Mathematical Optimization Strategy for Effectiveness Profile Estimation in Two-Dose Vaccines and Its Use in Designing Improved Vaccination Strategies Focused on Pandemic Containment.

Since late 2019, most efforts to control the COVID-19 pandemic have focused on developing vaccines. By mid-2020, some vaccines fulfilled international regulations for their application. However, these vaccines have shown a decline in effectiveness several weeks after the last dose, highlighting the need to optimize vaccine administration due to supply chain limitations. While methods exist to prioritize population groups for vaccination, there is a lack of research on how to optimally define the time between doses when two-dose vaccines are administrated to such groups. Under such conditions, modeling the real effect of each vaccine on the population is critical. Even though several efforts have been made to characterize vaccine effectiveness profiles, none of these initiatives enable characterization of the individual effect of each dose. Thus, this paper presents a novel methodology for estimating the vaccine effectiveness profile. It addresses the vaccine characterization problem by considering a deconvolution of relevant data profiles, treating them as an optimization process. The results of this approach enabled the independent estimation of the effectiveness profiles for the first and second vaccine doses and their use to find sweet spots for designing efficient vaccination strategies. Our methodology can enable a more effective and efficient contemporary response against the COVID-19 pandemic, as well as for any other disease in the future.

Brain-wide functional connectivity of face patch neurons during rest.

The brain is a highly organized, dynamic system whose network architecture is often assessed through resting functional magnetic resonance imaging (fMRI) functional connectivity. The functional interactions between brain areas, including those observed during rest, are assumed to stem from the collective influence of action potentials carried by long-range neural projections. However, the contribution of individual neurons to brain-wide functional connectivity has not been systematically assessed. Here we developed a method to concurrently measure and compare the spiking activity of local neurons with fMRI signals measured across the brain during rest. We recorded spontaneous activity from neural populations in cortical face patches in the macaque during fMRI scanning sessions. Individual cells exhibited prominent, bilateral coupling with fMRI fluctuations in a restricted set of cortical areas inside and outside the face patch network, partially matching the pattern of known anatomical projections. Within each face patch population, a subset of neurons was positively coupled with the face patch network and another was negatively coupled. The same cells showed inverse correlations with distinct subcortical structures, most notably the lateral geniculate nucleus and brainstem neuromodulatory centers. Corresponding connectivity maps derived from fMRI seeds and local field potentials differed from the single unit maps, particularly in subcortical areas. Together, the results demonstrate that the spiking fluctuations of neurons are selectively coupled with discrete brain regions, with the coupling governed in part by anatomical network connections and in part by indirect neuromodulatory pathways.

An agent-based transmission model of COVID-19 for re-opening policy design.

The global pandemic caused by the coronavirus (COVID-19) disease has collapsed the worldwide economy. Elements such as non-obligatory vaccination, new strain variants and lack of discipline to follow social distancing measures suggest the possibility that COVID-19 may continue to exist, exhibiting the behavior of a seasonal disease. As the socio-economic crisis has become unsustainable, all countries are planning strategies to gradually restart their economic and social activities. Initially, several containment measures have been adopted involving social distancing, infection detection tests, and ventilation systems. Despite the implementation of such policies, there exists a lack of evaluation of their performance to reduce the contagion index. This means there are no appropriate indicators to decide which intervention or set of interventions present the most effective result. Under these conditions, the development of models that provide useful information in the design and evaluation of containment measures and re-opening policies is of prime concern. In this paper, a novel approach to model the transmission process of COVID-19 in closed environments is proposed. The proposed model can simulate the effects that result from the complex interaction among individuals when they follow a particular containment measure or re-opening policy. With the proposed model, different hypothetical re-opening policies, that are otherwise impossible to analyze in real conditions, can be tested. Computer experiments demonstrate that the proposed model provides suitable information and realistic predictions, which are appropriate for designing strategies that allow a safe return to economic activities.

Two distinct profiles of fMRI and neurophysiological activity elicited by acetylcholine in visual cortex.

Cholinergic neuromodulation is involved in all aspects of sensory processing and is crucial for processes such as attention, learning and memory, etc. However, despite the known roles of acetylcholine (ACh), we still do not how to disentangle ACh contributions from sensory or task-evoked changes in functional magnetic resonance imaging (fMRI). Here, we investigated the effects of local injection of ACh on fMRI and neural signals in the primary visual cortex (V1) of anesthetized macaques by combining pharmaco-based MRI (phMRI) with electrophysiological recordings, using single electrodes and electrode arrays. We found that local injection of ACh elicited two distinct profiles of fMRI and neurophysiological activity, depending on the distance from the injector. Near the injection site, we observed an increase in the baseline blood oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) responses, while their visual modulation decreased. In contrast, further from the injection site, we observed an increase in the visually induced BOLD and CBF modulation without changes in baseline. Neurophysiological recordings suggest that the spatial correspondence between fMRI responses and neural activity does not change in the gamma, high-gamma, and multiunit activity (MUA) bands. The results near the injection site suggest increased inhibitory drive and decreased metabolism, contrasting to the far region. These changes are thought to reflect the kinetics of ACh and its metabolism to choline.

A novel bio-inspired optimization model based on Yellow Saddle Goatfish behavior.

Several species of fish live in groups to increase their foraging efficiency and reproduction rates. Such groups are considered self-organized since they can adopt different cooperative actions without the presence of an apparent leader. One of their most interesting collaborative behaviors found in fish is the hunting strategy presented by the Yellow Saddle Goatfish (Parupeneus cyclostomus). In this strategy, the complete group of fish is distributed in subpopulations to cover the whole hunting region. In each sub-population, all fish participate collectively in the hunt considering two different roles: chaser and blocker. In the hunt, a chaser fish actively tries to find the prey in a certain area whereas a blocker fish moves spatially to avoid the escape of the prey. In this paper, we develop the hunting model of Yellow Saddle Goatfish, which at some abstraction level can be characterized as a search strategy for optimization proposes. In the approach, different computational operators are designed in order to emulate this peculiar hunting behavior. With the use of this biological model, the new search strategy improves the optimization results in terms of accuracy and convergence in comparison to other popular optimization techniques. The performance of this method is tested by analyzing its results with other related evolutionary computation techniques. Several standard benchmark functions commonly used in the literature were considered to obtain optimization results. Furthermore, the proposed model is applied to solve certain engineering optimization problems. Analysis of the experimental results exhibits the efficiency, accuracy, and robustness of the proposed algorithm.

Dopamine Is Signaled by Mid-frequency Oscillations and Boosts Output Layers Visual Information in Visual Cortex.

Neural oscillations are ubiquitously observed in cortical activity, and are widely believed to be crucial for mediating transmission of information across the cortex. Yet, the neural phenomena contributing to each oscillation band, and their effect on information coding and transmission, are largely unknown. Here, we investigated whether individual frequency bands specifically reflect changes in the concentrations of dopamine, an important neuromodulator, and how dopamine affects oscillatory information processing. We recorded the local field potential (LFP) at different depths of primary visual cortex (V1) in anesthetized monkeys (Macaca mulatta) during spontaneous activity and during visual stimulation with Hollywood movie clips while pharmacologically mimicking dopaminergic neuromodulation by systemic injection of L-DOPA (a metabolic precursor of dopamine). We found that dopaminergic neuromodulation had marked effects on both spontaneous and movie-evoked neural activity. During spontaneous activity, dopaminergic neuromodulation increased the power of the LFP specifically in the [19-38 Hz] band, suggesting that the power of endogenous visual cortex oscillations in this band can be used as a robust marker of dopaminergic neuromodulation. Moreover, dopamine increased visual information encoding over all frequencies during movie stimulation. The information increase due to dopamine was prominent in the supragranular layers of cortex that project to higher cortical areas and in the gamma [50-100 Hz] band that has been previously implicated in mediating feedforward information transfer. These results thus individuate new neural mechanisms by which dopamine may promote the readout of relevant sensory information by strengthening the transmission of information from primary to higher areas.

In vivo characterization of the downfield part of 1 H MR spectra of human brain at 9.4 T: Magnetization exchange with water and relation to conventionally determined metabolite content.

PURPOSE: To perform exchange-rate measurements on the in vivo human brain downfield spectrum (5-10 ppm) at 9.4 T and to compare the variation in concentrations of the downfield resonances and of known upfield metabolites to determine potential peak labels. METHODS: Non-water-suppressed metabolite cycling was used in combination with an inversion transfer technique in two brain locations in healthy volunteers to measure the exchange rates and T1 values of exchanging peaks. Spectra were fitted with a heuristic model of a series of 13 or 14 Voigt lines, and a Bloch-McConnell model was used to fit the exchange rate curves. Concentrations from non-water-inverted spectra upfield and downfield were compared. RESULTS: Mean T1 values ranged from 0.40 to 0.77 s, and exchange rates from 0.74 to 13.8 s-1 . There were no significant correlations between downfield and upfield concentrations, except for N-acetylaspartate, with a correlation coefficient of 0.63 and P < 0.01. CONCLUSIONS: Using ultrahigh field allowed improved separation of peaks in the 8.2 to 8.5 ppm amide proton region, and the exchange rates of multiple downfield resonances including the 5.8-ppm peak, previously tentatively assigned to urea, were measured in vivo in human brain. Downfield peaks consisted of overlapping components, and largely missing correlations between upfield and downfield resonances-although not conclusive-indicate limited contributions from metabolites present upfield to the downfield spectrum. Magn Reson Med 79:2863-2873, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

A Multiobjective Approach to Homography Estimation.

In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data. A method to find such estimation is the random sampling consensus (RANSAC); in this, the goal is to maximize the number of matching points given a permissible error (Pe), according to a candidate model. However, those objectives are in conflict: a low Pe value increases the accuracy of the model but degrades its generalization ability that refers to the number of matching points that tolerate noisy data, whereas a high Pe value improves the noise tolerance of the model but adversely drives the process to false detections. This work considers the estimation process as a multiobjective optimization problem that seeks to maximize the number of matching points whereas Pe is simultaneously minimized. In order to solve the multiobjective formulation, two different evolutionary algorithms have been explored: the Nondominated Sorting Genetic Algorithm II (NSGA-II) and the Nondominated Sorting Differential Evolution (NSDE). Results considering acknowledged quality measures among original and transformed images over a well-known image benchmark show superior performance of the proposal than Random Sample Consensus algorithm.

Dopamine-induced dissociation of BOLD and neural activity in macaque visual cortex.

Neuromodulators determine how neural circuits process information during cognitive states such as wakefulness, attention, learning, and memory. fMRI can provide insight into their function and dynamics, but their exact effect on BOLD responses remains unclear, limiting our ability to interpret the effects of changes in behavioral state using fMRI. Here, we investigated the effects of dopamine (DA) injections on neural responses and haemodynamic signals in macaque primary visual cortex (V1) using fMRI (7T) and intracortical electrophysiology. Aside from DA's involvement in diseases such as Parkinson's and schizophrenia, it also plays a role in visual perception. We mimicked DAergic neuromodulation by systemic injection of L-DOPA and Carbidopa (LDC) or by local application of DA in V1 and found that systemic application of LDC increased the signal-to-noise ratio (SNR) and amplitude of the visually evoked neural responses in V1. However, visually induced BOLD responses decreased, whereas cerebral blood flow (CBF) responses increased. This dissociation of BOLD and CBF suggests that dopamine increases energy metabolism by a disproportionate amount relative to the CBF response, causing the reduced BOLD response. Local application of DA in V1 had no effect on neural activity, suggesting that the dopaminergic effects are mediated by long-range interactions. The combination of BOLD-based and CBF-based fMRI can provide a signature of dopaminergic neuromodulation, indicating that the application of multimodal methods can improve our ability to distinguish sensory processing from neuromodulatory effects.

An improved computer vision method for white blood cells detection.

The automatic detection of white blood cells (WBCs) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and computer vision alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elements. This paper presents an algorithm for the automatic detection of WBC embedded in complicated and cluttered smear images that considers the complete process as a multiellipse detection problem. The approach, which is based on the differential evolution (DE) algorithm, transforms the detection task into an optimization problem whose individuals represent candidate ellipses. An objective function evaluates if such candidate ellipses are actually present in the edge map of the smear image. Guided by the values of such function, the set of encoded candidate ellipses (individuals) are evolved using the DE algorithm so that they can fit into the WBCs which are enclosed within the edge map of the smear image. Experimental results from white blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique in terms of its accuracy and robustness.

