Early consequences of the phospholamban mutation PLN-R14del+/- in a transgenic mouse model.

AIMS: The heterozygous phospholamban (PLN) mutation R14del (PLN R14del+/- ) is associated with a severe arrhythmogenic cardiomyopathy (ACM) developing in the adult. "Superinhibition" of SERCA2a by PLN R14del is widely assumed to underlie the pathogenesis, but alternative mechanisms such abnormal energy metabolism have also been reported. This work aims to (1) to evaluate Ca2+ dynamics and energy metabolism in a transgenic (TG) mouse model of the mutation prior to cardiomyopathy development; (2) to test whether they are causally connected. METHODS: Ca2+ dynamics, energy metabolism parameters, reporters of mitochondrial integrity, energy, and redox homeostasis were measured in ventricular myocytes of 8-12 weeks-old, phenotypically silent, TG mice. Mutation effects were compared to pharmacological PLN antagonism and analyzed during modulation of sarcoplasmic reticulum (SR) and cytosolic Ca2+ compartments. Transcripts and proteins of relevant signaling pathways were evaluated. RESULTS: The mutation was characterized by hyperdynamic Ca2+ handling, compatible with a loss of SERCA2a inhibition by PLN. All components of energy metabolism were depressed; myocyte energy charge was preserved under quiescence but reduced during stimulation. Cytosolic Ca2+ buffering or SERCA2a blockade reduced O2 consumption with larger effect in the mutant. Signaling changes suggest cellular adaptation to perturbed Ca2+ dynamics and response to stress. CONCLUSIONS: (1) PLN R14del+/- loses its ability to inhibit SERCA2a, which argues against SERCA2a superinhibition as a pathogenetic mechanism; (2) depressed energy metabolism, its enhanced dependency on Ca2+ and activation of signaling responses point to an early involvement of metabolic stress in the pathogenesis of this ACM model.

Remote monitoring of implantable cardiac monitors in patients with unexplained syncope: Predictors of false-positive alert episodes.

BACKGROUND: Remote monitoring is recommended for patients with implantable cardiac monitors (ICMs), but compared to other cardiac implantable devices, ICMs are less accurate and transmit a higher number of alerts. OBJECTIVE: The aim of this study was to investigate the predictors of false-positive (FP) arrhythmic alerts in patients with unexplained syncope who were implanted with ICM and followed by an automatic remote monitoring system. METHODS: We retrospectively evaluated all consecutive patients who received a long-sensing vector ICM for unexplained syncope between January 2019 to September 2021 at our Syncope Unit. The primary endpoint was the incidence of the first FP episode. The secondary endpoints included assessing the incidence of FP episodes for all types of algorhythms and indentifying the reasons for the misdetection of these episodes. RESULTS: Among 105 patients (44.8% males, median age 51 years), 51 (48.6%) transmitted at least one FP alert during a median follow-up of 301 days. The presence of pre-ventricular complexes (PVCs) on the resting electrocardiogram was the only clinical characteristic associated with an increased risk of FP alerts (adjusted Hazard ratio [HR] 5.76 [2.66-12.4], p = 0.010). The other significant device-related variables were a low-frequency filter at 0.05 Hz versus the default 0.5 Hz (adjusted HR 3.82 [1.38-10.5], p = 0.010) and the R-wave amplitude (adjusted HR 0.35 [0.13-0.99], p = 0.049). CONCLUSION: Patients who have PVCs are at higher risk of inappropriate ICM activations. To reduce the occurrence of FP alerts, it may be beneficial to target a large R-wave amplitude during device insertion and avoid programming a low-frequency filter at 0.05 Hz.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications.

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

Community consensus on core open science practices to monitor in biomedicine.

The state of open science needs to be monitored to track changes over time and identify areas to create interventions to drive improvements. In order to monitor open science practices, they first need to be well defined and operationalized. To reach consensus on what open science practices to monitor at biomedical research institutions, we conducted a modified 3-round Delphi study. Participants were research administrators, researchers, specialists in dedicated open science roles, and librarians. In rounds 1 and 2, participants completed an online survey evaluating a set of potential open science practices, and for round 3, we hosted two half-day virtual meetings to discuss and vote on items that had not reached consensus. Ultimately, participants reached consensus on 19 open science practices. This core set of open science practices will form the foundation for institutional dashboards and may also be of value for the development of policy, education, and interventions.

