Potential Sites Research Articles

Species communities can accurately predict the occurrence of an imperilled fish

Species distribution information is essential for conservation. However, sampling the full range of a species’ potential distribution is rarely feasible, necessitating the development of models to predict distributions, as well as relevant environmental and biotic drivers. We applied a novel approach to model the distribution of a species at risk in Canada, silver shiner (SS; Notropis photogenis) in tributaries of Lake Ontario using the fish community as a predictor of SS occurrence. Associative rule learning (ARL) identified simple species combinations that provided strong insight into SS distribution, which may be particularly useful for identifying new occupied locations, including making sampling decisions in real time. The species with the most positive or negative associations with SS identified by ARL were included in a random forests model, which predicted SS distribution with high accuracy in test data from the study tributary system and in a neighbouring system where SS is exceedingly rare. Predicting species distributions based on biotic associations presents opportunities for discovering new populations, identifying critical habitat, and evaluating the suitability of sites for re-introduction potential.

Analyzing the upscaling potential and geospatial siting of calcination-free calcium hydroxide production in the United States

This study evaluates the techno-economic feasibility and the embodied carbon dioxide intensity (eCI) of a novel process for producing nominally pure (>95 mass %) calcium hydroxide without the need for the thermal calcination of limestone. The process relies on the aqueous extraction of calcium from alkaline industrial wastes following which portlandite (Ca(OH)2: CH, a.k.a. slaked lime or hydrated lime) is precipitated by application of a waste-heat based thermal swing. This approach takes advantage of the temperature dependent solubility of CH at ambient pressure. We evaluated the feasibility of implementing this process in the U.S. based on the geospatial availability of waste heat and slags as a Ca-source. For the base case, the cost of production of “Low-Temperature Portlandite (LTP)” is 2-to-3 times that of traditional portlandite (∼$180/tonne). The main driver of cost is the electricity demand for reverse osmosis (RO) which is used to concentrate Ca-ions in solution, and the costs of membrane replacement. Our sensitivity analysis showed that parity with the cost of production of traditional portlandite is readily achievable by selecting membranes with better durability (i.e., better pH resistance) and flux (i.e., higher permeability) without sacrificing selectivity. Significantly, LTP features an eCI that is between 40%- and - 80 % lower than its traditional counterpart when electricity is sourced from natural gas combustion or wind power, respectively. Finally, our geospatial analysis reveals that there are three areas in the U.S. with the potential for implementation of industrial-scale facilities that could produce at least 50 tonnes of pure Ca(OH)2 per day, while achieving a production cost of ∼$270 per tonne of Ca(OH)2, owing to the proximity between slag feedstocks and waste heat sources.

Discovering consensus regions for interpretable identification of RNA N6-methyladenosine modification sites via graph contrastive clustering.

As a pivotal post-transcriptional modification of RNA, N6-methyladenosine (m6A) has a substantial influence on gene expression modulation and cellular fate determination. Although a variety of computational models have been developed to accurately identify potential m6A modification sites, few of them are capable of interpreting the identification process with insights gained from consensus knowledge. To overcome this problem, we propose a deep learning model, namely M6A-DCR, by discovering consensus regions for interpretable identification of m6A modification sites. In particular, M6A-DCR first constructs an instance graph for each RNA sequence by integrating specific positions and types of nucleotides. The discovery of consensus regions is then formulated as a graph clustering problem in light of aggregating all instance graphs. After that, M6A-DCR adopts a motif-aware graph reconstruction optimization process to learn high-quality embeddings of input RNA sequences, thus achieving the identification of m6A modification sites in an end-to-end manner. Experimental results demonstrate the superior performance of M6A-DCR by comparing it with several state-of-the-art identification models. The consideration of consensus regions empowers our model to make interpretable predictions at the motif level. The analysis of cross validation through different species and tissues further verifies the consistency between the identification results of M6A-DCR and the evolutionary relationships among species.

