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Abstract Mitochondrial damage is implicated as a major contributing factor for a number of noncommunicable chronic diseases such as cardiovascular diseases, cancer, obesity, and insulin resistance/type 2 diabetes. Here, we discuss the role of mitochondria in maintaining cellular and whole-organism homeostasis, the mechanisms that promote mitochondrial dysfunction, and the role of this phenomenon in noncommunicable chronic diseases. We also review the state of the art regarding the preclinical evidence associated with the regulation of mitochondrial function and the development of current mitochondria-targeted therapeutics to treat noncommunicable chronic diseases. Finally, we give an integrated vision of how mitochondrial damage is implicated in these metabolic diseases. Graphical Abstract Graphical Abstract

Higher-order interactions underlie complex phenomena in systems such as biological and artificial neural networks, but their study is challenging due to the scarcity of tractable models. By leveraging a generalisation of the maximum entropy principle, we introduce curved neural networks as a class of models with a limited number of parameters that are particularly well-suited for studying higher-order phenomena. Through exact mean-field descriptions, we show that these curved neural networks implement a self-regulating annealing process that can accelerate memory retrieval, leading to explosive order-disorder phase transitions with multi-stability and hysteresis effects. Moreover, by analytically exploring their memory-retrieval capacity using the replica trick, we demonstrate that these networks can enhance memory capacity and robustness of retrieval over classical associative-memory networks. Overall, the proposed framework provides parsimonious models amenable to analytical study, revealing higher-order phenomena in complex networks. Higher-order interactions shape complex neural dynamics but are hard to model. Here, authors use a generalization of the maximum entropy principle to introduce a family of curved neural networks, revealing explosive phase transitions and enhanced memory via a self-regulating retrieval mechanism.

Key Points Sarco/endoplasmic reticulum–mitochondria communication and mitochondrial dynamics are essential regulators of mitochondrial function, cellular metabolism, and calcium homeostasis Sarco/endoplasmic reticulum–mitochondria contacts and mitochondrial dynamics modulate myocardial contractility and vascular smooth muscle cell differentiation Alterations in sarco/endoplasmic reticulum–mitochondria communication and in mitochondrial network morphology are implicated in several cardiovascular pathologies, including heart failure, coronary artery disease, and pulmonary hypertension More studies are required to define the role that alterations in sarco/endoplasmic–mitochondria contacts and mitochondrial dynamics have in the pathogenesis of cardiovascular diseases Mitochondrial metabolism is essential for the dynamic regulation of cardiac and vascular tissues, and the relevance of basic mitochondrial biology in cardiovascular disease is being increasingly recognized. In this Review, the authors explore the physical interaction between mitochondria and sarco/endoplasmic reticulum, discussing how the communication between these two organelles is involved in cardiovascular pathologies. Repetitive, calcium-mediated contractile activity renders cardiomyocytes critically dependent on a sustained energy supply and adequate calcium buffering, both of which are provided by mitochondria. Moreover, in vascular smooth muscle cells, mitochondrial metabolism modulates cell growth and proliferation, whereas cytosolic calcium levels regulate the arterial vascular tone. Physical and functional communication between mitochondria and sarco/endoplasmic reticulum and balanced mitochondrial dynamics seem to have a critical role for optimal calcium transfer to mitochondria, which is crucial in calcium homeostasis and mitochondrial metabolism in both types of muscle cells. Moreover, mitochondrial dysfunction has been associated with myocardial damage and dysregulation of vascular smooth muscle proliferation. Therefore, sarco/endoplasmic reticulum–mitochondria coupling and mitochondrial dynamics are now viewed as relevant factors in the pathogenesis of cardiac and vascular diseases, including coronary artery disease, heart failure, and pulmonary arterial hypertension. In this Review, we summarize the evidence related to the role of sarco/endoplasmic reticulum–mitochondria communication in cardiac and vascular muscle physiology, with a focus on how perturbations contribute to the pathogenesis of cardiovascular disorders.

This paper investigates generalized thermodynamic relationships in physical systems where relevant macroscopic variables are determined by the exponential Kolmogorov–Nagumo average. We show that while the thermodynamic entropy of such systems is naturally described by Rényi’s entropy with parameter γ , an ordinary Boltzmann distribution still describes their statistics under equilibrium thermodynamics. Our results show that systems described by exponential Kolmogorov–Nagumo averages can be interpreted as systems originally in thermal equilibrium with a heat reservoir with inverse temperature β that are suddenly quenched to another heat reservoir with inverse temperature β ′ = ( 1 − γ ) β . Furthermore, we show the connection with multifractal thermodynamics. For the non-equilibrium case, we show that the dynamics of systems described by exponential Kolmogorov–Nagumo averages still observe a second law of thermodynamics and the H-theorem. We further discuss the applications of stochastic thermodynamics in those systems—namely, the validity of fluctuation theorems—and the connection with thermodynamic length.

