Immunoglobulin G N-glycan biomarkers for autoimmune diseases: Current state and a glycoinformatics perspective

The effective treatment of autoimmune disorders can greatly benefit from disease-specific biomarkers that are functionally involved in immune system regulation and can be collected through minimally invasive procedures. In this regard, human serum IgG N-glycans are promising for uncovering disease predisposition and monitoring progression, and for the identification of specific molecular targets for advanced therapies. In particular, the IgG N-glycome in diseased tissues is considered to be disease-dependent; thus, specific glycan structures may be involved in the pathophysiology of autoimmune diseases. This study provides a critical overview of the literature on human IgG N-glycomics, with a focus on the identification of disease-specific glycan alterations. In order to expedite the establishment of clinically-relevant N-glycan biomarkers, the employment of advanced computational tools for the interpretation of clinical data and their relationship with the underlying molecular mechanisms may be critical. Glycoinformatics tools, including artificial intelligence and systems glycobiology approaches, are reviewed for their potential to provide insight into patient stratification and disease etiology. Challenges in the integration of such glycoinformatics approaches in N-glycan biomarker research are critically discussed

Dynamics of trimming the content of face representations for categorization in the brain

To understand visual cognition, it is imperative to determine when, how and with what information the human brain categorizes the visual input. Visual categorization consistently involves at least an early and a late stage: the occipito-temporal N170 event related potential related to stimulus encoding and the parietal P300 involved in perceptual decisions. Here we sought to understand how the brain globally transforms its representations of face categories from their early encoding to the later decision stage over the 400 ms time window encompassing the N170 and P300 brain events. We applied classification image techniques to the behavioral and electroencephalographic data of three observers who categorized seven facial expressions of emotion and report two main findings: (1) Over the 400 ms time course, processing of facial features initially spreads bilaterally across the left and right occipito-temporal regions to dynamically converge onto the centro-parietal region; (2) Concurrently, information processing gradually shifts from encoding common face features across all spatial scales (e.g. the eyes) to representing only the finer scales of the diagnostic features that are richer in useful information for behavior (e.g. the wide opened eyes in 'fear'; the detailed mouth in 'happy'). Our findings suggest that the brain refines its diagnostic representations of visual categories over the first 400 ms of processing by trimming a thorough encoding of features over the N170, to leave only the detailed information important for perceptual decisions over the P300

Cross-Racial Misidentification: A Call to Action in Washington State and Beyond

Research indicates eyewitness identifications are incorrect approximately one-third of the time in criminal investigations. For years, this phenomenon has significantly contributed to wrongful convictions all over the country, including in Washington State. But jurors, attorneys, and police remain unaware of the nature and extent of the problem and continue to give undue weight to eyewitness evidence. Experts have estimated that approximately 5,000–10,000 felony convictions in the United States each year are wrongful, and research suggests that approximately 75% of wrongful convictions involve eyewitness misidentification. The phenomenon of eyewitness misidentification is also amplified and most troublesome in the context of cross-racial identification—when a witness identifies someone of another race. Experimental research suggests that an eyewitness trying to identify a stranger is over 50% more likely to make a misidentification when the stranger and eyewitness are of different races. Consistent with this finding, approximately one-third of wrongful convictions uncovered by DNA analysis nationwide have involved whites misidentifying blacks. For these reasons, this Article focuses on cross-racial misidentification, and discusses the nature and extent of the problem and potential tools for addressing it; however, this Article’s reasoning applies in large part to eyewitness misidentification in general. The Washington State Supreme Court had two recent opportunities to address the issue of cross-racial misidentification in State v. Cheatam and State v. Allen. These cases establish that Washington State trial courts have broad discretion to permit expert testimony and jury instruction on cross-racial misidentification when relevant. In light of this precedent, this Article proposes that Washington State trial courts begin exercising their broad discretion regularly to admit such testimony and instruction whenever relevant as an initial step toward preventing wrongful convictions and improving our criminal justice system. Going forward, additional education and reform efforts will be needed to solve this ongoing problem

Shifting attention in viewer- and object-based reference frames after unilateral brain injury

The aims of the present study were to investigate the respective roles that object- and viewer-based reference frames play in reorienting visual attention, and to assess their influence after unilateral brain injury. To do so, we studied 16 right hemisphere injured (RHI) and 13 left hemisphere injured (LHI) patients. We used a cueing design that manipulates the location of cues and targets relative to a display comprised of two rectangles (i.e., objects). Unlike previous studies with patients, we presented all cues at midline rather than in the left or right visual fields. Thus, in the critical conditions in which targets were presented laterally, reorienting of attention was always from a midline cue. Performance was measured for lateralized target detection as a function of viewer-based (contra- and ipsilesional sides) and object-based (requiring reorienting within or between objects) reference frames. As expected, contralesional detection was slower than ipsilesional detection for the patients. More importantly, objects influenced target detection differently in the contralesional and ipsilesional fields. Contralesionally, reorienting to a target within the cued object took longer than reorienting to a target in the same location but in the uncued object. This finding is consistent with object-based neglect. Ipsilesionally, the means were in the opposite direction. Furthermore, no significant difference was found in object-based influences between the patient groups (RHI vs. LHI). These findings are discussed in the context of reference frames used in reorienting attention for target detection

Citizen Science and Open Data: a model for Invasive Alien Species in Europe

Invasive Alien Species (IAS) are a growing threat to Europe's biodiversity. The implementation of European Union Regulation on IAS can benefit from the involvement of the public in IAS recording and management through Citizen Science (CS) initiatives. Aiming to tackle issues related with the use of CS projects on IAS topics, a dedicated workshop titled “Citizen Science and Open Data: a model for Invasive Alien Species in Europe” was organized by the Joint Research Centre (JRC) and the European Cooperation in Science and Technology (COST Association). Fifty key stakeholders from all Europe, including two Members of the European Parliament, attended the workshop. With a clear focus on IAS, the workshop aimed at addressing the following issues: a) CS and policy, b) citizen engagement, and c) CS data management. Nine short presentations provided input on CS and IAS issues. Participants discussed specific topics in several round tables (“world café” style) and reported back their conclusions to the audience and full assembly moderated discussions. Overall, the workshop enabled the sharing of ideas, approaches and best practices regarding CS and IAS. Specific opportunities and pitfalls of using CS data in the whole policy cycle for IAS were recognized. Concerning the implementation of the IAS Regulation, CS data could complement official surveillance systems, and contribute to the early warning of the IAS of Union concern after appropriate validation by the Member States’ competent authorities. CS projects can additionally increase awareness and empower citizens. Attendees pointed out the importance for further public engagement in CS projects on IAS that demonstrate specific initiatives and approaches and analyze lessons learned from past experiences. In addition, the workshop noted that the data gathered from different CS projects on IAS are fragmented. It highlighted the need for using an open and accessible platform to upload data originating from CS sources or to mirror validated data into a single, easy-to-use web service, in line with the EU Open Science Strategic Priority. The workshop provided ten key recommendations of best practices for CS projects on IAS, addressed to researchers, policy makers and implementing authorities, indicating future research and policy directions and opportunities

Priming global and local processing of composite faces: revisiting the processing-bias effect on face perception

We used the composite-face illusion and Navon stimuli to determine the consequences of priming local or global processing on subsequent face recognition. The composite-face illusion reflects the difficulty of ignoring the task-irrelevant half-face while attending the task-relevant half if the half-faces in the composite are aligned. On each trial, participants first matched two Navon stimuli, attending to either the global or the local level, and then matched the upper halves of two composite faces presented sequentially. Global processing of Navon stimuli increased the sensitivity to incongruence between the upper and the lower halves of the composite face, relative to a baseline in which the composite faces were not primed. Local processing of Navon stimuli did not influence the sensitivity to incongruence. Although incongruence induced a bias toward different responses, this bias was not modulated by priming. We conclude that global processing of Navon stimuli augments holistic processing of the face

Machine learning framework to extract the biomarker potential of plasma IgG N-glycans towards disease risk stratification

