Feasibility and Short-Term Outcomes in Liver-First Approach: A Spanish Snapshot Study (the RENACI Project).

(1) Background: The liver-first approach may be indicated for colorectal cancer patients with synchronous liver metastases to whom preoperative chemotherapy opens a potential window in which liver resection may be undertaken. This study aims to present the data of feasibility and short-term outcomes in the liver-first approach. (2) Methods: A prospective observational study was performed in Spanish hospitals that had a medium/high-volume of HPB surgeries from 1 June 2019 to 31 August 2020. (3) Results: In total, 40 hospitals participated, including a total of 2288 hepatectomies, 1350 for colorectal liver metastases, 150 of them (11.1%) using the liver-first approach, 63 (42.0%) in hospitals performing <50 hepatectomies/year. The proportion of patients as ASA III was significantly higher in centers performing ≥50 hepatectomies/year (difference: 18.9%; p = 0.0213). In 81.1% of the cases, the primary tumor was in the rectum or sigmoid colon. In total, 40% of the patients underwent major hepatectomies. The surgical approach was open surgery in 87 (58.0%) patients. Resection margins were R0 in 78.5% of the patients. In total, 40 (26.7%) patients had complications after the liver resection and 36 (27.3%) had complications after the primary resection. One-hundred and thirty-two (89.3%) patients completed the therapeutic regime. (4) Conclusions: There were no differences in the surgical outcomes between the centers performing <50 and ≥50 hepatectomies/year. Further analysis evaluating factors associated with clinical outcomes and determining the best candidates for this approach will be subsequently conducted.

Critical appraisal of surgical margins according to KRAS status in liver resection for colorectal liver metastases: Should surgical strategy be influenced by tumor biology?

BACKGROUND: KRAS mutation is a negative prognostic factor for colorectal liver metastases. Several studies have investigated the resection margins according to KRAS status, with conflicting results. The aim of the study was to assess the oncologic outcomes of R0 and R1 resections for colorectal liver metastases according to KRAS status. METHODS: All patients who underwent resection for colorectal liver metastases between 2010 and 2015 with available KRAS status were enrolled in this multicentric international cohort study. Logistic regression models were used to investigate the outcomes of R0 and R1 colorectal liver metastases resections according to KRAS status: wild type versus mutated. The primary outcomes were overall survival and disease-free survival. RESULTS: The analysis included 593 patients. KRAS mutation was associated with shorter overall survival (40 vs 60 months; P = .0012) and disease-free survival (15 vs 21 months; P = .003). In KRAS-mutated tumors, the resection margin did not influence oncologic outcomes. In multivariable analysis, the only predictor of disease-free survival and overall survival was primary tumor location (P = .03 and P = .03, respectively). In KRAS wild-type tumors, R0 resection was associated with prolonged overall survival (74 vs 45 months, P < .001) and disease-free survival (30 vs 17 months, P < .001). The multivariable model confirmed that R0 resection margin was associated with prolonged overall survival (hazard ratio = 1.43, 95% confidence interval: 1.01-2.03) and disease-free survival (hazard ratio = 1.42; 95% confidence interval: 1.06-1.91). CONCLUSIONS: KRAS-mutated colorectal liver metastases showed more aggressive tumor biology with inferior overall survival and disease-free survival after liver resection. Although R0 resection was not associated with improved oncologic outcomes in the KRAS-mutated tumors group, it seems to be of paramount importance for achieving prolonged long-term survival in KRAS wild-type tumors.

Sparse species interactions reproduce abundance correlation patterns in microbial communities.

During the last decades, macroecology has identified broad-scale patterns of abundances and diversity of microbial communities and put forward some potential explanations for them. However, these advances are not paralleled by a full understanding of the dynamical processes behind them. In particular, abundance fluctuations of different species are found to be correlated, both across time and across communities in metagenomic samples. Reproducing such correlations through appropriate population models remains an open challenge. The present paper tackles this problem and points to sparse species interactions as a necessary mechanism to account for them. Specifically, we discuss several possibilities to include interactions in population models and recognize Lotka-Volterra constants as a successful ansatz. For this, we design a Bayesian inference algorithm to extract sets of interaction constants able to reproduce empirical probability distributions of pairwise correlations for diverse biomes. Importantly, the inferred models still reproduce well-known single-species macroecological patterns concerning abundance fluctuations across both species and communities. Endorsed by the agreement with the empirically observed phenomenology, our analyses provide insights into the properties of the networks of microbial interactions, revealing that sparsity is a crucial feature.

