Dysregulation of microtubule stability impairs morphofunctional connectivity in primary neuronal networks

Functionally related neurons assemble into connected networks that process and transmit electrochemical information. To do this in a coordinated manner, the number and strength of synaptic connections is tightly regulated. Synapse function relies on the microtubule (MT) cytoskeleton, the dynamics of which are in turn controlled by a plethora of MT-associated proteins, including the MT-stabilizing protein Tau. Although mutations in the Tau-encodingMAPT gene underlie a set of neurodegenerative disorders, termed tauopathies, the exact contribution of MT dynamics and the perturbation thereof to neuronal network connectivity has not yet been scrutinized. Therefore, we investigated the impact of targeted perturbations of MT stability on morphological (e.g., neurite- and synapse density) and functional (e.g., synchronous calcium bursting) correlates of connectivity in networks of primary hippocampal neurons. We found that treatment with MT-stabilizing or -destabilizing compounds impaired morphofunctional connectivity in a reversible manner. We also discovered that overexpression of MAPT induced significant connectivity defects, which were accompanied by alterations in MT dynamics and increased resistance to pharmacological MT depolymerization. Overexpression of a MAPT variant harboring the P301L point mutation in the MT-binding domain did far less, directly linking neuronal connectivity with Tau's MT binding affinity. Our results show that MT stability is a vulnerable node in tauopathies and that its precise pharmacological tuning may positively affect neuronal network connectivity. However, a critical balance in MT turnover causes it to be a difficult therapeutic target with a narrow operating window

What Should Businesses Know About Social Media Analytics?

Big social media data generated by customers can be employed start to identify which customer behaviour and actions creates more value. A study by conducted by MIT Sloan Management Review found that 67% of the total 2,500 survey respondents reported that by employing analytics their companies gained a competitive advantage as well it helped them to innovate. Still, many businesses struggle to plan and create value from social data analytics. Hence, using a thematic analysis of current social media analytics (SMA) literature and focus group interview with SMA experts, the aim of this article is to provide an executive overview of SMA concepts, theories, and tools that are vital for understanding and strategically using social media analytics for business intelligence purposes

Towards a Differentiation Perspective on Social Media Platforms’ Affordances and Use Cultures – An Organizing Literature Review

Since social media transformed the way how people communicate and consume content, companies explore how to effectively build relationships with users. Anecdotal reports of practical case experiences indicate that a key managerial challenge for companies lies in effectively coping with the individual requirements and the full range of options of the various different social media platforms as well as adapting to the target groups’ platform-specific use cultures. Current theoretical conceptualizations of generalized social media ‘per se’ appear too broad for addressing and differentiating the detailed affordances and their appropriation by networked users in the leading platforms Facebook, Instagram and Twitter. Based on a comprehensive organizing literature review that seeks to link the affordance and the use culture perspective in information systems research, we contribute to a better understanding of differences between social media platforms

Associations between regular cannabis use and brain resting-state functional connectivity in adolescents and adults

Background/aim: Cannabis use is highly prevalent in adolescents; however, little is known about its effects on adolescent brain function. Method: Resting-state functional magnetic resonance imaging was used in matched groups of regular cannabis users (N = 70, 35 adolescents: 16–17 years old, 35 adults: 26–29 years old) and non-regular-using controls (N = 70, 35 adolescents/35 adults). Pre-registered analyses examined the connectivity of seven major cortical and sub-cortical brain networks (default mode network, executive control network (ECN), salience network, hippocampal network and three striatal networks) using seed-based analysis methods with cross-sectional comparisons between user groups and age groups. Results: The regular cannabis use group (across both age groups), relative to controls, showed localised increases in connectivity only in the ECN analysis. All networks showed localised connectivity differences based on age group, with the adolescents generally showing weaker connectivity than adults, consistent with the developmental effects. Mean connectivity across entire network regions of interest (ROIs) was also significantly decreased in the ECN in adolescents. However, there were no significant interactions found between age group and user group in any of the seed-based or ROI analyses. There were also no associations found between cannabis use frequency and any of the derived connectivity measures. Conclusion: Regular cannabis use is associated with changes in connectivity of the ECN, which may reflect allostatic or compensatory changes in response to regular cannabis intoxication. However, these associations were not significantly different in adolescents compared to adults.</p

