB risk, which paralleled time of birth delivery. Conclusions This study establishes a generalized methodology for building-up an evidence-based holistic risk assessment for PTB to be used in clinical practice. Relevant and essential factors were selected and were able to provide an accurate estimation of degree of PTB risk based on the most informative constellation of IU and EU factors.

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