[Synchronies and asynchronies in the development of COVID-19 pandemic in Italy]. / Sincronie e asincronie negli sviluppi della pandemia di COVID-19 sul territorio.

BACKGROUND: the study of the possible determinants of the rise and fall of infections can be of great relevance, as was experienced during the COVID-19 pandemic. One of the methods to understand whether determinants are simultaneous or develop through contiguity between different areas is the study of the diagnostic replication index RDt among regions. OBJECTIVES: to introduce the analysis of RDt variability and the subsequent application of a recently introduced functional clustering method as highly useful procedures for recognizing the presence of clusters with similar trends in epidemic curves. DESIGN: within the considered period, trends in regional RDt are analyzed in detail over four different time intervals. SETTING AND PARTICIPANTS: to exemplify this methodology, the study of variability in the period from the end of 2021 to the beginning of 2022 may be of interest. MAIN OUTCOMES MEASURES: the variability in the regional RDt indices is assessed by means of the correlation coefficient weighted with respect to the populations of the individual regions. The clustering procedure is applied to the time series of absolute RDt values. RESULTS: it emerges that the periods of increasing variability in the RDt correspond to the initial growth or decrease in the number of infections, while functional clustering identifies macro-areas in which the epidemic curves have had similar trends. What caused contagions to increase seems to relate to a factor that is not specific to certain areas, with the contribution in some cases of a contagion dynamic between adjacent areas. CONCLUSIONS: the variability in the trend of regional diagnostic replication indices, which are calculated with only a few days delay, is a further indicator for the early detection of major changes in the trend of epidemic curves. The clustering of epidemic index curves may be useful to determine whether determinants act simultaneously or by contiguity between adjacent areas.

A new computational workflow to guide personalized drug therapy.

OBJECTIVE: Computational models are at the forefront of the pursuit of personalized medicine thanks to their descriptive and predictive abilities. In the presence of complex and heterogeneous data, patient stratification is a prerequisite for effective precision medicine, since disease development is often driven by individual variability and unpredictable environmental events. Herein, we present GreatNectorworkflow as a valuable tool for (i) the analysis and clustering of patient-derived longitudinal data, and (ii) the simulation of the resulting model of patient-specific disease dynamics. METHODS: GreatNectoris designed by combining an analytic strategy composed of CONNECTOR, a data-driven framework for the inspection of longitudinal data, and an unsupervised methodology to stratify the subjects with GreatMod, a quantitative modeling framework based on the Petri Net formalism and its generalizations. RESULTS: To illustrate GreatNectorcapabilities, we exploited longitudinal data of four immune cell populations collected from Multiple Sclerosis patients. Our main results report that the T-cell dynamics after alemtuzumab treatment separate non-responders versus responders patients, and the patients in the non-responders group are characterized by an increase of the Th17 concentration around 36 months. CONCLUSION: GreatNectoranalysis was able to stratify individual patients into three model meta-patients whose dynamics suggested insight into patient-tailored interventions.

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

MOTIVATION: The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging. RESULTS: We developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. We give a new perspective of mechanism interpretation, specifically, we define novel model aggregations and we identify unanticipated molecular associations with response to clinically approved therapies. AVAILABILITY AND IMPLEMENTATION: CONNECTOR is freely available under GNU GPL license at https://qbioturin.github.io/connector and https://doi.org/10.17504/protocols.io.8epv56e74g1b/v1.

Usefulness of 99mTc-Pertechnetate SPECT-CT in Thyroid Tissue Volumetry: Phantom Studies and a Clinical Case Series.

BACKGROUND: An accurate measurement of the target volume is of primary importance in theragnostics of hyperthyroidism. OBJECTIVE: Our purpose was to evaluate the accuracy of a threshold-based isocontour extraction procedure for thyroid tissue volumetry from SPECT-CT. METHODS: Cylindrical vials with a fixed volume of 99mTcO4 at different activities were inserted into a neck phantom in two different thickness settings. Images were acquired by orienting the phantom in different positions, i.e., 40 planar images and 40 SPECT-CT. The fixed values of the isocontouring threshold for SPECT and SPECT-CT were calculated by means of linear and spline regression models. Mean, Median, Standard Deviation, Standard Error, Mean Absolute Percentage Error and Root Mean-Square Error were computed. Any difference between the planar method, SPECT and SPECT-CT and the effective volume was evaluated by means of ANOVA and posthoc tests. Moreover, planar and SPECT-CT acquisitions were performed in 8 patients with hyperthyroidism, considering relevant percentage differences greater than > 20% from the CT gold standard. RESULTS: Concerning phantom studies, the planar method shows higher values of each parameter than the other two methods. SPECT-CT shows lower variability. However, no significant differences were observed between SPECT and SPECT-CT measurements. In patients, relevant differences were found in 7 out of 9 lesions with the planar method, in 6 lesions with SPECT, but in only one with SPECT-CT. CONCLUSION: Our study confirms the superiority of SPECT in volume measurement if compared with the planar method. A more accurate measurement can be obtained from SPECT-CT.

