Celastrus aculeatus Merr. has been widely used in traditional Chinese medicine to treat rheumatoid arthritis (RA) in clinic. However, the main active fraction of this plant is still unclear. In this study, we attempted to evaluate the suppressive effect of ethyl acetate extract (EAE) from Celastrus aculeatus Merr. on synovial inflammation in adjuvant arthritis (AA) rats induced by Mycobacterium...

Memory is the ability of an individual to record the information and recall it whenever needed. Dementia is a mental disorder characterized by loss of intellectual ability (judgment or abstract thinking) which invariably involves impairment of memory. The most common cause of dementia is Alzheimers disease (AD), which is a progressive neurodegenerative disorder associated with loss of neurons i...

Determination of phytochemical, antioxidant, antimicrobial, and protein binding qualities hydroethanolic extract Celastrus paniculatusVijay Kumar¥, Simranjeet Singh¥, Arjun Amit Kumar Dixit¥, Bhavana Shrivastava, Sapna Avinash Kondalkar, Joginder Singh, Ravindra Gurpreet Kaur Sidhu, Rajesh Partap Varanasi Subhose, Om Prakash

Background: Weedy non-native species have long been predicted to be more phenotypically plastic than native species. Question: Are weedy non-native species more plastic than natives? Organisms: Fourteen perennial plant species: Acer platanoides, Acer saccharum, Bromus inermis, Bromus latiglumis, Celastrus orbiculatus, Celastrus scandens, Elymus repens, Elymus trachycaulus, Plantago major, Plant...

When plants are subjected to leaf canopy shade in forest understories or from neighboring plants, they not only experience reduced light quantity, but light quality in lowered red : far red light (R : FR). Growth and other developmental responses of plants in reduced R : FR can vary and are not consistent across species. We compared how an invasive liana, Celastrus orbiculatus, and its closely ...

Many critical ecological issues require the analysis of large spatial point data sets - for example, modelling species distributions, abundance and spread from survey data. But modelling spatial relationships, especially in large point data sets, presents major computational challenges. We use a novel Bayesian hierarchical statistical approach, 'spatial predictive process' modelling, to predict...