Phosphorus and nitrogen adsorption capacities of biochars derived from feedstocks at different pyrolysis temperatures

This study investigates the P and NO3− adsorption capacities of different biochars made from plant waste including rice straw (RSB), Phragmites communis (PCB), sawdust (SDB), and egg shell (ESB) exposed to a range of pyrolysis temperatures (300, 500 and 700 °C). Results indicate that the effect of pyrolysis temperature on the physiochemical properties of biochar varied with feedstock material. Biochars derived from plant waste had limited adsorption or even released P and NO3−, but adsorption of P capacity could be improved by adjusting pyrolysis temperature. The maximum adsorption of P on RSB700, PCB300, and SDB300, produced at pyrolysis temperature of 700, 300 and 300 °C, was 5.41, 7.75 and 3.86 mg g−1, respectively. ESB can absorb both P and NO3−, and its adsorption capacity increased with an increase in pyrolysis temperature. The maximum NO3− and P adsorption for ESB700 was 1.43 and 6.08 mg g−1, respectively. The less negative charge and higher surface area of ESB enabled higher NO3− and P adsorption capacity. The P adsorption process on RSB, PCB, SDB and ESB, and the NO3− adsorption process on ESB were endothermic reactions. However, the NO3− adsorption process on RSB, PCB and SDB was exothermic. The study demonstrates that the use of egg shell biochar may be an effective way to remove, through adsorption, P and NO3− from wastewater

Role of WD domain of ATG16L1 and LC3 associated endocytosis in control of influenza virus infection

Autophagy is a conserved self-eating process that delivers intracellular material to lysosomes for degradation (Yu, Chen, & Tooze, 2018). Autophagy is activated by multiple cellular stresses, including starvation and pathogen infection and plays crucial roles in maintaining cellular homeostasis and in controlling pathogen infection and inflammation (Florey, Gammoh, Kim, Jiang, & Overholtzer, 2015) (Levine & Kroemer, 2008). Degradation during conventional (or canonical) autophagy is facilitated by autophagy protein ATG8/LC3 (LC3) which facilitates fusion of double-membraned autophagosomes with lysosomes. Recent work has revealed non-canonical autophagy pathways that use LC3 to target single-membraned endolysosome compartments to lysosomes during the uptake of extracellular material (Heckmann, Boada-Romero, Cunha, Magne, & Green, 2017). LC3-associated phagocytosis (LAP) has been used to describe recruitment of LC3 to phagosomes in phagocytic cells, while LC3-associated endocytosis describes a similar pathway targeting endosomes in non-phagocytic cells (Heckmann et al 2019). Conventional autophagy is a well-established as a defence against infection, but the roles played by non-canonical autophagy during infection ‘in vivo’ are less clear. This study uses a mouse model (δWD) with systemic loss of non-canonical autophagy to study the roles played by LAP and LC3-associated endocytosis during influenza A virus (IAV) infection. The δWD mice were exquisitely sensitive to IAV with elevated lung virus titres leading to exacerbated pro-inflammatory cytokine responses, fulminant pneumonia, extensive pulmonary inflammation and high mortality. Bone marrow transfers from control mice were unable to protect δWD mice from IAV. Protection against IAV infection ‘in vivo’ was therefore independent of LAP in phagocytic cells. In a reciprocal experiment LysMcre was used to delete LAP specifically from myeloid cells. These LAP-/- mice, which maintain LC3-associated endocytosis in other tissues were resistant to IAV suggesting that LC3 associated endocytosis, rather than LAP, provides a defence against IAV. Ex vivo studies suggest that this defence is most likely to take place in the epithelial cells that line the respiratory tract

Understanding short-timescale neuronal firing sequences via bias matrices

The brain generates persistent neuronal firing sequences across varying timescales. The short-timescale (~100ms) sequences are believed to be crucial in the formation and transfer of memories. Large-amplitude local field potentials known as sharp-wave ripples (SWRs) occur irregularly in hippocampus when an animal has minimal interaction with its environment, such as during resting, immobility, or slow-wave sleep. SWRs have been long hypothesized to play a critical role in transferring memories from the hippocampus to the neocortex [1]. While sequential firing during SWRs is known to be biased by the previous experiences of the animal, the exact relationship of the short-timescale sequences during SWRs and longer-timescale sequences during spatial and nonspatial behaviors is still poorly understood. One hypothesis is that the sequences during SWRs are “replays” or “preplays” of “master sequences”, which are sequences that closely mimic the order of place fields on a linear track [2,3]. Rather than particular hard-coded “master” sequences, an alternative explanation of the observed correlations is that similar sequences arise naturally from the intrinsic biases of firing between pairs of cells. To distinguish these and other possibilities, one needs mathematical tools beyond the center-of-mass sequences and Spearman’s rank-correlation coefficient that are currently used

Theta-modulation drives the emergence of connectivity patterns underlying replay in a network model of place cells

Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in any environment. Therefore for any given trajectory one observes a repeatable sequence of place cell activations. When the animal is quiescent or sleeping, one can observe similar sequences of activation known as replay, which underlie the process of memory consolidation. However, it remains unclear how replay is generated. Here we show how a temporally asymmetric plasticity rule during spatial exploration gives rise to spontaneous replay in a model network by shaping the recurrent connectivity to reflect the topology of the learned environment. Crucially, the rate of this encoding is strongly modulated by ongoing rhythms. Oscillations in the theta range optimize learning by generating repeated pre-post pairings on a time-scale commensurate with the window for plasticity, while lower and higher frequencies generate learning rates which are lower by orders of magnitude

Personalized Negative Reservoir for Incremental Learning in Recommender Systems

Recommender systems have become an integral part of online platforms. Every day the volume of training data is expanding and the number of user interactions is constantly increasing. The exploration of larger and more expressive models has become a necessary pursuit to improve user experience. However, this progression carries with it an increased computational burden. In commercial settings, once a recommendation system model has been trained and deployed it typically needs to be updated frequently as new client data arrive. Cumulatively, the mounting volume of data is guaranteed to eventually make full batch retraining of the model from scratch computationally infeasible. Naively fine-tuning solely on the new data runs into the well-documented problem of catastrophic forgetting. Despite the fact that negative sampling is a crucial part of training with implicit feedback, no specialized technique exists that is tailored to the incremental learning framework. In this work, we take the first step to propose, a personalized negative reservoir strategy which is used to obtain negative samples for the standard triplet loss. This technique balances alleviation of forgetting with plasticity by encouraging the model to remember stable user preferences and selectively forget when user interests change. We derive the mathematical formulation of a negative sampler to populate and update the reservoir. We integrate our design in three SOTA and commonly used incremental recommendation models. We show that these concrete realizations of our negative reservoir framework achieve state-of-the-art results in standard benchmarks, on multiple standard top-k evaluation metrics

Theta-modulation drives the emergence of connectivity patterns underlying replay in a network model of place cells

Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in any environment. Therefore for any given trajectory one observes a repeatable sequence of place cell activations. When the animal is quiescent or sleeping, one can observe similar sequences of activation known as replay, which underlie the process of memory consolidation. However, it remains unclear how replay is generated. Here we show how a temporally asymmetric plasticity rule during spatial exploration gives rise to spontaneous replay in a model network by shaping the recurrent connectivity to reflect the topology of the learned environment. Crucially, the rate of this encoding is strongly modulated by ongoing rhythms. Oscillations in the theta range optimize learning by generating repeated pre-post pairings on a time-scale commensurate with the window for plasticity, while lower and higher frequencies generate learning rates which are lower by orders of magnitude

The ATG5-binding and coiled coil domains of ATG16L1 maintain autophagy and tissue homeostasis in mice independently of the WD domain required for LC3 associated phagocytosis

Macroautophagy/autophagy delivers damaged proteins and organelles to lysosomes for degradation, and plays important roles in maintaining tissue homeostasis by reducing tissue damage. The translocation of LC3 to the limiting membrane of the phagophore, the precursor to the autophagosome, during autophagy provides a binding site for autophagy cargoes, and facilitates fusion with lysosomes. An autophagy-related pathway called LC3-associated phagocytosis (LAP) targets LC3 to phagosome and endosome membranes during uptake of bacterial and fungal pathogens, and targets LC3 to swollen endosomes containing particulate material or apoptotic cells. We have investigated the roles played by autophagy and LAP in vivo by exploiting the observation that the WD domain of ATG16L1 is required for LAP, but not autophagy. Mice lacking the linker and WD domains, activate autophagy, but are deficient in LAP. The LAP −/- mice survive postnatal starvation, grow at the same rate as littermate controls, and are fertile. The liver, kidney, brain and muscle of these mice maintain levels of autophagy cargoes such as LC3 and SQSTM1/p62 similar to littermate controls, and prevent accumulation of SQSTM1 inclusions and tissue damage associated with loss of autophagy. The results suggest that autophagy maintains tissue homeostasis in mice independently of LC3-associated phagocytosis. Further deletion of glutamate E230 in the coiled-coil domain required for WIPI2 binding produced mice with defective autophagy that survived neonatal starvation. Analysis of brain lysates suggested that interactions between WIPI2 and ATG16L1 were less critical for autophagy in the brain, which may allow a low level of autophagy to overcome neonatal lethality. Abbreviations: CCD: coiled-coil domain; CYBB/NOX2: cytochrome b-245: beta polypeptide; GPT/ALT: glutamic pyruvic transaminase: soluble; LAP: LC3-associated phagocytosis; LC3: microtubule-associated protein 1 light chain 3; MEF: mouse embryonic fibroblast; NOD: nucleotide-binding oligomerization domain; NADPH: nicotinamide adenine dinucleotide phosphate; RUBCN/Rubicon: RUN domain and cysteine-rich domain containing Beclin 1-interacting protein; SLE: systemic lupus erythematosus; SQSTM1/p62: sequestosome 1; TLR: toll-like receptor; TMEM: transmembrane protein; TRIM: tripartite motif-containing protein; UVRAG: UV radiation resistance associated gene; WD: tryptophan-aspartic acid; WIPI: WD 40 repeat domain: phosphoinositide interacting

Pyrimido[4,5‐ d ]pyrimidin‐4(1 H )‐one Derivatives as Selective Inhibitors of EGFR Threonine 790 to Methionine 790 (T790M) Mutants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99681/1/8387_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99681/2/anie_201302313_sm_miscellaneous_information.pd

Pyrimido[4,5‐ d ]pyrimidin‐4(1 H )‐one Derivatives as Selective Inhibitors of EGFR Threonine 790 to Methionine 790 (T790M) Mutants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99673/1/8545_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99673/2/ange_201302313_sm_miscellaneous_information.pd