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Evidence from models and experiments suggests that the networked structure observed in mitochondria emerges at the critical point of a phase transition controlled by fission and fusion rates. If mitochondria are poised at criticality, the relevant network quantities should scale with the system’s size. However, whether or not the expected finite-size effects take place has not been demonstrated yet. Here, we first provide a theoretical framework to interpret the scaling behavior of mitochondrial network quantities by analyzing two conceptually different models of mitochondrial dynamics. Then, we perform a finite-size scaling analysis of real mitochondrial networks extracted from microscopy images and obtain scaling exponents comparable with critical exponents from models and theory. Overall, we provide a universal description of the structural phase transition in mammalian mitochondria.

Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural properties are often interwinded, here we characterized the structure of mitochondrial networks in mouse embryonic fibroblasts using network tools and percolation theory. Subsequently we perturbed the system either by promoting the fusion of mitochondrial segments or by inducing mitochondrial fission. Quantitative analysis of mitochondrial clusters revealed that structural parameters of healthy mitochondria laid in between the extremes of highly fragmented and completely fusioned networks. We confirmed our results by contrasting our empirical findings with the predictions of a recently described computational model of mitochondrial network emergence based on fission-fusion kinetics. Altogether these results offer not only an objective methodology to parametrize the complexity of this organelle but also support the idea that mitochondrial networks behave as critical systems and undergo structural phase transitions.

Although Parkinson’s disease (PD) is usually considered as a movement disorder, it is strongly associated with non-motor symptoms (NMS), including smell and taste dysfunctions, cognitive impairment, apathy, fatigue, and autonomic dysregulation. Olfactory deficit is considered the most common NMS in PD preceding the motor symptoms for years. The aim of this study was to investigate olfactory function, cognitive impairment, apathy, and fatigue in patients with PD in comparison with healthy controls, and subsequently to analyse the correlations between these NMS and motor symptoms severity in subjects with PD. One hundred and forty-seven participants were enrolled (96 PD patients, mean age in years 67.5, SD 7.2; 51 healthy controls; mean age 65.1, SD 11.8). Olfactory function was evaluated using the Sniffin’ Sticks test (odor detection threshold, discrimination and identification). The Montreal Cognitive Assessment (MoCA) was used to assess cognitive impairment. Apathy was examined by the self-report version of Starkstein Apathy Scale and fatigue was evaluated with the Parkinson’s Disease Fatigue Scale. PD patients showed severe impairment in odor detection threshold, discrimination, and identification compared to healthy controls. Moreover, in PD patients, apathy and fatigue scores were significantly increased, while MoCA scores were decreased in comparison with controls. Multivariate linear regression analyses showed that both apathy and Unified PD Rating Scale (UPDRS) were associated with odor identification, discrimination and Threshold–Discrimination–Identification (TDI) score. In conclusion, our results reported changes in apathy and motor disability as significant predictors in alterations of odor identification, discrimination and TDI score. Furthermore, these data suggest that olfactory dysfunction might progress in tight relation with motor impairment UPDRS but also with non-motor symptoms such as apathy.

Many complex systems exhibit large fluctuations both across space and over time. These fluctuations have often been linked to the presence of some kind of critical phenomena, where it is well known that the emerging correlation functions in space and time are closely related to each other. Here we test whether the time correlation properties allow systems exhibiting a phase transition to self-tune to their critical point. We describe results in three models: the 2D Ising ferromagnetic model, the 3D Vicsek flocking model and a small-world neuronal network model. We demonstrate that feedback from the autocorrelation function of the order parameter fluctuations shifts the system towards its critical point. Our results rely on universal properties of critical systems and are expected to be relevant to a variety of other settings.

