Ghosts of Landuse Past: Legacy Effects of Milldams for Riparian Nitrogen (N) Processing and Water Quality Functions

Milldams and their legacies have significantly influenced fluvial processes and geomorphology. However, less is known about their effects on riparian zone hydrology, biogeochemistry, and water quality. Here, we discuss the potential effects of existing and breached milldams on riparian nitrogen (N) processing through multiple competing hypotheses and observations from complementary studies. Competing hypotheses characterize riparian zone processes that remove (sink) or release (source) N. Elevated groundwater levels and reducing soil conditions upstream of milldams suggest that riparian zones above dams could be hotspots for N removal via denitrification and plant N uptake. On the other hand, dam removals and subsequent drops in stream and riparian groundwater levels result in drained, oxic soils which could increase soil nitrification and decrease riparian plant uptake due to groundwater bypassing the root zone. Whether dam removals would result in a net increase or decrease of N in riparian groundwaters is unknown and needs to be investigated. While nitrification, denitrification, and plant N uptake have typically received the most attention in riparian studies, other N cycle processes such as dissimilatory nitrate reduction to ammonium (DNRA) need to be considered. We also propose a novel concept of riparian discontinuum, which highlights the hydrologic and biogeochemical discontinuities introduced in riparian zones by anthropogenic structures such as milldams. Understanding and quantifying how milldams and similar structures influence the net source or sink behavior of riparian zones is urgently needed for guiding watershed management practices and for informed decision making with regard to dam removals

Class I histone deacetylases (HDAC1-3) are histone lysine delactylases

Lysine L-lactylation [K(L-la)] is a newly discovered histone mark stimulated under conditions of high glycolysis, such as the Warburg effect. K(L-la) is associated with functions that are different from the widely studied histone acetylation. While K(L-la) can be introduced by the acetyltransferase p300, histone delactylases enzymes remained unknown. Here, we report the systematic evaluation of zinc- and nicotinamide adenine dinucleotide-dependent histone deacetylases (HDACs) for their ability to cleave ε-N-L-lactyllysine marks. Our screens identified HDAC1-3 and SIRT1-3 as delactylases in vitro. HDAC1-3 show robust activity toward not only K(L-la) but also K(D-la) and diverse short-chain acyl modifications. We further confirmed the de-L-lactylase activity of HDACs 1 and 3 in cells. Together, these data suggest that histone lactylation is installed and removed by regulatory enzymes as opposed to spontaneous chemical reactivity. Our results therefore represent an important step toward full characterization of this pathway's regulatory elements

Genetic variants in the TIRAP gene are associated with increased risk of sepsis-associated acute lung injury

<p>Abstract</p> <p>Background</p> <p>Toll like receptors (TLRs) signaling pathways, including the adaptor protein Mal encoded by the TIRAP gene, play a central role in the development of acute lung injury (ALI). Recently, the <it>TIRAP </it>variants have been described association with susceptibility to inflammatory diseases. The aim of this study was to investigate whether genetic variants in <it>TIRAP </it>are associated with the development of ALI.</p> <p>Methods</p> <p>A case-control collection from Han Chinese of 298 healthy subjects, 278 sepsis-associated ALI and 288 sepsis alone patients were included. Three tag single nucleotide polymorphisms (SNPs) of the TIRAP gene and two additional SNPs that have previously showed association with susceptibility to other inflammatory diseases were genotyped by direct sequencing. The differences of allele, genotype and haplotype frequencies were evaluated between three groups.</p> <p>Results</p> <p>The minor allele frequencies of both rs595209 and rs8177375 were significantly increased in ALI patients compared with both healthy subjects (odds ratio (OR) = 1.47, 95% confidence interval (CI):1.15-1.88, P = 0.0027 and OR = 1.97, 95% CI: (1.38-2.80), P = 0.0001, respectively) and sepsis alone patients (OR = 1.44, 95% CI: 1.12-1.85, P = 0.0041 and OR = 1.82, 95% CI: 1.28-2.57, P = 0.00079, respectively). Haplotype consisting of these two associated SNPs strengthened the association with ALI susceptibility. The frequency of haplotype AG (rs595209A, rs8177375G) in the ALI samples was significantly higher than that in the healthy control group (OR = 2.13, 95% CI: 1.46-3.09, P = 0.00006) and the sepsis alone group (OR = 2.24, 95% CI: 1.52-3.29, P = 0.00003). Carriers of the haplotype CA (rs595209C, rs8177375A) had a lower risk for ALI compared with healthy control group (OR = 0.69, 95% CI: 0.54-0.88, P = 0.0003) and sepsis alone group (OR = 0.71, 95% CI: 0.55-0.91, P = 0.0006). These associations remained significant after adjustment for covariates in multiple logistic regression analysis and for multiple comparisons.</p> <p>Conclusions</p> <p>These results indicated that genetic variants in the TIRAP gene might be associated with susceptibility to sepsis-associated ALI in Han Chinese population. However, the association needs to be replicated in independent studies.</p

Transient mTOR Inhibition Facilitates Continuous Growth of Liver Tumors by Modulating the Maintenance of CD133+ Cell Populations

The mammalian target of the rapamycin (mTOR) pathway, which drives cell proliferation, is frequently hyperactivated in a variety of malignancies. Therefore, the inhibition of the mTOR pathway has been considered as an appropriate approach for cancer therapy. In this study, we examined the roles of mTOR in the maintenance and differentiation of cancer stem-like cells (CSCs), the conversion of conventional cancer cells to CSCs and continuous tumor growth in vivo. In H-Ras-transformed mouse liver tumor cells, we found that pharmacological inhibition of mTOR with rapamycin greatly increased not only the CD133+ populations both in vitro and in vivo but also the expression of stem cell-like genes. Enhancing mTOR activity by over-expressing Rheb significantly decreased CD133 expression, whereas knockdown of the mTOR yielded an opposite effect. In addition, mTOR inhibition severely blocked the differentiation of CD133+ to CD133- liver tumor cells. Strikingly, single-cell culture experiments revealed that CD133- liver tumor cells were capable of converting to CD133+ cells and the inhibition of mTOR signaling substantially promoted this conversion. In serial implantation of tumor xenografts in nude BALB/c mice, the residual tumor cells that were exposed to rapamycin in vivo displayed higher CD133 expression and had increased secondary tumorigenicity compared with the control group. Moreover, rapamycin treatment also enhanced the level of stem cell-associated genes and CD133 expression in certain human liver tumor cell lines, such as Huh7, PLC/PRC/7 and Hep3B. The mTOR pathway is significantly involved in the generation and the differentiation of tumorigenic liver CSCs. These results may be valuable for the design of more rational strategies to control clinical malignant HCC using mTOR inhibitors

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics