Social support exchanges with coresiding family and non-coresiding family and relatives were not associated with MoCA-J scores at follow-up . The provision of emotional support to neighbors and friends had the largest effect on MoCA-J scores. Our findings suggest that social support exchanges with neighbors and friends are protective against cognitive decline.There is evidence that social relationships may modify cognitive decline in older people. We examined the prospective association between social support and cognitive function among community-dwelling older people. Japanese adults recruited at health checkups in suburban towns were surveyed at baseline and one-year follow-up. Cognitive function was assessed using the Montreal Cognitive Assessment, Japanese version (MoCA-J). Social support from coresiding family, non-coresiding family, and neighbors/friends was assessed using self-administered questionnaires. Multivariable linear regression analysis was conducted to examine the effects of social support on MoCA-J scores at follow-up. Data were analyzed from 121 older people (mean age (standard deviation): 73.86 (4.95) years). There was a positive association between social support exchanges with neighbors and friends and MoCA-J scores at follow-up after covariate adjustment (unstandardized β = 1.23,  Dementia is a global health problem, as the number of people with dementia worldwide may exceed 82 million by 2030 . DementiAccording to the World Health Organization’s (WHO) policy framework on active aging, social relationships are a key factor in achieving active aging  and a poSocial support can be defined as an exchange between persons and is embedded in people’s social networks ,16. SociA few previous studies have shown that different sources of social support have different effects. One cross-sectional study reported that family support was protectively associated with cognitive function among older people, but support from friends was not . Anothern = 33), a history of diagnosis of dementia or mental illness (n = 5), non-independent walking ability (n = 4), and missing data for the cognitive function item (n = 4). The remaining 241 participants were followed for one year from baseline assessment and underwent cognitive testing again at the same center. Participants who did not complete a cognitive function survey at one year of follow-up (n = 120) were excluded. Therefore, 121 older adults met the criteria and were available for the final analysis.In this prospective cohort study, baseline data were used from the Togo town study, which was carried out in cooperation with Nagoya University  and Togo town office. It was a community-based health-check survey conducted in July and August 2017. Individuals were selected for participation from people living in Togo town, a city in Aichi, Japan, and were recruited from a health-check project held in Togo town. A total of 284 adults were enrolled in the study. Baseline exclusion criteria were age < 65 years . The study was conducted in accordance with the guidelines of the Declaration of Helsinki.We assessed cognitive function at baseline and at follow-up using the Japanese version of the Montreal Cognitive Assessment (MoCA-J) ,20. The To assess social support, participants completed a self-administered questionnaire at baseline. This comprised the Two-Way Social Support Scale . Four tySociodemographic characteristics, physical and psychological function, and healthy behaviors at baseline were assessed using a self-administered questionnaire and were included in the analyses as covariates: Age, sex, body mass index (BMI), living alone, equivalent income, medical history  , depressWe first calculated descriptive statistics to compare dropout and non-dropout participants. Continuous variables  were analyzed using an unpaired t-test. Categorical variables  were analyzed using the chi-squared test. Next, to examine the prospective association between cognitive function and the three types of social support , we conducted multivariable linear regression analysis to obtain unstandardized regression coefficients (βs) and standard errors (SEs) for MoCA-J scores at follow-up. First, we conducted an analysis adjusted by age, sex, and MoCA-J score at baseline (model 1). Then we added BMI, living alone, equivalent income, medical history, GDS score, IADL score, walking speed, and walking time (model 2). In addition, we entered each social support item  into the analysis model to examine the impact of each item on MoCA-J scores at follow-up.To mitigate potential biases caused by missing information, we used the multiple imputation approach with the missing at random assumption . We generated 20 imputed data sets using the multiple imputation by chained equations (MICE) procedure and pooled the results using the standard Rubin’s rule .p < 0.05. We used R version 3.4.3 for Windows R  for all statistical analyses. The multiple imputation approach involved the use of the MICE function (MICE package).The significance level was set at p = 0.015).Data from 121 participants were included in the analysis. The characteristics of both dropout and non-dropout participants are shown in p = 0.009). There was no significant association between social support exchanges with coresiding family and with non-coresiding family and relatives and MoCA-J score at follow-up . In model 2, the association between exchange of social support with neighbors and friends and MoCA-J score at follow-up was also significant, adjusted for all covariates . The association between social support from other sources and MoCA-J score at follow-up was not significant .p = 0.029). Other subcomponents of social support exchanges with neighbors and friends were not significantly related to MoCA-J scores .To further examine the exchange of social support with neighbors and friends, we examined which subcomponents were strongly associated with MoCA-J scores at follow-up. This study investigated the prospective association between social support sources and cognitive function in community-dwelling older people through a one-year follow-up. We found that social support exchanges with neighbors and friends were positively associated with cognitive function at one-year follow-up. Regarding the type of social support from neighbors and friends, the provision of emotional support had a significant impact on the maintenance of cognitive function. Our findings suggest the importance of sources of social support in the community, such as neighbors and friends, for maintaining cognitive function among older people.The findings showed that the exchange of social support with neighbors and friends was positively associated with cognitive function at follow-up. Some previous studies have reported that social support outside the family is positively associated with cognitive function ,17. In aProviding emotional support to neighbors and friends had a significantly positive effect on cognitive function after adjustment for all covariates. Some previous studies have also shown that emotional support is protective of cognitive function ,11,14. AOur results indicate that social support from both coresiding and non-coresiding family members was not significantly related to cognitive function. These findings are inconsistent with those of previous studies indicating that social support from family is protective against the onset of dementia or cognitive function decline ,10,12. Ap = 0.015). However, there were no significant differences between non-dropout and dropout participants on the other variables, including social support. Therefore, we believe that the effects of dropout on the association between social support and cognitive function at follow-up may be relatively small. Third, the follow-up period was relatively short. The possibility of reverse causality in the association between social support and cognitive function owing to the effects of unidentified variables on the data cannot be ruled out. Further studies using long-term follow-up periods are needed. Fourth, the sample size was quite small. This did not permit the examination of gender differences using stratification analysis, although research suggests gender-related differences in the effects of social support [The present study has several strengths. First, the prospective study design allowed the identification of a possible causal effect of social support on cognitive function. Second, cognitive function was assessed using psychological tests for which validity has been confirmed. However, several study limitations should be considered. First, participants were recruited from individuals participating in a health checkup held in a suburban town hall. The participants were somewhat healthier and younger than typical community-dwelling older people living in the town. This may reduce the generalizability of our results. Second, there may have been selection bias. The follow-up rate was quite low (50.2%). Cognitive function at baseline for dropout participants was lower than that of non-dropout participants (MoCA-J score dropout participants: Mean = 25.01, SD = 3.42, non-dropout participants: Mean = 25.98, SD = 2.75,  support . We confDespite these limitations, the findings provide evidence of the prospective association between social support and cognitive function. As the global population ages, the number of older people living alone without family support is increasing . As famiIn conclusion, this prospective study showed that social support exchanges with neighbors and friends are positively associated with cognitive function among community-dwelling older people. Regarding supportive exchanges with neighbors and friends, providing emotional support had the largest effect on maintaining cognitive function. Our findings suggest the importance of social support exchanges in the community, including those with neighbors and friends, for maintaining cognitive function among older people.


In recent years, regression trackers have drawn increasing attention in the visual-object tracking community due to their favorable performance and easy implementation. The tracker algorithms directly learn mapping from dense samples around the target object to Gaussian-like soft labels. However, in many real applications, when applied to test data, the extreme imbalanced distribution of training samples usually hinders the robustness and accuracy of regression trackers. In this paper, we propose a novel effective distractor-aware loss function to balance this issue by highlighting the significant domain and by severely penalizing the pure background. In addition, we introduce a full differentiable hierarchy-normalized concatenation connection to exploit abstractions across multiple convolutional layers. Extensive experiments were conducted on five challenging benchmark-tracking datasets, that is, OTB-13, OTB-15, TC-128, UAV-123, and VOT17. The experimental results are promising and show that the proposed tracker performs much better than nearly all the compared state-of-the-art approaches. Visual-object tracking aims to estimate the trajectory of the specified target in a video sequence, which is labeled in the initial frame with a bounding box. It is widely used in various applications, ranging from video surveillance, motion analysis, and autonomous driving. The main difficulty of visual tracking is how to accurately and effectively locate the object in challenging scenarios caused by illumination, deformation, occlusion, out of view, background cluttering, and other variations ,2,3.Modern tracking methods can be classified as either generative or discriminative. Generative methods aim at describing the target appearance using some generative processes  algorithm follows a general one-channel-output regression framework. In addition, we exploit a novel distractor-aware loss function to handle data imbalance and introduce a hierarchy-normalized concatenation connection to fully exploit multilevel semantics across convolutional layers. X, and generate corresponding Gaussian function labels Y. The coefficients W for regression function W and samples X into an elementwise product in the Fourier domain. Here, we try to solve the regression problem in the spatial domain by reformulating the problem as loss minimization of the convolutional neural network.The regression model for visual tracking aims to regress dense samples to Gaussian-like soft labels. Here, we revisit the linear-ridge regression model and formulate the regression model as one convolutional layer. Given an initial image with labeled target, we can extract dense sample features W is the network weights, and Y is the ground-truth labels. The convolution operation on X can be carried out via a convolution layer with one-channel output. The size of the convolution kernel in the regression layer is different from conventional convolution layers that adopt a small fixed receptive field, such as 3 × 3 and 5 × 5. We set the receptive-field size of the regression layer to the size of a tracked target in our framework. The convolutional weights can be effectively calculated by iteratively optimizing W in Equation (The loss function in Equation  can be rL(W)=∥F contains a large amount of context surrounding the target object, as shown in D is a distractor-aware modulating factor that balances training sample loss, and ⊙ denotes the elementwise product. In this work, we adaptively carried out the modulating factor for each optimization iteration. We denote the regression network output in every iteration by R, which generally indicates the probability of a position to be the target object. Once we obtained the probability map, we first identitied a number of N semantic objects by locating the local maximum of R. In general, there is always one positive sample at the map center and N minus one distributed negative distract samples. For each semantic sample, we generated a basic modulator Db in terms of soft labels Y centered at the identified positions:k is a scalar penalization factor. Modulator Db aims at highlighting the central influence and suppressing the surrounding influence. Then, we merged the N basic modulators by summation. In addition, we took one more modulator on the target location to increase the importance of positive samples. k and N. We observed that the larger the value of k was, the larger the penalty to the surrounding contexts. A larger N means taking more distractors to take into account, which may overwhelm the only positive sample. On the other hand, a smaller N makes the training process overfit to the target. Considering the proportion of positive and distractor samples, we fixed the N to be 6 in all our experiments, meaning we introduced five adversarial distractors to go against the positive sample.Existing solutions to the data-imbalance issue mainly focus on penalizing the importance of easy negative samples. However, we observed that semantic distractors have a significant contribution in learning deep-regression networks. We propose to add a modulating factor to the loss that highly suppresses pure backgrounds and protrudes the target and semantic distractors, as shown in By applying the modulating factor, distractor-aware loss mainly focuses on positive samples and adversarial distractors. Extensive comparison with other losses shows that our distractor-aware loss not only promotes tracking accuracy but also accelerates training speed see .conv1 and conv5 layers and merges the corresponding output response maps with empirical weights. Wang et al. [conv4 and conv5 layers, and merge the output response map with a distractor-detection scheme. Song et al. [conv4 layer to capture the difference between the base layer output and the ground truth. Lu et al. [conv4 and conv5 layers as well as their output response maps. Here, we propose a novel hierarchy-normalized concatenation connection to make full use of multiple-level semantic abstraction. We introduced a normalize operation to balance the features’ numeric value and then concatenated the conv3, conv4, and conv5 layers to form a strong representation for visual tracking. We compare our scheme with the aforementioned connections in The convolutional layers of a typical CNN model, e.g., VGG , provideg et al.  proposedg et al.  proposedu et al.  exploiteVGG16 convolutional layers in Different-level layers represent different types of semantic abstraction. We observed that integrating across multiple convolutional layers usually suffers from the numeric issue, in which different layers have significant divergence numeric distribution. We illustrate the numerical statistics of features from three Model Initialization. At this stage, we follow the general tracking initialization process [VGG16 network as the backbone-feature extractor and feed the sample patch into the extractor. Then, we take the output of the conv3_3, conv4_3, and conv5_3 layers as deep features for further training the regression network. The data flow is illustrated in  process ,32,38 to process ,58. In iOnline Detection. For current frame Scale Estimation. After obtaining the target position in the current frame, we extract scale search patches following the scale pyramid scheme as in ACF [t, respectively; and s in ACF . We geneModel Update. In order to accommodate the model to the varied object appearance, we incrementally update our tracker frame by frame. For each frame, we crop the training patch relying on the estimated location and scale and generate corresponding soft labels. To alleviate model drift from noisy updates, training data pairs from past T frames are all adopted for online update.We illustrate the detailed procedure of DaDRT for visual tracking. We decomposed our tracking process into four stages, namely, model initialization, online detection, scale estimation, and model update. Details are as follows:In this section, we introduce the implementation details and compare our DaDRT tracker with state-of-the-art trackers on five frequently used benchmark datasets for performance evaluation. Then, we conduct extensive ablation studies to analyze the effects of distractor-aware loss and hierarchy-normalized concatenation connection.VGG16 with only the first two pooling layers retrained. We extract the feature abstractions from the conv3_3, conv4_3 and conv5_3 layers; then, we apply a 1 × 1 convolutional layer to reduce the feature channels to 48. Regression labels and the motion map are both generated using a two-dimensional Gaussian function with a peak value of 1.0. We set the kernel width to be proportional (0.08) to the target size for the regression labels and proportional (1.0) to the geometric mean of target size for motion constraint map. In the initial training stage, we iteratively apply the SGD optimizer to update the weights in the regression network with a fixed learning rate of We implement the proposed DaDRT in Matlab using the matconvnet toolbox . Our bacHere, we extensively evaluate the proposed DaDRT algorithm on five challenging benchmark datasets, OTB-13 , TC128 , UAV123 There are two versions of OTB datasets, OTB-13 and OTB-15. OTB-15 is an extension of OTB-13, and the two datasets contain 50 and 100 challenging sequences, respectively. All sequences are labeled with ground-truth bounding boxes and various attributes including illumination variation (IV), scale variation (SV), occlusion (OCC), deformation (DEF), motion blur (MB), fast motion (FM), in-plane rotation (IPR), out-of-plane rotation (OPR), out-of-view (OV), background clutters (BC), and low resolution (LR). We compared our tracker with 29 trackers from the OTB benchmark and 39 other state-of-the-art trackers, including C-COT , CF2 29, DCFNet In addition, we further evaluated tracker performance under different video attributes on the OTB-15 dataset. The Temple Color 128 (TC-128) dataset contains 128 colorful video sequences. We conducted one-pass evaluation with the same setting as OTB datasets. We evaluated with 18 baseline trackers provided by the authors of the TC-128 and other state-of-the-art trackers, including TLD , SAMF 1, deepSRDThe UAV-123 dataset contains 123 video sequences captured from low-altitude unmanned aerial vehicles. Besides the baseline trackers evaluated in the UAV-123 benchmark, we compared the proposed trackers with several representative trackers, including ECO , SiamRPNVOT datasets are from the visual-object-tracking (VOT) challenges that provide the tracking community with a precisely defined and repeatable way of comparing short- and long-term trackers, as well as a common platform for discussing the evaluation and advancements made in the field of visual tracking. The standard VOT evaluation scheme applies a reset-based methodology. Whenever a failure (zero overlap with the ground truth) is detected, the tracker is reinitialized five frames after failure. The overall performance is measured by the expected average overlap (EAO), which combines the raw values of per-frame accuracies and failures in a principled manner. Here, we compared the proposed tracker with 51 other state-of-the-art trackers on VOT17 challenges.In DaDRT, we trained the regression network using three convolutional layers and distractor-aware loss. We conducted several experiments to validate the effectiveness of each component. By choosing two of the three used convolutional layers as features, we implemented three alternative approaches to validate multiple convolutional-layer connections. We denoted the three approaches as DaDRT_34, DaDRT_45, and DaDRT_35, where numbers indicate the used convolutional layers. Keeping the proposed regression network bone unchanged, we exploited two other data-imbalance schemes, hard-negative mining loss (HN)  and shribird1). On the other hand, for nonrigid deformation with scale change (e.g., We show some typical failure cases of the proposed tracker in In this paper, we proposed novel distractor-aware loss to alleviate the data-imbalance issue in learning regression networks. This enables the model to focus on positive and hard-negative samples during the training process. We also applied a hierarchy-normalized concatenation scheme to improve regression learning by exploiting strong representation across multiple convolutional layers. The proposed regression network is fully differentiable and can be trained end to end. Furthermore, incorporating other types of features is straightforward. Extensive experiments on five benchmarks demonstrate that the proposed DaDRT tracker performs favorably against state-of-the-art methods.


E-cadherin is the core component of epithelial adherens junctions, essential for tissue development, differentiation, and maintenance. It is also fundamental for tissue barrier formation, a critical function of epithelial tissues. The colon or large intestine is lined by an epithelial monolayer that encompasses an E-cadherin-dependent barrier, critical for the homeostasis of the organ. Compromised barriers of the colonic epithelium lead to inflammation, fibrosis, and are commonly observed in colorectal cancer. In addition to its architectural role, E-cadherin is also considered a tumor suppressor in the colon, primarily a result of its opposing function to Wnt signaling, the predominant driver of colon tumorigenesis. Beyond these well-established traditional roles, several studies have portrayed an evolving role of E-cadherin as a signaling epicenter that regulates cell behavior in response to intra- and extra-cellular cues. Intriguingly, these recent findings also reveal tumor-promoting functions of E-cadherin in colon tumorigenesis and new interacting partners, opening future avenues of investigation. In this Review, we focus on these emerging aspects of E-cadherin signaling, and we discuss their implications in colon biology and disease. Cell-cell adhesion complexes are indispensable for tissue integrity and organ function; however, their disruption can lead to numerous diseases, including inflammation and cancer. The Adherens Junction (AJ) is a major cell-cell adhesion structure, key for maintaining tissue integrity and architecture through its intimate tethering to the actin and microtubule cytoskeleton . The corCDH1 gene. Classical mammalian cadherins have five extracellular domains, spanning EC1 to EC5, with calcium-binding sites. Each of these sites contain negatively charged motifs that can bind to three Ca2+ molecules, thus strengthening the interactions between the extracellular domains  increased the E-cadherin levels in SW480 colon adenocarcinoma cells [Other conditions in the body can locally affect adherens junction integrity, leading to the development of IBD. Creatine kinases (CKs) are enzymes regulated by hypoxia-inducible transcription factors (HIFs), which fluctuate with oxygen concentrations. CKM and CKB have been shown to localize at the apical junctions, suggesting a role in regulating epithelial permeability in IBD ; however colitis . In the  colitis . Neverthma cells . Notablyma cells . Taken tBacteroides fragilis is one such microorganism that has a positive correlation with IBD patients, both in CD and UC [Candida albicans is a yeast species that has been shown to disturb the epithelial integrity of Caco2 colon epithelial cells by cleaving E-cadherin into an extracellular fragment and an intracellular fragment that acts as a substrate for γ-secretase  domain, promoting β-catenin signaling and stimulating proliferation in CRC cells, as confirmed by in vitro and in vivo studies [Fusobacterium nucleatum can mediate β-catenin signaling [Campylobacter jejuni, proteolytically cleaves E-cadherin through proteases secreted in outer membrane vesicles  . Impaire embryos . The eff embryos .Cells adhere to the ECM through integrins, which connect to the cytoskeleton and are mediators of extracellular signals. Integrins and the ECM have an intimate relationship with the AJs . IntegriE-cadherin has long been considered a critical homeostatic component of the colonic epithelium, primarily due to its central role in cellular architecture and barrier function. It has also been thought to primarily act as a tumor suppressor in CRC. However, numerous emerging roles of E-cadherin in intracellular signaling and cell behavior as well as its extensive cross-talk with the colonic epithelial microenvironment reveal a broader and more complicated role. Furthermore, the identification of new E-cadherin partners at the AJs add to the complexity, introducing new aspects and questions in cadherin biology. These recent findings portray E-cadherin and of the AJs as not merely structural components of cells and tissues but in new roles as signaling hubs, opening novel and exciting avenues of investigation.


