Quantitative evaluation of the impact of variation of optical parameters on the estimation of blood hematocrit and oxygen saturation for dual-wavelength photoacoustics.

Photoacoustic (PA) spectroscopy is considered to be one of the most effective ways to measure the levels of hematocrit (H) and oxygenation saturation (S O 2) of blood, which are essential for diagnosing blood-related illnesses. This simulation study aims to investigate the impact of individual optical parameters, i.e., optical absorption coefficient (µ a), scattering coefficient (µ s), and anisotropy factor (g), on the accuracy of this technique in estimating the blood properties. We first performed the Monte Carlo simulations, using realistic optical parameters, to obtain the fluence maps for various samples. The wavelengths of the incident light were chosen to be 532, 700, 1000, and 1064 nm. Thereafter, the k-Wave simulations were executed, incorporating those fluence maps to generate the PA signals. The blood properties were obtained using the PA signals. We introduced variations in µ a, µ s, and g ranging from -10% to +10%, -10% to +10%, and -5% to +1%, respectively, at 700 and 1000 nm wavelengths. One parameter, at both wavelengths, was changed at a time, keeping others fixed. Subsequently, we examined how accurately the blood parameters could be determined at physiological hematocrit levels. A 10% variation in µ a induces a 10% change in H estimation but no change in S O 2 determination. Almost no change has been seen for µ s variation. However, a 5% (-5% to 0%) variation in the g factor resulted in approximately 160% and 115% changes in the PA signal amplitudes at 700 and 1000 nm, respectively, leading to ≈125% error in hematocrit estimation and ≈14% deviation in S O 2 assessment when nominal S O 2=70%. It is clear from this study that the scattering anisotropy factor is a very sensitive parameter and a small change in its value can result in large errors in the PA estimation of blood properties. In the future, in vitro experiments with pathological blood (inducing variation in the g parameter) will be performed, and accordingly, the accuracy of the PA technique in quantifying blood H and S O 2 will be evaluated.

Deep learning on photoacoustic tomography to remove image distortion due to inaccurate measurement of the scanning radius.

Photoacoustic tomography (PAT) is a non-invasive, non-ionizing hybrid imaging modality that holds great potential for various biomedical applications and the incorporation with deep learning (DL) methods has experienced notable advancements in recent times. In a typical 2D PAT setup, a single-element ultrasound detector (USD) is used to collect the PA signals by making a 360° full scan of the imaging region. The traditional backprojection (BP) algorithm has been widely used to reconstruct the PAT images from the acquired signals. Accurate determination of the scanning radius (SR) is required for proper image reconstruction. Even a slight deviation from its nominal value can lead to image distortion compromising the quality of the reconstruction. To address this challenge, two approaches have been developed and examined herein. The first framework includes a modified version of dense U-Net (DUNet) architecture. The second procedure involves a DL-based convolutional neural network (CNN) for image classification followed by a DUNet. The first protocol was trained with heterogeneous simulated images generated from three different phantoms to learn the relationship between the reconstructed and the corresponding ground truth (GT) images. In the case of the second scheme, the first stage was trained with the same heterogeneous dataset to classify the image type and the second stage was trained individually with the appropriate images. The performance of these architectures has been tested on both simulated and experimental images. The first method can sustain SR deviation up to approximately 6% for simulated images and 5% for experimental images and can accurately reproduce the GTs. The proposed DL-approach extends the limits further (approximately 7% and 8% for simulated and experimental images, respectively). Our results suggest that classification-based DL method does not need a precise assessment of SR for accurate PAT image formation.

Characterizing gait and exploring neuro-morphometry in patients with PSP-Richardson's syndrome and vascular parkinsonism.

