Proteomic Analysis of Anticancer TCMs Targeted at Mitochondria

Traditional Chinese medicine (TCM) is a rich resource of anticancer drugs. Increasing bioactive natural compounds extracted from TCMs are known to exert significant antitumor effects, but the action mechanisms of TCMs are far from clear. Proteomics, a powerful platform to comprehensively profile drug-regulated proteins, has been widely applied to the mechanistic investigation of TCMs and the identification of drug targets. In this paper, we discuss several bioactive TCM products including terpenoids, flavonoids, and glycosides that were extensively investigated by proteomics to illustrate their antitumor mechanisms in various cancers. Interestingly, many of these natural compounds isolated from TCMs mostly exert their tumor-suppressing functions by specifically targeting mitochondria in cancer cells. These TCM components induce the loss of mitochondrial membrane potential, the release of cytochrome c, and the accumulation of ROS, initiating apoptosis cascade signaling. Proteomics provides systematic views that help to understand the molecular mechanisms of the TCM in tumor cells; it bears the inherent limitations in uncovering the drug-protein interactions, however. Subcellular fractionation may be coupled with proteomics to capture and identify target proteins in mitochondria-enriched lysates. Furthermore, translating mRNA analysis, a new technology profiling the drug-regulated genes in translatome level, may be integrated into the systematic investigation, revealing global information valuable for understanding the action mechanism of TCMs

AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis

Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments. Existing methods make great efforts to align the whole image to corresponding aspects. However, different regions of the image may relate to different aspects in the same sentence, and coarsely establishing image-aspect alignment will introduce noise to aspect-based sentiment analysis (i.e., visual noise). Besides, the sentiment of a specific aspect can also be interfered by descriptions of other aspects (i.e., textual noise). Considering the aforementioned noises, this paper proposes an Aspect-oriented Method (AoM) to detect aspect-relevant semantic and sentiment information. Specifically, an aspect-aware attention module is designed to simultaneously select textual tokens and image blocks that are semantically related to the aspects. To accurately aggregate sentiment information, we explicitly introduce sentiment embedding into AoM, and use a graph convolutional network to model the vision-text and text-text interaction. Extensive experiments demonstrate the superiority of AoM to existing methods. The source code is publicly released at https://github.com/SilyRab/AoM.Comment: Findings of ACL 202

The Outflow from the Luminous Young Stellar Object IRAS 20126+4104: From 4000 AU to 0.4 pc

We have imaged the outflow from the luminous young stellar object IRAS 20126+4104 (I20126) with the Submillimeter Array in CO (3-2), HCN (4-3), and SiO (5-4) at 1''-2'' resolutions within a radius of ~20'' from the central driving source. Our observations reveal at least three different components of the outflowing gas: (1) A compact (~4000 AU) bipolar outflow toward the central young stellar object. With a dynamical timescale of ~120 yr, this component represents a very new jet/outflow activity in I20126. (2) A collimated outflow with an extent of ~0.2 pc previously detected in SiO (2-1). Both morphology and kinematics favor this component being a jet-driven bow shock system. (3) An S-shaped CO outflow with an extent of ~0.4 pc. This component records the precession history very well. Its kinematic feature, where the velocity increases with distance from the YSO, indicates, independently of other evidence, that the outflow axis is moving toward the plane of the sky. The three outflow components record the history of the primary jet precession over scales ranging from a few hundred AU to approximately 0.4 pc. Our results indicate that CO (3-2) emission is a good tracer to probe the primary jet. The gas densities and SiO relative abundances in I20126 shocks are estimated using the large velocity gradient calculations. The inferred SiO abundances of (1-5) × 10-8 in I20126 outflow lobes are comparable to the expected enhancement at shocked regions

Resilience-enhancing solution to mitigate risk for sustainable supply chain-an empirical study of elevator manufacturing

