Integrated Calendar

The oxygen isotopic signature of marine deep-sea cherts was previously used to reconstruct past ocean temperature and bottom water δ18O through the Cenozoic and Mesozoic periods. Oxygen isotopes of deep-sea cherts, which were never exposed to meteoric water, exhibit a wide range of values indicating that the evolution and maturation of biogenic amorphous opal (opal-A) to opal-CT and microquartz chert is accompanied by isotopic changes. We measured δ18O of diatom opal-A, opal-CT, and microquartz chert from deep sea cores retrieved from the Japan Sea. The δ18O of opal-CT and microquartz chert phases correspond to the depth in the sediments where these transitions occur, ~400 m and 40 °C for opal-A to opal-CT and ~500 m and 60 °C for opal-CT to microquartz chert. The δ18O values of opal-CT and microquartz chert appear to reflect equilibrium formation temperatures of silica, corresponding to the geothermal gradient and the local porewater δ18O. The δ18O of opal-CT and microquartz chert are controlled by the geothermal gradient and compositions of pore waters during polymorphic transformations deep within the sediment, indicating that the δ18O of these phases cannot be used to determine temperature or composition of seawater during diatom growth.
Opal-A is the most susceptible phase for isotope alteration. We separated opal-A (i.e., diatoms, radiolaria, and siliceous sponge spicules) of Cenozoic age and measured its isotope composition. The results do not indicate any significant change in δ18O. This will be discussed within the general framework of global climatic change.

Individual differences are an essential property of all living things, and personality provides a unique glimpse into the biology underlying behavioral variability. And yet, because of the lack of a systematic approach to personality, most works on animal personalities still end up examining a limited subset of subjectively chosen behavioral readouts. Lately, we have shown how personality can be inferred directly and objectively from high-dimensional natural behavioral space. While this approach is not species-specific, we have demonstrated it on mice as it is one of the most common model animals. The mice were videoed over several days, and their behavior automatically analyzed in depth. Altogether, the computer identified 60 separate behaviors such as approaching others, chasing or fleeing, sharing food or keeping others away from food, exploring, or hiding. We found the mice personalities by working backward from behavior and extracting the underlying traits that differ among individuals while being stable over time and across contexts. We validated that traits found this way (which we term identity domains) were stable across social context, do not change with age, explain the variability in performance in classical tests, and significantly correlates with gene expression in brain regions related to personality. Expanding this method to human behavior, by using location and physiological data from cellphones and smartwatches, revealed a highly structured personality space which resembles that of the mice. This method allows for better informed mechanistic investigations into the biology of individual differences, systematically comparing behaviors across species, as well as develop more personalized psychiatry. Recently we have also been employing this approach to subjectively quantify wellness and welfare in both people and animals, towards the biology of happiness.