Parenclitic and Synolytic Networks Revisited

© 2021 Nazarenko, Whitwell, Blyuss and Zaikin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). https://creativecommons.org/licenses/by/4.0/Parenclitic networks provide a powerful and relatively new way to coerce multidimensional data into a graph form, enabling the application of graph theory to evaluate features. Different algorithms have been published for constructing parenclitic networks, leading to the question—which algorithm should be chosen? Initially, it was suggested to calculate the weight of an edge between two nodes of the network as a deviation from a linear regression, calculated for a dependence of one of these features on the other. This method works well, but not when features do not have a linear relationship. To overcome this, it was suggested to calculate edge weights as the distance from the area of most probable values by using a kernel density estimation. In these two approaches only one class (typically controls or healthy population) is used to construct a model. To take account of a second class, we have introduced synolytic networks, using a boundary between two classes on the feature-feature plane to estimate the weight of the edge between these features. Common to all these approaches is that topological indices can be used to evaluate the structure represented by the graphs. To compare these network approaches alongside more traditional machine-learning algorithms, we performed a substantial analysis using both synthetic data with a priori known structure and publicly available datasets used for the benchmarking of ML-algorithms. Such a comparison has shown that the main advantage of parenclitic and synolytic networks is their resistance to over-fitting (occurring when the number of features is greater than the number of subjects) compared to other ML approaches. Secondly, the capability to visualise data in a structured form, even when this structure is not a priori available allows for visual inspection and the application of well-established graph theory to their interpretation/application, eliminating the “black-box” nature of other ML approaches.Peer reviewedFinal Published versio

Achieving hip fracture surgery within 36 hours: an investigation of risk factors to surgical delay and recommendations for practice

BACKGROUND: The UK hip fracture best practice tariff (BPT) aims to deliver hip fracture surgery within 36 h of admission. Ensuring that delays are reserved for conditions which compromise survival, but are responsive to medical optimisation, would help to achieve this target. We aimed to identify medical risk factors of surgical delay, and assess their impact on mortality. MATERIALS AND METHODS: Prospectively collected patient data was obtained from the National Hip Fracture Database (NHFD). Medical determinants of surgical delay were identified and analysed using a multivariate regression analysis. The mortality risk associated with each factor contributing to surgical delay was then calculated. RESULTS: A total 1361 patients underwent hip fracture surgery, of which 537 patients (39.5 %) received surgery within 36 h of admission. Following multivariate analyses, only hyponatraemia was deduced to be a significant risk factor for delay RR = 1.24 (95 % CI 1.06-1.44). However, following a validated propensity score matching process, a Pearson chi-square test failed to demonstrate a statistical difference in mortality incidence between the hypo- and normonatraemic patients [χ (2) (1, N = 512) = 0.10, p = 0.757]. CONCLUSIONS: Hip fracture surgery should not be delayed in the presence of non-severe and isolated hyponatraemia. Instead, surgical delay may only be warranted in the presence of medical conditions which contribute to mortality and are optimisable. LEVEL OF EVIDENCE: III

Eye movements and pupil dilation during event perception

Human observers segment ongoing activities into events that are reliable across observers [Newtson and Engquist 1976]. Segments can be small ("fine") or large ("coarse") with clusters of fine-grained segments relating hierarchically to coarse segments. Segmentation behaviour occurs even without instruction indicated by neural activity in the Medial Temporal complex (MT+)and Frontal Eye Field (FEF). Similar activation is observed during active segmentation [Zacks et al. 2001]. These two brain regions are known to be active during the processing of visual motion (MT+) and guiding saccadic eye movements (FEF). This, along with behavioural evidence [Zacks 2004], indicates that visual motion may play an important role in identifying events

The correlation of Brock String response, fixation disparity, and anticipation timing

Background: This study investigated the relationship between ocular alignment measurements taken from the standard distance Brock String and the Mentor 0&0 B-VAT II. Also studied was the possible relationship between ocular alignment and the anticipation of a dynamic event as measured by the Bassin Anticipation Timer. Methods: 71 subjects performed a standard distance Brock String test. The subjects were asked whether they perceived the bead within a fused area of string, and if so, the subject was asked to identify the portion of the fused area where the bead appeared. The subjects\u27 fixation disparity was also used to determine if there is a correlation with anticipation timing as measured by the Bassin Anticipation Timer. Results: 47 of 71 subjects (66%) perceived fused sections of the distance Brock String. Of these 47 subjects, 38 (81%) stated the bead was in the front 113 of the fused section. 6 (13%) subjects said the bead was in the middle 1/3 of the fused portion. The remaining 3 (6%) subjects reported the bead to appear in the rear 113 of the fused area. BVAT analysis claimed 29 (41%) subjects had a mean exo di sparity, while 17 (24%) subjects had a mean fixation disparity of ortho, and the remaining 25 (35%) subjects had mean eso fixation disparities. Correlations between fixation disparity and anticipation timing were found to be quite low. Conclusions: Statistical comparisons made between distance Brock String and By AT fixation disparity performances did not yield the significant results necessary to conclude that distance Brock String responses accurately represent any one fixation disparity category ( eso, exo, or ortho ). In addition, no statistically significant relationship was determined between distance Brock String orB-VAT fixation disparities and any of the Bassin Anticipation Timer dat