A Comprehensive Characterization of Stemness in Cell Lines and Primary Cells of Pancreatic Ductal Adenocarcinoma.

The aim of this study is to provide a comprehensive characterization of stemness in pancreatic ductal adenocarcinoma (PDAC) cell lines. Seventeen cell lines were evaluated for the expression of cancer stem cell (CSC) markers. The two putative pancreatic CSC phenotypes were expressed heterogeneously ranging from 0 to 99.35% (median 3.46) for ESA+CD24+CD44+ and 0 to 1.94% (median 0.13) for CXCR4+CD133+. Cell lines were classified according to ESA+CD24+CD44+ expression as: Low-Stemness (LS; <5%, n = 9, median 0.31%); Medium-Stemness (MS; 6−20%, n = 4, median 12.4%); and High-Stemness (HS; >20%, n = 4, median 95.8%) cell lines. Higher degree of stemness was associated with in vivo tumorigenicity but not with in vitro growth kinetics, clonogenicity, and chemo-resistance. A wide characterization (chemokine receptors, factors involved in pancreatic organogenesis, markers of epithelial−mesenchymal transition, and secretome) revealed that the degree of stemness was associated with KRT19 and NKX2.2 mRNA expression, with CD49a and CA19.9/Tie2 protein expression, and with the secretion of VEGF, IL-7, IL-12p70, IL-6, CCL3, IL-10, and CXCL9. The expression of stem cell markers was also evaluated on primary tumor cells from 55 PDAC patients who underwent pancreatectomy with radical intent, revealing that CXCR4+/CD133+ and CD24+ cells, but not ESA+CD24+CD44+, are independent predictors of mortality.

An inter-method comparison of four Human Reliability Assessment models.

This paper presents a comparison of four common Human Reliability Assessment (HRA) models through a scoping literature review and sensitivity analysis. The scoping literature review identified 72 relevant studies which formed the basis of the comparison. Studies reported the four selected models have similarities in terms of the sector of origin, applied sectors, output calculation, and a lack of clear guidelines on Performance Influencing Factors (PIFs) selection and risk level allocation. The studied models have differences in the number and type of PIF inputs and Human Error Probability (HEP) calculation procedures. The One Factor At a Time (OFAT) and "combined" sensitivity analysis were conducted to examine the HRA models' responses to systematic risk level changes when each of 8 matching PIFs were systematically set to "high" and then "low" levels individually and simultaneously. The OFAT analysis showed coefficients of variation (CV) in HEP varying from 9% for skills/training up to 94% for work procedure when the PIFs are assigned to a "low" risk level individually. The combined analysis showed the median HEP value close to 97% and 1% when PIFs are assigned to" high" and "low" risk levels respectively. Although the selected HRA models were reported to be validated in high-risk domains there was no study found that validated these models in low-risk domains such as manual order picking, or manual assembly lines. The HRA models examined here are disconnected from specific system design elements which can inhibit design improvement efforts. The study outcome suggests the need for clear guidelines for PIFs selection and risk level allocation. Future research should address both the connection of error assessment to the design of the system and the features of new HRA models that affect its reliability and validity in a variety of industrial contexts.

An Optimized Workflow for the Analysis of Metabolic Fluxes in Cancer Spheroids Using Seahorse Technology.

Three-dimensional cancer models, such as spheroids, are increasingly being used to study cancer metabolism because they can better recapitulate the molecular and physiological aspects of the tumor architecture than conventional monolayer cultures. Although Agilent Seahorse XFe96 (Agilent Technologies, Santa Clara, CA, United States) is a valuable technology for studying metabolic alterations occurring in cancer cells, its application to three-dimensional cultures is still poorly optimized. We present a reliable and reproducible workflow for the Seahorse metabolic analysis of three-dimensional cultures. An optimized protocol enables the formation of spheroids highly regular in shape and homogenous in size, reducing variability in metabolic parameters among the experimental replicates, both under basal and drug treatment conditions. High-resolution imaging allows the calculation of the number of viable cells in each spheroid, the normalization of metabolic parameters on a per-cell basis, and grouping of the spheroids as a function of their size. Multivariate statistical tests on metabolic parameters determined by the Mito Stress test on two breast cancer cell lines show that metabolic differences among the studied spheroids are mostly related to the cell line rather than to the size of the spheroid. The optimized workflow allows high-resolution metabolic characterization of three-dimensional cultures, their comparison with monolayer cultures, and may aid in the design and interpretation of (multi)drug protocols.

Profiling and Targeting of Energy and Redox Metabolism in Grade 2 Bladder Cancer Cells with Different Invasiveness Properties.

Bladder cancer is one of the most prevalent deadly diseases worldwide. Grade 2 tumors represent a good window of therapeutic intervention, whose optimization requires high resolution biomarker identification. Here we characterize energy metabolism and cellular properties associated with spreading and tumor progression of RT112 and 5637, two Grade 2 cancer cell lines derived from human bladder, representative of luminal-like and basal-like tumors, respectively. The two cell lines have similar proliferation rates, but only 5637 cells show efficient lateral migration. In contrast, RT112 cells are more prone to form spheroids. RT112 cells produce more ATP by glycolysis and OXPHOS, present overall higher metabolic plasticity and are less sensitive than 5637 to nutritional perturbation of cell proliferation and migration induced by treatment with 2-deoxyglucose and metformin. On the contrary, spheroid formation is less sensitive to metabolic perturbations in 5637 than RT112 cells. The ability of metformin to reduce, although with different efficiency, cell proliferation, sphere formation and migration in both cell lines, suggests that OXPHOS targeting could be an effective strategy to reduce the invasiveness of Grade 2 bladder cancer cells.

Differential Effects of Open- and Closed-Loop Intracortical Microstimulation on Firing Patterns of Neurons in Distant Cortical Areas.

Intracortical microstimulation can be used successfully to modulate neuronal activity. Activity-dependent stimulation (ADS), in which action potentials recorded extracellularly from a single neuron are used to trigger stimulation at another cortical location (closed-loop), is an effective treatment for behavioral recovery after brain lesion, but the related neurophysiological changes are still not clear. Here, we investigated the ability of ADS and random stimulation (RS) to alter firing patterns of distant cortical locations. We recorded 591 neuronal units from 23 Long-Evan healthy anesthetized rats. Stimulation was delivered to either forelimb or barrel field somatosensory cortex, using either RS or ADS triggered from spikes recorded in the rostral forelimb area (RFA). Both RS and ADS stimulation protocols rapidly altered spike firing within RFA compared with no stimulation. We observed increase in firing rates and change of spike patterns. ADS was more effective than RS in increasing evoked spikes during the stimulation periods, by producing a reliable, progressive increase in stimulus-related activity over time and an increased coupling of the trigger channel with the network. These results are critical for understanding the efficacy of closed-loop electrical microstimulation protocols in altering activity patterns in interconnected brain networks, thus modulating cortical state and functional connectivity.

A Neuromorphic Prosthesis to Restore Communication in Neuronal Networks.

Recent advances in bioelectronics and neural engineering allowed the development of brain machine interfaces and neuroprostheses, capable of facilitating or recovering functionality in people with neurological disability. To realize energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation systems for brain repair. We demonstrate here a real-time hardware neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or missing. We used in vitro modular cell cultures to mimic the mutual interaction between neuronal assemblies and created a focal lesion to functionally disconnect the two populations. Then, we employed our neuromorphic prosthesis for bidirectional bridging to artificially reconnect two disconnected neuronal modules and for hybrid bidirectional bridging to replace the activity of one module with a real-time hardware neuromorphic Spiking Neural Network. Our neuroprosthetic system opens avenues for the exploitation of neuromorphic-based devices in bioelectrical therapeutics for health care.

Closed-Loop Systems and In Vitro Neuronal Cultures: Overview and Applications.

One of the main limitations preventing the realization of a successful dialogue between the brain and a putative enabling device is the intricacy of brain signals. In this perspective, closed-loop in vitro systems can be used to investigate the interactions between a network of neurons and an external system, such as an interacting environment or an artificial device. In this chapter, we provide an overview of closed-loop in vitro systems, which have been developed for investigating potential neuroprosthetic applications. In particular, we first explore how to modify or set a target dynamical behavior in a network of neurons. We then analyze the behavior of in vitro systems connected to artificial devices, such as robots. Finally, we provide an overview of biological neuronal networks interacting with artificial neuronal networks, a configuration currently offering a promising solution for clinical applications.