Individuals from lower-socio-economic status (SES) communities have increased risk of developing obesity in developed countries such as Australia. Given the influence of the environment on dietary behaviour, this paper seeks to examine food environments in areas of differing social advantage. An established measurement tool (the NEMS—Nutrition Environment Measurement Survey), that captures aspects of support for healthy eating within restaurants (NEMS-R) and grocery/convenience stores (NEMS-S), was applied to both a high-SES and a low-SES suburb within Brisbane, Australia. The study found a significantly more supportive restaurant food environment in the high-SES suburb, with greater access to and availability of healthful foods, as well as facilitators for, reduced barriers to, and substantially more nutrition information for healthful eating. A higher number of outlets were found in the high-SES suburb, and later opening times were also observed. Overall, the results from stores (NEMS-S) suggest poor support for healthful eating across both suburbs. This study highlights how food environments in low-SES regions continue to be less supportive of healthful eating. Public health strategies must move beyond individual-focused strategies to ensure that our most disadvantaged, low-SES communities have an equal opportunity to access healthful foods. Obesity is a global epidemic . AustralThe food environment refers to the places individuals go to purchase and/or consume food and beverages. The consumer food environment (or consumer nutrition environment) considers what individuals encounter within a food outlet , and incReduced availability of healthful food items has been noted in outlets from low-SES communities, with healthful items given less shelf space and restaurant menus containing fewer healthful options than in high-SES communities ,17,25. IResearchers have called for further investigation to enhance the understanding of the food environment and its relation to socio-economic status ,31. Mostwww.med.upenn.edu/nems). The food environment has been measured in different ways, with the Nutrition Environment Measures Survey (NEMS), one of the most common instruments , known fp = 0.05) difference in a NEMS score of 5 points . To assess the food environment, the NEMS-R (for restaurants/takeaway outlets) and the NEMS-S (for grocery/convenience stores) instruments were used, as adapted for Australian metric measurements, common terms, and brands . AssessmStatistical analyses were performed using SPSS . Inter-rater and test–retest reliability was determined using kappa coefficients (κ) and percent agreement. Independent samples t-tests examined differences between suburbs for continuous variables, and chi-square tests and Fisher’s exact test were used for dichotomous variables.Enumeration was conducted in May 2016, with totals of 47 outlets (low-SES) and 83 outlets (high-SES) identified in each suburb. Random samples of 30 eating outlets (low-SES) and 35 eating outlets (high-SES) were drawn from the list enumerated in each suburb, providing a sufficient sample size for measurement with NEMS-R, with a buffer. A loss rate of approximately 10% had been identified in previous studies  ,20,39. Dx = 7.08) was below mid-range, and the mean NEMS-R score for the high-SES suburb (x = 20.38) was mid-range . NEMS-R scores can range from −24 to +63 for restaurants, meaning that the mean NEMS-R score for the low-SES suburb . No restaurant offered smaller portions at a reduced price .2 = 29.5, p < 0.001).Trading patterns were examined to determine whether accessibility differed between suburbs. There was no significant difference between the suburbs in whether outlets traded on each of the week days or weekend days, nor in the frequency of opening for the lunch time meal. However, a higher proportion of outlets were open for breakfast in the low-SES suburb compared to the high-SES on weekdays and weekends. The opposite was observed for the dinner meal, with more outlets open in the high-SES suburb. Closing time was later in the high-SES suburb, although more eating outlets were located in a shopping complex in the low-SES suburb, which may have constrained closing times . There was no difference between suburbs for the NEMS-S score or the sub-scores of availability and quality. However, the small sample size, and therefore the reduced power to detect a difference, must be acknowledged. Calculations indicate that a minimum sample size of 39 per group provides 80% power at α = 0.05 level to detect a mean difference of 5.5 (the difference we observed) with a standard deviation of 9.6 (the standard deviations that we observed), and our study did not achieve that sample size. There was one significant difference (p = 0.035) in the NEM-S pricing support dimension; the lower score in the high-SES suburb indicates less support, or a greater price difference between healthful and non-healthful alternatives in stores. Fruits and vegetables are not included in the pricing support comparison, as they are all considered healthful items, so a comparison of absolute price of these commodities was conducted. Not all stores stocked each variety, so only the most frequently found items were compared, and again the small sample size and reduced power to detect a difference raise concerns. Mean scores and suburb comparisons for the NEMS-S key elements are shown in Both suburbs provided a moderate amount of support for healthful eating. NEMS-S scores can range from −9 to +52 for restaurants, so the mean NEMS-S score for both suburbs was mid-range, or just below  scores were identified in the low-SES suburb for its total score and all sub-components. A larger sample is needed to confirm these findings, which contradict those of other studies that have consistently associated inferior food store environments with low-SES communities ,24,40,41This study contributes to the literature with an examination of the consumer environment within outlets. Few Australian studies have explored this; most have focused on the number of (un)healthful outlets, and have instead determined the healthfulness of a community based on the types of RFOs located in a suburb ,40. The While health education is critical, and has been shown to improve dietary behaviour , these fOf concern, low-SES consumers are frequently dependent on the food environment that surrounds them, with many of these communities lacking transport and transport infrastructure ,24,47,48This study measured support for healthful eating in the food environment, delivering evidence of low support for healthful eating. Further research is recommended to increase sample sizes across low-SES areas to ensure that definitive conclusions can be drawn from the findings obtained in the current study. This study acknowledges that other factors are associated with poor diet. In line with a call for a greater scope of analysis, future research is needed to develop tools that assess the supportiveness of the Australian food environment, regardless of ethnic diversity within those regions . Future A study that aims to track the food environment over a period of time is recommended, and is in line with the call for a wider research focus . SpecifiThis study explored differences between low- and high-SES suburbs in terms of support for healthful eating in retail food outlets that provide prepared meals, finding a greater level of support in the high-SES area. The tools used to assess these outlets were adequate across ethnically diverse environments; however, the equivalent tool for stores was not. Given the cultural diversity noticed in Australian communities, particularly low-SES communities, additional tools are needed. These findings have numerous implications for health in these communities and more broadly for society, and support a growing body of literature suggesting that healthful eating requires a supportive food environment.


