Interaction between spatial perception and temporal perception enables preservation of cause-effect relationship: Visual psychophysics and neuronal dynamics.

INTRODUCTION: Visual perception of moving objects is integral to our day-to-day life, integrating visual spatial and temporal perception. Most research studies have focused on finding the brain regions activated during motion perception. However, an empirically validated general mathematical model is required to understand the modulation of the motion perception. Here, we develop a mathematical formulation of the modulation of the perception of a moving object due to a change in speed, under the formulation of the invariance of causality. METHODS: We formulated the perception of a moving object as the coordinate transformation from a retinotopic space onto perceptual space and derived a quantitative relationship between spatiotemporal coordinates. To validate our model, we undertook the analysis of two experiments: (i) the perceived length of the moving arc, and (ii) the perceived time while observing moving stimuli. We performed a magnetic resonance imaging (MRI) tractography investigation of subjects to demarcate the anatomical correlation of the modulation of the perception of moving objects. RESULTS: Our theoretical model shows that the interaction between visual-spatial and temporal perception, during the perception of moving object is described by coupled linear equations; and experimental observations validate our model. We observed that cerebral area V5 may be an anatomical correlate for this interaction. The physiological basis of interaction is shown by a Lotka-Volterra system delineating interplay between acetylcholine and dopamine neurotransmitters, whose concentrations vary periodically with the orthogonal phase shift between them, occurring at the axodendritic synapse of complex cells at area V5. CONCLUSION: Under the invariance of causality in the representation of events in retinotopic space and perceptual space, the speed modulates the perception of a moving object. This modulation may be due to variations of the tuning properties of complex cells at area V5 due to the dynamic interaction between acetylcholine and dopamine. Our analysis is the first significant study, to our knowledge, that establishes a mathematical linkage between motion perception and causality invariance.

Computational systems biology approach for permanent tumor elimination and normal tissue protection using negative biasing: Experimental validation in malignant melanoma as case study.

Complete spontaneous tumor regression (without treatment) is well documented to occur in animals and humans as epidemiological analysis show, whereby the malignancy is permanently eliminated. We have developed a novel computational systems biology model for this unique phenomenon to furnish insight into the possibility of therapeutically replicating such regression processes on tumors clinically, without toxic side effects. We have formulated oncological informatics approach using cell-kinetics coupled differential equations while protecting normal tissue. We investigated three main tumor-lysis components: (ⅰ) DNA blockade factors, (ⅱ) Interleukin-2 (IL-2), and (ⅲ) Cytotoxic T-cells (CD8+ T). We studied the temporal variations of these factors, utilizing preclinical experimental investigations on malignant tumors, using mammalian melanoma microarray and histiocytoma immunochemical assessment. We found that permanent tumor regression can occur by: 1) Negative-Bias shift in population trajectory of tumor cells, eradicating them under first-order asymptotic kinetics, and 2) Temporal alteration in the three antitumor components (DNA replication-blockade, Antitumor T-lymphocyte, IL-2), which are respectively characterized by the following patterns: (a) Unimodal Inverted-U function, (b) Bimodal M-function, (c) Stationary-step function. These provide a time-wise orchestrated tri-phasic cytotoxic profile. We have also elucidated gene-expression levels corresponding to the above three components: (ⅰ) DNA-damage G2/M checkpoint regulation [genes: CDC2-CHEK], (ⅱ) Chemokine signaling: IL-2/15 [genes: IL2RG-IKT3], (ⅲ) T-lymphocyte signaling (genes: TRGV5-CD28). All three components quantitatively followed the same activation profiles predicted by our computational model (Smirnov-Kolmogorov statistical test satisfied, α = 5%). We have shown that the genes CASP7-GZMB are signatures of Negative-bias dynamics, enabling eradication of the residual tumor. Using the negative-biasing principle, we have furnished the dose-time profile of equivalent therapeutic agents (DNA-alkylator, IL-2, T-cell input) so that melanoma tumor may therapeutically undergo permanent extinction by replicating the spontaneous tumor regression dynamics.

Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal.

Introduction: Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space. Methods: We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex. Results: We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation. Conclusion: We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers.

A mechanistic analysis of spontaneous cancer remission phenomenon: identification of genomic basis and effector biomolecules for therapeutic applicability.

Based on the well-documented studies, numerous tumors episodically regress permanently without treatment. Knowing the host tissue-initiated causative factors would offer considerable translational applicability, as a permanent regression process may be therapeutically replicated on patients. For this, we developed a systems biological formulation of the regression process with experimental verification and identified the relevant candidate biomolecules for therapeutic utility. We devised a cellular kinetics-based quantitative model of tumor extinction in terms of the temporal behavior of three main tumor-lysis entities: DNA blockade factor, cytotoxic T-lymphocyte and interleukin-2. As a case study, we analyzed the time-wise biopsy and microarrays of spontaneously regressing melanoma and fibrosarcoma tumors in mammalian/human hosts. We analyzed the differentially expressed genes (DEGs), signaling pathways, and bioinformatics framework of regression. Additionally, prospective biomolecules that could cause complete tumor regression were investigated. The tumor regression process follows a first-order cellular dynamics with a small negative bias, as verified by experimental fibrosarcoma regression; the bias is necessary to eliminate the residual tumor. We identified 176 upregulated and 116 downregulated DEGs, and enrichment analysis showed that the most significant were downregulated cell-division genes: TOP2A-KIF20A-KIF23-CDK1-CCNB1. Moreover, Topoisomerase-IIA inhibition might actuate spontaneous regression, with collateral confirmation provided from survival and genomic analysis of melanoma patients. Candidate molecules such as Dexrazoxane/Mitoxantrone, with interleukin-2 and antitumor lymphocytes, may potentially replicate permanent tumor regression process of melanoma. To conclude, episodic permanent tumor regression is a unique biological reversal process of malignant progression, and signaling pathway understanding, with candidate biomolecules, may plausibly therapeutically replicate the regression process on tumors clinically. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03515-0.

Conjoint hepatobiliary-enterohepatic cycles for amyloid excretion and enhancing its drug-induced clearance: a systems biology approach to Alzheimer's disease.

The liver is the major organ responsible for metabolism of amyloid-beta, the primary toxic misfolded protein responsible for Alzheimer's disease (AD). The present study focuses on the crucial role of liver in AD. We have developed a framework that formulates and integrates two reciprocal transport processes of amyloid, via hepato-biliary and enterohepatic circulations (EHC). Our system analysis approach shows that activating the liver X-receptor (LXR) can reduce amyloid-beta formation by increasing expression of the genes: ATP-binding-cassette-transporter (ABCA1) and Stearoyl-CoA-desaturase (SCD). Besides, activating the pregnane-X-receptor (PXR) can enhance the clearance of amyloid-beta by increasing the expression of the genes: ATP-Binding-Cassette-Superfamily-G-member-2 (ABCG2) and multidrug-resistance protein-1 (MDR1). We also identified receptor-like apical sodium-dependent bile-acid transporter (ASBT) of intestinal enterocyte, showing affinity towards amyloid-beta, suggesting amyloid-beta's possible reuptake from intestinal contents to the systemic circulation through this receptor. Further, we have performed protein-protein interaction to evaluate the binding affinity of amyloid-beta to these receptors. Moreover, we undertook molecular docking and molecular dynamic simulation of some repurposed drugs (rifampicin, 24-hydroxycholesterols, resveratrol, cilostazol) which can target the aforesaid receptors to enhance amyloid-beta's fecal clearance, reduce amyloid-beta formation, and prevent the reuptake of amyloid-beta from intestinal feces. Additionally, network pharmacology and synergism analysis were utilized to validate our hypothesis and identify the drug combinations, respectively. Gene-ontology investigation, network pharmacology, and consolidated pathway analysis validate the alteration of the above-mentioned gene expression profiles. Furthermore, our neuropharmacological synergism study identifies the optimal combination of the repurposed drugs. Finally, our findings on candidate drugs are substantiated by clinical-trial outcomes.Communicated by Ramaswamy H. Sarma.

