Search

The conditions that allow for the sustained growth of a protocell population are investigated in the case of asymmetrical division. The results are compared to those of previous studies concerning models of symmetrical division, where synchronization (between duplication of the genetic material and fission of the lipid container) was found under a variety of different assumptions about the kinetic equations and about the place where molecular replication takes place. Such synchronization allows a sustained proliferation of the protocell population. In the asymmetrical case, there can be no true synchronization, since the time to duplication may depend upon the initial size, but we introduce a notion of homogeneous growth that actually allows for the sustained reproduction of a population of protocells. We first analyze Surface Reaction Models, defined in the text, and we show that in many cases they undergo homogeneous growth under the same kinetic laws that lead to synchronization in the symmetrical case. This is the case also for Internal Reaction Models (IRMs), which, however, require a deeper understanding of what homogeneous growth actually means, as discussed below.

Background: Non-alcoholic fatty liver disease (NAFLD) has a high prevalence in obesity and its presence should be screened. Laparoscopic sleeve gastrectomy (LSG) is an effective treatment for obesity, but its effects on NAFLD are still to be firmly established. The diagnosis of non-alcoholic steatohepatitis (NASH) is currently performed by liver biopsy, a costly and invasive procedure. Squamous cell carcinoma antigen-IgM (SCCA-IgM) is a biomarker of viral hepatitis to hepatocellular carcinoma development and its role in NAFLD to NASH progression has not yet been investigated. Objective: The aim of this study was to evaluate SCCA-IgM as a non-invasive biomarker of NAFLD/NASH in patients with different degrees of metabolic-complicated obesity before and after LSG. Method: Fifty-six patients with obesity were studied before and 12 months after LSG; anthropometric, biochemical, clinical, and imaging data were collected. Results: At baseline steatosis was strongly associated with the glycaemic profile (p = 0.016) and was already present in prediabetic patients with obesity (82%). Only 3 patients had an SCCA-IgM level above the normal cut-off. SCCA-IgM titre did not change according to glycaemic profile or steatosis. Metabolic and inflammatory factors and transaminases significantly reduced after LSG-induced weight loss, except for SCCA-IgM. The ALT/AST ratio decreased post-LSG correlated with BMI (r = 0.297, p = 0.031), insulin (r = 0.354, p = 0.014), and triglycerides (r = 0.355, p = 0.009) reduction. Conclusions: Our results confirm the tight link between NAFLD and metabolic complications, suggesting prediabetes as a new risk factor of steatosis. SCCA-IgM does not seem to have a role in the identification and prognosis of NAFLD.

Background. Adequate levels of selenium (Se) have protective effects against several chronic diseases, such as obesity. The aim of this study was to assess the effect of Se supplementation in a selected group of patients with obesity. Methods. This randomized prospective study included 37 overweight/obese individuals aged 18–65 years, who adopted a slightly hypocaloric diet for 3 months. An intervention group received 240 μg/day of L-selenomethionine for 3 months; a control group received a placebo. Clinical and biochemical parameters, body composition measurements, and the Psychological General Well-Being Index (PGWBI) questionnaire were tested at the beginning and end of the treatment. Results. A comparison of the two groups showed a significant change in body composition, involving a decrease in body fat mass, between the baseline and the end of the follow-up, in the intervention group. Unlike the placebo group, the group given Se had a significant increase in lean body and muscle mass and a significant decrease in leptin levels after 3 months on diet. At the end of the follow-up, the group given Se scored higher on the PGWBI than those who did not. Conclusion. Se could reinforce the effects of diet for overweight and obesity. This work was registered in the ISRCTN registry with study ID ISRCTN6106073.