Unconventional criticality, scaling breakdown, and diverse universality classes in the Wilson-Cowan model of neural dynamics.

The Wilson-Cowan model constitutes a paradigmatic approach to understanding the collective dynamics of networks of excitatory and inhibitory units. It has been profusely used in the literature to analyze the possible phases of neural networks at a mean-field level, e.g., assuming large fully connected networks. Moreover, its stochastic counterpart allows one to study fluctuation-induced phenomena, such as avalanches. Here we revisit the stochastic Wilson-Cowan model paying special attention to the possible phase transitions between quiescent and active phases. We unveil eight possible types of such transitions, including continuous ones with scaling behavior belonging to known universality classes-such as directed percolation and tricritical directed percolation-as well as six distinct ones. In particular, we show that under some special circumstances, at a so-called "Hopf tricritical directed percolation" transition, rather unconventional behavior is observed, including the emergence of scaling breakdown. Other transitions are discontinuous and show different types of anomalies in scaling and/or exhibit mixed features of continuous and discontinuous transitions. These results broaden our knowledge of the possible types of critical behavior in networks of excitatory and inhibitory units and are, thus, of relevance to understanding avalanche dynamics in actual neuronal recordings. From a more general perspective, these results help extend the theory of nonequilibrium phase transitions into quiescent or absorbing states.

The prognostic value of neutrophile/lymphocyte ratio and serum chemerin to predict maternal-fetal complications in pregnant systemic lupus erythematosus patients.

BACKGROUND: Pregnancy in SLE continues to be a challenge. The neutrophil-to-lymphocyte ratio (NLR) and chemerin are predictors of preeclampsia in the general population; however, their role as predictors of maternal-fetal complications in pregnant SLE patients has not been analyzed. OBJECTIVE: To investigate the prognostic value of NLR and serum chemerin, to predict maternal-fetal complications in pregnant SLE patients, and compare both biomarkers among three study groups. METHODS: Design: Analytical cross-sectional study of cases and controls with the following study groups: systemic lupus erythematosus (SLE), preeclampsia, and healthy. NLR and chemerin serum were determined between 20 and 25 weeks of gestation. Patients were evaluated every 4-6 weeks until pregnancy resolution. Maternal and fetal outcomes were registered. We employed Receiver Operating Characteristic (ROC) curves to validate prognostic values. RESULTS: Seventy pregnant patients were included: 20 with SLE, 20 with preeclampsia, and 30 healthy pregnant women; NLR values were 4 (2.3-5.6) in SLE, 6 (4.6-9.2) in preeclampsia, and 2.8 (2.1-2.9) in the group of healthy women (p = .0001). Chemerin levels were: 26 (15.3-56.2) in SLE, 96 (37.3-146.2) in preeclampsia, and 24.6 ng/mL (15.3-47.4) in the healthy group (p = .007) Maternal complications were observed in 11 (55%), 20 (100%), and 8 (26%) per group, respectively. Thrombocytopenia was the most frequent complication in all pregnant women, followed by hypertensive disorders. Fetal complications were registered in 12 (60%), 16 (80%), and 2 (6.7%), respectively. Congenital malformations and prematurity were the most frequent fetal complications. NLR had good diagnostic accuracy in predicting maternal-fetal complications (AUROC 0.715) p = .015, CI 95% 0.56-0.86, cut-off point level: 2.9, sensitivity 61%, specificity 78%, positive predictive value (PPV) 65%, negative predictive value (NPV) 75%. Regarding chemerin, a cut-off point level >43 ng/mL had a sensitivity of 75%, specificity of 72% AUROC 0.75, p = .001, CI 95% 0.61-0.89, PPV 51.7% NPV 87.8%, meaning that 51.7% of patients with chemerin levels >43 ng/mL have or will have preeclampsia. CONCLUSION: The NLR may help predict maternal-fetal complications in SLE pregnancy, constituting a marker of subclinical inflammation. Chemerin levels may be associated with preeclampsia. These biomarkers could improve the care of SLE patients with timely intervention of potential complications during pregnancy.

