Can we constrain warm dark matter masses with individual galaxies?

We study the impact of warm dark matter mass on the internal properties of individual galaxies using a large suite of 1,024 state-of-the-art cosmological hydrodynamic simulations from the DREAMS project. We take individual galaxies' properties from the simulations, which have different cosmologies, astrophysics, and warm dark matter masses, and train normalizing flows to learn the posterior of the parameters. We find that our models cannot infer the value of the warm dark matter mass, even when the values of the cosmological and astrophysical parameters are given explicitly. This result holds for galaxies with stellar mass larger than $2\times10^8 M_\odot/h$ at both low and high redshifts. We calculate the mutual information and find no significant dependence between the WDM mass and galaxy properties. On the other hand, our models can infer the value of $\Omega_{\rm m}$ with a $\sim10\%$ accuracy from the properties of individual galaxies while marginalizing astrophysics and warm dark matter masses.Comment: 13 pages, 8 figure

Expression, Purification and Antibacterial Activity of NK-Lysin Mature Peptides from the Channel Catfish (Ictalurus punctatus)

Antimicrobial peptides (AMPs) are small peptides and play important roles in host innate immune response against microbial invasion. Aquatic animals secrete different kinds of antimicrobial peptides which have antimicrobial activity towards microorganisms. NK-lysins, mature peptides produced by cytotoxic T lymphocytes and natural killer cells, are comprised of 74–78 amino acid residues, demonstrating broad-spectrum antimicrobial activity against bacteria, fungi, protozoa, and parasites. In this study, three distinct NK-lysin mature peptide (mNKLs), transcripts (76 amino acid residues) cloned from the channel catfish (Ictalurus punctatus) head kidney were ligated into plasmid vector pET-32a(+) to express the mNKLs fusion protein. The fusion protein was successfully expressed in E. coli Rosetta (DE3) under optimized conditions. After purification by affinity column chromatography, the fusion protein was successfully cleaved by enterokinase and released the peptide mNKLs. Tricine-SDS-PAGE results showed that mNKLs (approximately 8.6 kDa) were successfully expressed. The purified peptide mNKLs exhibited antibacterial activity against Staphylococcus aureus and E. coli

Urban Growth Modeling and Future Scenario Projection Using Cellular Automata (CA) Models and the R Package Optimx

Cellular automata (CA) is a spatially explicit modeling tool that has been shown to be effective in simulating urban growth dynamics and in projecting future scenarios across scales. At the core of urban CA models are transition rules that define land transformation from non-urban to urban. Our objective is to compare the urban growth simulation and prediction abilities of different metaheuristics included in the R package optimx. We applied five metaheuristics in optimx to near-optimally parameterize CA transition rules and construct CA models for urban simulation. One advantage of metaheuristics is their ability to optimize complexly constrained computational problems, yielding objective parameterization with strong predictive power. From these five models, we selected conjugate gradient-based CA (CG-CA) and spectral projected gradient-based CA (SPG-CA) to simulate the 2005-2015 urban growth and to project future scenarios to 2035 with four strategies for Su-Xi-Chang Agglomeration in China. The two CA models produced about 86% overall accuracy with standard Kappa coefficient above 69%, indicating their good ability to capture urban growth dynamics. Four alternative scenarios out to the year 2035 were constructed considering the overall effect of all candidate influencing factors and the enhanced effects of county centers, road networks and population density. These scenarios can provide insight into future urban patterns resulting from today's urban planning and infrastructure, and can inform future development strategies for sustainable cities. Our proposed metaheuristic CA models are also applicable in modeling land-use and urban growth in other rapidly developing areas

Urban expansion simulation and scenario prediction using cellular automata: comparison between individual and multiple influencing factors

Quantifying the contribution of driving factors is crucial to urban expansion modeling based on cellular automata (CA). The objective of this study is to compare individual-factor-based (IFB) models and multi-factor-based (MFB) models as well as examine the impacts of each factor on future urban scenarios. We quantified the contribution of driving factors using a generalized additive model (GAM), and calibrated six IFB-DE-CA models and fifteen MFB-DE-CA models using a differential evolution (DE) algorithm. The six IFB-DE-CA models and five MFB-DE-CA models were selected to simulate the 2005–2015 urban expansion of Hangzhou, China, and all IFB-DE-CA models were applied to project future urban scenarios out to the year 2030. Our results show that terrain (DEM) and population density (POP) are the two most influential factors affecting urban expansion of Hangzhou, indicating the dominance of biophysical and demographic drivers. All DE-CA models produced defensible simulations for 2015, with overall accuracy exceeding 89%. The IFB-DE-CA models based on DEM and POP outperformed some MFB-DE-CA models, suggesting that multiple factors are not necessarily more effective than a single factor in simulating present urban patterns. The future scenarios produced by the IFB-DE-CA models are substantially shaped by the corresponding factors. These scenarios can inform urban modelers and policy-makers as to how Hangzhou city will evolve if the corresponding factors are individually focused. This study improves our understanding of the effects of driving factors on urban expansion and future scenarios when incorporating the factors separately

