Cellular and Molecular Analysis of Chromosomal Passenger Complex in Vertebrate Cells

Sucessful cell division is primarily controlled by temporal and spatial regulation of two critical events in the cell cycle: the faithful replication of chromosomes and the accurate segregation of the replicated chromosomes. Of all the cellular proteins involved in regulating these processes, the chromosomal passenger complex displays some of the most visually striking patterns of behaviours during mitosis. The chromosomal passenger proteins associate with chromosomes as cells prepare to segregate them during mitosis. Subsequently, when chromosomes are aligned on the spindle microtubules that do the mechanical work of segregation, the passenger proteins become concentrated in distinct foci between paired kinetochores—the protein-based structures on chromosomes where the microtubules attach. Then, as chromosomes start to segregate, the passenger proteins abruptly dissociate from the kinetochores and instead localize to the central spindle in the area midway between the separating chromosomes. This ultimately becomes the midbody during cytokinesis. The first protein found to display such dramatic changes in localization during nuclear division was named INCENP. Three further proteins—Aurora B, Survivin and Borealin were later found to show localization patterns similar to INCENP. Structural analyses revealed that these four proteins form a well conserved chromosomal passenger complex throughout mitosis, in which INCENP acts as a scaffold to recruit Survivin and Borealin to its N-terminus, while Aurora B associates with its C-terminus. The function of this complex parallels its dynamic localization. These include roles in spindle assembly, correcting erroneous kinetochore microtubule interactions that are inappropriate for chromosome alignment, signaling to the spindle checkpoint, and the completion of cytokinesis. Functional analysis of kinetochore proteins in vertebrates using DT40 cells has greatly improved our understanding of kinetochore assembly, kinetochore structure and functions in guiding cell division. Following the identification of chicken Aurora B, Borealin/Dasra B and Dasra A, we are now able to address the pleiotropic functions of the conserved chromosomal passenger complex in DT40 cells using gene disruption. Gene disruption of INCENP using a novel promoter hijack technique in DT40 cells has demonstrated that accurate cell division requires coordination of spindle dynamics, chromosome segregation and cell cleavage and that INCENP integrates these diverse processes. Recent concentrated efforts on elucidating the precise contribution of each subunit in localizing the complex have provided great insights of how CPC executes its mitotic function. Here, through introducing a series of INCENP structural mutants into this sophisticated INCENP knockout system, my in vivo data presented here indicated that interaction between INCENP-Aurora B is essential for cell division. Remarkably, dissociation of Aurora B from INCENP does not disturb the other passengers targeting to the centromere, but Aurora B activity through binding and activation by INCENP plays a direct role in guiding the transfer of the complex to the spindle midzone. Furthermore, a feed-back loop involving phosphorylation of INCENP at its TSS motif by Aurora B is essential for cell viability, even though its disruption by mutation to TAA does not prevent the passengers eventually transfer to spindle midzone and midbody. Thus, this final step to maximize the activity of Aurora B is a critical function of INCENP. The outstanding question I have addressed in my study is why the passenger proteins are interdependent. More importantly, my work reveals that the intrinsic modulation within chromosomal passenger complex directed by the interactions between INCENP and Aurora B regulates the transfer of the complex to the spindle midzone and midbody. Thus, the results here with previous study suggest that regulation of the centromere and spindle midzone targeting of the complex involves two distinctly intrinsic mechanisms directed by two targeting sub-complexes within CPC, in which INCENP, Borealin and Survivin form the core sub-complex for centromere targeting, and Aurora B regulated by INCENP forms the sub-complex serving to direct the CPC transfer to spindle midzone by modulation of Aurora B activity

Modeling of counter-current spontaneous imbibition in independent capillaries with unequal diameters

Spontaneous imbibition is a crucial process for oil recovery from fractured and unconventional reservoirs. Herein, with the assumption of capillaries being independent, a new mathematical model for spontaneous imbibition is proposed and solved using a numerical method. The simulated results show that the wetting phase preferentially enters smaller capillaries where the advancement velocity is higher than that in larger ones, while the non-wetting phase can be displaced out in the larger capillaries. In addition, the effect of fluid viscosity ratio on counter-current imbibition is analyzed. The results show that imbibition velocity becomes higher with the increase in the viscosity ratio. When the viscosity of the non-wetting phase is larger than that of the wetting phase, the end pressure gradually increases as the imbibition front advances. In contrast, when the viscosity of the non-wetting phase is less than that of the wetting phase, the end pressure decreases with the infiltration. With a higher viscosity ratio of non-wetting and wetting phase, the heterogeneity of the interface advancement among different capillaries increases.Cited as: Chen, K., Xu, H., Zhang, Z., Meng, Q., Zhang, T. Modeling of counter-current spontaneous imbibition in independent capillaries with unequal diameters. Capillarity, 2022, 5(6): 115-122. https://doi.org/10.46690/capi.2022.06.0

SRDA-Net: Super-Resolution Domain Adaptation Networks for Semantic Segmentation

Recently, Unsupervised Domain Adaptation was proposed to address the domain shift problem in semantic segmentation task, but it may perform poor when source and target domains belong to different resolutions. In this work, we design a novel end-to-end semantic segmentation network, Super-Resolution Domain Adaptation Network (SRDA-Net), which could simultaneously complete super-resolution and domain adaptation. Such characteristics exactly meet the requirement of semantic segmentation for remote sensing images which usually involve various resolutions. Generally, SRDA-Net includes three deep neural networks: a Super-Resolution and Segmentation (SRS) model focuses on recovering high-resolution image and predicting segmentation map; a pixel-level domain classifier (PDC) tries to distinguish the images from which domains; and output-space domain classifier (ODC) discriminates pixel label distributions from which domains. PDC and ODC are considered as the discriminators, and SRS is treated as the generator. By the adversarial learning, SRS tries to align the source with target domains on pixel-level visual appearance and output-space. Experiments are conducted on the two remote sensing datasets with different resolutions. SRDA-Net performs favorably against the state-of-the-art methods in terms of accuracy and visual quality. Code and models are available at https://github.com/tangzhenjie/SRDA-Net