Environmental fluctuations explain the universal decay of species-abundance correlations with phylogenetic distance.

Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches-which combine phylogenetic relationships between species with community ecology-have the potential to disentangle such forces but are often hard to connect with quantitative predictions from theoretical models. On the other hand, macroecology, which focuses on statistical patterns of abundance and diversity, provides natural connections with theoretical models but often neglects interspecific correlations and interactions. Here, we propose a unified framework combining both such approaches to analyze microbial communities. In particular, by using both cross-sectional and longitudinal metagenomic data for species abundances, we reveal the existence of an empirical macroecological law establishing that correlations in species-abundance fluctuations across communities decay from positive to null values as a function of phylogenetic dissimilarity in a consistent manner across ecologically distinct microbiomes. We formulate three variants of a mechanistic model-each relying on alternative ecological forces-that lead to radically different predictions. From these analyses, we conclude that the empirically observed macroecological pattern can be quantitatively explained as a result of shared population-independent fluctuating resources, i.e., environmental filtering and not as a consequence of, e.g., species competition. Finally, we show that the macroecological law is also valid for temporal data of a single community and that the properties of delayed temporal correlations can be reproduced as well by the model with environmental filtering.

Modular architecture facilitates noise-driven control of synchrony in neuronal networks.

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

Depinning in the quenched Kardar-Parisi-Zhang class. I. Mappings, simulations, and algorithm.

Depinning of elastic systems advancing on disordered media can usually be described by the quenched Edwards-Wilkinson equation (qEW). However, additional ingredients such as anharmonicity and forces that cannot be derived from a potential energy may generate a different scaling behavior at depinning. The most experimentally relevant is the Kardar-Parisi-Zhang (KPZ) term, proportional to the square of the slope at each site, which drives the critical behavior into the so-called quenched KPZ (qKPZ) universality class. We study this universality class both numerically and analytically: by using exact mappings we show that at least for d=1,2 this class encompasses not only the qKPZ equation itself, but also anharmonic depinning and a well-known class of cellular automata introduced by Tang and Leschhorn. We develop scaling arguments for all critical exponents, including size and duration of avalanches. The scale is set by the confining potential strength m^{2}. This allows us to estimate numerically these exponents as well as the m-dependent effective force correlator Δ(w), and its correlation length ρ:=Δ(0)/|Δ^{'}(0)|. Finally, we present an algorithm to numerically estimate the effective (m-dependent) elasticity c, and the effective KPZ nonlinearity λ. This allows us to define a dimensionless universal KPZ amplitude A:=ρλ/c, which takes the value A=1.10(2) in all systems considered in d=1. This proves that qKPZ is the effective field theory for all these models. Our work paves the way for a deeper understanding of depinning in the qKPZ class, and in particular, for the construction of a field theory that we describe in a companion paper.

Use and outcome of minimally invasive pancreatic surgery in the European E-MIPS registry.