The scaling of correlations as a function of size provides important hints to understand critical phenomena on a variety of systems. Its study in biological structures offers two challenges: usually they are not of infinite size, and, in the majority of cases, dimensions can not be varied at will. Here we discuss how finite-size scaling can be approximated in an experimental system of fixed and relatively small extent, by computing correlations inside of a reduced field of view of various widths (we will refer to this procedure as “box-scaling”). A relation among the size of the field of view, and measured correlation length, is derived at, and away from, the critical regime. Numerical simulations of a neuronal network, as well as the ferromagnetic 2D Ising model, are used to verify such approximations. Numerical results support the validity of the heuristic approach, which should be useful to characterize relevant aspects of critical phenomena in biological systems.

Sixty-six dairy farms (as average, 167.0 ± 106.5 milking cows and milk yield of 31.4 ± 5.1) were visited to identify different nutritional approaches adopted in dairy cows diet formulation. Forage, TMR, faecal, and milk samples from lactating herds were collected and diet composition, in vitro methane production, in vivo nutrient digestibility, faecal fermentation profile and milk yield and milk quality were characterised. A hierarchical cluster analysis was applied and six nutritional approaches in diet formulation corresponding with six different clusters (CL) were identified. The CL discriminated the farm feeding choices in the following nutritional strategies, based on high use of: (i) high moisture corn (HMC) and legume silage, (ii) compound feed, (iii) corn and soy meals, (iv) HMC and soy meal, (v) corn meal and protein compound feeds, or (vi) HMC and protein compound feed strategies, respectively for CL1 to CL6. The milk yield tended (p = .061) to differ among CL. The greatest (>1.60) feed efficiency was calculated for CL1 and 5, whereas the lowest (<1.45) for CL 2. The CL2 and 5 had the highest feed costs (i.e. 0.24 or 0.22 €/kg of milk, respectively). Interestingly, the high use of HMC or steam flaked corn resulted associated to higher farm performances. Particularly, HMC and legume silage (CL1), HCM and soy meal (CL4) and HCM and protein compound feed (CL6) nutritional strategies resulted more efficient and profitable, having the greatest feed efficiency, protein and starch degradability as well as income over feed costs. Differentiate carbohydrates in dairy cow diets seems highly convenient. HIGHLIGHTS Six different nutritional strategies were identified based on use of single ingredients and a great variability in both economic and feed efficiency was observed for dairy farms clustering into different groups The use of high moisture ear corn in substitution of corn meal increased dry matter intake, feed efficiency, milk yield and lactose content of milk, whereas the use of steam flaked corn reduced the faecal fermentations The in vitro methane emission potential of diets did not differ among clustered nutritional strategies

We analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans . The robot interacts with the environment through a sensor that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow emergent robot actions in complex environments, such as avoiding collisions with obstacles. Working with robotic models makes it possible to simultaneously keep track of the dynamics of all the neurons and also register the actions of the robot in the environment in real time, while avoiding the complex technicalities of simulating a real environment. This allowed us to identify several relevant features of the neural dynamics associated with the emergent actions of the robot, some of which have already been observed in biological worms. These results suggest that some basic aspects of behaviors observed in living beings are determined by the underlying structure of the associated neural network.

Multidrug-resistant tuberculosis (MDR-TB) is a major burden to public health in low incidence countries in Europe. The aim of this study was to attempt to have a better insight into the trends of MDR-TB in the metropolitan area of Rome, within the Italian and the foreign-born population, based on microbiological and demographic data. We performed a prospective study, collecting microbiological data based on phenotypic drug-resistant testing (DST) of TB strains consecutively isolated in a referral hospital in Rome, the capital city of a low TB incidence country, over a 6-year period, and correlated them to the geographical origin of patients. This study was carried out in a referral hospital for patients with drug-resistant TB from the whole region. Drug-resistance data from 926 patients with a microbiological diagnosis of TB from 2011 to 2016 show a 5.5% rate of MDR-TB, mostly occurring in patients born in a single East European country, that has a high incidence of MDR-TB. The strains isolated from these patients frequently carry additional resistances, leading to an increased risk of developing extensively drug-resistant (XDR) TB. In the great metropolitan area of Rome, MDR-TB more frequently occurs in patients who were born in a single country from Eastern Europe known to have high rates of MDR-TB and long-time residents in Italy. Recent immigrants from non-European countries do not appear to contribute to the rates of MDR-TB reported in this article. This knowledge of local TB trends could help improve the measures of surveillance and prevention of disease.