Gait differentiation in progressive supranuclear palsy (PSP) and vascular parkinsonism (VaP) is sometimes difficult to detect with the naked eye. Here, we compared specific gait parameters, neuro-morphometric indices, and their associations between patients with PSP Richardson's syndrome (PSP-RS) and VaP. A total of 18 PSP-RS and 13 VaP patients were recruited. Spatio-temporal gait parameters (GAITRite®) and neuroanatomical morphometry (FreeSurfer pipeline) were assessed. The groups were compared using unpaired t-tests involving 10000 random permutations after statistically controlling for total UPDRS-III and H&Y scores. Statistically significant differences between the groups were decided at < 5% Benjamini-Hochberg False Discovery Rate (FDR) for multiple-comparison related corrections. Spearman's correlations were performed to assess the significant associations (p < 0.05) between the gait parameters and morphometry indices. Among all the spatio-temporal gait parameters, PSP-RS patients displayed greater stride time, step time, swing time, and stance time variabilities compared to VaP. Morphometric analyses showed that thalamus, and caudate volumes were significantly lower, but cerebellar cortex, hippocampus, amygdala, accumbens, and putamen volumes were higher in PSP-RS than VaP. Moreover, the bilateral insula was significantly thinner in VaP than in PSP-RS. Correlation analyses support the involvement of limbic structures besides cerebellum in postural control during self-paced walking of PSP-RS patients. Our findings underline the importance of examining individual brain regions to understand the association of cortical and subcortical morphometric estimates and gait variability parameters in PSP-RS and VaP. This study suggests the involvement of the limbic system in addition to the classical neural structures for motor control and gait.

Machine learning classification of chronic traumatic brain injury using diffusion tensor imaging and NODDI: A replication and extension study.

Individuals with acute and chronic traumatic brain injury (TBI) are associated with unique white matter (WM) structural abnormalities, including fractional anisotropy (FA) differences. Our research group previously used FA as a feature in a linear support vector machine (SVM) pattern classifier, observing high classification between individuals with and without acute TBI (i.e., an area under the curve [AUC] value of 75.50%). However, it is not known whether FA could similarly classify between individuals with and without history of chronic TBI. Here, we attempted to replicate our previous work with a new sample, investigating whether FA could similarly classify between incarcerated men with (n = 80) and without (n = 80) self-reported history of chronic TBI. Additionally, given limitations associated with FA, including underestimation of FA values in WM tracts containing crossing fibers, we extended upon our previous study by incorporating neurite orientation dispersion and density imaging (NODDI) metrics, including orientation dispersion (ODI) and isotropic volume (Viso). A linear SVM based classification approach, similar to our previous study, was incorporated here to classify between individuals with and without self-reported chronic TBI using FA and NODDI metrics as separate features. Overall classification rates were similar when incorporating FA and NODDI ODI metrics as features (AUC: 82.50%). Additionally, NODDI-based metrics provided the highest sensitivity (ODI: 85.00%) and specificity (Viso: 82.50%) rates. The current study serves as a replication and extension of our previous study, observing that multiple diffusion MRI metrics can reliably classify between individuals with and without self-reported history of chronic TBI.

Nanocomposite-based smart fertilizers: A boon to agricultural and environmental sustainability.

Fertilizers are indispensable agri-inputs to accomplish the growing food demand. The injudicious use of conventional fertilizer products has resulted in several environmental and human health complications. To mitigate these problems, nanocomposite-based fertilizers are viable alternative options. Nanocomposites, a novel class of materials having improved mechanical strength, barrier properties, and mechanical and thermal stability, are suitable candidates to develop eco-friendly slow/controlled release fertilizer formulations. In this review, the use of different nanocomposite materials developed for nutrient management in agriculture has been summarized with a major focus on their synthesis and characterization techniques, and application aspects in plant nutrition, along with addressing constraints and future opportunities of this domain. Further detailed studies on nanocomposite-based fertilizers are required to evaluate the cost-effective synthesis methods, in-depth field efficacy, environmental fate, stability, etc. before commercialization in the field of agriculture. The present review is expected to help the policy makers and all the stakeholders in the large-scale commercialization and application of nanocomposite-based smart fertilizer products with greater societal acceptance and environmental sustainability in near future.

Reduced structural integrity of the uncinate fasciculus in incarcerated women scoring high on psychopathy.