Unconsciously Influential. Understanding sociotechnical Influence on social media

Over the last two decades, the rise of social media platforms such as Instagram, YouTube, and TikTok has sparked a global shift in commercial practices worldwide. People are exposed to and influenced by massive amounts of commercial content carefully and strategically integrated into these platforms’ social content. In addition, due to network structures, people’s engagement in the form of likes, comments, and simply viewing content results in the influence of people within and outside their network. In this study, we adopt a sociotechnical perspective and study the interplay between social and technical components in how influence is exercised on social media. Specifically, we identify the actors involved in the influence of commercial content and analyse how they exercise their influence for commercial purposes. Based on our findings and analysis, we present three contributions to Information systems literature: (1) how people have become unconsciously influential in spreading commercial content, which is the premise for social media commercial success, (2) how people’s social and commercial lives and contents are increasingly intertwined and (3) how this interweaving effect removes peoples’ ability to reflect on the content they engage with critically. Our study draws attention to the societal outcomes caused by technologies in practice

Associations between regular cannabis use and brain resting-state functional connectivity in adolescents and adults

BACKGROUND/AIM: Cannabis use is highly prevalent in adolescents; however, little is known about its effects on adolescent brain function. METHOD: Resting-state functional magnetic resonance imaging was used in matched groups of regular cannabis users (N = 70, 35 adolescents: 16-17 years old, 35 adults: 26-29 years old) and non-regular-using controls (N = 70, 35 adolescents/35 adults). Pre-registered analyses examined the connectivity of seven major cortical and sub-cortical brain networks (default mode network, executive control network (ECN), salience network, hippocampal network and three striatal networks) using seed-based analysis methods with cross-sectional comparisons between user groups and age groups. RESULTS: The regular cannabis use group (across both age groups), relative to controls, showed localised increases in connectivity only in the ECN analysis. All networks showed localised connectivity differences based on age group, with the adolescents generally showing weaker connectivity than adults, consistent with the developmental effects. Mean connectivity across entire network regions of interest (ROIs) was also significantly decreased in the ECN in adolescents. However, there were no significant interactions found between age group and user group in any of the seed-based or ROI analyses. There were also no associations found between cannabis use frequency and any of the derived connectivity measures. CONCLUSION: Regular cannabis use is associated with changes in connectivity of the ECN, which may reflect allostatic or compensatory changes in response to regular cannabis intoxication. However, these associations were not significantly different in adolescents compared to adults

Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and clinical drive for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage.Comment: 32 pages, 16 figures. Homepage: https://atm22.grand-challenge.org/. Submitte

Distinct and Common Neural Coding of Semantic and Non-semantic Control Demands

The flexible retrieval of knowledge is critical in everyday situations involving problem solving, reasoning and social interaction. Current theories emphasise the importance of a left-lateralised semantic control network (SCN) in supporting flexible semantic behaviour, while a bilateral multiple-demand network (MDN) is implicated in executive functions across domains. No study, however, has examined whether semantic and non-semantic demands are reflected in a common neural code within regions specifically implicated in semantic control. Using functional MRI and univariate parametric modulation analysis as well as multivariate pattern analysis, we found that semantic and non-semantic demands gave rise to both similar and distinct neural responses across control-related networks. Though activity patterns in SCN and MDN could decode the difficulty of both semantic and verbal working memory decisions, there was no shared common neural coding of cognitive demands in SCN regions. In contrast, regions in MDN showed common patterns across manipulations of semantic and working memory control demands, with successful cross-classification of difficulty across tasks. Therefore, SCN and MDN can be dissociated according to the information they maintain about cognitive demands