Restless-Legs-Syndrome (RLS), also known as Willis-Ekbom disease, is a sleep- and rest related disorder characterized by the unpleasant urge to move the legs. Pharmacological therapy is mainly based on dopamine-agonists and delta-2-alpha calcium channel ligands. Also, randomized-controlled-trials (RCTs) reported effectiveness of oral oxycodone , and intrathecal opioids have also been administered for this indication. In the case reported here, a patient with advanced pancreatic cancer was referred to an acute palliative care unit for the treatment of cancer-related pain. Yet, in thorough exploration of her symptom burden, the patient reported that she felt her quality of life had been predominantly limited by symptoms other than cancer pain. Her medical history and neurological examination revealed that these symptoms were most obviously caused by severe RLS. In the years before, pharmacological therapies with dopamine-agonists and delta-2-alpha calcium channel ligands were initiated, but failed to relieve the RLS. In the palliative care ward, intravenous morphine was successfully titrated to treat her cancer pain. Concurrently, the patient also experienced almost complete relief from her RLS-symptoms and an increase in quality of life. The amelioration of her RLS-symptoms continued after morphine therapy was switched from intravenous to oral administration. Even after the patient was dismissed to home care and opioid rotation to transdermal fentanyl, symptom control of RLS remained excellent. To our knowledge, this is the first report of successfully treating RLS with intravenous and oral morphine. Since morphine is more easily available worldwide and the cost of morphine therapy is substantially lower compared to oxycodone/naloxone, comparisons to morphine may be an intriguing option for future RCTs. Restless-Legs-Syndrome (RLS), also known as Willis-Ekbom disease, is a sleep- and rest related disorder characterized by unpleasant sensations in the legs and the urge to move the legs, which may reduce the symptoms . RLS is If non-pharmacological interventions fail to relieve symptom burden, common pharmacological interventions include dopamine-agonists or an alpha-2-delta calcium channel ligand as first-line therapy . UnfortuAs a second-line approach, opioids have been used in clinical practice for years, but only a few placebo-controlled randomized trials have been conducted to prove their effectiveness. A recent phase III trial showed reduction of RLS-symptoms when patients were treated with oxycodone/naloxone , but theSeveral retrospective studies implicate other opioids -for example methadone , 8 and tA 75-year-old woman was admitted to our palliative ward with abdominal pain, nausea, and vomiting. The patient had been diagnosed with metastatic pancreas carcinoma with one singular liver metastasis 18 months before. She had received first- and second-line chemotherapy regimens; the latter had been stopped due to severe side effects. Two months prior to admission, when MRI scans revealed progressive disease, and together with her medical oncologist, the patient decided against continuing chemotherapy. Instead, symptom oriented, palliative care was chosen without any further antineoplastic therapy.The patient had been suffering from RLS for 12 years already, with moderate to strong symptoms [Numerical Rating Scale (NRS): 6-10/10] mostly in the evening and at night. The family history regarding RLS was not investigated. She reported symptom alleviation by long walks , and rigorous tennis playing, both of which she could no longer accomplish because of the progressive cancer related fatigue. Twelve years ago, her neurologist started treating RLS with levodpa, but after initial improvements in symptom control, symptoms began worsening again due to augmentation. Five years later, the patient was started on a transdermal application of the dopamine-agonist rotigotine (4 mg/d), but this treatment could not reduce RLS-symptoms satisfactorily. The patient reported that a trial of pregabalin was discontinued because of side effects (dizziness) and oxycodone was stopped because of nausea and vomiting. Thereafter transdermal rotigotine (4 mg/d) was continued with little effect until admission to our palliative care unit.To assess RLS-symptom burden and pain we used the 11-NRS, an established tool to assess pain and commonly used in the palliative care setting, where 0 = no pain and 10 = worst possible pain . We usedUpon initial admission, she reported abdominal cramps (NRS 8/10). Her temperature and blood pressure were normal with a heart rate of 100 bpm. The abdomen was distended, but soft with normal bowel sounds. The patient reported ubiquitous abdominal tenderness. The rest of the physical examination was normal. Initial laboratory testing included elevated gamma-glutamyl transferase at 194 U/l , lactate dehydrogenase at 364 U/L  and C-reactive protein at 42 mg/l . Bilirubin and lipase levels were normal. The peripheral-blood count was normal. An abdominal ultrasound dismissed possible bowel obstruction, hepatic cholestasis, and gall bladder abnormalities, but revealed a significant amount of ascites, which is why percutaneous ascites drainage was performed (3.5l). Cell counts in the ascites fluid revealed elevated neutrophils/μl indicating spontaneous bacterial peritonitis. Calculated antibiotic treatment was started with tazobactam/piperacillin.The patient also received intravenous fluids, analgesics  and antiemetics . At day 5 after admission the abdominal pain exacerbated. Symptomatic analgesia with intravenous morphine (20 mg/d) was initiated. Pain management was excellent after 1 day with a NRS of 0-3/10. Unintendedly, the patient also reported almost complete symptom relief regarding her RLS , which hWe report a case of a patient with advanced pancreatic cancer, treated with intravenous and oral morphine for cancer pain, who experienced markedly reduced symptom burden of her RLS-syndrome. While there are several publications reporting successful use of intrathecal morphine –12 and oA systematic review by Trenkwalder et al. on association of RLS with certain diseases could not identify increased prevalence in malignant disease, although MEIS1, the RLS gene most strongly associated with RLS risk in GWAS studies, is a transcription factor with implications in leukemia and neuroblastoma . To our The pathophysiology of RLS is poorly understood. Three main pathways seem to be involved: iron metabolism, dopaminergic dysfunction, and the central opioid system . Why areOur patient had previously been treated with the dopamine agonist rotigotine and levodopa. According to the practice guidelines, second line therapy should include delta-2-alpha calcium channel ligands such as gabapentin (level A recommendation) or pregabalin (level B) , 23. In A concern in the long-term use of opioids is addiction. While opioids are well-established in treatment of cancer-pain, in chronic pain their use is controversial and should only be considered under certain precautions . There iA patient with advanced pancreatic cancer experienced pronounced and sustained amelioration of RLS-symptoms by intravenous and oral morphine therapy and due to transdermal fentanyl therapy. In the literature no case reports or studies of oral or intravenous morphine or transdermal fentanyl against RLS could be identified. As morphine is more readily available worldwide and therapy costs of morphine are substantially lower compared to oxycodone/naloxone, randomized clinical trials are warranted to investigate the role of morphine in the treatment of RLS. Yet, in the non-palliative care population, thorough individual risk-benefit appraisal should be conducted for every patient before initiating opioid therapy due to safety issues concerning misuse (addiction) and potential immunosuppression.The patient provided verbal and written consent for use of the patient's personal health information in this case report.CB and JG wrote the manuscript. CB prepared the figure, and GB and KJ edited the final manuscript.JG has received research grants, speaker's fees and honoraria for advisory boards from several manufacturers of opioids. These include: Grünenthal, Mundipharma, Teva, and Sanofi-Aventis. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chronic lymphocytic leukemia (CLL) is characterized by an acquired immune dysfunction. CLL cells affect the phenotype and function of the entire spectrum of innate and adaptive immune cells, including monocytes, T cells, and natural killer (NK) cells, leading to a tumor-supportive environment and reduced immunosurveillance. Novel immunotherapies like immune checkpoint blockade, bi- and tri-specific antibodies, and chimeric antigen receptor (CAR) T cells use the patients’ immune system to induce therapeutic responses. Although these novel immunotherapies showed impressive results in several B cell lymphomas, responses in CLL were often disappointing. The strong immunomodulatory effect of CLL is believed to play a pivotal role in the low response rates to these immunotherapeutic strategies. In this review, we summarize how CLL influences the function of non-malignant lymphocytes, with a special focus on T and NK cells, two important cellular mediators for immunotherapy. Secondly, we provide a short overview of the activity of several immunotherapeutics in CLL, and discuss how novel strategies may overcome the disappointing response rates in CLL. A tandem antibody targeting CD16xCD30 showed promising clinical efficacy in refractory Hodgkin’s lymphoma . For CLLIn addition, the CD16xCD19 construct was modified further to include the stimulatory IL-15 cytokine, which resulted in significantly higher levels of NK cell proliferation and killing . These rAlthough the use of BiKE and TriKE constructs is in an early phase of clinical testing for CLL, the in vitro results of these constructs demonstrate high potential for CLL therapy.By far the best studied immunotherapeutic strategy for CLL in the last decade is the use of chimeric antigen receptor (CAR)-transduced T cells. Comprising an extracellular scFv fragment that recognizes a target antigen on tumor cells coupled to an intracellular tail containing T cell receptor (TCR) activation motifs and co-stimulatory domains, CAR constructs simultaneously redirect T cells toward tumor cells while inducing activating signaling and effector responses . Since aTET2 gene in transduced T cells (leading to a block in effector cell differentiation), which caused a clonal outgrowth of a highly effective CAR T-cell population within the patient, and ultimately led to the achievement of a delayed CR [The immunomodulatory environment of CLL is assumed to have an important role in determining the response to CAR T-cell therapy. This is demonstrated by the fact that reducing the tumor load before transfusion of CAR T cells with lymphodepleting agents was shown to improve responses to CAR T-cell therapy ,81. Sinclayed CR .Similar to the BiKE and TriKE constructs, CARs can be modified relatively easily to increase functionality of the transduced T cells. For example, the CD28 and 4-1BB co-stimulatory domains of second-generation CARs lead to distinct differentiation states, with the CD28 domain inducing effector-memory T cells, while the 4-1BB domain leads to the formation of central memory cells, making the latter probably better suited for CLL therapy . Third-gDespite the fact that NK cells retain cytotoxic function within the CLL micro-environment, the use of NK cells for CAR therapies is limited in CLL. This is probably related to several disadvantages NK cells have compared to T cells for CAR therapy. NK cell numbers are relatively low in peripheral blood, and NK cells are much more difficult to expand in vitro, making it hard to obtain enough autologous NK cells from each patient ,96. FurtHowever, the use of NK cells does have several advantages over the use of T cells. Firstly, the risk of development of cytokine release syndrome (CRS), the most serious side effect of CAR T-cell therapy , is consCD19 CAR-transduced NK-92 cells showed cytotoxic efficacy toward multiple B-cell lines . CAR NK These data demonstrate the potential of NK cells in CAR therapy for CLL. Multiple clinical trials are currently ongoing with CAR NK cells for other B-cell malignancies, using similar CAR constructs that are under investigation for CAR T-cell therapy. Future studies should continue to include CLL patients to determine the effectivity of CAR NK cell therapy in this disease, especially if response rates to CAR T-cell therapy are difficult to improve.fh and Treg cells, while also reducing T-cell exhaustion [In addition to their direct effects on CLL cells, several small-molecule inhibitors were reported to improve the function of non-malignant immune cells. Ibrutinib and venetoclax are two compounds associated with immune recovery in CLL patients ,105. Althaustion ,105. TheLenalidomide is an immunomodulatory drug that, despite inducing low levels of cell death in CLL cells, leads to therapeutic responses by restoring the function of the tumor micro-environment ,107. Lenreg cells in particular were found to be sensitive to idelalisib treatment, but effector T-cell differentiation and functionality were also affected [reg numbers and function is considered to be responsible for the long-term auto-immune mediated toxicity of idelalisib treatment in CLL patients, especially colitis, pneumonitis, and hepatitis [Phosphoinositide 3-kinase delta (PI3Kδ) inhibition by idelalisib does induce direct cell death in CLL cells, but inhibition of PI3Kδ also affects T cells. Taffected ,112. Theepatitis . A recenepatitis . This shreg numbers are decreased, and anti-tumor TH1 responses are increased [Another drug with well-documented effects on non-malignant immune cells is ibrutinib . Ibrutinncreased ,116. Altncreased . T cellsncreased ,68. Sincncreased . Ibrutinncreased ,78. In ancreased ,119. At ncreased .One aspect that may currently not receive sufficient attention is the potential of immunotherapy as consolidation therapy in CLL. As disappearance of the tumor clone ameliorates immunosuppression, effective treatment with small-molecule inhibitors like ibrutinib and venetoclax could open the door for improved responses to immunotherapy in tumor remission. This strategy could, on the one hand, lead to long-lasting remission and protection from relapse by immunotherapeutics, while, on the other hand, it could give the opportunity to stop treatment with small-molecule inhibitors, leading to decreased development of tumor escape mechanisms and possibly a reduction in treatment costs. An important issue in the development of such combined strategies is the timing of administering immunotherapy. Finding the right balance between inducing sufficient remission to restore anti-tumor responses while still having enough antigen present to induce effective immune responses should be addressed in clinical studies.Taken together, small-molecule inhibitors may play an important role in future immunotherapy in CLL by modulating tumor cells, the tumor micro-environment, and/or the cytotoxic effector cells. Future studies should further investigate the influence of small-molecule inhibitors on the non-malignant immune system, and evaluate the potential of different drug combinations for successful CLL therapy.As the requirements for optimal activity of immunotherapy become clear, response rates of CLL patients will continue to improve. Although T cells are currently on the forefront and were shown to be able to induce complete responses in some patients, CLL patients may benefit from the recruitment of NK cells into immunotherapeutic regimens, as these cells were shown to be less functionally impaired compared to autologous T cells. Furthermore, long-lasting immune protection by immunotherapy may also be induced by strategies combining treatment with small-molecule inhibitors, followed by immunotherapy as a consolidation treatment.The plethora of different strategies available fuels the belief that both T and NK cells can be used in an effective way to overcome the immunosuppressive tumor micro-environment and induce lasting therapeutic responses in, and possibly even cure CLL.


Acute kidney injury requiring dialysis (AKI-D) during hospitalization is associated with both in-hospital and post-discharge mortality. Its incidence has risen over time in Canada and the USA. While the majority of AKI-D will recover to dialysis independence at the time of hospital discharge, 10–30% will transition to outpatient dialysis. The risk factors that determine dialysis independence after AKI-D and its optimal outpatient management remain unclear. Eliciting prognostic predictors of kidney recovery in patients who remain on dialysis after hospital discharge will guide subsequent clinical decision making. The objective of this study is to assess the association between patient- and treatment-related factors with short- and long-term outcomes in patients who remained dialysis-dependent after hospitalization with AKI-D.A literature search in EMBASE, MEDLINE, and PubMed will be performed based on pre-specified criteria. There are no restrictions on language and publication dates. The supplemental search will include manual scan of bibliographies of eligible studies and grey literature assessment. Pre-specified criteria will be used to select eligible studies. Relevant data will be extracted and quality assessments performed per validated tools. Qualitative data synthesis will be performed to reflect directions of associations. Meta-analysis will be formed if two or more studies with similar prognostic factors, outcomes, and adequate quality are identified. Strength of association will be quantified as odds ratios. Reporting of this review will be guided by recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.This systematic review aims to synthesize association between modifiable and non-modifiable prognostic factors with renal outcomes in AKI-D patients who remain dialysis-dependent after hospital discharge. Our findings will help inform the development of evidence-based management and guide long-term treatment planning for AKI-D patients.CRD42019127394.PROSPERO registration number  Acute kidney injury requiring dialysis (AKI-D) occurs in 1–2% of hospitalized patients . A retroAn improved understanding of predictors of kidney recovery to dialysis independence in outpatients who require ongoing dialysis after a hospital encounter with AKI-D (as well as the gaps in knowledge in this area) can improve patient-centered decision-making and clarify the need for further research in this area. For patients unlikely to have kidney recovery, earlier and better-informed decision-making regarding long-term arteriovenous access, home therapies, and transplantation would be facilitated. This could improve patients’ quality of care; improve access, integration, and utilization of chronic kidney disease system resources; and improve access to transplant and home dialysis. For caregivers of patients more likely to recover, frequent assessment for recovery and strategies to limit further kidney damage  may facilitate shorter recovery times and increase the likelihood of recovery to dialysis independence. Lastly, a better understanding of the risks of death and dialysis dependence would help patients navigate their options regarding palliative/conservative care after having gained some experience as to what is involved in undergoing maintenance dialysis in the outpatient setting.The optimal outpatient management of AKI-D patients remains uncertain. Currently, no evidence based-guidelines exist for the best management of AKI-D patients in order to optimize kidney recovery , 2. ManyAll studies that have reported on predictors of kidney recovery and clinically relevant outcomes (listed below) in AKI-D patients requiring post-hospitalization dialysis are eligible. These studies must present predictive/prognostic factors from baseline to follow-up period. In addition, studies must be full-text, peer-reviewed articles. This review will include both observational and interventional studies. Case reports or case series of less than or equal to 10 patients will be excluded. No restrictions will be placed on the study duration, study period, or date of publication. Studies must have analyzed potential predictors of kidney recovery in AKI-D patients who remain dialysis-dependent after hospital discharge. Only original peer-reviewed literature will be included. Studies published in all languages will be included. In addition, the following criteria must also be met:Patient populations: Patients 18 years or older with acute kidney injury treated with dialysis of any type during a hospitalization who transition to outpatient dialysis after hospital discharge. Those with pre-existing end-stage renal disease defined as estimated glomerular filtration rate (eGFR) < 15 ml per minute per 1.73 m2 prior to hospitalization will be excluded.Variables of interest or predictive factors: Any independent variable examined for potential prognostic ability will be included. We will begin with a broad study approach that spans a variety of prognostic factors which will subsequently be grouped into relevant domains. Potential domains include demographics , hospitalization-related factors , ward versus intensive care unit admission, duration of hospitalization, urinary output at the time of hospital discharge), and treatment-related factors including modality of RRT initiated in hospital and characteristics of RRT after discharge.The primary outcome of interest in this systematic review is kidney recovery to dialysis independence within 90 days after hospital discharge. This time interval is regarded as the threshold at which most patients would be considered to have reached end-stage renal disease . The secclinicaltrials.gov, and screening for relevant titles in the first three pages of the Google Scholar search. Relevant articles will be screened at two levels: title/abstract then full-text screening, by two reviewers (CW and EC) in the systematic review software, Covidence .No prior published studies that addressed similar topics were found in PubMed, MEDLINE (via Ovid), and EMBASE (via Ovid). Similar systematic review study protocols have not been registered on PROSPERO. A health sciences librarian (LS) searched the following databases: MEDLINE and MEDLINE in Process (via OVID), Embase Classic + Embase (via OVID), Cochrane’s Central Registry for Randomized Controlled Trials, CENTRAL (via OVID), and PubMed. Appendix Relevant data will be extracted from Covidence  and managed with Microsoft Excel. Data will be synthesized with the Comprehensive Meta-Analysis  software.Two investigators (CW and EC) will independently screen relevant study titles and abstracts per pre-specified criteria to determine their eligibilities for full-text assessment. The same investigators will subsequently examine the full texts of the selected studies according to the inclusion and exclusion criteria. Relevant studies published in English or French will be included. Disagreements will be resolved with discussion until consensus is reached. A PRISMA diagram will be generated to document the study selection process .Patient demographics: age, gender, ethnicity.Patient comorbidities: baseline creatinine (if available), pre-existing chronic kidney disease, diabetes, congestive heart failure, etc.Hospitalization-related factors: etiology of acute kidney injury, volume status at initiation of RRT, ward versus intensive care unit admission, duration of hospitalization, urine output at the time of hospital discharge.Treatment-related factors: modality of RRT initiated in hospital, characteristics of outpatient RRT after discharge.Investigated independent variables/predictors:Outcomes: kidney recovery after hospital discharge, mortality at any time point after hospital discharge, progression to end-stage renal disease with transition to long-term RRT, eGFR at the time of kidney recovery, time from hospital discharge to kidney recovery, and kidney transplantation.Study characteristics: author, publication year, number of study participants, type of study (research design), and duration of follow-up.A data extraction form will be created and populated with the following information:The qualities of reporting and risk for bias of each included study will be appraised using validated tools. Prognostic studies that meet the inclusion criteria will be assessed for internal validity with the Quality In Prognostic Studies (QUIPS) tool . The quaA narrative synthesis will be performed to reflect directions of associations between prognostic factors and outcomes of interest. These associations will be reported as positive, negative, or none for each domain of risk factors.I2 test will be used to examine the statistical heterogeneity between studies [Meta-analyses will be performed if the data is appropriate for quantitative synthesis. Minimum of two studies is required to provide data of the same prognostic factors pertaining to outcomes of interest to permit data pooling and synthesis. The strength of association between identified prognostic factors and outcomes will be quantified as odds ratios for each outcome of interest. Cochran’s Q and the  studies . Publica studies . StatistAny amendments to the protocol will be outlined in an addendum made to specify and justify changes. These modifications and their justifications will also be included in the final report.AKI-D during hospitalization is a frequent occurrence and is associated with poor outcomes. To date, there is a paucity of data on the epidemiology and outcomes of patients with AKI-D who remain dialysis-dependent at hospital discharge. Our proposed systematic review will synthesize what is known about the association of patient and treatment-related factors with short- and long-term outcomes in this population. We hope to shed light on modifiable prognostic factors that influence renal outcomes. The results could help inform the development of evidence-based clinical decision-making both during and after hospitalization of AKI-D patients in addition to guide patient counseling and navigate long-term care planning.