Thalamic Drive of Cortical Parvalbumin-Positive Interneurons during Down States in Anesthetized Mice.

Up and down states are among the most prominent features of the thalamo-cortical system during non-rapid eye movement (NREM) sleep and many forms of anesthesia. Cortical interneurons, including parvalbumin (PV) cells, display firing activity during cortical down states, and this GABAergic signaling is associated with prolonged down-state durations. However, what drives PV interneurons to fire during down states remains unclear. We here tested the hypothesis that background thalamic activity may lead to suprathreshold activation of PV cells during down states. To this aim, we performed two-photon guided juxtasomal recordings from PV interneurons in the barrel field of the somatosensory cortex (S1bf) of anesthetized mice, while simultaneously collecting the local field potential (LFP) in S1bf and the multi-unit activity (MUA) in the ventral posteromedial (VPM) thalamic nucleus. We found that activity in the VPM was associated with longer down-state duration in S1bf and that down states displaying PV cell firing were associated with increased VPM activity. Moreover, thalamic inhibition through application of muscimol reduced the fraction of spikes discharged by PV cells during cortical down states. Finally, we inhibited PV interneurons using optogenetics during down states while monitoring cortical LFP under control conditions and after thalamic muscimol injection. We found increased latency of the optogenetically triggered down-to-up transitions upon thalamic pharmacological blockade compared to controls. These findings demonstrate that spontaneous thalamic activity inhibits cortex during down states through the activation of PV interneurons.

Glucose metabolism during tumorigenesis in the genetic mouse model of pancreatic cancer.

AIM: More than 40% of pancreatic ductal adenocarcinoma (PDAC) patients have glucose intolerance or diabetes. The association has led to two hypotheses: PDAC causes diabetes or diabetes shares risk factors for the development of PDAC. In order to elucidate the relationship between diabetes and PDAC, we investigated the glucose metabolism during tumorigenesis in the LSL-KrasG12D/+; LSL-Trp53R172H/+; and Pdx-1-Cre (KPC) mouse, a genetically engineered model of PDAC. METHODS: Male and female KPCs have been fed with standard diet (SD) or high-fat diet (HFD). The imaging-based 4-class tumor staging was used to follow pancreatic cancer development. Not fasting glycemia, 4-h fasting glycemia, insulin, C-peptide, glucose tolerance after OGTT and abdominal fat volume were measured during tumorigenesis. RESULTS: PDAC development did not lead to an overt diabetic phenotype or to any alterations in glucose tolerance in KPC fed with SD. Consumption of HFD induced higher body weight/abdominal fat volume and worsened glucose homeostasis both in control CRE mice and only in early tumorigenesis stages of the KPC mice, excluding that the cancer development itself acts as a trigger for the onset of dysmetabolic features. CONCLUSION: Our data demonstrate that carcinogenesis in KPC mice is not associated with paraneoplastic diabetes.

Gene expression analysis of embryonic pancreas development master regulators and terminal cell fate markers in resected pancreatic cancer: A correlation with clinical outcome.

BACKGROUND: Despite the recent introduction of new drugs and the development of innovative multi-target treatments, the prognosis of pancreatic ductal adenocarcinoma (PDAC) remains very poor. Even when PDAC is resectable, the rate of local or widespread disease recurrence remains particularly high. Currently, reliable prognostic biomarkers of recurrence are lacking. We decided to explore the potential usefulness of pancreatic developmental regulators as biomarkers of PDAC relapse. METHODS: We analyzed by quantitative real-time PCR the mRNA of selected factors involved either in pancreatic organogenesis (ISL1, NEUROD1, NGN3, NKX2.2, NKX6.1, PAX4, PAX6, PDX1 and PTF1α) or associated with terminally committed pancreatic cells (CHGA, CHGB, GAD2, GCG, HNF6α, INS, KRT19, SYP) in 17 PDAC cell lines and in frozen tumor samples from 41 PDAC patients. RESULTS: High baseline levels of the ISL1, KRT19, PAX6 and PDX1 mRNAs in PDAC cell lines, were risk factors for time-dependent xenograft appearance after subcutaneous injection in CD1-Nude mice. Consistently, in human PDAC samples, high levels of KRT19 mRNA were associated with reduced overall survival and earlier recurrence. Higher levels of PDX1 or PAX6 mRNAs were instead associated with a higher frequency of local recurrence. CONCLUSIONS: Our findings suggest that selected factors associated with pancreas development or its terminal differentiation might be implicated in mechanisms of PDAC progression and/or metastatic spread and that the measurement of their mRNA in tumors might be potentially used to improve patient prognostic stratification and prediction of the relapse site.

