Systematic Characterization of Heterogeneity caused by Neuroinflammation in Alzheimer’s Disease based on Integrative Network Analysis

Background: Alzheimer's disease (AD) is the most common cause of dementia. As a heterogenous disease, there are several clinically and pathobiological defined subtypes with different molecular signatures. Neuroinflammation contributed to AD pathogenesis, however, the roles it played in the heterogeneity of AD was unclear. Objective: We aimed to illustrate the roles neuroinflammation played in the heterogeneity of AD. Method: An integrative network analysis based on transcriptomics, miRNOmics, and proteomics was performed to illustrate the heterogeneous characters of AD. Combined-functional-networks and hypothesis-network were constructed and analyzed to explore the roles neuroinflammation played in AD heterogeneity. Results: Astrocytes, microglia, ‘M2 macrophage-Neuron’, and ‘Microglia- Neuron’ were shown to be enriched in neuroinflammation related functional terms in a cell- and spatial-specific way. The microglia and neurons could interact with each other in three different ways including indirect interactions via intermediate cells, indirect interactions via soluble factors, and direct interactions established localized and functionally distinct signaling, all of which were used to control different biological processes. The combined network analyses exhibited the key roles neuroinflammation plays in the 'AD hypothesis network’. Conclusion : The AD heterogeneity may be caused by the heterogeneous cells involved in neuroinflammation and the crosstalks between spatial-specific molecular signatures.

Pyk2 regulates cell-edge protrusion dynamics by interacting with Crk

A novel model is described by which Pyk2 regulates the dynamics of cell-edge protrusions via direct and indirect interactions with Crk, which enable fine-tuning of cell-edge protrusion dynamics and consequent cell motility on the one hand together with tight regulation of cell motility on the other hand.

Indirect interactions among co-infecting parasites and a microbial mutualist impact disease progression

Interactions among parasites and other microbes within hosts can impact disease progression, yet study of such interactions has been mostly limited to pairwise combinations of microbes. Given the diversity of microbes within hosts, indirect interactions among more than two microbial species may also impact disease. To test this hypothesis, we performed inoculation experiments that investigated interactions among two fungal parasites, Rhizoctonia solani and Colletotrichum cereale, and a systemic fungal endophyte, Epichloë coenophiala, within the grass, tall fescue ( Lolium arundinaceum ). Both direct and indirect interactions impacted disease progression. While the endophyte did not directly influence R. solani disease progression or C. cereale symptom development, the endophyte modified the interaction between the two parasites . The magnitude of the facilitative effect of C. cereale on the growth of R. solani tended to be greater when the endophyte was present. Moreover, this interaction modification strongly affected leaf mortality. For plants lacking the endophyte, parasite co-inoculation did not increase leaf mortality compared to single-parasite inoculations. By contrast, for endophyte-infected plants, parasite co-inoculation increased leaf mortality compared to inoculation with R. solani or C. cereale alone by 1.9 or 4.9 times, respectively. Together, these results show that disease progression can be strongly impacted by indirect interactions among microbial symbionts.

Impact of the Host-Microbiome on Osteomyelitis Pathogenesis

The microbiome is a collection of genomes from microbiota, including all microorganisms in a niche, through direct and indirect interactions with the host. Certain microorganisms can exist in areas conventionally considered to be sterile, such as the bone matrix. Osseous microbiota dysbiosis caused by host-microbiome perturbation or external infections may ultimately lead to osteomyelitis, a bone inflammatory disorder. Our review covers the current discoveries on the impact of host-microbiome on osteomyelitis and some common osseous diseases. Some studies suggest that the microbiotas from both osseous and non-osseous tissues (e.g., blood or gut) impact the pathogenicity of osteomyelitis and other osseous diseases (e.g., rheumatoid arthritis). We believe that this review will provide readers with a better understanding on the role of the microbiome to the host’s bone health.

Humor Analysis Of Ideological Discussion In Twitter Account Interactions @NUgarislucu and @MuhammadiyinGL

This study aims to analyze the humorous interaction of ideological discourses between twitter account @NUgarislucu and @MuhammadiyinGL. In social media twitter because they often interact with organizational ideological issues in a joke. Researchers cite 5 direct and indirect interactions between the @NUgarislucu and @MuhammadiyinGL twitter accounts during January-February 2021 with different interaction backgrounds. In the interaction between the two accounts above, there are actually ideologies of their respective organizations that want to be conveyed to the public. However, the two accounts also show the general public that conveying beliefs, religious doctrines can actually be done with jokes and humor. You don't have to think that one group is right and the other is wrong.

Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches

Biological pest control (i.e. ‘biocontrol’) agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect impacts) remains a central challenge in biocontrol risk assessment. The analysis of ecological networks offers a promising approach to understanding the community-wide impacts of biocontrol agents (via direct and indirect interactions). Independently, species traits and phylogenies have been shown to successfully predict species interactions and network structure (alleviating the need to collect quantitative interaction data), but whether these approaches can be combined to predict indirect impacts of natural enemies remains untested. Whether predictions of interactions (i.e. direct effects) can be made equally well for generalists vs. specialists, abundant vs. less abundant species, and across different habitat types is also untested for consumer-prey interactions. Here, we used two machine-learning techniques (random forest and k-nearest neighbour; KNN) to test whether we could accurately predict empirically-observed quantitative host-parasitoid networks using trait and phylogenetic information. Then, we tested whether the accuracy of machine-learning-predicted interactions depended on the generality or abundance of the interacting partners, or on the source (habitat type) of the training data. Finally, we used these predicted networks to generate predictions of indirect effects via shared natural enemies (i.e. apparent competition), and tested these predictions against empirically observed indirect effects between hosts. We found that random-forest models predicted host-parasitoid pairwise interactions (which could be used to predict attack of non-target host species) more successfully than KNN. This predictive ability depended on the generality of the interacting partners for KNN models, and depended on species’ abundances for both random-forest and KNN models, but did not depend on the source (habitat type) of data used to train the models. Further, although our machine-learning informed methods could significantly predict indirect effects, the explanatory power of our machine-learning models for indirect interactions was reasonably low. Combining machine-learning and network approaches provides a starting point for reducing risk in biocontrol introductions, and could be applied more generally to predicting species interactions such as impacts of invasive species.

Exotic plants accumulate and share herbivores yet dominate communities via rapid growth

Herbivores may facilitate or impede exotic plant invasion, depending on their direct and indirect interactions with exotic plants relative to co-occurring natives. However, previous studies investigating direct effects have mostly used pairwise native-exotic comparisons with few enemies, reached conflicting conclusions, and largely overlooked indirect interactions such as apparent competition. Here, we ask whether native and exotic plants differ in their interactions with invertebrate herbivores. We manipulate and measure plant-herbivore and plant-soil biota interactions in 160 experimental mesocosm communities to test several invasion hypotheses. We find that compared with natives, exotic plants support higher herbivore diversity and biomass, and experience larger proportional biomass reductions from herbivory, regardless of whether specialist soil biota are present. Yet, exotics consistently dominate community biomass, likely due to their fast growth rates rather than strong potential to exert apparent competition on neighbors. We conclude that polyphagous invertebrate herbivores are unlikely to play significant direct or indirect roles in mediating plant invasions, especially for fast-growing exotic plants.