Neuroprotective Drug Discovery From Phytochemicals and Metabolites for CNS Viral Infection: A Systems Biology Approach With Clinical and Imaging Validation.

Background: Recent studies have reported that pulmo-neurotropic viruses can cause systemic invasion leading to acute respiratory failure and neuroinfection. The tetracycline class of secondary metabolites of microorganisms is effective against several migrating neurotropic viral disorders, as Japanese-Encephalitis (JE), Severe-Acute-Respiratory-Syndrome Coronavirus-2 (SARS-COV2), Human-Immunodeficiency-Virus (HIV), and Simian-Immunodeficiency-Virus (SIV). Another microbial secondary metabolite, cephalosporin, can be used for anti-viral combination therapy. However, a substantial public health debacle is viral resistance to such antibiotics, and, thus, one needs to explore the antiviral efficiency of other secondary metabolites, as phytochemicals. Hence, here, we investigate phytochemicals like podophyllotoxin, chlorogenic acid, naringenin, and quercetin for therapeutic efficiency in neurotropic viral infections. Methods: To investigate the possibility of the afferent neural pathway of migrating virus in man, MRI scanning was performed on human subjects, whereby the connections between cranial nerves and the brain-stem/limbic-region were assessed by fiber-tractography. Moreover, human clinical-trial assessment (n = 140, p = 0.028) was done for formulating a quantitative model of antiviral pharmacological intervention. Furthermore, docking studies were performed to identify the binding affinity of phytochemicals toward antiviral targets as (i) host receptor [Angiotensin-converting Enzyme-2], (ii) main protease of SARS-COV2 virus (iii) NS3-Helicase/Nucleoside triphosphatase of Japanese-encephalitis-virus, and the affinities were compared to standard tetracycline and cephalosporin antibiotics. Then, network pharmacology analysis was utilized to identify the possible mechanism of action of those phytochemicals. Results: Human MRI-tractography analysis showed fiber connectivity, as: (a) Path-1: From the olfactory nerve to the limbic region (2) Path-2: From the peripheral glossopharyngeal nerve and vagus nerves to the midbrain-respiratory-center. Docking studies revealed comparable binding affinity of phytochemicals, tetracycline, and cephalosporin antibiotics toward both (a) virus receptors, (b) host cell receptors where virus-receptor binds. The phytochemicals effectively countered the cytokine storm-induced neuroinflammation, a critical pathogenic pathway. We also found that a systems-biology-based double-hit mathematical bi-exponential model accounts for patient survival-curve under antiviral treatment, thus furnishing a quantitative-clinical framework of secondary metabolite action on virus and host cells. Conclusion: Due to the current viral resistance to antibiotics, we identified novel phytochemicals that can have clinical therapeutic application to neurotropic virus infection. Based on human MRI scanning and clinical-trial analysis, we demarcated the anatomical pathway and systems-biology-based quantitative formulation of the mechanism of antiviral action.

Corpus Callosum Remodeling in Glioma: Constancy of Fiber Density and Anisotropy in MRI.

Corpus callosum (CC) is the primary fiber system bridging the cerebral hemispheres and is of critical importance for glioma migration which downgrades the prognosis. Here we present the specific pattern of CC restructuring in glioma patients. We probe that the magnetic resonance imaging-based fiber count decrease can be a ready noninvasive indicator of glioma aggressivity and prognosis. We find that to maintain the callosal neural transmission efficiency, the optimum architectural density of white matter fibers remains unchanged, even though there is gross fiber loss. This adaptation occurs by CC's isotonic restructuration, a protective compensatory behavior for maintaining CC's optimal functional efficiency despite malignant infiltration.

A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility.

There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

Autistic traits and individual brain differences: functional network efficiency reflects attentional and social impairments, structural nodal efficiencies index systemising and theory-of-mind skills.

BACKGROUND: Autism is characterised not only by impaired social cognitive 'empathising' but also by superior rule-based 'systemising'. These cognitive domains intertwine within the categorical diagnosis of autism, yet behavioural genetics suggest largely independent heritability, and separable brain mechanisms. We sought to determine whether quantitative behavioural measures of autistic traits are dimensionally associated with structural and functional brain network integrity, and whether brain bases of autistic traits vary independently across individuals. METHODS: Thirty right-handed neurotypical adults (12 females) were administered psychometric (Social Responsiveness Scale, Autism Spectrum Quotient and Systemising Quotient) and behavioural (Attention Network Test and theory-of-mind reaction time) measures of autistic traits, and structurally (diffusion tensor imaging) and functionally (500 s of 2 Hz eyes-closed resting fMRI) derived graph-theoretic measures of efficiency of information integration were computed throughout the brain and within subregions. RESULTS: Social impairment was positively associated with functional efficiency (r = .47, p = .006), globally and within temporo-parietal and prefrontal cortices. Delayed orienting of attention likewise was associated with greater functional efficiency (r = - .46, p = .0133). Systemising was positively associated with global structural efficiency (r = .38, p = 0.018), driven specifically by temporal pole; theory-of-mind reaction time was related to structural efficiency (r = - .40, p = 0.0153) within right supramarginal gyrus. LIMITATIONS: Interpretation of these relationships is complicated by the many senses of the term 'connectivity', including functional, structural and computational; by the approximation inherent in group functional anatomical parcellations when confronted with individual variation in functional anatomy; and by the validity, sensitivity and specificity of the several survey and experimental behavioural measures applied as correlates of brain structure and function. CONCLUSIONS: Functional connectivities highlight distributed networks associated with domain-general properties such as attentional orienting and social cognition broadly, associating more impaired behaviour with more efficient brain networks that may reflect heightened feedforward information flow subserving autistic strengths and deficits alike. Structural connectivity results highlight specific anatomical nodes of convergence, reflecting cognitive and neuroanatomical independence of systemising and theory-of-mind. In addition, this work shows that individual differences in theory-of-mind related to brain structure can be measured behaviourally, and offers neuroanatomical evidence to pin down the slippery construct of 'systemising' as the capacity to construct invariant contextual associations.

Role of Neuroimaging Modality in the Assessment of Oxidative Stress in Brain: A Comprehensive Review.

BACKGROUND & OBJECTIVE: Oxidative stress (OS) is the secondary source of an injury in consequence to the earlier caused primary injury; it is the condition of an imbalance between oxidants and antioxidants within the physiological system. OS causes alterations in proteins and DNA structure, leading to inflammation, apoptotic cell death, and tissue damage. Neurodegenerative diseases (NDDs) such as Alzheimer's disease, Parkinson's disease, Glioma-induced neurodegeneration and the normal aging-related neuro-degeneration are primarily associated with the increased OS. The present review article is committed to delivering a comprehensive overview of the current neuroimaging modalities which estimates an indirect correlate of OS in the brain. OS-induced changes in white matter tracts and the gray matter volumes are reviewed assessing the role of diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) respectively. Further, the role of magnetic resonance spectroscopy (MRS) to assess the OS-induced alterations of chemical moieties, and thus the resultant structural implications in the neurological disorders are also briefly as well as precisely reviewed. CONCLUSION: In the present review article we present an overview of the role of neuroimaging modalities in the diagnosis, and longitudinal assessment during treatment of the OS induced changes.

Patterning of corpus callosum integrity in glioma observed by MRI: Effect of 2D bi-axial lamellar brain architecture.

PURPOSE: Corpus callosum (CC) is a main channel histologically for glioma spreading, downgrading the prognosis, the infiltration occurring through cellular reaction-diffusion process. Preliminary clinical trial indicates that CC's surgical interruption appreciably enhances clinical outcome. We aim to find how high-grade glioma phenomenology is reflected in CC parameters, including various 3D diffusion eigenvalues differentially, whereby this information may be utilized for planning radiotherapy and surgical intervention. METHODS: Using 3 Tesla MRI diffusion-tensor imaging of glioma patients and matched controls, we formulated the callosal volume, fibre count, and 3D directional diffusivity eigenvalues (λ1-λ2-λ3), utilizing FDT/FMRIB-based analysis. RESULTS: In glioma, the callosal volume, fibre count and normalized volume decreases (p < 0.001), while axial diffusivity λ1 and radial diffusivity component λ2 significantly increase (p = 0.03, p = 0.04). Though not expected, the other radial diffusivity component λ3 remains unchanged (p = 0.11). Increase of λ1 and λ2 is due to gliomatous migration across the two directions (eigenvectors of λ1, λ2), which correlate respectively with medio-lateral commissural fibres and dorso-ventral perforating fibres in CC. These are corroborated by collateral radiological findings and immunohistological staining of those two fibre-systems in cat and human. CONCLUSION: In glioma, the two diffusivities (λ1, λ2), enhance due to fluidic edema permeation through CC's bi-axial lamina-type structural scaffold, formed by mediolateral commissural fibres and dorsoventral perforating cingulo-septal fibres. On other hand, the two radial diffusivities (λ2, λ3) are physiologically different and can be distinguished as lamellar diffusivity and focal diffusivity respectively. Lamellar diffusivity λ2 needs to be considered for MRI-assisted surgical intervention and radiotherapy planning in glioma.

A Correlational Study between Microstructural White Matter Properties and Macrostructural Gray Matter Volume Across Normal Ageing: Conjoint DTI and VBM Analysis.

We investigate the relationship between Gray matter's volume vis-a-vis White matter's integrity indices, such Axial diffusivity, Radial diffusivity, Mean diffusivity, and Fractional anisotropy, in individuals undergoing healthy aging. We investigated MRI scans of 177 adults across 20 to 85 years. We used Voxel-based morphometry, and FDT-FSL analysis for estimation of Gray matter volume and White matter's diffusion indices respectively. Across the life span, we observed an inter-relationship between the Gray matter and White matter, namely that both Axial diffusivity and Mean Diffusivity show strong correlation with Gray matter volume, along the aging process. Furthermore, across all ages the Fractional anisotropy and Mean diffusivity are found to be significantly reduced in females when compared to males, but there are no significant gender differences in Axial Diffusivity and Radial diffusivity. We conclude that for both genders across all ages, the Gray matter's Volume is strongly correlated with White matter's Axial Diffusivity and Mean Diffusivity, while being weakly correlated with Fractional Anisotropy. Our study clarifies the multi-scale relationship in brain tissue, by elucidating how the White matter's micro-structural parameters influences the Gray matter's macro-structural characteristics, during healthy aging across the life-span.

Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks.

OBJECTIVE: Effective connectivity (EC) is the methodology for determining functional-integration among the functionally active segregated regions of the brain. By definition EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modeling of the two modalities: functional MRI (fMRI) and diffusion tensor imaging (DTI). We aim to propose a unified probabilistic framework that combines information from both sources to learn EC using dynamic Bayesian networks (DBNs). METHOD: DBNs are probabilistic graphical temporal models that learn EC in an exploratory fashion. Specifically, we propose a novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously. The AI score is employed in structure learning of DBN given the data. RESULTS: Experiments with synthetic-data demonstrate the face validity of structure learning with our AI score over anatomically uninformed counterpart. Moreover, real-data results are cross-validated by performing classification-experiments. CONCLUSION: EC inferred on real fMRI-DTI datasets is found to be consistent with previous literature and show promising results in light of the AC present as compared to other classically used techniques such as Granger-causality. SIGNIFICANCE: Multimodal analyses provide a more reliable basis for differentiating brain under abnormal/diseased conditions than the single modality analysis.