Four-class tumor staging for early diagnosis and monitoring of murine pancreatic cancer using magnetic resonance and ultrasound.

Background: The widely used genetically engineered mouse LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre, termed KPC, spontaneously develops pancreatic cancer mirroring all phases of the carcinogenesis but in asynchronous manner. Preclinical studies need defined criteria for the enrollment of the KPC sharing the same stage of carcinogenesis. Aim: To define a tumor-staging criteria using magnetic resonance (MR) and ultrasound (US) and then to correlate the imaging stage with overall survival of KPC mice. Methods: Forty KPC (2- to 5-month-old mice) were imaged by axial fat-saturated T2-weighted sequences at MR and by brightness mode US to establish criteria for tumor staging. Immunohistopathology was used to validate imaging. A second cohort of 25 KPC was used to correlate imaging stage with survival by Kaplan-Meier analysis. Results: We defined a four-class tumor staging system ranking from stages 1 to 4. Stage 1 was described as radiologically healthy pancreas; precursor lesions were detectable in histology only. Cystic papillary neoplasms, besides other premalignant alterations, marked stage 2 in the absence of cancer nodules. Stages 3 and 4 identified mice affected by overt pancreatic cancer with size <5 or ≥5 mm, respectively. Regarding the prognosis, this staging system correlated with disease-related mortality whatever may be the KPC age when they staged. Conclusion: This imaging-based four-class tumor staging is an effective and safe method to stage pancreatic cancer development in KPC. As a result, regardless of their age, KPC mice can be synchronized based on prognosis or on a specific phase of tumorigenesis, such as the early but already radiologically detectable one (stage 2).

No evidence of pancreatic ductal adenocarcinoma specific autoantibodies to Ezrin in a liquid phase LIPS immunoassay.

BACKGROUND: Sensitive and specific biomarkers of Pancreatic Ductal Adenocarcinoma (PDAC) are desperately needed to allow early diagnosis and improve patient's survival. Ezrin autoantibodies were recently described as present in 93% of PDAC patients and 40% of healthy subjects who later developed PDAC. However, another prospective study failed to replicate these findings. Both studies were based on the use of a solid phase ELISA immunoassay. OBJECTIVE: We aimed at re-evaluating the usefulness of Ezrin autoantibodies as PDAC biomarkers using the Luciferase Immuno Precipitation System (LIPS), an alternative immunoassay format that found successful application for the measurement of autoantibodies against pancreatic autoantigens. METHODS: We produced a Nanoluciferase™ tagged Ezrin (NLuc-Ezrin). NLuc-Ezrin was then used as antigen in LIPS to test for Ezrin autoantibodies patients affected by PDAC (n= 40), other pancreatic diseases (OPD, n= 50), and healthy controls (n= 60). RESULTS: Overall, binding in liquid phase to Ezrin by serum antibodies was rare and low titer. Furthermore, we did not find statistically significant differences in the prevalence of Ezrin autoantibodies between patients affected by either PDAC or OPD compared to control. CONCLUSIONS: Our results do not confirm the usefulness of Ezrin autoAbs as biomarker of PDAC.

Integrating T cell metabolism in cancer immunotherapy.

Activation and maintenance of the T cell response occurs concurrently with metabolic reprogramming. This ensures the T cell response is supported by sufficient energy and substrates necessary for cell survival, growth and proliferation. Different metabolic programs are associated with differentiation into different cell subsets, effector function and development of long-lasting memory. This provides an opportunity to improve the T cell response through manipulation of metabolism, which is instrumental to ameliorate the current protocols for cancer immunotherapy. Using drugs and molecules targeting selective metabolic pathways it is now possible to generate T cells that can mount a durable and stable anti-tumor response. On the other hand, cancer cells can take advantage of the metabolic requirements of T cells to evade the immune response. In this brief review we discuss recent findings of T cell metabolism in quiescence and activation, how the tumor microenvironment can affect T cell metabolism, and how T cell metabolism can be manipulated to improve the T cell response to tumors.