Quantifying seasonal variations in space use within the home range of Burbot

AbstractObjectiveAdvances in acoustic telemetry have assisted biologists in understanding migration patterns, space use, survival, and the effects of human influences on aquatic species. Using fine‐scale positioning, fisheries managers can quantify home range size fluctuations throughout the year and even identify spawning areas. Burbot Lota lota population dynamics have been studied across their range, while movement dynamics have been briefly investigated. Our objective was to assess seasonal variations of Burbot space use using estimations of home range size with an attempt to infer spawn timing.MethodsThirty‐two acoustic‐tagged Burbot were used to study home range size in Bad Medicine Lake, Minnesota, from April 2019 to June 2020.ResultFemale estimated home range size was significantly larger than that of males. Estimated home range size increased following ice formation in December and continued through March. Average home range estimates were largest in the middle of March and smallest in April, assumed to be caused by spawning and postspawn behaviors, respectively.ConclusionThe results suggest that Burbot movement increased during the winter months, which may cause potential increases in vulnerability during spawning. High exploitation rates are possible in situations where spawning and feeding Burbot encounter elevated angling pressure. Future research should continue to assess the movement dynamics and potential site fidelity of Burbot populations by monitoring spawning grounds and if the same areas are used year after year. The results of this study improve the knowledge of areas used by Burbot in lakes, which can assist with management of Burbot in Bad Medicine Lake. Furthermore, we highlighted how Burbot movement increased during spawn timing, which could contribute to increased encounters with anglers.

Targeting ATP-binding site of WRN Helicase: Identification of novel inhibitors through pocket analysis and Molecular Dynamics-Enhanced virtual screening

WRN helicase is a critical protein involved in maintaining genomic stability, utilizing ATP hydrolysis to dissolve DNA secondary structures. It has been identified as a promising synthetic lethal target for microsatellite instable (MSI) cancers. However, few WRN helicase inhibitors have been discovered, and their potential binding sites remain unexplored. In this study, we analyzed potential binding sites for WRN inhibitors and focused on the ATP-binding site for screening new inhibitors. Through molecular dynamics-enhanced virtual screening, we identified two compounds, h6 and h15, which effectively inhibited WRN's helicase and ATPase activity in vitro. Importantly, these compounds selectively targeted WRN's ATPase activity, setting them apart from other non-homologous proteins with ATPase activity. In comparison to the homologous protein BLM, h6 exhibits some degree of selectivity towards WRN. We also investigated the binding mode of these compounds to WRN's ATP-binding sites. These findings offer a promising strategy for discovering new WRN inhibitors and present two novel scaffolds, which might be potential for the development of MSI cancer treatment.

METTL3 promotes osteogenic differentiation of human umbilical cord mesenchymal stem cells by up-regulating m6A modification of circCTTN.

Human umbilical cord mesenchymal stem cells (hUCMSCs) are promising seed cells in bone tissue engineering. circRNA and N6-methyladenosine (m6A) RNA methylation play important roles in osteogenic differentiation. Here, we investigated the potential relevance of a critical circRNA, hsa_circ_0003376 (circCTTN), and methyltransferase-like 3 (METTL3) in osteogenic differentiation of hUCMSCs. Expression of circCTTN after hUCMSC osteogenic induction was detected by qRT-PCR. Three databases (RMBase v2.0, BERMP, and SRAMP) were used to predict m6A sites of circCTTN. RNA was enriched by methylated RNA immunoprecipitation (MeRIP), followed by quantitative real-time polymerase chain reaction to detect m6A level of circCTTN after METTL3 overexpression and osteogenic induction. RNA pull-down, Western blotting, and protein mass spectrometry were performed to investigate the potential mechanisms by which METTL3 promoted m6A modification of circCTTN. Bioinformatic analyses based on database (STRING) search and co-immunoprecipitation were used to analyze the proteins that interacted with METTL3. Overexpression of METTL3 promoted osteogenic differentiation of hUCMSCs and increased m6A level of circCTTN. Two potential m6A modification sites of circCTTN were predicted. No direct interaction between METTL3 and circCTTN was observed. Thirty-one proteins were pulled down by probes specific for circCTTN, including NOP2, and two m6A reading proteins, EIF3A and SND1. Bioinformatics analysis and co-immunoprecipitation showed that METTL3 interacted with EIF3A indirectly through NOP2. METTL3 promotes the osteogenic differentiation of hUCMSCs by increasing the m6A level of circCTTN. However, METTL3 does not bind directly to circCTTN. METTL3 interacts with circCTTN indirectly through NOP2 and EIF3A.