Systems Biology of Immunomodulation for Post-Stroke Neuroplasticity: Multimodal Implications of Pharmacotherapy and Neurorehabilitation.

AIMS: Recent studies indicate that anti-inflammatory drugs, act as a double-edged sword, not only exacerbating secondary brain injury but also contributing to neurological recovery after stroke. Our aim is to explore whether there is a beneficial role for neuroprotection and functional recovery using anti-inflammatory drug along with neurorehabilitation therapy using transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), so as to improve functional recovery after ischemic stroke. METHODS: We develop a computational systems biology approach from preclinical data, using ordinary differential equations, to study the behavior of both phenotypes of microglia, such as M1 type (pro-inflammatory) vis-à-vis M2 type (anti-inflammatory) under anti-inflammatory drug action (minocycline). We explore whether pharmacological treatment along with cerebral stimulation using tDCS and rTMS is beneficial or not. We utilize the systems pathway analysis of minocycline in nuclear factor kappa beta (NF-κB) signaling and neurorehabilitation therapy using tDCS and rTMS that act through brain-derived neurotrophic factor (BDNF) and tropomyosin-related kinase B (TrkB) signaling pathways. RESULTS: We demarcate the role of neuroinflammation and immunomodulation in post-stroke recovery, under minocycline activated-microglia and neuroprotection together with improved neurogenesis, synaptogenesis, and functional recovery under the action of rTMS or tDCS. We elucidate the feasibility of utilizing rTMS/tDCS to increase neuroprotection across the reperfusion stage during minocycline administration. We delineate that the signaling pathways of minocycline by modulation of inflammatory genes in NF-κB and proteins activated by tDCS and rTMS through BDNF, TrkB, and calmodulin kinase (CaMK) signaling. Utilizing systems biology approach, we show that the activation pathways for pharmacotherapy (minocycline) and neurorehabilitation (rTMS applied to ipsilesional cortex and tDCS) results into increased neuronal and synaptic activity that commonly occur through activation of N-methyl-d-aspartate receptors. We construe that considerable additive neuroprotection effect would be obtained and delayed reperfusion injury can be remedied, if one uses multimodal intervention of minocycline together with tDCS and rTMS. CONCLUSION: Additive beneficial effect is, thus, noticed for pharmacotherapy along with neurorehabilitation therapy, by maneuvering the dynamics of immunomodulation using anti-inflammatory drug and cerebral stimulation for augmenting the functional recovery after stroke, which may engender clinical applicability for enhancing plasticity, rehabilitation, and neurorestoration.

Age-Related Differences in White Matter Integrity in Healthy Human Brain: Evidence from Structural MRI and Diffusion Tensor Imaging.

The aim is to investigate the relationship between microstructural white matter (WM) diffusivity indices and macrostructural WM volume (WMV) among healthy individuals (20-85 years). Whole-brain diffusion measures were calculated from diffusion tensor imaging using FMRIB software library while WMV was estimated through voxel-based morphometry, and voxel-based analysis was carried out using tract-based spatial statistics. Our results revealed that mean diffusivity, axial diffusivity, and radial diffusivity had shown good correlation with WMV but not for fractional anisotropy (FA). Voxel-wise tract-based spatial statistics analysis for FA showed a significant decrease in four regions for middle-aged group compared to young-aged group, in 22 regions for old-aged group compared to middle-aged group, and in 26 regions for old-aged group compared to young-aged group (P < 0.05). We found significantly lower WMV, FA, and mean diffusivity values in females than males and inverted-U trend for FA in males. We conclude differential age- and gender-related changes for structural WMV and WM diffusion indices.

Aging alterations in whole-brain networks during adulthood mapped with the minimum spanning tree indices: the interplay of density, connectivity cost and life-time trajectory.