Spineless cactus is a useful feed for various animal species in arid and semiarid regions due to its adaptability to dry and harsh soil, high efficiency of water use and carbohydrates storage. This meta-analysis was carried out to assess the effect of spineless cactus on animal performance, and develop and evaluate equations to predict dry matter intake (DMI) and average daily gain (ADG) in meat lambs. Equations for predicting DMI and ADG as a function of animal and diet characteristics were developed using data from eight experiments. The dataset was comprised of 40 treatment means from 289 meat lambs, in which cactus was included from 0 to 75% of the diet dry matter (DM). Accuracy and precision were evaluated by cross-validation using the mean square error of prediction (MSEP), which was decomposed into mean bias, systematic bias and random error; concordance correlation coefficient, which was decomposed into accuracy (C b) and precision (ρ); and coefficient of determination (R 2). In addition, the data set was used to evaluate the predicting accuracy and precision of the main lamb feeding systems (Agricultural and Food Research Council, Small Ruminant Nutritional System, National Research Council and Institut National de la Recherche Agronomique) and also two Brazilian studies. The DMI, CP intake (CPI), metabolizable energy (ME) intake and ADG increased when cactus was included up to 499 g/kg DM (P<0.001). In contrast, animals fed high levels of cactus (>500 g/kg DM) had a decreased DMI, CPI and NDF intake, but increased feed efficiency (P<0.001) and similar ADG compared with those without cactus addition. The DMI was positively correlated with initial BW, final BW, concentrate and ADG, while it was negatively correlated with cactus inclusion and ME of the diet. On other hand, ADG was positively correlated with DMI, initial and mean BW and concentrate, and it was negatively correlated with cactus inclusion. The two developed equations had high accuracy (Cb of 0.95 for DMI and 0.94 for ADG) and the random error of MSEP was 99% for both equations. The precision of both equations was moderate, with R2 values of 0.53 and 0.50 and ρ values of 0.73 and 0.71 for DMI and ADG, respectively. In conclusion, the developed equation to predict DMI had moderate precision and high accuracy, nonetheless, it was more efficient than those reported in the literature. The proposed equations can be a useful alternative to estimate intake and performance of lambs fed cactus.

Introduction Safinamide is a recent antiparkinsonian drug that modulates both dopaminergic and glutamatergic systems with positive effects on motor and nonmotor symptoms of Parkinson’s disease (PD). Here, we aimed to describe the efficacy and safety of safinamide in the Italian PD patients in real-life conditions. Methods We performed a sub-analysis of the Italian cohort of the SYNAPSES study, a multi-country, multi-center, retrospective-prospective cohort observational study, designed to investigate the use of safinamide in routine clinical practice. Patients received for the first time a treatment with safinamide and were followed up for 12 months. The analysis was conducted on the overall population and in subgroups of interest: i) patients > 75 years, ii) patients with relevant comorbidities and iii) patients affected by psychiatric symptoms. Results Italy enrolled 616/1610 patients in 52 centers, accounting for 38% of the entire SYNAPSES cohort. Of the patients enrolled, 86.0% were evaluable at 12 months, with 23.3% being > 75 years, 42.4% with psychiatric conditions and 67.7% with relevant comorbidities. Safinamide was effective on motor symptoms and fluctuations as measured through the Unified PD rating scale III and IV scores, and on the total score, without safety issues in none of the subgroups considered. Conclusion The SYNAPSES data related to Italian patients confirms the good safety profile of safinamide even in special groups of patients. Motor fluctuations and motor impairment improved at the follow-up suggesting the significant role of safinamide in managing motor symptoms in PD patients.