Background: Agoraphobia was described in 1871 as a condition of fear-related alterations in spatial orientation and locomotor control triggered by places or situations that might cause a patient to panic and feel trapped. In contemporary nosology, however, this original concept of agoraphobia was split into two diagnostic entities, i.e., the modern anxiety disorder of agoraphobia, consisting solely of phobic/avoidant symptoms in public spaces, and the recently defined vestibular disorder of persistent postural perceptual dizziness (PPPD), characterized by dizziness, and unsteadiness exacerbated by visual motion stimuli. Previous neuroimaging studies found altered brain activity and connectivity in visual-vestibular networks of patients with PPPD vs. healthy controls. Neuroticism and introversion, which pre-dispose to both agoraphobia and PPPD, influenced brain responses to vestibular and visual motion stimuli in patients with PPPD. Similar neuroimaging studies have not been undertaken in patients with agoraphobia in its current definition. Given their shared history and pre-disposing factors, we sought to test the hypotheses that individuals with agoraphobic symptoms have alterations in visual-vestibular networks similar to those of patients with PPPD, and that these alterations are influenced by neuroticism and introversion.Methods: Drawing from the Human Connectome Project (HCP) database, we matched 52 participants with sub-clinical agoraphobia and 52 control subjects without agoraphobic symptoms on 19 demographic and psychological/psychiatric variables. We then employed a graph-theoretical framework to compare resting-state functional magnetic resonance images between groups and evaluated the interactive effects of neuroticism and introversion on the brain signatures of agoraphobia.Results: Individuals with subclinical agoraphobia had lower global clustering, efficiency and transitivity relative to controls. They also had lower connectivity metrics in two brain networks, one positioned to process incoming visual space-motion information, assess threat, and initiate/inhibit behavioral responses  and one positioned to control and monitor locomotion . Introversion interacted with agoraphobic symptoms to lower the connectivity of the visuospatial-emotional network. This contrasted with previous findings describing neuroticism-associated higher connectivity in a narrower visual-spatial-frontal network in patients with PPPD.Conclusion: Functional connectivity was lower in two brain networks in subclinical agoraphobia as compared to healthy controls. These networks integrate visual vestibular and emotional response to guide movement in space. Agoraphobia (fear of the marketplace), was first described by the German neuroscientist C.F. Westphal in 1871 as a syndrome of altered spatial perception, cognitive distortions about safe locomotion, and fear-driven limitations of mobility , and theSeveral lines of evidence suggest a shared pre-disposition and partially overlapping clinical manifestations of agoraphobia and PPPD. For example, the personality traits of neuroticism and introversion may be associated with both conditions. A study of twin siblings found independent genetic contributions of neuroticism and introversion to agoraphobia . StudiesGiven their shared history and the overlapping clinical features, it is possible for agoraphobia and PPPD to share underlying brain mechanisms. Neuroanatomical studies identified extensive connections between vestibular and anxiety systems, extending from the brainstem to the cortex , and funThe structure and function of brain regions that comprise the multimodal visuo-vestibular network have been studied in patients with PPPD and its precursors using various neuroimaging methods –44. In sThe brain mechanisms presumed to underlie agoraphobic anxiety have been described extensively , 47. In In this study we aimed to explore the functional brain connectivity signatures of sub-clinical agoraphobia through a graph-theoretical framework applied to task-free functional MRI in a group of healthy participants selected from the database of the Human Connectome Project (HCP) . The exthttp://www.humanconnectome.org/documentation/S1200/). Due to the dominance of the right hemisphere representation of the vestibular function in right-handed individuals (and of the left hemisphere in left-handers) .We used rsfMRI data from the S1200 HCP data release, which comprises MRI data and psychological assessments from 1,003 healthy volunteers (handers)  we selechanders) , to avoihanders)  in agreehanders) . Fear-sohanders) , 57 and handers) , respecthanders) . Perceivhanders)  and on tn = 1,003 HCP database; (ii) for each sample, group-wise comparison (against the agoraphobia group) of mean values (Mann-Whitney U-Test for continuous variables and Chi-Squared test for dichotomous variables) and variances (Brown Forsythe test) for all matching variables, and (iii) acceptance of the first “matched” sample of 52 healthy subjects when all resulting p-values (19 comparisons for both means and variances) were p ≥ 0.05 , presence of psychiatric disorders , and personality scores . The matching procedure was as follows: (i) repeated random sampling (with replacement) of 52 non-agoraphobic subjects from the whole , resolution  = 2.0 × 2.0 × 2.0 mm3, Multiband factor = 8, bandwidth = 2290 Hz/Px).Within HCP scanning procedures, fMRI data were acquired on a Siemens Skyra 3T in four runs of ~15 min each, through a Gradient-echo EPI sequence  is obtained through regression and therefore defined over the whole brain, there is a steep roll-off in areas which are mostly related to other components. In order to highlight the brain areas which are dominant/unique in each component, for visualization and description purposes in this paper we thresholded each map at the 98th percentile. For analysis, we employed the individual adjacency matrices computed by the HCP consortium based on group-PCA at dimensionality 100. These which were based on partial correlation coefficients between node timeseries (“netmats2”). The graph representation of each adjacency matrix therefore comprised 100 nodes. Each node can be considered a resting state network in itself [see e.g.,  are calculated by averaging over all nodes, while transitivity is defined for the whole graph. The clustering coefficient of a node estimates how much a single node tends to aggregate, through edges , with its nearest neighbors. Transitivity is a variant of the clustering coefficient in which a network-wide normalization strategy mitigates the influence of outliers  on the clustering coefficient. Local efficiency is a similar measure, which estimates, in each location within the graph, how well a node's neighbors can exchange information when the node itself is removed . All graph-theoretical measures were computed via the Brain Connectivity Toolbox (https://sites.google.com/site/bctnet/). In addition, given that no consensus exist on thresholding strategies before computing graph-theoretical computations, we repeated the main analyses after thresholding all adjacency matrices at 50% density.After matching, in all adjacency matrices negative correlations were set to zero. For each subject matrix, we calculated node-wise, local graph metrics quantifying the centrality of a node within a network , its ability to transmit information at local level , its integration or segregation properties (clustering coefficient), and its overall influence in a network  . Similar Toolbox  (https:/U test. Results were corrected for multiple comparisons across the number of nodes (100) using an FDR approach at p < 0.05. Whenever a significant group effect was found , we separately tested the interaction of agoraphobia and anxiety-related personality traits (neuroticism and introversion) using a general linear model which included group, trait and group*trait interaction. Additionally, whenever a significant group effect was found in local graph metrics in a certain node , we separately ranked the adjacency matrix elements for the agoraphobic and control group in order to identify, for each group, nodes with greatest overall connectivity to the rest of the brain.All metrics were compared between groups  through the non-parametric Mann-Whitney p = 0.01, 0.01, and 0.02, respectively, Mann-Whitney U test)  with significant lower local clustering coefficient and efficiency in subjects with agoraphobic symptoms vs. matched controls. These extended across multiple cortical regions.Globally, we found lower clustering coefficient, efficiency and transitivity in the agoraphobic group compared to the matched control group ( U test) . These rpcorr = 0.0002) and efficiency (pcorr = 0.0003) of this network were both lower in the agoraphobic than control groups  was lower in subjects with agoraphobic symptoms compared to controls , primary somatosensory and motor cortex , pre-motor cortex (6d), medial SPL, cingulate cortex , and rostral hippocampus  and local efficiency (pcorr = 0.023) in visuospatial-emotional network (node number 23) as compared to controls. In addition, in subclinical agoraphobia the local clustering coefficient was lower  also in the vestibular-navigational network (node 41).These results were confirmed when using matrices thresholded at 50% density. In this case, individuals with subclinical agoraphobia were found to have lower clustering coefficient (p's > 0.6) or neuroticism  on graph theoretical-metrics. In the visuospatial-emotional network, however, introversion interacted significantly with the main effect of agoraphobia to reduce the clustering coefficient and efficiency of subjects with agoraphobic symptoms compared to controls   . Thus, ip = 0.012) and clustering coefficient (p = 0.009) were significantly affected by the interaction of agoraphobic group and introversion.These results were confirmed when using matrices thresholded at 50% density. Also in this case, in the visuospatial-emotional network both local efficiency , link them to vestibular and somatosensory inputs , and use this information to plan and initiate or inhibit locomotor commands  in response to desires and threats in the environment . However, the lower level of efficiency and clustering of this network suggests that patients with sub-clinical agoraphobic symptoms may not incorporate all of this information into high level management of their behaviors, but perhaps react more instinctively to agoraphobic stimuli. The fact that introversion further reduced efficiency and clustering of this network raises the possibility that individuals with this personality trait are even more strongly driven by innately determined reactions to agoraphobic stimuli.The vestibular-navigational network encompassed core regions of the multimodal vestibular cortex in the parietal operculum bilaterally plus areas of the primary somatosensory cortex, motor cortex, pre-motor cortex, cingulate and hippocampus. This suggests a pre-dominant role on the output side of locomotor control. The vestibular-navigational network is well-positioned to control (motor and pre-motor cortices) and monitor (somatosensory and vestibular cortices) movements in space (hippocampus) and compare intended to actual outcomes (cingulate cortex). The lower level of clustering of this network corroborates the fact that agoraphobic stimuli are salient for networks that are dedicated to control of movement in space.Spatial and navigation systems are characterized by a high degree of redundancy. Detection