The correlation of Brock String Response, fixation disparity, and anticipation timing

This study investigated the relationship between ocular alignment as measured by the standard distance Brock String, and by the Mentor 0&0 B-VAT II. It also studied the possible relationship between ocular alignment and the anticipation of the occurrence of a dynamic event, as measured by the Bassin Anticipation Timer. In addition to the standard lateral fixation disparity measurements taken with the B-VAT and distance Brock String, a second Brock String measurement was taken. Subjects were asked if they perceived a fused portion of the string and if so, to determine the bead\u27s location within the fused section of string. Statistical comparisons made between distance Brock String and B-VAT fixation disparity performances did not yield the significant results neccesary to conclude that distance Brock String responses accurately represent any one fixation disparity category (eso, exo, or ortho). In addition, no statistically significant relationship was determined between distance Brock String or B-VAT fixation disparities and any of the Bassin Anticipation Timer data. 47 of 71 subjects (66%) perceived fused sections of the distance Brock String. This high frequency of occurrence indicates the need to expand the standard instruction set when utilizing the distance Brock String

Identification of a serum biomarker panel for the differential diagnosis of cholangiocarcinoma and primary sclerosing cholagnitis

The non-invasive differentiation of malignant and benign biliary disease is a clinical challenge. Carbohydrate antigen 19-9 (CA19-9), leucine-rich α2-glycoprotein (LRG1), interleukin 6 (IL6), pyruvate kinase M2 (PKM2), cytokeratin 19 fragment (CYFRA21.1) and mucin 5AC (MUC5AC) have reported utility for differentiating cholangiocarcinoma (CCA) from benign biliary disease. Herein, serum levels of these markers were tested in 66 cases of CCA and 62 cases of primary sclerosing cholangitis (PSC) and compared with markers of liver function and inflammation. Markers panels were assessed for their ability to discriminate malignant and benign disease. Several of the markers were also assessed in pre-diagnosis biliary tract cancer (BTC) samples with performances evaluated at different times prior to diagnosis. We show that LRG1 and IL6 were unable to accurately distinguish CCA from PSC, whereas CA19-9, PKM2, CYFRA21.1 and MUC5AC were significantly elevated in malignancy. Area under the receiver operating characteristic curves for these individual markers ranged from 0.73–0.84, with the best single marker (PKM2) providing 61% sensitivity at 90% specificity. A panel combining PKM2, CYFRA21.1 and MUC5AC gave 76% sensitivity at 90% specificity, which increased to 82% sensitivity by adding gamma-glutamyltransferase (GGT). In the pre-diagnosis setting, LRG1, IL6 and PKM2 were poor predictors of BTC, whilst CA19-9 and C-reactive protein were elevated up to 2 years before diagnosis. In conclusion, LRG1, IL6 and PKM2 were not useful for early detection of BTC, whilst a model combining PKM2, CYFRA21.1, MUC5AC and GGT was beneficial in differentiating malignant from benign biliary disease, warranting validation in a prospective trial

Improved early detection of ovarian cancer using longitudinal multimarker models

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Background: Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer. Methods: This case–control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer. Results: The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time. Conclusions: We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.Peer reviewe

The Role of Haptic Expectations in Reaching to Grasp: From Pantomime to Natural Grasps and Back Again

© Copyright © 2020 Whitwell, Katz, Goodale and Enns. When we reach to pick up an object, our actions are effortlessly informed by the object’s spatial information, the position of our limbs, stored knowledge of the object’s material properties, and what we want to do with the object. A substantial body of evidence suggests that grasps are under the control of “automatic, unconscious” sensorimotor modules housed in the “dorsal stream” of the posterior parietal cortex. Visual online feedback has a strong effect on the hand’s in-flight grasp aperture. Previous work of ours exploited this effect to show that grasps are refractory to cued expectations for visual feedback. Nonetheless, when we reach out to pretend to grasp an object (pantomime grasp), our actions are performed with greater cognitive effort and they engage structures outside of the dorsal stream, including the ventral stream. Here we ask whether our previous finding would extend to cued expectations for haptic feedback. Our method involved a mirror apparatus that allowed participants to see a “virtual” target cylinder as a reflection in the mirror at the start of all trials. On “haptic feedback” trials, participants reached behind the mirror to grasp a size-matched cylinder, spatially coincident with the virtual one. On “no-haptic feedback” trials, participants reached behind the mirror and grasped into “thin air” because no cylinder was present. To manipulate haptic expectation, we organized the haptic conditions into blocked, alternating, and randomized schedules with and without verbal cues about the availability of haptic feedback. Replicating earlier work, we found the strongest haptic effects with the blocked schedules and the weakest effects in the randomized uncued schedule. Crucially, the haptic effects in the cued randomized schedule was intermediate. An analysis of the influence of the upcoming and immediately preceding haptic feedback condition in the cued and uncued random schedules showed that cuing the upcoming haptic condition shifted the haptic influence on grip aperture from the immediately preceding trial to the upcoming trial. These findings indicate that, unlike cues to the availability of visual feedback, participants take advantage of cues to the availability of haptic feedback, flexibly engaging pantomime, and natural modes of grasping to optimize the movement

Neuroimaging signatures of frontotemporal dementia genetics: C9ORF72, tau, progranulin and sporadics

A major recent discovery was the identification of an expansion of a non-coding GGGGCC hexanucleotide repeat in the C9ORF72 gene in patients with frontotemporal dementia and amyotrophic lateral sclerosis. Mutations in two other genes are known to account for familial frontotemporal dementia: microtubule-associated protein tau and progranulin. Although imaging features have been previously reported in subjects with mutations in tau and progranulin, no imaging features have been published in C9ORF72. Furthermore, it remains unknown whether there are differences in atrophy patterns across these mutations, and whether regional differences could help differentiate C9ORF72 from the other two mutations at the single-subject level. We aimed to determine the regional pattern of brain atrophy associated with the C9ORF72 gene mutation, and to determine which regions best differentiate C9ORF72 from subjects with mutations in tau and progranulin, and from sporadic frontotemporal dementia. A total of 76 subjects, including 56 with a clinical diagnosis of behavioural variant frontotemporal dementia and a mutation in one of these genes (19 with C9ORF72 mutations, 25 with tau mutations and 12 with progranulin mutations) and 20 sporadic subjects with behavioural variant frontotemporal dementia (including 50% with amyotrophic lateral sclerosis), with magnetic resonance imaging were included in this study. Voxel-based morphometry was used to assess and compare patterns of grey matter atrophy. Atlas-based parcellation was performed utilizing the automated anatomical labelling atlas and Statistical Parametric Mapping software to compute volumes of 37 regions of interest. Hemispheric asymmetry was calculated. Penalized multinomial logistic regression was utilized to create a prediction model to discriminate among groups using regional volumes and asymmetry score. Principal component analysis assessed for variance within groups. C9ORF72 was associated with symmetric atrophy predominantly involving dorsolateral, medial and orbitofrontal lobes, with additional loss in anterior temporal lobes, parietal lobes, occipital lobes and cerebellum. In contrast, striking anteromedial temporal atrophy was associated with tau mutations and temporoparietal atrophy was associated with progranulin mutations. The sporadic group was associated with frontal and anterior temporal atrophy. A conservative penalized multinomial logistic regression model identified 14 variables that could accurately classify subjects, including frontal, temporal, parietal, occipital and cerebellum volume. The principal component analysis revealed similar degrees of heterogeneity within all disease groups. Patterns of atrophy therefore differed across subjects with C9ORF72, tau and progranulin mutations and sporadic frontotemporal dementia. Our analysis suggested that imaging has the potential to be useful to help differentiate C9ORF72 from these other groups at the single-subject level

Impact of modular mitochondrial epistatic interactions on the evolution of human subpopulations

Investigation of human mitochondrial (mt) genome variation has been shown to provide insights to the human history and natural selection. By analyzing 24,167 human mt-genome samples, collected for five continents, we have developed a co-mutation network model to investigate characteristic human evolutionary patterns. The analysis highlighted richer co-mutating regions of the mt-genome, suggesting the presence of epistasis. Specifically, a large portion of COX genes was found to co-mutate in Asian and American populations, whereas, in African, European, and Oceanic populations, there was greater co-mutation bias in hypervariable regions. Interestingly, this study demonstrated hierarchical modularity as a crucial agent for these co-mutation networks. More profoundly, our ancestry-based co-mutation module analyses showed that mutations cluster preferentially in known mitochondrial haplogroups. Contemporary human mt-genome nucleotides most closely resembled the ancestral state, and very few of them were found to be ancestral-variants. Overall, these results demonstrated that subpopulation-based biases may favor mitochondrial gene specific epistasis