Multi-institutional analysis of outcomes for thermosphere microwave ablation treatment of colorectal liver metastases: the SMAC study.

OBJECTIVES: Oligometastatic colorectal cancer benefits of locoregional treatments but data concerning microwave ablation (MWA) are limited and interactions with systemic therapy are still debated. The aim of this study is to evaluate safety and effectiveness of Thermosphere™ MWA (T-MWA) of colorectal liver metastases (CLM) and factors affecting local tumor progression-free survival (LTPFS). METHODS: In this multi-institutional retrospective study (January 2015-September 2019), patients who underwent T-MWA for CLM were enrolled. Complications according to SIR classification were collected, primary efficacy and LTP were calculated. Analyzed variables included CLM size at diagnosis and at ablation, CLM number, ablation margins, intra-segment progression, chemotherapy before ablation (CBA), variations in size (ΔSDIA-ABL), and velocity of size variation (VDIA-ABL) between CLM diagnosis and ablation. Uni/multivariate analyses were performed using mixed effects Cox model to account for the hierarchical structure of data, patient/lesions. RESULTS: One hundred thirty-two patients with 213 CLM were evaluated. Complications were reported in 6/150 procedures (4%); no biliary complications occurred. Primary efficacy was achieved in 204/213 CLM (95.7%). LTP occurred in 58/204 CLM (28.4%). Six-, twelve-, and eighteen-month LTPFS were 88.2%, 75.8%, and 69.9%, respectively. At multivariate analysis, CLM size at ablation (p = 0.00045), CLM number (p = 0.046), ablation margin < 5 mm (p = 0.0035), and intra-segment progression (p < 0.0001) were statistically significant for LTPFS. ΔSDIA-ABL (p = 0.63) and VDIA-ABL (p = 0.38) did not affect LTPFS. Ablation margins in the chemo-naïve group were larger than those in the CBA group (p < 0.0001). CONCLUSION: T-MWA is a safe and effective technology with adequate LTPFS rates. Intra-segment progression is significantly linked to LTPFS. CBA does not affect LTPFS. Anticipating ablation before chemotherapy may take the advantages of adequate tumor size with correct ablation margin planning. KEY POINTS: • Thermosphere™-Microwave ablation is a safe and effective treatment for colorectal liver metastases with no registered biliary complications in more than 200 ablations. • Metastases size at time of ablation, intra-segment progression, and minimal ablation margin < 5 mm were found statistically significant for local tumor progression-free survival. • Chemotherapy before ablation modifies kinetics growth of the lesions but deteriorates ablation margins and does not significantly impact local tumor progression-free survival.

Following the gold trail: Reward influences on spatial exploration in neglect.

Spatial attention is guided by the perceived salience and relevance of objects in the environment, a process considered to depend on a broad parieto-frontal cortical network. Signals arising from the limbic and nigrostriatal pathways conveying affective and motivational cues are also known to modulate visual selection, but the nature of this contribution and its relation to spatial attention remain unclear. We investigated the role of reward information in 15 patients with left hemispatial neglect and 15 control subjects playing multiple rounds of a virtual foraging game. Participants' exploration tracked dynamically adjusted underlying reward distributions, largely unbeknownst to them. Both control and neglect participants showed typical exploration/exploitation balance, dependent on abundance or scarcity of rewards. De-reinforcing previously favored, mostly right, regions of space attenuated left space under-exploration in patients. Multiple regression analysis indicates that such reward-based training may benefit mostly patients early after lesion onset, with mild neglect and small lesions sparing subcortical regions. Our findings support the view that spatial exploration recruits heavily right hemispheric visuospatial attentional mechanisms as well as reward signals processed by basal ganglia and prefrontal cortical circuits, which serve to learn about the motivational relevance of environmental stimuli and help prioritize attention and motor response selection.

A new firing paradigm for integrate and fire stochastic neuronal models.

