970 research outputs found
Large scale total synthesis of apoptolidinone and progress towards the total synthesis of ammocidin
Apoptolidin 1.1 was isolated in 1997 by Hayakawa and co-workers from a soil
bacterium Nocardiopsis sp. during screening for specific apoptosis inducers. The
primary biological test revealed that this polyketide macrolide induced apoptosis in cells
transformed with the adenovirus type E1A oncognene, but not normal cells. This
dissertation describes the latest studies in understanding of apoptolidin’s biological
activity mechanism and previous contributions towards its total synthesis. Synthesizing
apoptolidinone 1.26 by an intra-molecular Horner-Wadsworth-Emmons approach
featuring a Suzuki coupling, cross metathesis and two diastereoselective aldol reactions is
discussed. 15 mg apoptolidinone is prepared via our previously developed intramolecular
Suzuking coupling approach.
Ammocidin 3.1, which was found to induce apoptosis in Ba/F3-v12 cells in an IL-
3 free medium, is a specific apoptosis inducer discovered by Hayakawa and co-workers
in 2001 from Saccharothrix sp. AJ9571. A strategy featuring Suzuki coupling, cross
metathesis, Yamaguchi macrolactonization and three asymmetric aldol reactions was
applied to the total synthesis of ammocidinone 3.6, the aglycone of ammocidin. The
preparation of the key building blocks was discussed in the following chapter: aldehyde
3.8 (C14-C19) was synthesized via Sharpless asymmetric epoxidation; ethyl ketone 3.9’ (C20-C28) was prepared via Kobayashi and Crimmins’s asymmetric aldol
methodologies; aldehyde 3.14 (C7-C13) was generated by Brown crotylation and cross
metathesis
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
Time series forecasting is an important and forefront task in many real-world
applications. However, most of time series forecasting techniques assume that
the training data is clean without anomalies. This assumption is unrealistic
since the collected time series data can be contaminated in practice. The
forecasting model will be inferior if it is directly trained by time series
with anomalies. Thus it is essential to develop methods to automatically learn
a robust forecasting model from the contaminated data. In this paper, we first
statistically define three types of anomalies, then theoretically and
experimentally analyze the loss robustness and sample robustness when these
anomalies exist. Based on our analyses, we propose a simple and efficient
algorithm to learn a robust forecasting model. Extensive experiments show that
our method is highly robust and outperforms all existing approaches. The code
is available at https://github.com/haochenglouis/RobustTSF.Comment: Accepted by the 12th International Conference on Learning
Representations (ICLR 2024
Construction of CaF2-appended PVA nanofibre scaffold
In this work, a new material, calcium fluoride ( CaF2 )-appended poly(vinyl alcohol) (PVA) nanofibre scaffold, was prepared through electrospinning technique successfully. Scanning electron microscopy result showed that the morphology of the fibres was uniform and smooth, and the average diameter of the fibres was about 200 nm. Transmission electron microscopy results showed that many CaF2 nanoparticles were well dispersed in the PVA fibre matrix. The water-resistant ability of the scaffold was improved through intermolecular crosslinking of PVA by formaldehyde vapour. This novel material seems to be a promising scaffold for bone tissue engineering
Analysis of Spatial Travel Association Rules for Rail Transit Based on AFC and POI Data
In order to explore the spatial distribution rules and causes of urban rail transit passenger travel, this paper mines the spatial 1-frequent itemset and 2-frequent itemsets of weekdays and weekends metro passenger travel based on Apriori algorithm using the continuous week of Automatic Fare Collection System (AFC) swipe card. At the same time, the K-Means algorithm is used to cluster the subway stations and explore the causes of association rules by combining the Point of Interest (POI) data of the same period within the radiation range of the subway stations. The study shows that the spatial distribution pattern of inbound and outbound passenger flow of Shanghai rail transit is consistent between weekdays and weekends, and the outbound passenger flow is more concentrated than the inbound passenger flow, and the significance of weekends is higher; the spatial distribution of metro stations is "circled"; the analysis of the high-lift association rules show that a large passenger flow group centered on the type 3 station is formed in the spatial location, and the passenger flow within the group is mainly commuter flow with separation of employment and residence. The association rule mining of metro passenger travel data is beneficial to understanding the spatial distribution pattern and causes of metro ridership, which can provide reference for rail network planning and operation management
Partition of a Binary Matrix into k
A biclustering problem consists of objects and an attribute vector for each object. Biclustering aims at finding a bicluster—a subset of objects that exhibit similar behavior across a subset of attributes, or vice versa. Biclustering in matrices with binary entries (“0”/“1”) can be simplified into the problem of finding submatrices with entries of “1.” In this paper, we consider a variant of the biclustering problem: the k-submatrix partition of binary matrices problem. The input of the problem contains an n×m matrix with entries (“0”/“1”) and a constant positive integer k. The k-submatrix partition of binary matrices problem is to find exactly k submatrices with entries of “1” such that these k submatrices are pairwise row and column exclusive and each row (column) in the matrix occurs in exactly one of the k submatrices. We discuss the complexity of the k-submatrix partition of binary matrices problem and show that the problem is NP-hard for any k≥3 by reduction from a biclustering problem in bipartite graphs
Quantitative and functional post-translational modification proteomics reveals that TREPH1 plays a role in plant thigmomorphogenesis
Plants can sense both intracellular and extracellular mechanical forces and
can respond through morphological changes. The signaling components responsible
for mechanotransduction of the touch response are largely unknown. Here, we
performed a high-throughput SILIA (stable isotope labeling in
Arabidopsis)-based quantitative phosphoproteomics analysis to profile changes
in protein phosphorylation resulting from 40 seconds of force stimulation in
Arabidopsis thaliana. Of the 24 touch-responsive phosphopeptides identified,
many were derived from kinases, phosphatases, cytoskeleton proteins, membrane
proteins and ion transporters. TOUCH-REGULATED PHOSPHOPROTEIN1 (TREPH1) and MAP
KINASE KINASE 2 (MKK2) and/or MKK1 became rapidly phosphorylated in
touch-stimulated plants. Both TREPH1 and MKK2 are required for touch-induced
delayed flowering, a major component of thigmomorphogenesis. The treph1-1 and
mkk2 mutants also exhibited defects in touch-inducible gene expression. A
non-phosphorylatable site-specific isoform of TREPH1 (S625A) failed to restore
touch-induced flowering delay of treph1-1, indicating the necessity of S625 for
TREPH1 function and providing evidence consistent with the possible functional
relevance of the touch-regulated TREPH1 phosphorylation. Bioinformatic analysis
and biochemical subcellular fractionation of TREPH1 protein indicate that it is
a soluble protein. Altogether, these findings identify new protein players in
Arabidopsis thigmomorphogenesis regulation, suggesting that protein
phosphorylation may play a critical role in plant force responses
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