Stimulation triggers endogenous activity patterns in cultured cortical networks.

Cultures of dissociated cortical neurons represent a powerful trade-off between more realistic experimental models and abstract modeling approaches, allowing to investigate mechanisms of synchronized activity generation. These networks spontaneously alternate periods of high activity (i.e. network bursts) with periods of quiescence in a dynamic state which recalls the fluctuation of in vivo UP and DOWN states. Network bursts can also be elicited by external stimulation and their spatial propagation patterns tracked by means of multi-channel micro-electrode arrays. In this study, we used rat cortical cultures coupled to micro-electrode arrays to investigate the similarity between spontaneous and evoked activity patterns. We performed experiments by applying electrical stimulation to different network locations and demonstrated that the rank orders of electrodes during evoked and spontaneous events are remarkably similar independently from the stimulation source. We linked this result to the capability of stimulation to evoke firing in highly active and "leader" sites of the network, reliably and rapidly recruited within both spontaneous and evoked bursts. Our study provides the first evidence that spontaneous and evoked activity similarity is reliably observed also in dissociated cortical networks.

A preoperative score to predict early death after pancreatic cancer resection.

BACKGROUND: This study aimed to develop and validate a preoperative prognostic model for death within one year post-surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC). METHODS: A derivation cohort study of 296 patients who underwent surgical resection of PDAC was prospectively enrolled in an observational study. Preoperative predictors of one year mortality were used to develop a risk score which was then validated in an external cohort of 182 patients with resectable PDAC. RESULTS: Seventy-eight out of 296 patients (26%) died within the first year. Preoperative independent predictors of one year mortality were: nutritional status (Geriatric Nutritional Risk Index, OR 2.23, 1.14-4.38; p=0.02), American Society of Anaesthesiologists' score (OR 2.56, 1.1-5.98; p=0.03), abdominal or back pain at presentation (OR 2.51, 1.05-5.9; p=0.038) and non metastatic liver disease as comorbidity (OR 4.5, 1.05-19.3; p=0.043). A score ranging from 0 to 7 points was developed. In the validation cohort, the model was able to predict early mortality (OR 7.1, 3.9-12.7; p<0.0001), with a predictive ability of 53.5% (Nagelkerke R2), an area under the receiver operating characteristic curve of 88.7% and an acceptable calibration (goodness-of-fit test, p=0.403). CONCLUSIONS: Our new simple risk score proved reliable in forecasting one year mortality in patients with resectable PDAC.

Investigating the impact of electrical stimulation temporal distribution on cortical network responses.

BACKGROUND: The brain is continuously targeted by a wealth of stimuli with complex spatio-temporal patterns and has presumably evolved in order to cope with those inputs in an optimal way. Previous studies investigating the response capabilities of either single neurons or intact sensory systems to external stimulation demonstrated that stimuli temporal distribution is an important, if often overlooked, parameter. RESULTS: In this study we investigated how cortical networks plated over micro-electrode arrays respond to different stimulation sequences in which inter-pulse intervals followed a 1/f ß distribution, for different values of ß ranging from 0 to ∞. Cross-correlation analysis revealed that network activity preferentially synchronizes with external input sequences featuring ß closer to 1 and, in any case, never for regular (i.e. fixed-frequency) stimulation sequences. We then tested the interplay between different average stimulation frequencies (based on the intrinsic firing/bursting frequency of the network) for two selected values of ß, i.e. 1 (scale free) and ∞ (regular). In general, we observed no preference for stimulation frequencies matching the endogenous rhythms of the network. Moreover, we found that in case of regular stimulation the capability of the network to follow the stimulation sequence was negatively correlated to the absolute stimulation frequency, whereas using scale-free stimulation cross-correlation between input and output sequences was independent from average input frequency. CONCLUSIONS: Our results point out that the preference for a scale-free distribution of the stimuli is observed also at network level and should be taken into account in designing more efficient protocols for neuromodulation purposes.