Both men and women scoring high on psychopathy exhibit similar structural and functional neural abnormalities, including reduced volume of the orbitofrontal cortex (OFC) and reduced hemodynamic activity in the amygdala during affective processing experimental paradigms. The uncinate fasciculus (UF) is a white matter (WM) tract that connects the amygdala to the OFC. Reduced structural integrity of the UF, measured via fractional anisotropy (FA), is commonly associated with men scoring high on psychopathy. However, only one study to date has investigated the relationship between psychopathic traits and UF structural integrity in women, recruiting participants from a community sample. Here, we investigated whether Hare Psychopathy Checklist-Revised (PCL-R) facet scores (measuring interpersonal, affective, lifestyle/behavioral, and antisocial psychopathic traits, respectively) were associated with reduced FA in the left and right UF in a sample of 254 incarcerated women characterized by a wide range of psychopathy scores. We observed that PCL-R Facet 3 scores, assessing lifestyle/behavioral psychopathic traits, were associated with reduced FA in the left and right UF, even when controlling for participant's age and history of previous substance use. The results obtained in the current study help improve our understanding of structural abnormalities associated with women scoring high on psychopathy. Specifically, reduced UF structural integrity may contribute to some of the deficits commonly associated with women scoring high on psychopathy, including emotion dysregulation.

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.

Exploring polynomial based interpolation schemes for photoacoustic tomographic image reconstruction.

Photoacoustic tomography (PAT) imaging employing polynomial-based interpolation methods is discussed. Nearest-neighbor, bilinear, bicubic and biquintic algorithms were implemented for the construction of the model matrix, and images were formed using the Tikhonov regularization and total variation (TV) minimization procedures. The performance of the interpolation methods was assessed by comparing the reconstructed images of three numerical and two experimental phantoms. The numerical and experimental studies demonstrate that the performance of the interpolation schemes is nearly equal for large PA sources. The simplest nearest-neighbor technique provides better image reconstruction for a sparse source compared to the others. The nearest-neighbor protocol may be adopted in practice for vascular imaging using PAT.

Application of DNP-enhanced solid-state NMR to studies of amyloid-ß peptide interaction with lipid membranes.

The cellular membrane disruption induced by the aggregation of Aß peptide has been proposed as a plausible cause of neuronal cell death during Alzheimer's disease. The molecular-level details of the Aß interaction with cellular membranes were previously probed using solid state NMR (ssNMR), however, due to the limited sensitivity of the latter, studies were limited to samples with high Aß-to-lipid ratio. The dynamic nuclear polarization (DNP) is a technique for increasing the sensitivity of NMR. In this work we demonstrate the feasibility of DNP-enhanced ssNMR studies of Aß40 peptide interacting with various model liposomes: (1) a mixture of zwitterionic 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) and negatively charged 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (POPG); (2) a mixture of POPC, POPG, cholesterol, sphingomyelin and ganglioside GM1; (3) the synaptic plasma membrane vesicles (SPMVs) extracted from rat brain tissues. In addition, DNP-ssNMR was applied to capturing changes in Aß40 conformation taking place upon the peptide insertion into POPG liposomes. The signal enhancements under conditions of DNP allow carrying out informative 2D ssNMR experiments with about 0.25 mg of Aß40 peptides (i.e. reaching Aß40-to-lipid ratio of 1:200). In the studied liposome models, the 13C NMR chemical shifts at many 13C-labelled sites of Aß40 are characteristic of ß-sheets. In addition, in POPG liposomes the peptide forms hydrophobic contacts F19-L34 and F19-I32. Both the chemical shifts and hydrophobic contacts of Aß40 in POPG remain the same before and after 8 h of incubation. This suggests that conformation at the 13C-labelled sites of the peptide is similar before and after the insertion process. Overall, our results demonstrate that DNP helps to overcome the sensitivity limitation of ssNMR, and thereby expand the applicability of ssNMR for charactering the Aß peptide interacting with lipids.

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.

Cannabis use-related working memory deficit mediated by lower left hippocampal volume.