Reservoir Static Modelling towards Safe CO2 Storage in Depleted Oil Reservoirs of ‘CRK’ Field, Niger Delta, Nigeria

Geological carbon storage (GCS) is gradually gaining acceptance as the technology of highest repute for the mitigation against greenhouse gas effect. This involves the injection and long-term or permanent storage of carbon dioxide (CO2) in subsurface geological formations. The development of a robust 3D reservoir model then becomes necessary to understand the facies changes and the petrophysical properties distribution of candidate CO2 storage reservoirs. This study attempts the use of static modelling technique to investigate the depleted oil and gas reservoirs of ‘CRK’ field in the Niger Delta sedimentary Basin as a potential CO2 storage site. Using an integrated approach of 3D seismic and a suit of well logs from the study area, two reservoir sands (D10C0 and D6200) were mapped. 3D static modelling of discrete and continuous property distribution of the reservoirs revealed the reservoirs are composed majorly of clean sands with water saturation ranging from 8 to 75%. The average porosity and permeability values are between 20 to 29% and 250 to 890mD respectively. A theoretical storage capacity of 24.85Mt is estimated for the two reservoirs combined, while the median effective storage capacity is 6.22Mt. Comparison of the results obtained in the study with recommended standard values show the reservoirs are suitable for CO2 storage. The property models constructed can serve as primary input for dynamic simulation of the oilfield in future studies.

Offshore Windy Potential Sites Prioritization in the Gulf of South Suez

Offshore Windy Potential Sites Prioritization in the Gulf of South Suez

Preclinical toxicity analyses of lentiviral vectors expressing the HIV-1 LTR-specific designer-recombinase Brec1.

Drug-based antiretroviral therapies (ART) efficiently suppress HIV replication in humans, but the virus persists as integrated proviral reservoirs in small numbers of cells. Importantly, ART cannot eliminate HIV from an infected individual, since it does not target the integrated provirus. Therefore, genome editing-based strategies that can inactivate or excise HIV genomes would provide the technology for novel curative therapies. In fact, the HIV-1 LTR-specific designer-recombinase Brec1 has been shown to remove integrated proviruses from infected cells and is highly efficacious on clinical HIV-1 isolates in vitro and in vivo, suggesting that Brec1 has the potential for clinical development of advanced HIV-1 eradication strategies in people living with HIV. In line with the preparation of a first-in-human advanced therapy medicinal product gene therapy trial, we here present an extensive preclinical evaluation of Brec1 and lentiviral vectors expressing the Brec1 transgene. This included detailed functional analysis of potential genomic off-target sites, assessing vector safety by investigating vector copy number (VCN) and the risk for potential vector-related insertional mutagenesis, as well as analyzing the potential of Brec1 to trigger an undesired strong T cell immune response. In conclusion, the antiviral designer-recombinase Brec1 is shown to lack any detectable cytopathic, genotoxic or T cell-related immunogenic effects, thereby meeting an important precondition for clinical application of the therapeutic lentiviral vector LV-Brec1 in novel HIV-1 curative strategies.

Implementation of Solutions Reducing the Number of Cars in Polish Housing Estates—Based on the Experience of the Vauban Estate in Freiburg, Case of the City of Wroclaw

The number of cars in Polish housing estates is steadily increasing. Cars park in allocated parking spaces, but also occupy roads, pavements, and even green spaces. As the European experience shows, many countries have had this problem and have been looking for a solution. Due to the fact that Polish cities are at the beginning of the process, which limits the importance of individual transport, all good practices are a valuable source of information. The purpose of this article is to present the possibility of implementing solutions to limit the number of cars in Polish housing estates based on the experience of the Vauban housing estate in Freiburg, Germany. This housing estate was created with the great participation of the local community and one of its postulates was to reduce the use of cars. The methodology involved several consecutive steps. The first stage of the work was a review of the literature on the subject of low-carbon housing. Vauban was chosen as a model project with a sustainability of 20 years. Design solutions to reduce car traffic were analysed. The data collected were transformed into hard (numerical) and soft (descriptive) data, then systematised and catalogued. Based on these guidelines, a model of an estate with a reduced number of cars was created. The final stage of the research was the implementation of the model. The model formulates the most important aspects related to the location of a car-free housing estate and allows one to indicate its potential location in the city. It is a valuable tool for opening up a broad discussion on urban planning, location, and the future of car-free housing estates. The results of the study should be interpreted at two levels: land use and location. The results of the analyses allowed parameters and guidelines to be defined. These guidelines provide a guideline for the development of car-reduced housing estates in future cities. The second set of conclusions concerns the location of a potential car-reduced housing estate. The area of the potential site is shown using the city of Wroclaw, Poland, as an example.

Finite Element Analysis and Fatigue Test of INTEGRA Dental Implant System.

The study involved numerical FEA (finite element analysis) of dental implants. Based on this, fatigue tests were conducted according to the PN-EN 14801 standard required for the certification of dental products. Thanks to the research methodology developed by the authors, it was possible to conduct a thorough analysis of the impact of external and internal factors such as material, geometry, loading, and assembly of the dental system on the achieved value of fatigue strength limit in the examined object. For this purpose, FEM studies were based on identifying potential sites of fatigue crack initiation in reference to the results of the test conducted on a real model. The actions described in the study helped in the final evaluation of the dental system design process named by the manufacturer as INTEGRA OPTIMA 3.35. The objective of the research was to identify potential sites for fatigue crack initiation in a selected dental system built on the INTEGRA OPTIMA 3.35 set. The material used in the research was titanium grade 4. A map of reduced von Mises stresses was used to search for potential fatigue crack areas. The research [loading] was conducted on two mutually perpendicular planes positioned in such a way that the edge intersecting the planes coincided with the axis of the system. The research indicated that the connecting screw showed the least sensitivity (stress change) to the change in the loading plane, while the value of preload has a significant impact on the achieved fatigue strength of the system. In contrast, the endosteal implant (root) and the prosthetic connector showed the greatest sensitivity to the change in the loading plane. The method of mounting [securing] the endosteal implant using a holder, despite meeting the standards, may contribute to generating excessive stress concentration in the threaded part. Observation of the prosthetic connector in the Optima 3.35 system, cyclically loaded with a force of F ≈ 300 N in the area of the upper hexagonal peg, revealed a fatigue fracture. The observed change in stress peak in the dental connector for two different force application surfaces shows that the positioning of the dental system (setting of the socket in relation to the force action plane) is significantly decisive in estimating the limited fatigue strength.

Isoreticular Contraction of Cage-like Metal-Organic Frameworks with Optimized Pore Space for Enhanced C2H2/CO2 and C2H2/C2H4 Separations.

The C2H2 separation from CO2 and C2H4 is of great importance yet highly challenging in the petrochemical industry, owing to their similar physical and chemical properties. Herein, the pore nanospace engineering of cage-like mixed-ligand MFOF-1 has been accomplished via contracting the size of the pyridine- and carboxylic acid-functionalized linkers and introducing a fluoride- and sulfate-bridging cobalt cluster, based on a reticular chemistry strategy. Compared with the prototypical MFOF-1, the constructed FJUT-1 with the same topology presents significantly improved C2H2 adsorption capacity, and selective C2H2 separation performance due to the reduced cage cavity size, functionalized pore surface, and appropriate pore volume. The introduction of fluoride- and sulfate-bridging cubane-type tetranuclear cobalt clusters bestows FJUT-1 with exceptional chemical stability under harsh conditions while providing multiple potential C2H2 binding sites, thus rendering the adequate ability for practical C2H2 separation application as confirmed by the dynamic breakthrough experiments under dry and humid conditions. Additionally, the distinct binding mechanism is suggested by theoretical calculations in which the multiple supramolecular interactions involving C-H···O, C-H···F, and other van der Waals forces play a critical role in the selective C2H2 separation.

Choosing the best way: how wild common marmosets travel to efficiently exploit resources

While foraging, animals have to find potential food sites, remember these sites, and plan the best navigation route. To deal with problems associated with foraging for multiple and patchy resources, primates may employ heuristic strategies to improve foraging success. Until now, no study has attempted to investigate experimentally the use of such strategies by a primate in a context involving foraging in large-scale space. Thus, we carried out an experimental field study that aimed to test if wild common marmosets (Callithrix jacchus) employ heuristic strategies to efficiently navigate through multiple feeding sites distributed in a large-scale space. In our experiment, we arranged four feeding platforms in a trapezoid configuration with up to 60 possible routes and observe marmosets’ decisions under two experimental conditions. In experimental condition I, all platforms contained the same amount of food; in experimental condition II, the platforms had different amounts of food. According to the number and arrangement of the platforms, we tested two heuristic strategies: the Nearest Neighbor Rule and the Gravity Rule. Our results revealed that wild common marmosets prefer to use routes consistent with a heuristic strategy more than expected by chance, regardless of food distribution. The findings also demonstrate that common marmosets seem to integrate different factors such as distance and quantity of food across multiple sites distributed over a large-scale space, employing a combination of heuristic strategies to select the most efficient routes available. In summary, our findings confirm our expectations and provide important insights into the spatial cognition of these small neotropical primates.

Deciding where to put them: Sensitivity tests and independent evaluation are critical when using species distribution models to inform conservation translocations

Abstract Conservation translocations are an important tool for combating species declines and population losses. Species distribution models (SDMs) can facilitate the selection of suitable release sites for translocation programs. However, these models can be sensitive to several modelling decisions. In this study, we explore the impacts of three key modelling decisions on Maxent models developed to inform reintroductions of the long‐toed salamander (Ambystoma macrodactylum) in southwestern Alberta. We specifically test the sensitivity of model predictions to (1) the type of environmental variables used to generate models, (2) whether the background points used to calibrate the models reflects the potential bias in the input locality records and (3) the choice of geographic study extent. We use independent presence‐absence data from an extensive field survey to test the accuracy of models based on different decisions. Both model predictions and performance were sensitive to these modelling decisions. Models developed using local study extents were more accurate than those based on range‐wide extents. Both study extent and type of background points impacted model predictions and performance more than the set of environmental variables included in the models for this species. We further demonstrate the impacts of these decisions on the ranking of potential release sites and present a final set of recommendations that accounts for this uncertainty under both current and future climatic conditions. We specifically identify three sites that are expected to be suitable in both present and future time periods as potential release sites for salamander reintroductions in southwestern Alberta. Synthesis and applications: Our study adds to our understanding of how different modelling decisions impact SDMs and the downstream conclusions from these models while simultaneously demonstrating a rigorous approach for the use of SDMs in conservation translocation planning.

The architecture of basalt reservoirs in the North Atlantic Igneous Province with implications for basalt carbon sequestration

Abstract Offshore CO 2 sequestration in basaltic formations of the North Atlantic Igneous Province may allow permanent storage of large volumes of CO 2 through rapid carbonate mineralization. Characterizing the internal architecture of such reservoirs is key to assessing the storage potential. In this study, six photogrammetry models and three boreholes on the Faroe Islands have been used to characterize the internal lava sequence architectures as a direct analogue to potential offshore North Atlantic Igneous Province storage sites. The studied formations are dominated by c. 5 to 50 m thick simple and compound lava flows, with drill core observations documenting a transition from pāhoehoe moving towards ‘a’ā lava flow types interbedded with thin (<5 m thick) volcaniclastic rock units. The identification of flow margin breccias is potentially important as these units form excellent reservoirs in several other localities globally. Stacked, thick simple flows may present sealing units associated with dense flow interiors. Connected porous and permeable lava flow crusts present potential reservoirs; however, the degree of secondary mineralization and alteration can alter initially good reservoir units to impermeable barriers for fluid flow. Large-scale reservoir volumes may be present mainly within both vesicular, fractured pāhoehoe and brecciated flow margins of transitional simple lava flows.