Effective management of chronic diseases and cancer can greatly benefit from disease-specific biomarkers that enable informative screening and timely diagnosis. IgG N-glycans found in human plasma have the potential to be minimally invasive disease-specific biomarkers for all stages of disease development due to their plasticity in response to various genetic and environmental stimuli. Data analysis and machine learning (ML) approaches can assist in harnessing the potential of IgG glycomics towards biomarker discovery and the development of reliable predictive tools for disease screening. This study proposes an ML-based N-glycomic analysis framework that can be employed to build, optimise, and evaluate multiple ML pipelines to stratify patients based on disease risk in an interpretable manner. To design and test this framework, a published colorectal cancer (CRC) dataset from the Study of Colorectal Cancer in Scotland (SOCCS) cohort (1999-2006) was used. In particular, among the different pipelines tested, an XGBoost-based ML pipeline, which was tuned using multi-objective optimisation, calibrated using an inductive Venn-Abers predictor (IVAP), and evaluated via a nested cross-validation (NCV) scheme, achieved a mean area under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.771 when classifying between age-, and sex-matched healthy controls and CRC patients. This performance suggests the potential of using the relative abundance of IgG N-glycans to define populations at elevated CRC risk who merit investigation or surveillance. Finally, the IgG N-glycans that highly impact CRC classification decisions were identified using a global model-agnostic interpretability technique, namely Accumulated Local Effects (ALE). We envision that open-source computational frameworks, such as the one presented herein, will be useful in supporting the translation of glycan-based biomarkers into clinical applications

Processing of spatial-frequency altered faces in schizophrenia: Effects of illness phase and duration

Low spatial frequency (SF) processing has been shown to be impaired in people with schizophrenia, but it is not clear how this varies with clinical state or illness chronicity. We compared schizophrenia patients (SCZ, n534), first episode psychosis patients (FEP, n522), and healthy controls (CON, n535) on a gender/facial discrimination task. Images were either unaltered (broadband spatial frequency, BSF), or had high or low SF information removed (LSF and HSF conditions, respectively). The task was performed at hospital admission and discharge for patients, and at corresponding time points for controls. Groups were matched on visual acuity. At admission, compared to their BSF performance, each group was significantly worse with low SF stimuli, and most impaired with high SF stimuli. The level of impairment at each SF did not depend on group. At discharge, the SCZ group performed more poorly in the LSF condition than the other groups, and showed the greatest degree of performance decline collapsed over HSF and LSF conditions, although the latter finding was not significant when controlling for visual acuity. Performance did not change significantly over time for any group. HSF processing was strongly related to visual acuity at both time points for all groups. We conclude the following: 1) SF processing abilities in schizophrenia are relatively stable across clinical state; 2) face processing abnormalities in SCZ are not secondary to problems processing specific SFs, but are due to other known difficulties constructing visual representations from degraded information; and 3) the relationship between HSF processing and visual acuity, along with known SCZ- and medication-related acuity reductions, and the elimination of a SCZ-related impairment after controlling for visual acuity in this study, all raise the possibility that some prior findings of impaired perception in SCZ may be secondary to acuity reductions

From Coarse to Fine? Spatial and Temporal Dynamics of Cortical Face Processing

Primary vision segregates information along 2 main dimensions: orientation and spatial frequency (SF). An important question is how this primary visual information is integrated to support high-level representations. It is generally assumed that the information carried by different SF is combined following a coarse-to-fine sequence. We directly addressed this assumption by investigating how the network of face-preferring cortical regions processes distinct SF over time. Face stimuli were flashed during 75, 150, or 300 ms and masked. They were filtered to preserve low SF (LSF), middle SF (MSF), or high SF (HSF). Most face-preferring regions robustly responded to coarse LSF, face information in early stages of visual processing (i.e., until 75 ms of exposure duration). LSF processing decayed as a function of exposure duration (mostly until 150 ms). In contrast, the processing of fine HSF, face information became more robust over time in the bilateral fusiform face regions and in the right occipital face area. The present evidence suggests the coarse-to-fine strategy as a plausible modus operandi in high-level visual cortex