BACKGROUND: The European registry for minimally invasive pancreatic surgery (E-MIPS) collects data on laparoscopic and robotic MIPS in low- and high-volume centers across Europe. METHODS: Analysis of the first year (2019) of the E-MIPS registry, including minimally invasive distal pancreatectomy (MIDP) and minimally invasive pancreatoduodenectomy (MIPD). Primary outcome was 90-day mortality. RESULTS: Overall, 959 patients from 54 centers in 15 countries were included, 558 patients underwent MIDP and 401 patients MIPD. Median volume of MIDP was 10 (7-20) and 9 (2-20) for MIPD. Median use of MIDP was 56.0% (IQR 39.0-77.3%) and median use of MIPD 27.7% (IQR 9.7-45.3%). MIDP was mostly performed laparoscopic (401/558, 71.9%) and MIPD mostly robotic (234/401, 58.3%). MIPD was performed in 50/54 (89.3%) centers, of which 15/50 (30.0%) performed ≥20 MIPD annually. This was 30/54 (55.6%) centers and 13/30 (43%) centers for MIPD respectively. Conversion rate was 10.9% for MIDP and 8.4% for MIPD. Overall 90 day mortality was 1.1% (n = 6) for MIDP and 3.7% (n = 15) for MIPD. CONCLUSION: Within the E-MIPS registry, MIDP is performed in about half of all patients, mostly using laparoscopy. MIPD is performed in about a quarter of patients, slightly more often using the robotic approach. A minority of centers met the Miami guideline volume criteria for MIPD.

Anomalous finite-size scaling in higher-order processes with absorbing states.

Here we study standard and higher-order birth-death processes on fully connected networks, within the perspective of large-deviation theory [also referred to as the Wentzel-Kramers-Brillouin (WKB) method in some contexts]. We obtain a general expression for the leading and next-to-leading terms of the stationary probability distribution of the fraction of "active" sites as a function of parameters and network size N. We reproduce several results from the literature and, in particular, we derive all the moments of the stationary distribution for the q-susceptible-infected-susceptible (q-SIS) model, i.e., a high-order epidemic model requiring q active ("infected") sites to activate an additional one. We uncover a very rich scenario for the fluctuations of the fraction of active sites, with nontrivial finite-size-scaling properties. In particular, we show that the variance-to-mean ratio diverges at criticality for [1≤q≤3], with a maximal variability at q=2, confirming that complex-contagion processes can exhibit peculiar scaling features including wild variability. Moreover, the leading order in a large-deviation approach does not suffice to describe them: next-to-leading terms are essential to capture the intrinsic singularity at the origin of systems with absorbing states. Some possible extensions of this work are also discussed.

Quasiuniversal scaling in mouse-brain neuronal activity stems from edge-of-instability critical dynamics.

The brain is in a state of perpetual reverberant neural activity, even in the absence of specific tasks or stimuli. Shedding light on the origin and functional significance of such a dynamical state is essential to understanding how the brain transmits, processes, and stores information. An inspiring, albeit controversial, conjecture proposes that some statistical characteristics of empirically observed neuronal activity can be understood by assuming that brain networks operate in a dynamical regime with features, including the emergence of scale invariance, resembling those seen typically near phase transitions. Here, we present a data-driven analysis based on simultaneous high-throughput recordings of the activity of thousands of individual neurons in various regions of the mouse brain. To analyze these data, we construct a unified theoretical framework that synergistically combines a phenomenological renormalization group approach and techniques that infer the general dynamical state of a neural population, while designing complementary tools. This strategy allows us to uncover strong signatures of scale invariance that are "quasiuniversal" across brain regions and experiments, revealing that all the analyzed areas operate, to a greater or lesser extent, near the edge of instability.

Treatment with sotrovimab for SARS-CoV-2 infection in a cohort of high-risk kidney transplant recipients.

Background: Sotrovimab is a neutralizing monoclonal antibody (mAb) that seems to remain active against recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. The evidence on its use in kidney transplant (KT) recipients, however, is limited. Methods: We performed a multicenter, retrospective cohort study of 82 KT patients with SARS-CoV-2 infection {coronavirus disease 2019 [COVID-19]} treated with sotrovimab. Results: Median age was 63 years. Diabetes was present in 43.9% of patients, and obesity in 32.9% of patients; 48.8% of patients had an estimated glomerular filtration rate under 30 mL/minute/1.73 m2. Additional anti-COVID-19 therapies were administered to 56 patients, especially intravenous steroids (65.9%). Sotrovimab was administered early (<5 days from the onset of the symptoms) in 46 patients (56%). Early-treated patients showed less likely progression to severe COVID-19 than those treated later, represented as a lower need for ventilator support (2.2% vs 36.1%; P < .001) or intensive care admission (2.2% vs 25%; P = .002) and COVID-19-related mortality (2.2% vs 16.7%; P = .020). In the multivariable analysis, controlling for baseline risk factors to severe COVID-19 in KT recipients, early use of sotrovimab remained as a protective factor for a composite outcome, including need for ventilator support, intensive care, and COVID-19-related mortality. No anaphylactic reactions, acute rejection episodes, impaired kidney function events, or non-kidney side effects related to sotrovimab were observed. Conclusions: Sotrovimab had an excellent safety profile, even in high-comorbidity patients and advanced chronic kidney disease stages. Earlier administration could prevent progression to severe disease, while clinical outcomes were poor in patients treated later. Larger controlled studies enrolling KT recipients are warranted to elucidate the true efficacy of monoclonal antibody therapies.