Determinants of resting energy expenditure (REE) in humans are still under investigation, especially the association with insulin resistance. Brown adipose tissue (AT) regulates energy expenditure through the activity of the uncoupling protein 1 (UCP1). White AT browning is the process by which some adipocytes within AT depots acquire properties of brown adipocytes (“brite” adipocytes) and it correlates with metabolic improvement. We analyzed determinants of REE in patients with obesity and assessed UCP1 expression as a “brite” marker in abdominal subcutaneous AT (SAT) and visceral omental AT (VAT). Clinical data, REE, free fat mass (FFM), and fat mass (FM) were determined in 209 patients with obesity. UCP1, PPARG coactivator 1 alpha (PPARGC1A), transcription factor A, mitochondrial (TFAM), T-box transcription factor 1 (TBX1), and solute carrier family 27 member 1 (SLC27A1) expression was assayed in SAT and VAT samples, obtained during sleeve gastrectomy from 62 patients with obesity. REE and body composition data were also available for a subgroup of 35 of whom. In 209 patients with obesity a multiple regression model was computed with REE as the dependent variable and sex, waist, FFM, FM, homeostasis model assessment-insulin resistance (HOMA), interleukin-6 and High Density Lipoprotein-cholesterol as the independent variables. Only FFM, FM and HOMA were independently correlated with REE (r = 0.787, AdjRsqr = 0.602). In each patient VAT displayed a higher UCP1, PPARGC1A, TFAM, TBX1, and SLC27A1 expression than SAT and UCP1 expression in VAT (UCP1-VAT) correlated with Body Mass Index (BMI) (r = 0.287, p < 0.05). Introducing UCP1-VAT in the multivariate model, we showed that FFM, HOMA, interleukin-6, High Density Lipoprotein-cholesterol, and UCP1-VAT were independent factors correlated with REE (r = 0.736, AdjRsqr = 0.612). We confirmed that REE correlates with FFM, FM and HOMA in a large cohort of patients. Our results clearly showed that UCP1-VAT expression was significantly increased in severe human obesity (BMI > 50 kg/m2) and that it behaved as an independent predictor of REE. Lastly, we suggest that an increased REE and browning in metabolically complicated severe obesity could represent an effort to counteract further weight gain.

In many complex systems one observes the formation of medium-level structures, whose detection could allow a high-level description of the dynamical organization of the system itself, and thus to its better understanding. We have developed in the past a powerful method to achieve this goal, which however requires a heavy computational cost in several real-world cases. In this work we introduce a modified version of our approach, which reduces the computational burden. The design of the new algorithm allowed the realization of an original suite of methods able to work simultaneously at the micro level (that of the binary relationships of the single variables) and at meso level (the identification of dynamically relevant groups). We apply this suite to a particularly relevant case, in which we look for the dynamic organization of a gene regulatory network when it is subject to knock-outs. The approach combines information theory, graph analysis, and an iterated sieving algorithm in order to describe rather complex situations. Its application allowed to derive some general observations on the dynamical organization of gene regulatory networks, and to observe interesting characteristics in an experimental case.

The properties of most systems composed of many interacting elements are neither determined by the topology of the interaction network alone, nor by the dynamical laws in isolation. Rather, they are the outcome of the interplay between topology and dynamics. In this paper, we consider four different types of systems with critical dynamic regime and with increasingly complex dynamical organization (loosely defined as the emergent property of the interactions between topology and dynamics) and analyze them from a structural and dynamic point of view. A first noteworthy result, previously hypothesized but never quantified so far, is that the topology per se induces a notable increase in dynamic organization. A second observation is that evolution does not change dramatically the size distribution of the present dynamic groups, so it seems that it keeps track of the already present organization induced by the topology. Finally, and similarly to what happens in other applications of evolutionary algorithms, the types of dynamic changes strongly depend upon the used fitness function.

Living beings share several common features at the molecular level, but there are very few large-scale “operating principles” which hold for all (or almost all) organisms. However, biology is subject to a deluge of data, and as such, general concepts such as this would be extremely valuable. One interesting candidate is the “criticality” principle, which claims that biological evolution favors those dynamical regimes that are intermediaries between ordered and disordered states (i.e., “at the edge of chaos”). The reasons why this should be the case and experimental evidence are briefly discussed, observing that gene regulatory networks are indeed often found on, or close to, the critical boundaries. Therefore, assuming that criticality provides an edge, it is important to ascertain whether systems that are critical can further evolve while remaining critical. In order to explore the possibility of achieving such “always-critical” evolution, we resort to simulated evolution, by suitably modifying a genetic algorithm in such a way that the newly-generated individuals are constrained to be critical. It is then shown that these modified genetic algorithms can actually develop critical gene regulatory networks with two interesting (and quite different) features of biological significance, involving, in one case, the average gene activation values and, in the other case, the response to perturbations. These two cases suggest that it is often possible to evolve networks with interesting properties without losing the advantages of criticality. The evolved networks also show some interesting features which are discussed.

Hypercholesterolemia is a major risk factor for cardiovascular disease (CVD). Lowering low-density lipoproteins-cholesterol (LDL-C) has been shown to decrease the risk of CVD and of all-cause mortality. For appropriate management, estimation of each individual’s total cardiovascular risk is critical, as patients should receive treatment according to their cardiovascular risk category as well as their LDL-C level. However, available data indicate that a large proportion of patients fail to achieve lipid goals despite treatment, and a significant percentage of patients are not able to tolerate statin treatment. Researchers have therefore focused considerable attention on the development of novel LDL-C-lowering agents that act via different mechanisms. Among the most recent advances in clinical development are the proprotein convertase subtilisin/kexin 9 antibody inhibitors, including alirocumab and evolocumab, which appear particularly promising, with clinical trial data indicating these agents to be both well tolerated and highly efficacious in lowering LDL-C.