Data Driven Chiller Plant Energy Optimization with Domain Knowledge

Refrigeration and chiller optimization is an important and well studied topic in mechanical engineering, mostly taking advantage of physical models, designed on top of over-simplified assumptions, over the equipments. Conventional optimization techniques using physical models make decisions of online parameter tuning, based on very limited information of hardware specifications and external conditions, e.g., outdoor weather. In recent years, new generation of sensors is becoming essential part of new chiller plants, for the first time allowing the system administrators to continuously monitor the running status of all equipments in a timely and accurate way. The explosive growth of data flowing to databases, driven by the increasing analytical power by machine learning and data mining, unveils new possibilities of data-driven approaches for real-time chiller plant optimization. This paper presents our research and industrial experience on the adoption of data models and optimizations on chiller plant and discusses the lessons learnt from our practice on real world plants. Instead of employing complex machine learning models, we emphasize the incorporation of appropriate domain knowledge into data analysis tools, which turns out to be the key performance improver over state-of-the-art deep learning techniques by a significant margin. Our empirical evaluation on a real world chiller plant achieves savings by more than 7% on daily power consumption.Comment: CIKM2017. Proceedings of the 26th ACM International Conference on Information and Knowledge Management. 201

Identification and Separation of Transformed Products of tert-Butylhydroquinone Added in Different Oils and Fats during Storage

The transformation of tert-butylhydroquinone (TBHQ) added in lard, soybean and palm oil was investigated during storage. The results showed that when the storage time was extended, the sum of the remaining amount of TBHQ and the production of 2-tert-butyl-1,4-benzoquinone (TBBQ) in oil samples was less than the initial amount of TBHQ added. The same chromatographic peaks except for TBHQ and TBBQ were found in the gas chromatograms of the methanol extracts from different oil samples. The unknown chromatographic peaks were isolated and purified by preparative liquid chromatography (Prep-LC), and their structures were identified and characterized by ultra-high performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS), nuclear magnetic resonance (NMR), ultraviolet (UV) spectroscopy, and Fourier transform infrared (FTIR) spectroscopy. These results showed that the conversion products of added TBHQ were the same in different oils and fats, including TBBQ and 2-methylallyl-hydroquinone (MAHQ)

Differentially Private Histogram Publication

Abstract — Differential privacy (DP) is a promising scheme for releasing the results of statistical queries on sensitive data, with strong privacy guarantees against adversaries with arbitrary background knowledge. Existing studies on DP mostly focus on simple aggregations such as counts. This paper investigates the publication of DP-compliant histograms, which is an important analytical tool for showing the distribution of a random variable, e.g., hospital bill size for certain patients. Compared to simple aggregations whose results are purely numerical, a histogram query is inherently more complex, since it must also determine its structure, i.e., the ranges of the bins. As we demonstrate in the paper, a DP-compliant histogram with finer bins may actually lead to significantly lower accuracy than a coarser one, since the former requires stronger perturbations in order to satisfy DP. Moreover, the histogram structure itself may reveal sensitive information, which further complicates the problem. Motivated by this, we propose two novel algorithms, namely NoiseFirst and StructureFirst, for computing DP-compliant his-tograms. Their main difference lies in the relative order of the noise injection and the histogram structure computation steps. NoiseFirst has the additional benefit that it can improve the accuracy of an already published DP-complaint histogram computed using a naı̈ve method. Going one step further, we extend both solutions to answer arbitrary range queries. Exten-sive experiments, using several real data sets, confirm that the proposed methods output highly accurate query answers, and consistently outperform existing competitors. I

Temperature controlled microcapsule loaded with Perilla essential oil and its application in preservation of peaches

In this study, Perilla frutescens essential oil (PEO) loaded microcapsules (PEOM) were successfully prepared and their thermal stability, temperature-responsive releasing effect, antioxidant activity, antibacterial activity, and preservation of peach were systematically investigated. PEOM showed excellent encapsulation efficiency (91.5%) with a core-shell ratio of 1.4:1 and exhibited high thermal stability, indicating that PEOM could effectively maintain PEO release rate. In vitro assays indicated that the optimal kinetic model for PEO release fitted well with first order with a diffusion mechanism. A high level of antioxidant and antibacterial activity of PEOM was maintained. In addition, owing to its sustained release, PEOM could prolong the shelf life of peaches significantly. Therefore, PEOM has potential application and development prospects in the field of food preservation

Pressure-induced superconductivity in topological type II Dirac semimetal NiTe₂

Very recently, NiTe₂ has been reported to be a type II Dirac semimetal with Dirac nodes near the Fermi surface. Furthermore, it is unveiled that NiTe₂ presents the Hall Effect, which is ascribed to orbital magnetoresistance. The physical properties behavior of NiTe₂ under high pressure attracts us. In this paper, we investigate the electrical properties of polycrystalline NiTe₂ by application of pressure ranging from 3.4GPa to 54.45Gpa. Superconductivity emerges at critical pressure 12GPa with a transition temperature of 3.7K, and Tc reaches its maximum, 6.4 K, at the pressure of 52.8GPa. Comparing with the superconductivity in MoP, we purposed the possibility of topological superconductivity in NiTe₂. Two superconductivity transitions are observed with pressure increasing in single crystal