The broad edge of synchronization: Griffiths effects and collective phenomena in brain networks.

Many of the amazing functional capabilities of the brain are collective properties stemming from the interactions of large sets of individual neurons. In particular, the most salient collective phenomena in brain activity are oscillations, which require the synchronous activation of many neurons. Here, we analyse parsimonious dynamical models of neural synchronization running on top of synthetic networks that capture essential aspects of the actual brain anatomical connectivity such as a hierarchical-modular and core-periphery structure. These models reveal the emergence of complex collective states with intermediate and flexible levels of synchronization, halfway in the synchronous-asynchronous spectrum. These states are best described as broad Griffiths-like phases, i.e. an extension of standard critical points that emerge in structurally heterogeneous systems. We analyse different routes (bifurcations) to synchronization and stress the relevance of 'hybrid-type transitions' to generate rich dynamical patterns. Overall, our results illustrate the complex interplay between structure and dynamics, underlining key aspects leading to rich collective states needed to sustain brain functionality. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Tonic pain reduces autonomic responses and EEG functional connectivity elicited by affective stimuli.

Most pain studies have focused on only two aspects of pain: the influence of pain on attentional processing and the modulation of pain perception by affective stimuli. However, the influence of tonic pain on the attentional processing of affective stimuli has not been studied. In this study, we investigated the effects of tonic pain on the attentional processing of affective stimuli, focusing on autonomic responses and their relationship with both EEG power and functional connectivity. Forty participants (20 men and 20 women) received tonically painful and nonpainful thermal stimulation while viewing blocks of pleasant, unpleasant, or neutral images. The galvanic skin conductance response (SCR), electrocardiographic activity, and electroencephalographic (EEG) activity in the delta and theta bands were recorded. Participants rated the unpleasantness of the pain at the end of each block. Typical affective SCR and heart rate (HR) patterns were found in the no-pain condition, but when the pain was delivered, these patterns disappeared. EEG power and functional connectivity results showed that tonic pain affected the delta band in the central region during pleasant and unpleasant image blocks. Our findings suggest that tonic pain captured attentional focus and reduced the cognitive resources available for processing affective stimuli, altering the emotional experience associated with pain.

A Comparison of Clinical Characteristics and Outcomes Between Indigenous and Non-Indigenous Patients Presenting to Townsville Hospital Emergency Department With Chest Pain.