A new definition of firing time is given in the framework of Integrate and Fire neuronal models. The classical absorption condition at the threshold is relaxed and the firing time is defined as the first time the membrane potential process lies above a fixed depolarisation level for a sufficiently long time. The mathematical properties of the new firing time are investigated both for the Perfect Integrator and the Leaky Integrator. In the latter case, a simulation study is presented to complete the analysis where analytical results are not yet achieved.

Cooperative behavior in a jump diffusion model for a simple network of spiking neurons.

The distribution of time intervals between successive spikes generated by a neuronal cell --the interspike intervals (ISI)-- may reveal interesting features of the underlying dynamics. In this study we analyze the ISI sequence --the spike train-- generated by a simple network of neurons whose output activity is modeled by a jump-diffusion process. We prove that, when specific ranges of the involved parameters are chosen, it is possible to observe multimodal ISI distributions which reveal that the modeled network fires with more than one single preferred time interval. Furthermore, the system exhibits resonance behavior, with modulation of the spike timings by the noise intensity. We also show that inhibition helps the signal transmission between the units of the simple network.

Estimating input parameters from intracellular recordings in the Feller neuronal model.

We study the estimation of the input parameters in a Feller neuronal model from a trajectory of the membrane potential sampled at discrete times. These input parameters are identified with the drift and the infinitesimal variance of the underlying stochastic diffusion process with multiplicative noise. The state space of the process is restricted from below by an inaccessible boundary. Further, the model is characterized by the presence of an absorbing threshold, the first hitting of which determines the length of each trajectory and which constrains the state space from above. We compare, both in the presence and in the absence of the absorbing threshold, the efficiency of different known estimators. In addition, we propose an estimator for the drift term, which is proved to be more efficient than the others, at least in the explored range of the parameters. The presence of the threshold makes the estimates of the drift term biased, and two methods to correct it are proposed.

Altered molecular pathways in melanocytic lesions.

To identify gene expression changes in melanocytic lesions, biopsies from 18 common nevi (CMN), 11 dysplastic nevi (DN), 8 radial and 15 vertical growth phase melanomas (RGPM, VGPM), and 5 melanoma metastases (MTS) were analyzed using whole genome microarrays. The comparison between CMN and RGPM showed an enrichment of Gene Ontology terms related to inter and intracellular junctions, whereas the transition from RGPM to VGPM underlined the alteration of apoptosis. Upregulation of genes involved in dsDNA break repair and downregulation of cellular adhesion genes were observed in MTS with respect to VGPM. DN exhibited rather heterogeneous molecular profiles, with some proliferation genes expressed at higher levels than in CMN, altered regulation of transcription compared to RGPM and a subset of processes, such as mismatch repair, equally expressed as in VGPM. Furthermore, the expression profile of genes involved into cellular detoxification and antigen presentation split them into two classes, with different proliferation potential. Finally, molecular profiling of individual lesions identified altered biological processes, such as regulation of apoptosis, regulation of transcription and T-cell activation, not associated with specific histological classes but rather with subgroups of samples without apparent relationship. This holds true for dysplastic nevi in particular. Our data indicate that generally the intersection between stage specific and sample specific molecular alterations may lead to a more precise determination of the individual progression risk of melanocytic lesions.

A copulas approach to neuronal networks models.

Simultaneous recordings from groups of neurons request to improve models. To switch from single unit description to multivariate models describing the coding activity of two or more neurons, we propose to use the copula notion. This mathematical object catches the coupling properties and allows a mathematical description of the dependencies between two or more random variables. Its use is here illustrated by means of toy examples and further applications are discussed.

Errors in estimation of the input signal for integrate-and-fire neuronal models.

Estimation of the input parameters of stochastic (leaky) integrate-and-fire neuronal models is studied. It is shown that the presence of a firing threshold brings a systematic error to the estimation procedure. Analytical formulas for the bias are given for two models, the randomized random walk and the perfect integrator. For the third model considered, the leaky integrate-and-fire model, the study is performed by using Monte Carlo simulated trajectories. The bias is compared with other errors appearing during the estimation, and it is documented that the effect of the bias has to be taken into account in experimental studies.

Effects of random jumps on a very simple neuronal diffusion model.

The effects of taking into account in a perfect integrate and fire model of neuronal activity the spatial localization of the synapses are studied by superposing to the diffusion a simple discrete jump component. Different criteria are employed to assess the role of excitatory and inhibitory discrete contributions. Comparisons are performed with respect to the case where contributions coming from synapses more distal from the trigger zone are summed up in a continuous model. A systematic study of the output frequency and of the inter spike interval coefficient of variation (CV) is performed by means of examples as the model parameters are varied.