Expression, Purification and Antibacterial Activity of NK-Lysin Mature Peptides from the Channel Catfish (Ictalurus punctatus)

Antimicrobial peptides (AMPs) are small peptides and play important roles in host innate immune response against microbial invasion. Aquatic animals secrete different kinds of antimicrobial peptides which have antimicrobial activity towards microorganisms. NK-lysins, mature peptides produced by cytotoxic T lymphocytes and natural killer cells, are comprised of 74–78 amino acid residues, demonstrating broad-spectrum antimicrobial activity against bacteria, fungi, protozoa, and parasites. In this study, three distinct NK-lysin mature peptide (mNKLs), transcripts (76 amino acid residues) cloned from the channel catfish (Ictalurus punctatus) head kidney were ligated into plasmid vector pET-32a(+) to express the mNKLs fusion protein. The fusion protein was successfully expressed in E. coli Rosetta (DE3) under optimized conditions. After purification by affinity column chromatography, the fusion protein was successfully cleaved by enterokinase and released the peptide mNKLs. Tricine-SDS-PAGE results showed that mNKLs (approximately 8.6 kDa) were successfully expressed. The purified peptide mNKLs exhibited antibacterial activity against Staphylococcus aureus and E. coli

The altered hippocampal functional connectivity and serum brain-derived neurotrophic factor level predict cognitive decline in patients with knee osteoarthritis

Patients with knee osteoarthritis (KOA) often suffer from cognitive decline and increased dementia risk, but the neurobiological mechanisms remain unclear. In this study, we evaluated cognitive performance and collected brain magnetic resonance imaging (MRI) data and blood samples from cognitively normal KOA patients at baseline sessions and reevaluated their cognition after 5 years. We also collected MRI data from matched healthy controls. Results showed that KOA patients exhibited dysregulated functional connectivities between the hippocampus and thalamus/superior frontal gyrus compared with healthy controls. The altered hippocampal functional connectivities were associated with serum brain-derived neurotrophic factor (BDNF) levels and spatial expression of genes enriched in synaptic plasticity. The hippocampus-thalamus functional connectivity was significantly correlated with patients&#39; memory scores. Moreover, the baseline hippocampus-thalamus functional connectivity and BDNF levels significantly predicted the development of cognitive decline in KOA patients in the follow-up session. Our findings provide insight into the neurobiological underpinnings of KOA and cognitive decline.</p

A Novel Estrogen Receptor β Agonist Diminishes Ovarian Cancer Stem Cells via Suppressing the Epithelial-to-Mesenchymal Transition

Epithelial ovarian cancer is the most lethal malignancy of the female reproductive tract. A healthy ovary expresses both Estrogen Receptor α (ERα) and β (ERβ). Given that ERα is generally considered to promote cell survival and proliferation, thereby, enhancing tumor growth, while ERβ shows a protective effect against the development and progression of tumors, the activation of ERβ by its agonists could be therapeutically beneficial for ovarian cancer. Here, we demonstrate that the activation of ERβ using a newly developed ERβ agonist, OSU-ERb-12, can impede ovarian cancer cell expansion and tumor growth in an ERα-independent manner. More interestingly, we found that OSU-ERb-12 also reduces the cancer stem cell (CSC) population in ovarian cancer by compromising non-CSC-to-CSC conversion. Mechanistically, we revealed that OSU-ERb-12 decreased the expression of Snail, a master regulator of the epithelial-to-mesenchymal transition (EMT), which is associated with de novo CSC generation. Given that ERα can mediate EMT and facilitate maintenance of the CSC subpopulation and that OSU-ERb-12 can block the transactivity of ERα, we conclude that OSU-ERb-12 reduces the CSC subpopulation by inhibiting EMT in an ERα-dependent manner. Taken together, our data indicate that the ERβ agonist OSU-ERb-12 could be used to hinder tumor progression and limit the CSC subpopulation with the potential to prevent tumor relapse and metastasis in patients with ovarian cancer