As the complexity of supply chains increases, the enhancement of resilience for mitigating sustainable disruption risks in supply chains is an important issue. Quality function deployment (QFD) has been successfully applied in many domains to solve multicriteria decision-making (MCDM) problems. However, research on developing two houses of quality to connect sustainable supply chain disruption risks, resilience capacities, and resilience-enhancing features in elevator manufacturing supply chains by using the MCDM approach is lacking. This study aims to develop a framework for exploring useful decision-making by integrating the MCDM approach and QFD. By applying the framework, supply chain resilience can be improved by identifying the major sustainable risks and the key resilience to mitigate these risks. Important managerial insights and practical implications are obtained from the framework implementation in a case study of the elevator manufacturing industry. To strengthen resilience and thus mitigate key risks, the most urgent tasks are to connect the working site and the backstage to enhance product development and design and to share real-time job information. When these features are strengthened, agility, capacity, and visibility can be improved. Finally, unexpected events lead to changes in supplier delivery dates, and factors such as typhoon and lack of critical capacities/skilled employees with the greatest impact can be alleviated. This framework will provide an effective and pragmatic approach for constructing sustainable supply chain risk resilience in the elevator manufacturing industry.</p

The Hot and Clumpy Molecular Cocoon Surrounding the Ultracompact HII Region G5.89-0.39

We present observations of CH3CN (12-11) emission at a resolution of 2" toward the shell-like ultracompact HII region G5.89-0.39 with the Submillimeter Array. The integrated CH3CN emission reveals dense and hot molecular cocoon in the periphery of the HII region G5.89-0.39, with a CH3CN deficient region roughly centered at G5.89-0.39. By analyzing the CH3CN emission using population diagram analysis, we find, for the first time, a decreasing temperature structure from 150 to 40 K with the projected distance from Feldt's star, which is thought to be responsible for powering the HII region. Our results further indicate that the majority of the heating energy in the observed dense gas is supplied by the Feldt's star. From the derived CH3CN column density profile, we conclude that the dense gas is not uniformly-distributed but centrally-concentrated, with a power-law exponent of 5.5 for r < 8000 AU, and 2.0 for 8000 AU < r < 20000 AU, where r is the distance to Feldt's star. The estimated large power index of 5.5 can be attributed to an enhancement of CH3CN abundance in the close vicinity of Feldt's star.Comment: accepted for publication in The Astrophysical Journal Letter

Maize straw application as an interlayer improves organic carbon and total nitrogen concentrations in the soil profile: A four-year experiment in a saline soil

Soil salinization is a critical environmental issue restricting agricultural production. Deep return of straw to the soil as an interlayer (at 40 cm depth) has been a popular practice to alleviate salt stress. However, the legacy effects of straw added as an interlayer at different rates on soil organic carbon (SOC) and total nitrogen (TN) in saline soils still remain inconclusive. Therefore, a four-year (2015–2018) field experiment was conducted with four levels (i.e., 0, 6, 12 and 18 Mg ha–1) of straw returned as an interlayer. Compared with no straw interlayer (CK), straw addition increased SOC concentration by 14–32 and 11–57% in the 20–40 and 40–60 cm soil layers, respectively. The increases in soil TN concentration (8–22 and 6–34% in the 20–40 and 40–60 cm soil layers, respectively) were lower than that for SOC concentration, which led to increased soil C:N ratio in the 20–60 cm soil depth. Increases in SOC and TN concentrations in the 20–60 cm soil layer with straw addition led to a decrease in stratification ratios (0–20 cm:20–60 cm), which promoted uniform distributions of SOC and TN in the soil profile. Increases in SOC and TN concentrations were associated with soil salinity and moisture regulation and improved sunflower yield. Generally, compared with other treatments, the application of 12 Mg ha–1 straw had higher SOC, TN and C:N ratio, and lower soil stratification ratio in the 2015–2017 period. The results highlighted that legacy effects of straw application as an interlayer were maintained for at least four years, and demonstrated that deep soil straw application had a great potential for improving subsoil fertility in salt-affected soils.publishedVersio

Finite production rate model with backlogging, service level constraint, rework, and random breakdown

In most real-life production systems, both random machine breakdown and the production of nonconforming items are inevitable, and adopting a backlogging policy with a predetermined minimum acceptable service level can sometimes be an effective strategy to help the management reduce operating cost or smoothen the production schedule. With the aim of addressing the aforementioned practical situations in production, this study explores the optimal production runtime for the finite production rate (FPR) model with allowable backlogging and service level constraint, rework of defective products, and random machine breakdown. Mathematical modelling is employed along with optimization techniques to derive the optimal production runtime that minimizes the long-run average system costs for the proposed FPR model. The joint effects of the allowable backlogging with a planned service level, rework, and random machine breakdown on optimal runtime decision have been carefully investigated through a numerical example and sensitivity analysis. As a result, important insights regarding various system parameters are revealed in order to enable the management to better understand, plan, and control such a practical production system