FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

Background The majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear. Methods Liquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells. Results We found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth. Discussion We reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer

Misregulation of Alternative Splicing in a Mouse Model of Rett Syndrome

Mutations in the human MECP2 gene cause Rett syndrome (RTT), a severe neurodevelopmental disorder that predominantly affects girls. Despite decades of work, the molecular function of MeCP2 is not fully understood. Here we report a systematic identification of MeCP2-interacting proteins in the mouse brain. In addition to transcription regulators, we found that MeCP2 physically interacts with several modulators of RNA splicing, including LEDGF and DHX9. These interactions are disrupted by RTT causing mutations, suggesting that they may play a role in RTT pathogenesis. Consistent with the idea, deep RNA sequencing revealed misregulation of hundreds of splicing events in the cortex of Mecp2 knockout mice. To reveal the functional consequence of altered RNA splicing due to the loss of MeCP2, we focused on the regulation of the splicing of the flip/flop exon of Gria2 and other AMPAR genes. We found a significant splicing shift in the flip/flop exon toward the flop inclusion, leading to a faster decay in the AMPAR gated current and altered synaptic transmission. In summary, our study identified direct physical interaction between MeCP2 and splicing factors, a novel MeCP2 target gene, and established functional connection between a specific RNA splicing change and synaptic phenotypes in RTT mice. These results not only help our understanding of the molecular function of MeCP2, but also reveal potential drug targets for future therapies

FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

BackgroundThe majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear.MethodsLiquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells.ResultsWe found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth.DiscussionWe reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer

Timetable coordination of first trains in urban railway network: A case study of Beijing

A model of timetable coordination of first trains in urban railway networks, based on the importance of lines and transfer stations, is proposed in this paper. A sub-network connection method is developed, and a mathematical programming solver is utilized to solve the suggested model. A simple test network and a real network of Beijing urban railway network are modeled to verify the effectiveness of our suggested model. Results demonstrate that the proposed model is effective in improving the transfer performance in that they reduce the connection time significantly

Eco-reliable path finding in time-variant and stochastic networks

This paper addresses a route guidance problem for finding the most eco-reliable path in time-variant and stochastic networks such that travelers can arrive at the destination with the maximum on-time probability while meeting vehicle emission standards imposed by government regulators. To characterize the dynamics and randomness of transportation networks, the link travel times and emissions are assumed to be time-variant random variables correlated over the entire network. A 0–1 integer mathematical programming model is formulated to minimize the probability of late arrival by simultaneously considering the least expected emission constraint. Using the Lagrangian relaxation approach, the primal model is relaxed into a dualized model which is further decomposed into two simple sub-problems. A sub-gradient method is developed to reduce gaps between upper and lower bounds. Three sets of numerical experiments are tested to demonstrate the efficiency and performance of our proposed model and algorithm

Evaluation of the efficacy and safety of intravenous remdesivir in adult patients with severe COVID-19: study protocol for a phase 3 randomized, double-blind, placebo-controlled, multicentre trial.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by a novel corinavirus (later named SARS-CoV-2 virus), was fistly reported in Wuhan, Hubei Province, China towards the end of 2019. Large-scale spread within China and internationally led the World Health Organization to declare a Public Health Emergency of International Concern on 30th January 2020. The clinical manifestations of COVID-19 virus infection include asymptomatic infection, mild upper respiratory symptoms, severe viral pneumonia with respiratory failure, and even death. There are no antivirals of proven clinical efficacy in coronavirus infections. Remdesivir (GS-5734), a nucleoside analogue, has inhibitory effects on animal and human highly pathogenic coronaviruses, including MERS-CoV and SARS-CoV, in in vitro and in vivo experiments. It is also inhibitory against the COVID-19 virus in vitro. The aim of this study is to assess the efficacy and safety of remdesivir in adult patients with severe COVID-19. METHODS: The protocol is prepared in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines. This is a phase 3, randomized, double-blind, placebo-controlled, multicentre trial. Adults (≥ 18 years) with laboratory-confirmed COVID-19 virus infection, severe pneumonia signs or symptoms, and radiologically confirmed severe pneumonia are randomly assigned in a 2:1 ratio to intravenously administered remdesivir or placebo for 10 days. The primary endpoint is time to clinical improvement (censored at day 28), defined as the time (in days) from randomization of study treatment (remdesivir or placebo) until a decline of two categories on a six-category ordinal scale of clinical status (1 = discharged; 6 = death) or live discharge from hospital. One interim analysis for efficacy and futility will be conducted once half of the total number of events required has been observed. DISCUSSION: This is the first randomized, placebo-controlled trial in COVID-19. Enrolment began in sites in Wuhan, Hubei Province, China on 6th February 2020. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04257656. Registered on 6 February 2020

1-Aminocyclopropane-1-carboxylic acid (ACC) concentration and ACC synthase expression in soybean roots, root tips, and soybean cyst nematode (Heterodera glycines)-infected roots

Colonization of plant roots by root knot and cyst nematodes requires a functional ethylene response pathway. However, ethylene plays many roles in root development and whether its role in nematode colonization is direct or indirect, for example lateral root initiation or root hair growth, is not known. The temporal requirement for ethylene and localized synthesis of ethylene during the life span of soybean cyst nematode (SCN) on soybean roots was further investigated. Although a significant increase in ethylene evolution was not detected from SCN-colonized roots, the concentration of the immediate precursor to ethylene, 1-aminocyclopropane-1-carboxylic acid (ACC), was higher in SCN-colonized root pieces and root tips than in other parts of the root. Moreover, expression analysis of 17 ACC synthase (ACS) genes indicated that a select set of ACS genes is expressed in SCN-colonized root pieces that is clearly different from the set of genes expressed in non-colonized roots or root tips. Semi-quantitative real-time PCR indicated that ACS transcript accumulation correlates with the high concentration of ACC in root tips. In addition, an ACS-like sequence was found in the public SCN nucleotide database. Acquisition of a full-length sequence for this mRNA (accession GQ389647) and alignment with transcripts for other well-characterized ACS proteins indicated that the nematode sequence is missing a key element required for ACS activity and therefore probably is not a functional ACS. Moreover, no significant amount of ACC was found in any growth stage of SCN that was tested

Travel cost budget based user equilibrium in a bottleneck model with stochastic capacity

This paper studies a bottleneck model in which the capacity of the bottleneck is constant within a day but changes stochastically from day-to-day between a designed value (good condition) and a degraded one (bad condition). The study relates the travel cost variability due to stochastic capacity with commuters' departure time choice behaviors. We postulate that commuters acquire the variability of travel cost based on past experiences and factor such variability into their departure time choice consideration by minimizing their travel cost budget (TCB), defined as a weighted average of mean travel cost and standard deviation of travel cost. We show that the consideration of TCB yields seven possible equilibrium patterns. Closed form solutions to all possible equilibrium patterns and their corresponding parameter ranges are derived. The rationality of the patterns has been investigated. Dependence of travel cost and the duration of peak hours on the commuters' risk attitude has also been derived in each equilibrium pattern. Finally, numerical studies have been conducted to illustrate the properties

Analysis of road network pattern considering population distribution and central business district.

This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the haracteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks