Molecular Mechanisms of Phosphate Use Efficiency in via TLL1.

Beneficial fungi are promising tools for enhancing plant growth and crop yield in stressful environments. TLL1 (POT1) was identified as a potential biofertilizer enhancing plant growth and phosphate use efficiency especially under phosphate deficiency stress. Hence, we attempted to explore bioinformatic insights into how POT1 enhances plant growth under phosphate starvation.

Plant growth promotion under phosphate deficiency and improved phosphate acquisition by new fungal strain, TLL1.

Microbiomes in soil ecosystems play a significant role in solubilizing insoluble inorganic and organic phosphate sources with low availability and mobility in the soil. They transfer the phosphate ion to plants, thereby promoting plant growth. In this study, we isolated an unidentified fungal strain, POT1 ( TLL1) from indoor dust samples, and confirmed its ability to promote root growth, especially under phosphate deficiency, as well as solubilizing activity for insoluble phosphates such as AlPO, FePO·4HO, Ca(PO), and hydroxyapatite.

Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new "Integrated Epilepsy Classification"?

Over the last few decades the ILAE classifications for seizures and epilepsies (ILAE-EC) have been updated repeatedly to reflect the substantial progress that has been made in diagnosis and understanding of the etiology of epilepsies and seizures and to correct some of the shortcomings of the terminology used by the original taxonomy from the 1980s. However, these proposals have not been universally accepted or used in routine clinical practice. During the same period, a separate classification known as the "Four-dimensional epilepsy classification" (4D-EC) was developed which includes a seizure classification based exclusively on ictal symptomatology, which has been tested and adapted over the years.

Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore.

Singapore experienced its first Zika virus (ZIKV) cluster in August 2016. To understand the implication of human movement on disease spread, a retrospective study was conducted using aggregated and anonymized mobile phone data to examine movement from the cluster to identify areas of possible transmission. An origin⁻destination model was developed based on the movement of three groups of individuals: (i) construction workers, (ii) residents and (iii) visitors out of the cluster locality to other parts of the island.