Rapid glaciation and a two-step sea level plunge into the Last Glacial Maximum.

The approximately 10,000-year-long Last Glacial Maximum, before the termination of the last ice age, was the coldest period in Earth's recent climate history1. Relative to the Holocene epoch, atmospheric carbon dioxide was about 100 parts per million lower and tropical sea surface temperatures were about 3 to 5 degrees Celsius lower2,3. The Last Glacial Maximum began when global mean sea level (GMSL) abruptly dropped by about 40 metres around 31,000 years ago4 and was followed by about 10,000 years of rapid deglaciation into the Holocene1. The masses of the melting polar ice sheets and the change in ocean volume, and hence in GMSL, are primary constraints for climate models constructed to describe the transition between the Last Glacial Maximum and the Holocene, and future changes; but the rate, timing and magnitude of this transition remain uncertain. Here we show that sea level at the shelf edge of the Great Barrier Reef dropped by around 20 metres between 21,900 and 20,500 years ago, to -118 metres relative to the modern level. Our findings are based on recovered and radiometrically dated fossil corals and coralline algae assemblages, and represent relative sea level at the Great Barrier Reef, rather than GMSL. Subsequently, relative sea level rose at a rate of about 3.5 millimetres per year for around 4,000 years. The rise is consistent with the warming previously observed at 19,000 years ago1,5, but we now show that it occurred just after the 20-metre drop in relative sea level and the related increase in global ice volumes. The detailed structure of our record is robust because the Great Barrier Reef is remote from former ice sheets and tectonic activity. Relative sea level can be influenced by Earth's response to regional changes in ice and water loadings and may differ greatly from GMSL. Consequently, we used glacio-isostatic models to derive GMSL, and find that the Last Glacial Maximum culminated 20,500 years ago in a GMSL low of about -125 to -130 metres.

Maternal-Neonatal Pheromone/Interomone Added to Cat Litter Improves Litter Box Use and Reduces Aggression in Pair-Housed Cats.

Introducing a new cat into a household with one or more resident cats can be a significant source of stress for the cats involved. These studies sought to determine if rabbit maternal-neonatal pheromone (2-methyl-2-butenal [2M2B]) in litter impacted cat social behaviors and litter box use. Study 1 determined that cats preferred to eliminate in litter containing 2M2B; other semiochemicals tested did not change litter box use. Cats prone to aggression were identified in an intermediate pilot study, and eight pairs of these cats were selected for Study 2. In Study 2, cat pairs were provided litter containing either vehicle or 2M2B for 24 hours. Cats experiencing control litter displayed more aggression during the first 6 hours (p < .01) and spent more time using the litter box 12 hours and 18 hours after pairing compared with cats experiencing litter with 2M2B (p = .02). These results suggest 2M2B-infused cat litter may act as an interomone in cats housed domestically to prevent initial occurrences of aggression and may improve cat welfare in multicat households.

MutSα's Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

MutSα is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer's post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents-carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to all-atom molecular dynamics (MD) calculations, we predict that MutSα has a distinct response to each of the three damage types. Via a binary classification tree (a supervised machine learning technique), we identify key hydrogen bond motifs unique to each type of damage and suggest residues for experimental mutation studies. Through a combination of a recently developed clustering (unsupervised learning) algorithm, RMSF calculations, PCA, and correlated motions we predict that each type of damage causes MutSα to explore a specific region of conformation space. Detailed analysis suggests a short range effect for carboplatin-primarily altering the structures and kinetics of residues within 10 angstroms of the damaged DNA-and distinct longer-range effects for cisplatin and FdU. In our simulations, we also observe that a key phenylalanine residue-known to stack with a mismatched or unmatched bases in MMR-stacks with the base complementary to the damaged base in 88.61% of MD frames containing carboplatinated DNA. Similarly, this Phe71 stacks with the base complementary to damage in 91.73% of frames with cisplatinated DNA. This residue, however, stacks with the damaged base itself in 62.18% of trajectory frames with FdU-substituted DNA and has no stacking interaction at all in 30.72% of these frames. Each drug investigated here induces a unique perturbation in the MutSα complex, indicating the possibility of a distinct signaling event and specific repair or death pathway (or set of pathways) for a given type of damage.

Uncovering Large-Scale Conformational Change in Molecular Dynamics without Prior Knowledge.

As the length of molecular dynamics (MD) trajectories grows with increasing computational power, so does the importance of clustering methods for partitioning trajectories into conformational bins. Of the methods available, the vast majority require users to either have some a priori knowledge about the system to be clustered or to tune clustering parameters through trial and error. Here we present non-parametric uses of two modern clustering techniques suitable for first-pass investigation of an MD trajectory. Being non-parametric, these methods require neither prior knowledge nor parameter tuning. The first method, HDBSCAN, is fast-relative to other popular clustering methods-and is able to group unstructured or intrinsically disordered systems (such as intrinsically disordered proteins, or IDPs) into bins that represent global conformational shifts. HDBSCAN is also useful for determining the overall stability of a system-as it tends to group stable systems into one or two bins-and identifying transition events between metastable states. The second method, iMWK-Means, with explicit rescaling followed by K-Means, while slower than HDBSCAN, performs well with stable, structured systems such as folded proteins and is able to identify higher resolution details such as changes in relative position of secondary structural elements. Used in conjunction, these clustering methods allow a user to discern quickly and without prior knowledge the stability of a simulated system and identify both local and global conformational changes.

Intensification of the meridional temperature gradient in the Great Barrier Reef following the Last Glacial Maximum.

Tropical south-western Pacific temperatures are of vital importance to the Great Barrier Reef (GBR), but the role of sea surface temperatures (SSTs) in the growth of the GBR since the Last Glacial Maximum remains largely unknown. Here we present records of Sr/Ca and δ(18)O for Last Glacial Maximum and deglacial corals that show a considerably steeper meridional SST gradient than the present day in the central GBR. We find a 1-2 °C larger temperature decrease between 17° and 20°S about 20,000 to 13,000 years ago. The result is best explained by the northward expansion of cooler subtropical waters due to a weakening of the South Pacific gyre and East Australian Current. Our findings indicate that the GBR experienced substantial meridional temperature change during the last deglaciation, and serve to explain anomalous deglacial drying of northeastern Australia. Overall, the GBR developed through significant SST change and may be more resilient than previously thought.

Open-system coral ages reveal persistent suborbital sea-level cycles.

Sea level is a sensitive index of global climate that has been linked to Earth's orbital variations, with a minimum periodicity of about 21,000 years. Although there is ample evidence for climate oscillations that are too frequent to be explained by orbital forcing, suborbital-frequency sea-level change has been difficult to resolve, primarily because of problems with uranium/thorium coral dating. Here we use a new approach that corrects coral ages for the frequently observed open-system behavior of uranium-series nuclides, substantially improving the resolution of sea-level reconstruction. This curve reveals persistent sea-level oscillations that are too frequent to be explained exclusively by orbital forcing.