Deep learning-assisted Bayesian framework for real-time CO2 leakage locating at geologic sequestration sites

Accurate and efficient localization of CO2 leakage if occurred in subsurface formations, is of significant importance in achieving secure geological carbon sequestration (GCS) projects. However, this task is inherently challenging due to the considerable uncertainties in the subsurface. In this work, we develop a novel deep learning-assisted Bayesian framework for identifying potential CO2 leakage sites based on the reservoir pressure transient behavior measured at the wellbores of injection or observation wells. The method consists of two essential steps: 1) Deep learning surrogate: This step aims to effectively replace the intensive high-fidelity simulation with an efficient deep learning surrogate. 2) Bayesian inversion: In this step, the posterior distributions of potential CO2 leakage locations are inverted, in which the surrogate serves as the forward model. The above two processes are automated using Bayesian optimization instead of a labor-intensive trial-and-error approach. The proposed framework is verified using a 3D geological model simulating CO2 sequestration into a brine-filled reservoir. The results demonstrate the Bayesian-optimized surrogate could successfully capture the underlying process of subsurface CO2-brine flow. The Bayesian inversion algorithm enables localizing CO2 leakage with high accuracy. To our knowledge, the proposed Bayesian framework is implemented for the first time to locate multiple leakage sites at the field scale. The proposed workflow provides an accurate and efficient approach to detecting possible CO2 leakage locations in a real-time manner and has promising potential for field-scale GCS applications.

Designing Ti-6Al-4V microstructure for strain delocalization using neural networks

The deformation behavior of Ti-6Al-4V titanium alloy is significantly influenced by slip localized within crystallographic slip bands. Experimental observations reveal that intense slip bands in Ti-6Al-4V form at strains well below the macroscopic yield strain and may serially propagate across grain boundaries, resulting in long-range localization that percolates through the microstructure. These connected, localized slip bands serve as potential sites for crack initiation. Although slip localization in Ti-6Al-4V is known to be influenced by various factors, an investigation of optimal microstructures that limit localization remains lacking. In this work, we develop a novel strategy that integrates an explicit slip band crystal plasticity technique, graph networks, and neural network models to identify Ti-6Al-4V microstructures that reduce the propensity for strain localization. Simulations are conducted on a dataset of 3D polycrystals, each represented as a graph to account for grain neighborhood and connectivity. The results are then used to train neural network surrogate models that accurately predict localization-based properties of a polycrystal, given its microstructure. These properties include the ratio of slip accumulated in the band to that in the matrix, fraction of total applied strain accommodated by slip bands, and spatial connectivity of slip bands throughout the microstructure. The initial dataset is enriched by synthetic data generated by the surrogate models, and a grid search optimization is subsequently performed to find optimal microstructures. Describing a 3D polycrystal with only a few features and a combination of graph and neural network models offer robustness compared to the alternative approaches without compromising accuracy. We show that while each material property is optimized through a unique microstructure solution, elongated grain shape emerges as a recurring feature among all optimal microstructures. This finding suggests that designing microstructures with elongated grains could potentially mitigate strain localization without compromising strength.

Mowing wet meadows reduces the health of their snail communities.

Wet meadows harbor rich biodiversity, making them pivotal ecosystems worldwide. These habitats are commonly used for grazing or hay production for livestock. However, regular mowing can influence these habitats, potentially leading to significant repercussions for the animals residing within them. In order to investigate the effects of land management practices, we conducted an experimental study to compare snail communities in mowed and unmowed wet meadows in northern Hungary. We found that overall, mowing decreases snail populations, as well as species richness and diversity. Thus, our results suggest that routine mowing of wet meadows is deleterious to their snail communities. Based on these results, we suggest that designated patches of meadows that are regularly managed should be left uncultivated in their natural state. These patches can serve as potential colonization sites, facilitating the restoration of the entire meadow's ecological balance.