The association between cannabis exposure and working memory impairment and its neural substrates remain unclear. In this cross-sectional observational study, we investigated this by examining the relationship between frequency of exposure to cannabis, working memory performance and regional brain volumes and tested whether lower volumes of cortical and subcortical structures mediate the association between cannabis exposure and working memory deficit using the Human Connectome Project data from 234 individuals with self-reported cannabis exposure and 174 individuals unexposed to cannabis. We tested the relationship between self-reported frequency of cannabis exposure and list-sorting working memory task performance (total number of correct responses), between T1 weighted MRI-derived regional grey-matter volumes and working memory task performance as well as between frequency of cannabis exposure and brain volumes after controlling for potential confounders. Finally, mediation analysis was carried out to test whether deficit in working memory performance associated with cannabis use was mediated by its association with lower grey-matter volume. Participants who reported higher frequency of cannabis use tended to have lower number of correct responses in the list-sorting working memory task and lower bilateral hippocampal volumes. Association between severity of cannabis exposure as indexed by frequency of cannabis use and impairment in working memory was mediated by lower left hippocampal volume in cannabis users. We report evidence in support of the left hippocampus volume-mediated working memory impairment associated with recreational cannabis exposure. Future studies employing prospective longitudinal design are necessary to examine the cause-effect relationships of cannabis exposure on working memory and brain volumes.

Youth with elevated psychopathic traits exhibit structural integrity deficits in the uncinate fasciculus.

Youth with elevated psychopathic traits represent a particularly severe subgroup of adolescents characterized by extreme behavioral problems and exhibit comparable neurocognitive deficits as adult offenders with psychopathic traits. A consistent finding among adults with elevated psychopathic traits is reduced white matter structural integrity of the right uncinate fasciculus (UF). The UF is a major white matter tract that connects regions of the anterior temporal lobe (i.e., the amygdala) to higher-order executive control regions, including the ventromedial prefrontal cortex. However, the relationship between youth psychopathic traits and structural integrity of the UF has been mixed, with some studies identifying a negative relationship between adolescent psychopathy scores and FA in the UF, and others identifying a positive relationship. Here, we investigated structural integrity of the left and right UF using fractional anisotropy (FA) in a large sample of n = 254 male adolescent offenders recruited from maximum-security juvenile correctional facilities. Psychopathic traits were assessed using the Hare Psychopathy Checklist: Youth Version (PCL:YV). Consistent with hypotheses, interpersonal and affective traits (i.e., PCL:YV Factor 1 and Facet 1 scores) were associated with reduced FA in the right UF. Additionally, lifestyle traits (i.e., PCL:YV Facet 3 scores) were associated with increased FA in the left UF. Results are consistent with previously published studies reporting reduced FA in the right UF in adult psychopathic offenders and increased left UF FA in youth meeting criteria for certain externalizing disorders.

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.

Network organization of co-opetitive genetic influences on morphologies of the human cerebral cortex.

OBJECTIVE: The brain can be represented as a network, where anatomical regions are nodes and relations between regions are edges. Within a network, the co-existence of co-operative and competitive relationships between different nodes is called co-opetition. Inter-regional genetic influences on morphological phenotypes (thickness, surface area) of the cerebral cortex display such co-opetitive relationships. However, whether these co-operative and competitive genetic influences are organized similarly has remained elusive. How the collective organization of the co-operative and competitive genetic influences is related to the inter-individual variations of cortical morphological phenotypes has also remained unexplored. APPROACH: We constructed inter-regional genetic influence networks underlying the morphologies (thickness, surface area) of the human cerebral cortex combining the T1 weighted MRI of genetically confirmed 593 siblings and twin-study design. Graph theory was used to characterize the genetic influence networks and the collective organizations of genetic influences were characterized using the theory of structural balance. Principal component (PC) analysis was used to estimate the principal modes of morphological phenotype variations. MAIN RESULTS: The inter-regional co-operative genetic influences are assortative, while competitive influences are disassortative. Co-operative genetic influences are more cohesive and less diverse than the competitive influences. The collective organization of co-opetitive genetic influences partially explains the fifth principal modes of inter-individual variation of cortical morphological phenotypes. Other principal modes were not significantly associated with collective genetic influences. SIGNIFICANCE: Our study furnishes fundamental insight regarding the organization of co-opetitive genetic influences underlying the morphologies of the human cerebral cortex. In future studies, investigation of the alterations of co-opetitive genetic network properties in brain disorders may furnish disorder-specific insight that may be associated with the disease state or lead to vulnerability to those conditions.

Does thinner right entorhinal cortex underlie genetic liability to cannabis use?

BACKGROUND: Although alterations in medial temporal lobe structures have been previously associated with use of cannabis, one of the most widely used illicit drugs, whether such alterations are a cause or effect of cannabis use has been unclear. METHODS: In this cross-sectional observational study involving 404 twins/siblings, we have compared cortical thickness and surface area between groups of gender-matched sibling-pairs (concordant cannabis unexposed, concordant exposed and discordant for cannabis exposure) using permutation tests after controlling for potential confounds. Bi-variate polygenic model was used to assess the genetic and environmental contributions underlying cortical morphological phenotypes and frequency of cannabis use. RESULTS: Cortical thickness of the right entorhinal cortex was significantly lower in the concordant exposed siblings compared to both discordant unexposed and discordant exposed groups [false discovery rate (FDR)-corrected, q < 0.05]. The association between the right entorhinal cortex thickness and frequency of cannabis use is due to the contribution of significant shared additive genetic (ρg = -0.19 ± 0.08; p = 0.02) factors but not unique environment (ρe = 0.05 ± 0.09; p = 0.53). Significantly lower surface area of the right entorhinal cortex in discordant exposed group compared with the discordant unexposed group furnishes preliminary evidence in support of causal effect of cannabis use (FDR-corrected, q < 0.05). However, bi-variate polygenic model-based analysis did not show any significant effect. CONCLUSIONS: Shared genetic liability may underlie the association between cannabis exposure and thinner right entorhinal cortex. Prospective longitudinal studies are necessary to definitively disentangle the cause-effect relationships of cannabis use.

The consequence of day-to-day stochastic dose deviation from the planned dose in fractionated radiation therapy.

Radiation therapy is one of the important treatment procedures of cancer. The day-to-day delivered dose to the tissue in radiation therapy often deviates from the planned fixed dose per fraction. This day-to-day variation of radiation dose is stochastic. Here, we have developed the mathematical formulation to represent the day-to-day stochastic dose variation effect in radiation therapy. Our analysis shows that that the fixed dose delivery approximation under-estimates the biological effective dose, even if the average delivered dose per fraction is equal to the planned dose per fraction. The magnitude of the under-estimation effect relies upon the day-to-day stochastic dose variation level, the dose fraction size and the values of the radiobiological parameters of the tissue. We have further explored the application of our mathematical formulation for adaptive dose calculation. Our analysis implies that, compared to the premise of the Linear Quadratic Linear (LQL) framework, the Linear Quadratic framework based analytical formulation under-estimates the required dose per fraction necessary to produce the same biological effective dose as originally planned. Our study provides analytical formulation to calculate iso-effect in adaptive radiation therapy considering day-to-day stochastic dose deviation from planned dose and also indicates the potential utility of LQL framework in this context.

Strategy for stochastic dose-rate induced enhanced elimination of malignant tumour without dose escalation.

The efficacy of radiation therapy, a primary modality of cancer treatment, depends in general upon the total radiation dose administered to the tumour during the course of therapy. Nevertheless, the delivered radiation also irradiates normal tissues and dose escalation procedure often increases the elimination of normal tissue as well. In this article, we have developed theoretical frameworks under the premise of linear-quadratic-linear (LQL) model using stochastic differential equation and Jensen's inequality for exploring the possibility of attending to the two therapeutic performance objectives in contraposition-increasing the elimination of prostate tumour cells and enhancing the relative sparing of normal tissue in fractionated radiation therapy, within a prescribed limit of total radiation dose. Our study predicts that stochastic temporal modulation in radiation dose-rate appreciably enhances prostate tumour cell elimination, without needing dose escalation in radiation therapy. However, constant higher dose-rate can also enhance the elimination of tumour cells. In this context, we have shown that the sparing of normal tissue with stochastic dose-rate is considerably more than the sparing of normal tissue with the equivalent constant higher dose-rate. Further, by contrasting the stochastic dose-rate effects under LQL and linear-quadratic (LQ) models, we have also shown that the LQ model over-estimates stochastic dose-rate effect in tumour and under-estimates the stochastic dose-rate effect in normal tissue. Our study indicates the possibility of utilizing stochastic modulation of radiation dose-rate for designing enhanced radiation therapy protocol for cancer.

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.

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.