White blood cell segmentation by circle detection using electromagnetism-like optimization.

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability.

Effects of lactate on the early visual cortex of non-human primates, investigated by pharmaco-MRI and neurochemical analysis.

In contrast to the limited use of functional magnetic resonance imaging (fMRI) in clinical diagnostics, it is currently a mainstay of neuroimaging in clinical and basic brain research. However, its non-invasive use in combination with its high temporal and spatial resolution would make fMRI a perfect diagnostic tool. We are interested in whether a pharmacological challenge imposed on the brain can be reliably traced by the blood oxygen level-dependent (BOLD) signal and possibly further exploited for diagnostics. We have chosen a systemic challenge with lactate and pyruvate to test whether the physiological formation of these monocarboxylic acids contributes to the BOLD signal and can be detected using fMRI. This information is also of interest because lactate levels in the cerebrospinal fluid rise concomitantly with reduced vascular responsiveness of the brain during the progression of Alzheimer disease (AD). We studied the BOLD response after a low-dose lactate challenge and monitored the induced plasma lactate levels in anesthetized non-human primates. We observed reliable lactate-induced BOLD responses, which could be confirmed at population and individual level by their strong correlation with systemic lactate concentrations. Comparable BOLD effects where observed after a slow infusion of pyruvate. We show here that physiological changes in lactate and pyruvate levels are indeed reflected in the BOLD signal, and describe the technical prerequisites to reliably trace a lactate challenge using BOLD-fMRI.

Measuring multiple neurochemicals and related metabolites in blood and brain of the rhesus monkey by using dual microdialysis sampling and capillary hydrophilic interaction chromatography-mass spectrometry.

In vivo measurement of multiple functionally related neurochemicals and metabolites (NMs) is highly interesting but remains challenging in the field of basic neuroscience and clinical research. We present here an analytical method for determining five functionally and metabolically related polar substances, including acetylcholine (quaternary ammonium), lactate and pyruvate (organic acids), as well as glutamine and glutamate (amino acids). These NMs are acquired from samples of the brain and the blood of non-human primates in parallel by dual microdialysis, and subsequently analyzed by a direct capillary hydrophilic interaction chromatography (HILIC)-mass spectrometry (MS) based method. To obtain high sensitivity in electrospray ionization (ESI)-MS, lactate and pyruvate were detected in negative ionization mode whereas the other NMs were detected in positive ionization mode during each HILIC-MS run. The method was validated for linearity, the limits of detection and quantification, precision, accuracy, stability and matrix effect. The detection limit of acetylcholine, lactate, pyruvate, glutamine, and glutamate was 150 pM, 3 µM, 2 µM, 5 nM, and 50 nM, respectively. This allowed us to quantitatively and simultaneously measure the concentrations of all the substances from the acquired dialysates. The concentration ratios of both lactate/pyruvate and glutamine/glutamate were found to be higher in the brain compared to blood (p < 0.05). The reliable and simultaneous quantification of these five NMs from brain and blood samples allows us to investigate their relative distribution in the brain and blood, and most importantly paves the way for future non-invasive studies of the functional and metabolic relation of these substances to each other.

Ciliary neurotrophic factor promotes inactivation of muscle Ca2+ channels via PKC.

The actions of the ciliary neurotrophic factor (CNTF) were assessed on adult mouse skeletal muscle L-type Ca2+ currents and on Ca2+ release from sarcoplasmic reticulum. Currents were measured with the whole cell patch clamp technique. Ca2+ signals in response to single action potentials were recorded with Fluo3-AM. CNTF (20 ng/ml) reversibly reduced the amplitude of Ca2+ channel currents by 50% within 15 min. In addition, CNTF greatly increased the rate of inactivation during depolarizing pulses and shifted the steady state inactivation curve by -12 mV. The effects of CNTF were mimicked by the PKC activator PMA and prevented by the PKC-inhibitor chelerythrine. In contrast to the effects on the Ca2+ conductance, charge movement and Ca2+ signals remained unaffected by CNTF. These results suggest that CNTF can rapidly decrease muscle Ca2+ channel currents by promoting inactivation, probably through an intracellular PKC-dependent mechanism.