BACKGROUND: Indigenous Australians have a high rate of ischaemic heart disease (IHD). There is a paucity of local data for North Queensland regarding the clinical characteristics of Indigenous people who present to the emergency department (ED) with chest pain. The aim of the study is to compare the cardiovascular risk factors, social characteristics, and the clinical outcomes between Indigenous and non-Indigenous patients who presented with cardiac-related chest pain. METHODS: This is a retrospective single-centre audit. The data was collected through chart reviews of chest pain presentations to the Townsville University Hospital Emergency Department, Queensland, Australia, from January to December 2017. We categorised the patients into Indigenous and non-Indigenous groups and compared their cardiac risk factors and social characteristics. We further classified the patients into three diagnosis groups and we measured the clinical outcomes in the patients with a diagnosis of cardiac-related chest pain. We used a data linkage to the Registry of Births, Deaths and Marriages for the death outcomes. A multivariable analysis was done to determine the risk of major adverse cardiac event (MACE) for Indigenous vs non-Indigenous patients. RESULTS: Indigenous patients were over-represented making up 19.1% of the total cohort (compared with 11.1% of the North Queensland Indigenous population) and presented at a younger age (median age: 45 vs 52, p<0.005). Traditional cardiovascular risk factors were significantly higher in Indigenous patients. The incidence of discharge against medical advice was also higher (6.5% vs 2.7%, p<0.005). There was an underutilisation of the local chest pain pathway amongst the Indigenous group (35.8% vs 44.7%, p<0.005). In patients with a diagnosis of cardiac-related chest pain, the rate of receiving invasive coronary angiogram procedures was similar in both cohorts (44.5% vs 43.7%, p=0.836). With regards to outcomes, Indigenous patients suffered from acute coronary syndrome (ACS) at a younger median age (51 vs 64, p<0.005) and were more likely to have severe three vessel disease (17% vs 6%, p<0.005) leading to coronary bypass graft surgery (CABG) (19% vs 6%, p<0.005). When adjusted for age, gender, and comorbidities, Indigenous patients were more likely to have MACE within 1 year of their chest pain presentation, compared with non-Indigenous patients with the same diagnosis (adjusted odds ration [AOR]=2.0, 95% CI [1.1, 3.8], p=0.03). CONCLUSION: In our study, Indigenous patients carried a heavier burden of cardiovascular risk factors, presented at a younger age, with more severe coronary disease and had a higher rate of CABG. We found an underutilisation of the local chest pain protocol amongst the Indigenous cohort, which suggests a need to improve support structures in the ED. In our multivariable analysis, Indigenous patients suffered from a significantly higher MACE compared to non-Indigenous patients which indicates that more collaborative efforts are needed to improve the cardiovascular health of local Aboriginal and Torres Strait Islander people.

Statistical process control charts for better analysis of sequential data in psychology: The case of illusion of control experiments.

Illusion of control (IOC) is a bias in the judgment of personal success with implications to learning theories and health policies; some important questions in the investigation of IOC may be related to traditional measures in the field, namely self-assessment using Likert scales about the sense of control. Statistical process control (SPC) and Shewhart charts are methods developed to monitor and control industrial processes, never applied in psychological studies before. The present two studies investigated the use of the technique of Shewhart charts in the analysis of IOC. The purpose was to explore the use of SPC and Shewhart charts in the analysis of data sequences from psychological experiments; the objective was to analyze the results of reaction time (RT) data sequences plotted in SPC charts, in comparison with self-assessment judgments from an IOC task. Participants were 63 undergraduate students (Study 1) and 103 mine workers (Study 2) instructed to try to control a traffic light on a computer by pressing or not the keyboard. Higher probabilities of the successful outcome generated judgments of illusion and shifts (due to cognitive activity) in the charts of RT; lower probabilities resulted in null illusion and RT presented a random and stable profile. Patterns for different groups emerged in Shewhart charts. SPC can contribute to the analysis of the behavior of sequences of data in psychological studies, so that the charts indicate changes and patterns not detected by traditional ANOVA and other linear models.

EEG-heart rate connectivity changes after sensorimotor rhythm neurofeedback training: Ancillary study.

OBJECTIVES: Neurofeedback can induce long-term changes in brain functional connectivity, but its influence on the connectivity between different physiological systems is unknown. The present paper is an ancillary study of a previous paper that confirmed the effect of neurofeedback on brain connectivity associated with chronic pain. We analysed the influence of neurofeedback on the connectivity between the electroencephalograph (EEG) and heart rate (HR). METHODS: Seventeen patients diagnosed with fibromyalgia were divided into three groups: good sensorimotor rhythm (SMR) training responders (n = 4), bad SMR responders (n = 5) and fake training (SHAM, n = 8). Training consisted of six sessions in which participants learned to synchronize and desynchronize SMR power. Before the first training (pre-resting state) and sixth training (post-resting state) session, open-eye resting-state EEG and electrocardiograph signals were recorded. RESULTS: Good responders reduced pain ratings after SMR neurofeedback training. This improvement in fibromyalgia symptoms was associated with a reduction of the connectivity between the central area and HR, between central and frontal areas, within the central area itself, and between central and occipital areas. The sham group and poor responders experienced no changes in their fibromyalgia symptoms. CONCLUSIONS: Our results provide new evidence that neurofeedback is a promising tool that can be used to treat of chronic pain syndromes and to obtain a better understanding of the interactions between physiological networks. These findings are preliminary, but they may pave the way for future studies that are more methodologically robust. In addition, new research questions are raised: what is the role of the central-peripheral network in chronic pain and what is the effect of neurofeedback on this network.

