Rat neurosphere cells protect axotomized rat retinal ganglion cells and facilitate their regeneration

We investigated the ability of a population of rat neural stem and precursor cells derived from rat embryonic spinal cord to protect injured neurons in the rat central nervous system (CNS). The neonatal rat optic pathway was used as a model of CNS injury, whereby retinal ganglion cells (RGCs) were axotomized by lesion of the lateral geniculate nucleus one day after birth. Neural stem and precursor cells derived from expanded neurospheres (NS) were transplanted into the lesion site at the time of injury. Application of Fast Blue tracer dye to the lesion site demonstrated that significant numbers of RGCs survived at 4 and 8 weeks in animals that received a transplant, with an average of 28% survival, though in some individual cases survival was greater than 50%. No RGCs survived in animals that received a lesion alone. Furthermore, labeled RGCs were also observed when Fast Blue was applied to the superior colliculus (SC) at 4 weeks, suggesting that neurosphere cells also facilitated RGC to regenerate to their normal target. Transplanted cells did not migrate or express neural markers after transplantation, and secreted several neurotrophic factors in vitro. We conclude that NS cells can protect injured CNS neurons and promote their regeneration. These effects are not attributable to cell replacement, and may be mediated via secretion of neurotrophic factors. Thus, neuroprotection by stem cell populations may be a more viable approach for treatment of CNS disorders than cell replacement therapy.

Quantitative precipitation estimation over ocean using Bayesian approach from microwave observations during the typhoon season

We have developed a new Bayesian approach to retrieve oceanic rain rate from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), with an emphasis on typhoon cases in the West Pacific. Retrieved rain rates are validated with measurements of rain gauges located on Japanese islands. To demonstrate improvement, retrievals are also compared with those from the TRMM/Precipitation Radar (PR), the Goddard Profiling Algorithm (GPROF), and a multi-channel linear regression statistical method (MLRS). We have found that qualitatively, all methods retrieved similar horizontal distributions in terms of locations of eyes and rain bands of typhoons. Quantitatively, our new Bayesian retrievals have the best linearity and the smallest root mean square (RMS) error against rain gauge data for 16 typhoon overpasses in 2004. The correlation coefficient and RMS of our retrievals are 0.95 and ~2 mm hr-1, respectively. In particular, at heavy rain rates, our Bayesian retrievals outperform those retrieved from GPROF and MLRS. Overall, the new Bayesian approach accurately retrieves surface rain rate for typhoon cases. Accurate rain rate estimates from this method can be assimilated in models to improve forecast and prevent potential damages in Taiwan during typhoon seasons.

Effects of gelation temperature on the mozzarella-type curd made from buffalo and cows’ milk: 2. curd yield, overall quality & casein fractions

Buffalo curd gave higher amount of yield than cows’ curd at similar processing conditions. Curd moisture was decreased with the increase of gelation temperatures in both types of milk. Curd cutting time of 45 minutes was found optimum for Mozzarella cheese making from both milk samples. Centrifugation method is simpler, quicker and more reproducible than Buchner funnel method. Buffalo milk contains higher amounts of αs1- , β- and к-casein as compared to cows’ milk.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.