Telomeres are present at the ends of all eukaryotic chromosomes. Human telomeres play an important role in critical processes underlying genome stability, cancer, and aging, and their importance was ...recognized via the award of the 2009 Nobel Prize in Physiology or Medicine. Chemistry has made vast and almost unparalleled contributions to telomere biology. This critical review highlights the contributions of chemistry in human telomeres and summarizes the significant development of human telomere biology. First, I provide an overview of the advances in understanding of the structures and functions of human telomeres. Second, I focus on the current efforts on developing various chemical approaches to targeting human telomeres and telomerase for the treatment of cancer. Third, studies on a newly discovered telomeric repeat-containing RNA are discussed in detail. Last, future challenges in the field are outlined, including perspectives of both chemistry and biology (412 references).
This paper proposes a data-driven cooperative method for load frequency control (LFC) of the multi-area power system based on multi-agent deep reinforcement learning (MA-DRL) in continuous action ...domain. The proposed method can nonlinearly and adaptively derive the optimal coordinated control strategies for multiple LFC controllers through centralized learning and decentralized implementation. The centralized learning is achieved by MA-DRL based on a global action-value function to quantify overall LFC performance of the power system. To solve the MA-DRL problem, multi-agent deep deterministic policy gradient (DDPG) is derived to adjust control agents' parameters considering the nonlinear generator behaviors. For implementation, each individual controller only needs local information in its control area to deliver optimal control signals. Numerical simulations on a three-area power system and the fully-modeled New-England 39-bus system demonstrate that the proposed method can effectively minimize control errors against stochastic frequency variations caused by load and renewable power fluctuations.
Although clinical studies have shown promise for targeting programmed cell death protein-1 (PD-1) and ligand (PD-L1) signaling in non-small cell lung cancer (NSCLC), the factors that predict which ...subtype patients will be responsive to checkpoint blockade are not fully understood.
We performed an integrated analysis on the multiple-dimensional data types including genomic, transcriptomic, proteomic, and clinical data from cohorts of lung adenocarcinoma public (discovery set) and internal (validation set) database and immunotherapeutic patients. Gene set enrichment analysis (GSEA) was used to determine potentially relevant gene expression signatures between specific subgroups.
We observed that
mutation significantly increased expression of immune checkpoints and activated T-effector and interferon-γ signature. More importantly, the
comutated subgroup manifested exclusive increased expression of PD-L1 and a highest proportion of
Meanwhile,
or
-mutated tumors showed prominently increased mutation burden and specifically enriched in the transversion-high (TH) cohort. Further analysis focused on the potential molecular mechanism revealed that
or
mutation altered a group of genes involved in cell-cycle regulating, DNA replication and damage repair. Finally, immunotherapeutic analysis from public clinical trial and prospective observation in our center were further confirmed that
or
mutation patients, especially those with co-occurring
mutations, showed remarkable clinical benefit to PD-1 inhibitors.
This work provides evidence that
and
mutation in lung adenocarcinoma may be served as a pair of potential predictive factors in guiding anti-PD-1/PD-L1 immunotherapy.
.
More and more users are overusing social media and the situation is getting worse, yet there is still a lack of research on social media addiction. Based on attachment theory and the ...Cognition-Affect-Conation (CAC) framework, this study combines the perception of intrinsic motivation and the technical features of social media as extrinsic motivators and explores the formative factors in social media addiction. The results show that social media addiction is determined by an individual's emotional and functional attachment to the platform, and that attachment is in turn influenced by intrinsic motivation (perceived enjoyment and perceived relatedness) and extrinsic motivation (functional support and information quality). The SEM-PLS technique was used to analyze the data collected from a questionnaire survey of 562 WeChat users. The results showed that social media addiction is determined by an individual's emotional and functional attachment to the platform. This attachment is, in turn, influenced by intrinsic motivation (perceived enjoyment and perceived relatedness) and extrinsic motivation (functional support and informational quality). The study first explains the latent antecedents of social media addiction. Second, it examines user attachment, particularly the role of emotional and functional attachment, and explores the platform technology system, which plays a key role in the development of addiction. Third, it extends attachment theory to the study of social media addiction.
•Study combines intrinsic and extrinsic motivation to explore addiction with attachment theory and CAC framework.•Factors include emotional and functional attachment, platform technology, and extension of attachment theory.
Since the clear demonstration of lysophosphatidic acid (LPA)’s pathological roles in cancer in the mid-1990s, more than 1000 papers relating LPA to various types of cancer were published. Through ...these studies, LPA was established as a target for cancer. Although LPA-related inhibitors entered clinical trials for fibrosis, the concept of targeting LPA is yet to be moved to clinical cancer treatment. The major challenges that we are facing in moving LPA application from bench to bedside include the intrinsic and complicated metabolic, functional, and signaling properties of LPA, as well as technical issues, which are discussed in this review. Potential strategies and perspectives to improve the translational progress are suggested. Despite these challenges, we are optimistic that LPA blockage, particularly in combination with other agents, is on the horizon to be incorporated into clinical applications.
High-level penetration of intermittent renewable energy sources has introduced significant uncertainties and variabilities into modern power systems. In order to rapidly and economically respond to ...the changes in power system operating state, this letter proposes a real-time optimal power flow (RT-OPF) approach using Lagrangian -based deep reinforcement learning (DRL) in continuous action domain. A DRL agent to determine RT-OPF decisions is constructed and optimized using the deep deterministic policy gradient. The DRL action-value function is designed to simultaneously model RT-OPF objective and constraints. Instead of using the critic network, the deterministic gradient is derived analytically. The proposed method is tested on the IEEE 118-bus system. Compared with the state-of-the-art methods, the proposed method can achieve a high solution optimality and constraint compliance in real-time.
As one of the important cancer hallmarks, metabolism reprogramming, including lipid metabolism alterations, occurs in tumor cells and the tumor microenvironment (TME). It plays an important role in ...tumorigenesis, progression, and metastasis. Lipids, and several lysophospholipids in particular, are elevated in the blood, ascites, and/or epithelial ovarian cancer (EOC) tissues, making them not only useful biomarkers, but also potential therapeutic targets. While the roles and signaling of these lipids in tumor cells are extensively studied, there is a significant gap in our understanding of their regulations and functions in the context of the microenvironment. This review focuses on the recent study development in several oncolipids, including lysophosphatidic acid and sphingosine-1-phosphate, with emphasis on TME in ovarian cancer.
Photovoltaic (PV) inverters can provide fast and flexible reactive power support for voltage regulation and power loss reduction in distribution networks. Conventionally, central and local ...voltage/VAR control (VVC) strategies are separately determined, lacking a cross-hierarchy coordination. This paper proposes a novel hierarchically-coordinated VVC (HC-VVC) method where central hierarchy dispatches the inverter reactive power output to minimize network power loss and local hierarchy responds to real-time voltage deviation through a linear droop controller. The proposed method simultaneously optimizes inverter reactive power output setpoints for the central dispatch and droop functions for the local control so that the two control hierarchies are optimally coordinated under stochastic PV power generation and load variations. The coordination model is solved by a scenario-based stochastic optimization approach with probabilistic uncertainty modeling where real-time variations of the uncertainties are fully addressed. Simulation results show that, compared with existing methods, the proposed HC-VVC method is overall superior in minimizing power loss and voltage deviation.
With the rapid development of the smart grid and increasingly integrated communication networks, power grids are facing serious cyber-security problems. This paper reviews existing studies on the ...impact of false data injection attacks on power systems from three aspects. First, false data injection can adversely affect economic dispatch by increasing the operational cost of the power system or causing sequential overloads and even outages. Second, attackers can inject false data to the power system state estimator, and this will prevent the operators from obtaining the true operating conditions of the system. Third, false data injection attacks can degrade the distributed control of distributed generators or microgrids inducing a power imbalance between supply and demand. This paper fully covers the potential vulnerabilities of power systems to cyber-attacks to help system operators understand the system vulnerability and take effective countermeasures.
Many microorganisms in the environment participate in the fermentation process of Chinese liquor. However, it is unknown to what extent the environmental microbiota influences fermentation. In this ...study, high-throughput sequencing combined with multiphasic metabolite target analysis was applied to study the microbial succession and metabolism changes during Chinese liquor fermentation from two environments (old and new workshops). SourceTracker was applied to evaluate the contribution of environmental microbiota to fermentation. Results showed that Daqu contributed 9.10 to 27.39% of bacterial communities and 61.06 to 80.00% of fungal communities to fermentation, whereas environments (outdoor ground, indoor ground, tools, and other unknown environments) contributed 62.61 to 90.90% of bacterial communities and 20.00 to 38.94% of fungal communities to fermentation. In the old workshop, six bacterial genera (
11.73% average relative abundance,
20.78%,
6.13%,
10.99%,
16.64%, and
3.40%) and five fungal genera (
55.10%,
1.47%,
10.66%,
22.11%, and
3.35%) were abundant at the beginning of fermentation. However, in the new workshop, the change of environmental microbiota decreased the abundances of
(5.74%),
(6.64%),
(33.91%),
(7.08%), and
(0.12%), and increased the abundances of
(17.04%),
(13.31%),
(11.41%),
(3.02%),
(16.47%), and
(1.31%). Meanwhile, in the new workshop, the changes of microbial community resulted in the increase of acetic acid, lactic acid, malic acid, and ethyl acetate, and the decrease of ethyl lactate during fermentation. This study showed that the environmental microbiota was an important source of fermentation microbiota and could drive both microbial succession and metabolic profiles during liquor fermentation.
Traditional solid-state fermentation of foods and beverages is mainly carried out by complex microbial communities from raw materials, starters, and the processing environments. However, it is still unclear how the environmental microbiota influences the quality of fermented foods and beverages, especially for Chinese liquors. In this study, we utilized high-throughput sequencing, microbial source tracking, and multiphasic metabolite target analysis to analyze the origins of microbiota and the metabolic profiles during liquor fermentation. This study contributes to a deeper understanding of the role of environmental microbiota during fermentation.