Simple sugar intake and cancer incidence, cancer mortality and all-cause mortality: A cohort study from the PREDIMED trial.

OBJECTIVE: To examine associations between intake of simple sugars and cancer incidence, cancer mortality, and total mortality in a prospective cohort study based on the PREDIMED trial conducted from 2003 to 2010. METHODS: Participants were older individuals at high cardiovascular risk. Exposures were total sugar, glucose and fructose from solid or liquid sources, and fructose from fruit and 100% fruit juice. Cancer incidence was the primary outcome; cancer mortality and all-cause mortality were secondary outcomes. Multivariable-adjusted, time-dependent Cox proportional hazard models were used. RESULTS: Of 7447 individuals enrolled, 7056 (94.7%) were included (57.6% women, aged 67.0 ± 6.2 years). 534 incident cancers with 152 cancer deaths and 409 all-cause deaths were recorded after a median follow-up of 6 years. Intake of simple sugars in solid form was unrelated to outcomes. Higher cancer incidence was found per 5 g/day increase in intake of liquid sugars, with multivariable-adjusted HR of 1.08 (95% CI, 1.03-1.13) for total liquid sugar, 1.19 (95% CI, 1.07-1.31) for liquid glucose, 1.14 (95% CI, 1.05-1.23) for liquid fructose, and 1.39 (95% CI, 1.10-1.74) for fructose from fruit juice. Cancer and all-cause mortality increased to a similar extent with intake of all sugars in liquid form. In categorical models, cancer risk was dose-related for all liquid sugars. CONCLUSIONS: Simple sugar intake in drinks and fruit juice was associated with an increased risk of overall cancer incidence and mortality and all-cause mortality. This suggests that sugary beverages are a modifiable risk factor for cancer and all-cause mortality.

Phenotypic-dependent variability and the emergence of tolerance in bacterial populations.

Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intersperse much more tightly than traditionally assumed, especially in communities of microorganisms. Advancing the development of mathematical and computational approaches to shed novel light onto eco-evolutionary problems is a challenge of utmost relevance. With this motivation in mind, here we scrutinize recent experimental results showing evidence of rapid evolution of tolerance by lag in bacterial populations that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the distribution of single-cell lag times-i.e., the times that individual bacteria from the community remain in a dormant state to cope with stress-evolves its average value to approximately fit the antibiotic-exposure time. Moreover, the distribution develops right-skewed heavy tails, revealing the presence of individuals with anomalously large lag times. Here, we develop a parsimonious individual-based model mimicking the actual demographic processes of the experimental setup. Individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is transmitted with variation to the progeny. The model-in a version in which the amplitude of phenotypic variations grows with the parent's lag time-is able to reproduce quite well the key empirical observations. Furthermore, we develop a general mathematical framework allowing us to describe with good accuracy the properties of the stochastic model by means of a macroscopic equation, which generalizes the Crow-Kimura equation in population genetics. Even if the model does not account for all the biological mechanisms (e.g., genetic changes) in a detailed way-i.e., it is a phenomenological one-it sheds light onto the eco-evolutionary dynamics of the problem and can be helpful to design strategies to hinder the emergence of tolerance in bacterial communities. From a broader perspective, this work represents a benchmark for the mathematical framework designed to tackle much more general eco-evolutionary problems, thus paving the road to further research avenues.