Skeletal muscle is one of the main regulators of carbohydrate and lipid metabolism in our organism, and therefore, it is highly susceptible to changes in glucose and fatty acid (FA) availability. Skeletal muscle is an extremely complex tissue: its metabolic capacity depends on the type of fibers it is made up of and the level of stimulation it undergoes, such as acute or chronic contraction. Obesity is often associated with increased FA levels, which leads to the accumulation of toxic lipid intermediates, oxidative stress, and autophagy in skeletal fibers. This lipotoxicity is one of the most common causes of insulin resistance (IR). In this scenario, the “isolation” of certain lipids in specific cell compartments, through the action of the specific lipid droplet, perilipin (PLIN) family of proteins, is conceived as a lifeguard compensatory strategy. In this review, we summarize the cellular mechanism underlying lipid mobilization and metabolism inside skeletal muscle, focusing on the function of lipid droplets, the PLIN family of proteins, and how these entities are modified in exercise, obesity, and IR conditions.

Decreased skeletal muscle strength and mitochondrial dysfunction are characteristic of diabetes. The actions of insulin and IGF-1 through the insulin receptor (IR) and IGF-1 receptor (IGF1R) maintain muscle mass via suppression of forkhead box O (FoxO) transcription factors, but whether FoxO activation coordinates atrophy in concert with mitochondrial dysfunction is unknown. We show that mitochondrial respiration and complex I activity were decreased in streptozotocin (STZ) diabetic muscle, but these defects were reversed in muscle-specific FoxO1, -3, and -4 triple-KO (M-FoxO TKO) mice rendered diabetic with STZ. In the absence of systemic glucose or lipid abnormalities, muscle-specific IR KO (M-IR-/-) or combined IR/IGF1R KO (MIGIRKO) impaired mitochondrial respiration, decreased ATP production, and increased ROS. These mitochondrial abnormalities were not present in muscle-specific IR, IGF1R, and FoxO1, -3, and -4 quintuple-KO mice (M-QKO). Acute tamoxifen-inducible deletion of IR and IGF1R also decreased muscle pyruvate respiration, complex I activity, and supercomplex assembly. Although autophagy was increased when IR and IGF1R were deleted in muscle, mitophagy was not increased. Mechanistically, RNA-Seq revealed that complex I core subunits were decreased in STZ-diabetic and MIGIRKO muscle, and these changes were not present with FoxO KO in STZ-FoxO TKO and M-QKO mice. Thus, insulin-deficient diabetes or loss of insulin/IGF-1 action in muscle decreases complex I-driven mitochondrial respiration and supercomplex assembly in part by FoxO-mediated repression of complex I subunit expression.

Vascular smooth muscle cells (VSMC) dedifferentiation from a contractile to a synthetic phenotype contributes to atherosclerosis. Atherosclerotic tissue has a chronic inflammatory component with high levels of tumor necrosis factor-α (TNF-α). VSMC of atheromatous plaques have increased autophagy, a mechanism responsible for protein and intracellular organelle degradation. The aim of this study was to evaluate whether TNF-α induces phenotype switching of VSMCs and whether this effect depends on autophagy. Rat aortic Vascular smooth A7r5 cell line was used as a model to examine the phenotype switching and autophagy. These cells were stimulated with TNF-α 100 ng/mL. Autophagy was determined by measuring LC3-II and p62 protein levels. Autophagy was inhibited using chloroquine and siRNA Beclin1. Cell dedifferentiation was evaluated by measuring the expression of contractile proteins α-SMA and SM22, extracellular matrix protein osteopontin and type I collagen levels. Cell proliferation was measured by [3H]-thymidine incorporation and MTT assay, and migration was evaluated by wound healing and transwell assays. Expression of IL-1β, IL-6 and IL-10 was assessed by ELISA. TNF-α induced autophagy as determined by increased LC3-II (1.91±0.21, p<0.001) and decreased p62 (0.86±0.02, p<0.05) when compared to control. Additionally, TNF-α decreased α-SMA (0.74±0.12, p<0.05) and SM22 (0.54±0.01, p<0.01) protein levels. Consequently, TNF-α induced migration (1.25±0.05, p<0.05), proliferation (2.33±0.24, p<0.05), and the secretion of IL-6 (258±53, p<0.01), type I collagen (3.09±0.85, p<0.01) and osteopontin (2.32±0.46, p<0.01). Inhibition of autophagy prevented all the TNF-α-induced phenotypic changes. TNF-α induces phenotype switching in A7r5 cell line by a mechanism that required autophagy. Therefore, autophagy may be a potential therapeutic target for the treatment of atherosclerosis.

