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Background: Necrostatin-1 (Nec-1) is an inhibitor of the receptor interacting protein (RIP)1 kinase, which acts as an inhibitor of necroptosis, a special form of necrosis. In the present study, the effect of Nec-1 on peripheral nerve injury (PNI) was investigated. Methods: The PNI model was established by inducing sciatic nerve injury. Hematoxylin–eosin and immunofluorescence staining techniques were used to assess the extent of injury to nerve fibers and necrosis of Schwann cells (SCs). Western blotting was performed to detect the expression of necroptosis-related factors (RIP1 and RIP3). The concentrations of tumor necrosis factor-α, interleukin (IL)-1β, IL-6, and the oxidative stress-related enzyme malondialdehyde (MDA) were determined to indicate the degree of inflammation and oxidative stress. Results: Nec-1 could decrease the degree of peripheral nerve lesions after PNI and protect SCs and axons by inhibiting necroptosis. Furthermore, Nec-1 could reduce necroptosis by inhibiting RIP1 and effectively reduce inflammation and reactive oxygen species production at the early stage of PNI. Conclusions: Alleviation of necroptosis by Nec-1 may provide new insights into therapies for the early stages of peripheral nerve repair after PNI. [ABSTRACT FROM AUTHOR]

Background: Protein complexes are essential for biologists to understand cell organization and function effectively. In recent years, predicting complexes from protein–protein interaction (PPI) networks through computational methods is one of the current research hotspots. Many methods for protein complex prediction have been proposed. However, how to use the information of known protein complexes is still a fundamental problem that needs to be solved urgently in predicting protein complexes. Results: To solve these problems, we propose a supervised learning method based on network representation learning and gene ontology knowledge, which can fully use the information of known protein complexes to predict new protein complexes. This method first constructs a weighted PPI network based on gene ontology knowledge and topology information, reducing the network's noise problem. On this basis, the topological information of known protein complexes is extracted as features, and the supervised learning model SVCC is obtained according to the feature training. At the same time, the SVCC model is used to predict candidate protein complexes from the protein interaction network. Then, we use the network representation learning method to obtain the vector representation of the protein complex and train the random forest model. Finally, we use the random forest model to classify the candidate protein complexes to obtain the final predicted protein complexes. We evaluate the performance of the proposed method on two publicly PPI data sets. Conclusions: Experimental results show that our method can effectively improve the performance of protein complex recognition compared with existing methods. In addition, we also analyze the biological significance of protein complexes predicted by our method and other methods. The results show that the protein complexes predicted by our method have high biological significance. [ABSTRACT FROM AUTHOR]

Background: Enteric methane from the ruminant livestock is a significant source in global greenhouse gas emissions, which is mainly generated by the methanogens inhabiting the rumen and cecum. Sika deer (Cervus nippon) not only produces less methane than bovine, but they also harbor a distinct methanogen community. Whereas, knowledge of methanogens colonization in the rumen and cecum of sika deer is relatively still unknown, which could provide more insights to the manipulation of gut microbiota during early life. Results: Here, we examined the development of bacteria and methanogens in the rumen and cecum of juvenile sika deer from birth to post-weaning (1 day, 42 days and 70 days, respectively) based on next generation sequencing. The results showed that the facultative anaerobic bacteria were decreased and the cellulolytic bacteria were increased. However, methanogens established soon after birth thrived through the whole developmental period, indicating a different succession process than bacteria in the GIT, and the limited role of age and dietary change on GIT methanogens. We also found Methanobrevibacter spp. (Mean relative abundance = 44.2%) and Methanocorpusculum spp. (Mean relative abundance = 57.5%) were dominated in the rumen and cecum, respectively. The methanogens also formed specific correlations with bacteria under different niches, suggesting a role of ecology niche on methanogen community. Conclusions: This study contributes to our knowledge about the microbial succession in GIT of sika deer, that may facilitate the development of targeted strategies to improve GIT function of sika deer. [ABSTRACT FROM AUTHOR]

Background: The rate of autism spectrum disorder (ASD) has been rising worldwide, and therefore it is important to identify potential causes of ASD to facilitate early prevention. This study examined the role of breastfeeding and the association between caesarean delivery (CD) and children's autism spectrum disorder. Methods: The data were from the Ma'anshan birth cohort (MABC) in China, that was set up between May 2013 and September 2014. Women within 14 gestational weeks were recruited. The delivery mode was extracted from medical notes and infant feeding was obtained from questionnaire surveys. Autism-like behaviour was assessed using the Checklist for Autism in Toddlers (CHAT-23) when children were 18 months old, and 3 years of age. At 5 years of age, autism-like behaviour was assessed using the Clancy Autism Behavior Scale behavior. Structural equation models tested the mediation effects of breastfeeding between CD and children's autism spectrum disorder. Results: In all, 1520 (48.89%) women gave birth via CD, and 406 (13.86%) children were identified with autism-like behaviours at 18 months. Compared with women giving birth via vaginal delivery, those giving birth via CD were more likely to experience a higher proportion of delayed initiation of breastfeeding (p < 0.01), and delayed onset of lactogenesis (p < 0.01). CD was associated with a lower proportion of exclusive breastfeeding at 4 months after delivery (p = 0.02). Autism-like behaviour was less likely amongst infants with exclusively breastfeeding at 4 months than amongst those not exclusively breastfeeding at 4 months (p < 0.01). SEM indicated that women who gave birth by CD were more likely to stop exclusive breastfeeding in the first 4 months (standard estimations = − 0.04, p = 0.02), and those children who were not exclusively breastfed at 4 months were more likely to have autism-like behaviours (standard estimations = − 0.05, p < 0.01). The associations persisted at 3 years, but not at 5 years. Conclusions: Exclusive breastfeeding at 4 months of age mediated the association between caesarean delivery and children's autism-like behaviours. [ABSTRACT FROM AUTHOR]