IL6-STAT3-C/EBPβ-IL6 positive feedback loop in tumor-associated macrophages promotes the EMT and metastasis of lung adenocarcinoma

BackgroundLung cancer is one of the most common tumors in the world, and metastasis is one of the major causes of tumor-related death in lung cancer patients. Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and are frequently associated with tumor metastasis in human cancers. However, the regulatory mechanisms of TAMs in lung cancer metastasis remain unclear.MethodsSingle-cell sequencing analysis of lung cancer and normal tissues from public databases and from 14 patients who underwent surgery at Zhongshan Hospital was performed. In vitro co-culture experiments were performed to evaluate the effects of TAMs on lung cancer migration and invasion. Changes in the expression of IL-6, STAT3, C/EBPΒ, and EMT pathway were verified using RT-qPCR, western blotting, and immunofluorescence. Dual luciferase reporter assays and ChIP were used to reveal potential regulatory sites on the transcription factor sets. In addition, the effects of TAMs on lung cancer progression and metastasis were confirmed by in vivo models.ResultsTAM infiltration is associated with tumor progression and poor prognosis. IL-6 secreted by TAMs can activate the JAK2/STAT3 pathway through autocrine secretion, and STAT3 acts as a transcription factor to activate the expression of C/EBPβ, which further promotes the transcription and expression of IL-6, forming positive feedback loops for IL6-STAT3-C/EBPβ-IL6 in TAMs. IL-6 secreted by TAMs promotes lung cancer progression and metastasis in vivo and in vitro by activating the EMT pathway, which can be attenuated by the use of JAK2/STAT3 pathway inhibitors or IL-6 monoclonal antibodies.ConclusionsOur data suggest that TAMs promote IL-6 expression by forming an IL6-STAT3-C/EBPβ-IL6 positive feedback loop. Released IL-6 can induce the EMT pathway in lung cancer to enhance migration, invasion, and metastasis. The use of IL-6-neutralizing antibody can partially counteract the promotion of LUAD by TAMs. A novel mechanism of macrophage-promoted tumor progression was revealed, and the IL6-STAT3-C/EBPβ-IL6 signaling cascade may be a potential therapeutic target against lung cancer.Graphical IL-6 secreted by TAM acts on itself to promote STAT3 phosphorylation, and pSTAT3 transfers into the nucleus, promotes the expression of C/EBPβ. C/EBPβ is able to further promote IL-6 expression, which forms positive feedback for IL-6 secretion. IL-6 secreted by TAMs acts on lung cancer to promote their metastasis through activation of EMT.

SIRT1 mediates breast cancer development and tumorigenesis controlled by estrogen-related receptor β.

Silent mating type information regulation 2 homolog 1 (SIRT1) is a class III histone deacetylase (HDAC) that is NAD + dependent and essential for metabolism, senescence, and cell survival. SIRT1 is overexpressed in several cancers, including breast cancer. SIRT1 is a well-known target gene of the estrogen receptor alpha (ER alpha) and is closely related to ER alpha deacetylation. Transcription factor Estrogen-related receptors (ERRs) share sequence homology with ERs in the DNA-binding domain, therefore, the possibility of sharing target genes between them is high. Our current research aims togain insight into the function of ERRβ in regulating the activity of SIRT1 during the progression of breast cancer. ER-positive (ER + ve) breast cancer cells and tissues had considerably enhanced SIRT1 expression. Six potential ERRE sites were identified by analysis of the 5' upstream region of SIRT1, and both in vitro and in vivo experiments supported their presence. We found SIRT1 to be up-regulated in ERRβ overexpressed ER + ve breast cancer cells. Furthermore, our findings suggested that ectopic production of ERR and PCAF would increase SIRT1 activity. Our findings also indicated that ectopic production of ERRβ and PCAF increased SIRT1 activity. With sufficient evidence demonstrating the substantial involvement of SIRT1 in cell proliferation, migration, and colony formation capability, we were also able to illustrate the tumorigenic role of SIRT1. Overall, our findings highlight SIRT1's tumorigenic influence on breast cancer and suggest that SIRT1 inhibitors might serve as potential therapeutic drugs for the treatment of breast cancer.