The volume of labeled data is often the primary determinant of success in developing machine learning algorithms. This has increased interest in methods for leveraging crowds to scale data labeling efforts, and methods to learn from noisy crowd-sourced labels. The need to scale labeling is acute but particularly challenging in medical applications like pathology, due to the expertise required to generate quality labels and the limited availability of qualified experts. In this paper we investigate the application of Scalable Variational Gaussian Processes for Crowdsourcing (SVGPCR) in digital pathology. We compare SVGPCR with other crowdsourcing methods using a large multi-rater dataset where pathologists, pathology residents, and medical students annotated tissue regions breast cancer. Our study shows that SVGPCR is competitive with equivalent methods trained using gold-standard pathologist generated labels, and that SVGPCR meets or exceeds the performance of other crowdsourcing methods based on deep learning. We also show how SVGPCR can effectively learn the class-conditional reliabilities of individual annotators and demonstrate that Gaussian-process classifiers have comparable performance to similar deep learning methods. These results suggest that SVGPCR can meaningfully engage non-experts in pathology labeling tasks, and that the class-conditional reliabilities estimated by SVGPCR may assist in matching annotators to tasks where they perform well.

The development of biorefinery processes to platform chemicals for most lignocellulosic substrates, results in side processes to intermediates such as oligosaccharides. Agrofood wastes are most amenable to produce such intermediates, in particular, cellooligo-saccharides (COS), pectooligosaccharides (POS), xylooligosaccharides (XOS) and other less abundant oligomers containing mannose, arabinose, galactose and several sugar acids. These compounds show a remarkable bioactivity as prebiotics, elicitors in plants, food complements, healthy coadyuvants in certain therapies and more. They are medium to high added-value compounds with an increasing impact in the pharmaceutical, nutraceutical, cosmetic and food industries. This review is focused on the main production processes: autohydrolysis, acid and basic catalysis and enzymatic saccharification. Autohydrolysis of food residues at 160–190 °C leads to oligomer yields in the 0.06–0.3 g/g dry solid range, while acid hydrolysis of pectin (80–120 °C) or cellulose (45–180 °C) yields up to 0.7 g/g dry polymer. Enzymatic hydrolysis at 40–50 °C of pure polysaccharides results in 0.06–0.35 g/g dry solid (DS), with values in the range 0.08–0.2 g/g DS for original food residues.

Social adaptation arises from the interaction between the individual and the social environment. However, little empirical evidence exists regarding the relationship between social contact and social adaptation. We propose that loneliness and social networks are key factors explaining social adaptation. Sixty-four healthy subjects with no history of psychiatric conditions participated in this study. All participants completed self-report questionnaires about loneliness, social network, and social adaptation. On a separate day, subjects underwent a resting state fMRI recording session. A hierarchical regression model on self-report data revealed that loneliness and social network were negatively and positively associated with social adaptation. Functional connectivity (FC) analysis showed that loneliness was associated with decreased FC between the fronto-amygdalar and fronto-parietal regions. In contrast, the social network was positively associated with FC between the fronto-temporo-parietal network. Finally, an integrative path model examined the combined effects of behavioral and brain predictors of social adaptation. The model revealed that social networks mediated the effects of loneliness on social adaptation. Further, loneliness-related abnormal brain FC (previously shown to be associated with difficulties in cognitive control, emotion regulation, and sociocognitive processes) emerged as the strongest predictor of poor social adaptation. Findings offer insights into the brain indicators of social adaptation and highlight the role of social networks as a buffer against the maladaptive effects of loneliness. These findings can inform interventions aimed at minimizing loneliness and promoting social adaptation and are especially relevant due to the high prevalence of loneliness around the globe. These findings also serve the study of social adaptation since they provide potential neurocognitive factors that could influence social adaptation.