of movement of self is supported by the multimodal nature of the vestibular cortex in which vestibular signals, somatosensory inputs, and optic flow all provide information about self-motion . DetectiThe visuospatial-emotional and vestibular-navigational networks identified in patients with sub-clinical agoraphobia have comparable, though not identical, counterparts in patients with PPPD. Studies using sound-evoked vestibular stimuli found reduced activity and connectivity in a network encompassing the parietal opercula, posterior insula, posterior superior temporal sulcus, superior parietal cortex and motor vestibular regions in patients with chronic subjective dizziness, a PPPD precursor, compared to healthy controls . This isTaken together with previous neuroimaging work on PPPD and its precursors –45, the The investigation of a cohort of individuals with subclinical agoraphobic symptoms may be considered a strength and a weakness of study design. On the positive side, we were able to study the neural correlates of visual space-motion processing in our subjects without the potential confounds of serious panic/phobic symptoms. On the negative side, our findings are limited to sub-threshold symptoms and may not apply to patients with fully developed diagnoses of agoraphobia. This limitation is mitigated by the observation of other investigators that agoraphobic symptoms lie on a continuum from normal to pathological levels ; that ishttp://www.humanconnectome.org/.Publicly available datasets were analyzed in this study. This data can be found here: Data were provided by the Human Connectome Project, WU-Minn Consortium .II and NT managed the overall project . AC performed graph metric calculations. AC and NT performed statistical analysis. II, AC, and NT prepared the original draft, critically reviewed the manuscript, and approved the final manuscript as submitted. JS, FL, and LP provided methodological perspective on the study, critically reviewed, and edited the initial manuscript and approved the final manuscript as submitted. All authors contributed to manuscript revision and editing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Through their syntactic positions, pauses connect to the thoughts expressed. We investigated whether disturbances of thought in schizophrenia are manifest in patterns at this level of linguistic organization, whether these are seen in first degree relatives (FDR) and how specific they are to formal thought disorder (FTD). Spontaneous speech from 15 participants without FTD (SZ-FTD), 15 with FTD (SZ+FTD), 15 FDRs and 15 neurotypical controls (NC) was obtained from a comic strip retelling task and rated for pauses subclassified by syntactic position and duration. SZ-FTD produced significantly more unfilled pauses than NC in utterance-initial positions and before embedded clauses. Unfilled pauses occurring within clausal units did not distinguish any groups. SZ-FTD also differed from SZ+FTD in producing significantly more pauses before embedded clauses. SZ+FTD differed from NC and FDR only in producing longer utterance-initial pauses. FDRs produced significantly fewer fillers than NC. Results reveal that the temporal organization of speech is an important window on disturbances of the thought process and how these relate to language.Everyday speech is produced with an intricate timing pattern and rhythm. Speech units follow each other with short interleaving pauses, which can be either bridged by fillers ( An altered speech rhythm can thus reflect and illuminate disturbances of the thought process. People with schizophrenia have been found to differ from neurotypical controls in terms of a greater number of pauses, proportion of silence, total length of pauses, and mean pause duration, in a reading task  vs. between 1–3 secs. [long]) were annotated. Third, fillers were tagged according to the same three syntactic positions  total number of utterance-initial unfilled pauses/total utterances, (b) within-clause pauses/total clauses, and (c) unfilled pauses before embedded clauses/total embedded clauses , age, and education varied across groups, we ran covariance analyses for two main variables  to explore the effect of group on the production of unfilled pauses/fillers controlling for the effects of IQ, age, and education. For unfilled pauses/total utterances, which were normally-distributed, an analysis of covariance (ANCOVA) with Bonferroni ariance,  with theFor the remaining variables, non-parametric tests, including Mann-Whitney U pairwise comparisons  were used with Bonferroni correction. A Bonferroni correction was applied by dividing the alpha value by the number of group comparisons. The threshold was set at .008. Since the covariant analyses of unfilled/fillers did not reveal main effects of general cognition (IQ), age, and education, further covariant analyses for the remaining variables were not computed.The proportion of all dysfluency variables did not distinguish groups  ; and why, (iii), similarities appear between SZ+FTD and SZ-FTD only when the ‘long’ utterance-initial pauses (between 1 and 3 seconds) are considered. Taking these questions in turn, the clause is the smallest unit that maps onto a complete thought, in the sense that it can carry propositional information, for which minimally a subject and a predicate are required [involves these elements and the configuration in which they occur. Regarding the second and third questions, the two key facts are that patients with FTD show a speech rhythm pattern distinguishable from that of neurotypical controls only in utterance-initial ‘long’ unfilled pauses and distinguishable from patients without FTD only before embedded clauses. This pattern can be summarized by saying that SZ+FTD shows sensitivity to the same syntactic positions, but differs from controls only when duration is considered, with differences showing only in the long utterance-initial pauses. Although this pattern depends on the pragmatic choice we made in distinguishing ‘short’ and ‘long’ pauses, with a cut-off at the 1s boundary, while not coding pauses less than 250ms and more than 3s, the pattern is intriguing. In response, we offer the following speculation. As noted, pausing in speech is an inherent element of mental health, sustaining a thought process as a previous utterance is moved out of the workspace and a new unit of thought is internally configured so as to be generated next. SZ-FTD thus appear to suffer from a disruption in this intermittent loop, with empty gaps  in the thought process appearing, in positions where such thoughts are to be generated for production. We suggest that SZ+FTD may suffer from the same impairment, since significant differences from neurotypical controls in unfilled pauses show at least partially in the same syntactic positions . Yet, in traditional terms, patients with FTD also exhibit the symptom of ‘loosening of associations’: The latter may not allow this pattern of gaps to be seen in ‘short’ pauses, since an insufficiently controlled (‘loosened’) thought process leading to seemingly ‘unplanned’ and incoherent utterances may cover up such gaps, as long as they are short. Hence, while short gaps become undetectable, the thought disorder still shows in speech rhythmic patterns, yet now only when real gulfs are opening. That SZ+FTD significantly differed from SZ-FTD in pausing before embedded clauses may relate to the same loosening, as well as to embedded clauses being produced less by patients with FTD than without [The pattern of empty pauses reported here raises three main questions: (i) what is the significance of the clause and utterance boundaries; and (ii) why this pattern is mostly confined to people with SZ required . The res without .We also predicted that fillers would be produced less by patient groups than by non-clinical groups. Our results showed no evidence for this, insofar as neither differences between the SZ groups, nor between clinical and non-clinical groups reached significance after Bonferroni correction, unlike in previous studies of fillers in SZ , 22. By Results of the covariant analyses suggest that the pattern of fillers as well as unfilled pauses (when indexed to syntactic positions) in our patient groups are not linked to IQ, age, or education, which is unlike in other domains of language, where such correlations have been found , 40. TheOverall, this study has laid new groundwork for investigating alterations of the thought process that defines schizophrenia at the level of speech rhythm, highlighting the significance of clausal units and the utterance boundary and thereby specific forms of grammatical complexity and meaning exhibited. The units in question and their temporal organization in speech are inherently linked to the normal thought generation process. Speech generation and timing provide a window into this process and an objective basis for tapping into how it can be disturbed.S1 FileTable A. Number of neurotypical controls (NC), first degree relatives (FDR), and participants with (SZ+FTD) and without formal thought disorder (SZ-FTD) for psychotropic medication.Table B. Speech dysfluency patterns.Table C. Statistical significance for possible between-group differences in speech dysfluencies.Table D. Pairwise comparisons of unfilled pauses/total utterances over covariants of IQ, age, and education by neurotypical controls (NC), first degree relatives (FDR), participants with FTD (SZ+FTD), and without FTD (SZ-FTD) in univariate analysis of variance.Table E. Pairwise comparisons of residuals of fillers over covariants of IQ, age, and education by neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD), and without Formal Thought Disorder (SZ-FTD) in one-way analysis of variance.Table F. Pairwise comparisons of neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD), and without Formal Thought Disorder (SZ-FTD) on the production of utterance-initial pauses in the Mann Whitney U Test.Table G. Mean (M) and Standard Deviation (s.d.) for within-clause pauses with and without consideration of length.Table H. Pairwise comparisons of neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD), and without Formal Thought Disorder (SZ-FTD) on the production of pauses before embedded clauses with and without length in Mann Whitney U Test.Table I. Pairwise comparisons of neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD), and without formal thought disorder (SZ-FTD) on the production of fillers and their syntactic positions in the Mann Whitney U Test.Table J. Mean (M) and Standard Deviation (s.d.) for within-clause fillers and fillers before embedded clauses.Figure A. Average number of dysfluencies including both unfilled and filled pauses across neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).Figure B. Average of number of unfilled pauses across neurotypical controls (NC), first-degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).Figure C. Average number of utterance initial unfilled pauses across neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).Figure D. Average number of within-clause unfilled pauses across neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).Figure E. Average number of embedded clause unfilled pauses across neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).Figure F. Average number of filled pauses across neurotypical controls (NC), first degree relatives (FDR), participants with (SZ+FTD) and without thought disorder (SZ-FTD).(DOCX)Click here for additional data file.


Bacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer.Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA’s memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei.We introduce PanACEA  contains supplementary material, which is available to authorized users. Streptococcus agalactiae demonstrated that many more isolates are needed to capture strain diversity and helped define the concept of the bacterial pan-genome: the set of genes (core and variable) that are encoded within a bacterial species [Next-generation sequencing technologies and a realization that single reference genomes are insufficient to grasp species-level diversity have resulted in a phenomenal rise in the number of publicly available bacterial genome sequences. A comparison of just six strains of  species . Tools h species –10. Chan species . It is t species  and prov species .To facilitate the interpretation of results for biological discovery, visualization tools have been developed, but still suffer from a number of caveats. A subset of pan-genome visualization tools are web-based , but only work with pre-computed and/or static data and do not allow user-supplied sequence data –17. Pan-Pan-genome Atlas with Chromosome Explorer and Analyzer), an open source standalone computer program written in PERL that generates locally-computed (client side) JavaScript-driven interactive web-pages to view pan-chromosome data generated by PanOCT [Here we introduce PanACEA , Mozilla Firefox (v 58.0.1), Apple Safari (v 11.0.3), and Internet Explorer/Edge (v 11.0.9600.18816/38.14393.1066.0). The scripts also use the MSAViewer  to displhttps://sourceforge.net/projects/panoct/). An example dataset consisting of the PanOCT and gene_order.pl derived pangenome of 19 Acinetobacter baumannii genomes along with GO term and ARO term based gene annotations is also available at the PanACEA GitHub repository.PanACEA uses PERL scripts and a tab-delimited human-readable flat file that contains the following necessary information for the script to generate platform-independent visualizations: the gene order of the pan-chromosome “assemblies”, including the flexible and core regions (such as output of gene_order.pl ); detailBeyond generic input requirements, PanACEA is highly configurable, allowing for customization of input features specific to the needs and available data of the researcher. Additional information, such as that describing the functionality of the genes or the relationship between genomes, can be incorporated Fig. . Any funThe PanACEA interface enables the interactive exploration of pan-genomic data through multiple spatial views, from broad pan-chromosome/scaffold context through multi-gene regions to single gene details  and encodes metabolic pathways historically used to define phenotypic differences between E. hormaechei subspecies  as the sole carbon source via the gat operon [E. hormaechei subsp. oharae and subsp. steigerwaltii both encode a different fGI (the aga operon) for the metabolism of N-acetylgalactosamine [The biological utility and output of PanACEA is illustrated using the bspecies . The timbspecies , 25. Allt operon . In conttosamine  E. coli genome pan-chromosome has almost twice as many fGR paths compared to a 219 E. hormaechei genome pan-chromosome and showed relative increases in time and memory usage. However, this increase is limited to a few minutes in terms of the CPU and a few gigabytes in terms of memory usage.The memory and time usage required by the PanACEA scripts to run does not exceed the capabilities of most laptops, as shown in Additional file The modularity of PanACEA also allows for more functionality to be added. Further possible functions that can be included in future versions of PanACEA may include: multiple region views where genomes can be compared across neighboring fG and Core regions; additional gene annotation on the core region images, such as three letter gene names; graphs and text demonstrating the prevalence of different gene order and gene prevalence in clusters of genomes with the available metadata; and finally, to write additional scripts to transform the output from other pan-genome tools such as Roary  so that PanACEA is an interactive visualization tool that leverages bacterial genomic data for the analysis of pan-genomes in the context of a consensus pan-chromosome. Its browser interface displays customizable annotation features such as the anti-microbial resistance and gene ontologies, which expedite the point-and-click exploration of pan-chromosomes when compared to text files and previous visualizations that lacked contextual browsing of variable regions. Its hierarchical design enables the navigation of both detailed and high level views of the data. The search and zoom functions permit users to identify genes and regions of interest and view these regions in the context of the full pan-chromosome, zoomed in close, or in the detail views in another window, as shown in our use case. PanACEA is database independent and browser agnostic, easy to install, and works off generalized flat files promoting interoperability across pan-genome software.Project name: PanACEA.Project home page:https://github.com/JCVenterInstitute/PanACEA/Operating system(s): Platform independent.Programming language: PERL, HTML, Javascript.Other requirements: PERL v5.22.1, BioPerl v1.007001.License: GNU GPL.Any restrictions to use by non-academics: none.Additinal file 1:Table S1. Memory and CPU time requirement of multiple PanACEA runs on a 2.3GHz Linux VM. Figure S1. PanACEA HTML page flowchart. (DOCX 22 kb)


Cancer cells contain numerous mutations in the genome that are present in most or all malignant cells of a tumor. While not all mutations are significant for cancer progression, a subset of them, often termed driver mutations, have presumably been selected because they confer a distinctive fitness advantage for malignant cells in a heterogeneous tumor microenvironment ,2. CorreTwo disciplines are beginning to emerge to address the void left in tackling these challenges: (1) multiscale cancer modeling on the basic cancer biology front addresses the need for building quantitative models at multiple length and time-scales in characterizing the underlying complexity in cancer signaling at the molecular, cellular, and tissue length-scales ,10; (2) Network analyses enable us to identify underlying patterns in a programmatic fashion and enable us to formally postulate functional relationships such as between gene expressions, transcription factor activation, as well as propose mechanisms of activation of cell signaling pathways . A suiteinvolves identification of interaction motifs such as feedback or feed forward loops, methods to infer bistability and robustness, construction and curation of Boolean networks and directed graphs using statistical inference techniques, information theory, and Bayesian analysis .involves applying dimensionality reduction techniques such as principal component analysis, hierarchical clustering and tree constructions, differential equation based kinetic modeling, rules-based modeling, stochastic and Monte Carlo based modeling of network dynamics .provides the means for constructing models of intra- as well as inter-cellular signaling networks with the ability to encode the resolution of molecular decisions at key nodes ,14–16. IBeyond the modeling of intracellular signaling pathways, spatially regulated membrane-mediated phenomena such as cell adhesion and motility and intracellular trafficking are implicated in cancer progression. For example, altered endocytosis has been postulated as a mechanism by which malignant cells are able to generate hyper-proliferative signals (by modulating receptor tyrosine kinase activity), or decreased cell-adhesion and increased motility  ,20. The in silico i.e. on the computer. Additionally, it is a platform for simulating, investigating, better understanding and exploring the spatiotemporal natural phenomenon of cancer, facilitating the development of new treatment strategies, supporting the design and interpretation of clinico genomic trials and finally training doctors, researchers and interested patients alike. Imaging, histological, molecular, pharmacogenomic, clinical and treatment data at various time points constitute the main input of the Oncosimulator. A successful completion of its clinical adaptation, optimization and validation process currently under way is an obvious prerequisite for the clinical translation of the Oncosimulator.The ability to predict how small perturbations in molecular structure can lead to profoundly altered intracellular signaling pathways and subsequent cell-fate decisions is also crucial for predicting clinical outcome of cancer progression or efficacy of inhibition. In particular, the approaches summarized above enable the rationalization and prediction of the role and nature of molecular variability in networks by bridging the gap between molecular resolution/context, intracellular signaling, and pathway/target/biomarker validation personalized to the molecular profile/alterations in the individual patient. One viable mechanism for implementing these multiscale techniques to directly relate to the clinical setting is to create hyper-models, which are optimal and robust and can be used for predicting a physiological or a pathological function. Cell biology, histology, biomechanics, pharmacokinetics, pharmacodynamics, and radiobiology are some of the disciplines that are recruited in order to rationally link the molecular scale to the clinical one in the patient individualized context. Advanced mathematical, computational and visualization techniques play a crucial role in this endeavor. Such a hyper-model based decision support and treatment-planning system is the Oncosimulator –28. The The model predictions can be validated against multiscale clinical data in different cancer types. This vision brings to bear an in-silico platform, one that will allow clinicians and researchers alike to readily navigate within the heavily multidimensional space of multiscale data of each patient, to easily comprehend it, to run model simulations in silico, and finally to design treatment in the most scientifically grounded, quantitative and patient individualized fashion. This vision for in silico oncology represents a paradigm shift in medicine. The integrated computational and clinical considerations is also expected to improve interoperability of biomedical information and knowledge, increase the acceptance and use of realistic, clinically driven and oriented and validated models allowing researchers from different disciplines to exploit, share resources and develop new knowledge and improve accessibility to existing knowledge by bio-medical researchers. This need for multidisciplinary and integrated research is being fostered by several large-scale program projects such as the United States National Institutes of Health-funded Physical Sciences in Oncology Centers (PSOC), Integrative Cancer Biology Program (ICBP), Tumor Microenvironment Network (TMEN) , 30,31, In Silico Oncology” (FP7-ICT-2011–9-600841). We also acknowledge funding for this work from US National Science Foundation Grants CBET-0853389 and CBET-0853539. Computational resources were available partly through US extreme science and engineering discovery environment (XSEDE) through a supercomputing resource allocation grant.The research leading to these results has received funding from the European Commission under the projects “ACGT: Advancing Clinico genomic Trials on Cancer” (FP6–2005-IST-026996), “Contra Cancrum: Clinically Oriented Translational Cancer Multilevel Modeling” (FP7-ICT-2007–2-223979), “TUMOR: Transatlantic Tumor Model Repositories” (FP7-ICT-2009.5.4–247754), “p-medicine: Personalized Medicine” , “My Health Avatar: A Demonstration of 4D Digital Avatar Infrastructure for Access of Complete Patient Information” (FP7-ICT-2011.5.2–600929) and CHIC: Computational Horizons in Cancer: Computational Horizons In Cancer (CHIC): Developing Meta- and Hyper-Multiscale Models and Repositories for