The organizational network changes in the human brain across the lifespan have been mapped using functional and structural connectivity data. Brain network changes provide valuable insights into the processes underlying senescence. Nonetheless, the altered network density in the elderly severely compromises the usefulness of network analysis to study the aging brain. We successfully circumvented this problem by focusing on the critical structural network backbone, using a robust tree representation. Whole-brain networks' minimum spanning trees were determined in a dataset of diffusion-weighted images from 382 healthy subjects, ranging in age from 20.2 to 86.2 years. Tree-based metrics were compared with classical network metrics. In contrast to the tree-based metrics, classical metrics were highly influenced by age-related changes in network density. Tree-based metrics showed linear and non-linear correlation across adulthood and are in close accordance with results from previous histopathological characterizations of the changes in white matter integrity in the aging brain.

A patient-specific therapeutic approach for tumour cell population extinction and drug toxicity reduction using control systems-based dose-profile design.

BACKGROUND: When anti-tumour therapy is administered to a tumour-host environment, an asymptotic tapering extremity of the tumour cell distribution is noticed. This extremity harbors a small number of residual tumour cells that later lead to secondary malignances. Thus, a method is needed that would enable the malignant population to be completely eliminated within a desired time-frame, negating the possibility of recurrence and drug-induced toxicity. METHODS: In this study, we delineate a computational procedure using the inverse input-reconstruction approach to calculate the unknown drug stimulus input, when one desires a known output tissue-response (full tumour cell elimination, no excess toxicity). The asymptotic extremity is taken care of using a bias shift of tumour-cell distribution and guided control of drug administration, with toxicity limits enforced, during mutually-synchronized chemotherapy (as Temozolomide) and immunotherapy (Interleukin-2 and Cytotoxic T-lymphocyte). RESULTS: Quantitative modeling is done using representative characteristics of rapidly and slowly-growing tumours. Both were fully eliminated within 2 months with checks for recurrence and toxicity over a two-year time-line. The dose-time profile of the therapeutic agents has similar features across tumours: biphasic (lymphocytes), monophasic (chemotherapy) and stationary (interleukin), with terminal pulses of the three agents together ensuring elimination of all malignant cells. The model is then justified with clinical case studies and animal models of different neurooncological tumours like glioma, meningioma and glioblastoma. CONCLUSION: The conflicting oncological objectives of tumour-cell extinction and host protection can be simultaneously accommodated using the techniques of drug input reconstruction by enforcing a bias shift and guided control over the drug dose-time profile. For translational applicability, the procedure can be adapted to accommodate varying patient parameters, and for corrective clinical monitoring, to implement full tumour extinction, while maintaining the health profile of the patient.

The effect of stochastic fluctuation in radiation dose-rate on cell survival following fractionated radiation therapy.

In radiobiological models, it is often assumed that the radiation dose rate remains constant during the course of radiation delivery. However, instantaneous radiation dose rate undergoes random (stochastic) temporal fluctuation. The effect of stochastic dose rate in fractionated radiation therapy is unknown and there has been no analytical formulation of stochastic dose-rate fluctuation effect in fractionated radiation therapy which we endeavor to pursue here. We have obtained the quantitative expression of cellular survival fraction considering stochastic temporal fluctuation or noise in dose rate. We have shown that the constant dose-rate approximation overestimates the survival fraction compared to that under stochastic dose rate in a fractionated radiation therapy situation and this overestimation effect increases appreciably with the increase in the fluctuation level in dose rate. However, for a given level of fluctuation in dose rate, overestimation of survival fraction also depends on the value of cellular radiation sensitivity parameter ß and the repair rate of DNA lesion. This overestimation effect is higher for the cells which have a higher value of ß parameter or have a lower repair rate. Our study draws attention to stochastic temporal fluctuation in the radiation dose rate and its potential contribution to cell survival following fractionated radiotherapy.