Miracle-dz/UniFAR-FTUs huggingface dataset:
Platinum-group element geochemistry of the layered intrusions in the Emeishan large igneous province, SW China: Implications for the principal controls on magmatic sulfide immiscibility

It is widely accepted that the incorporation of external sulfur via crustal contamination is an important trigger for sulfide immiscibility that generates Ni-Cu-(PGE) sulfide mineralization, yet other controlling factors for sulfide immiscibility may also be present. The late Permian Panzhihua, Baima, Hongge, Xinjie and Taihe layered intrusions in the Emeishan Large Igneous Province (ELIP, SW China), are well-endowed with Fe-Ti oxide deposits, whereas their sulfide mineralization is mainly sub-economic. For example, the lower part of the Xinjie intrusion hosts a few thin PGE-rich ore layers, yet other ELIP layered intrusions do not contain any Ni-Cu sulfide mineralization and are PGE-depleted (0.01–1 ppb). Compared with the PGE-undepleted Emeishan high-Ti basalts that are genetically related to the intrusions, the extent of PGE depletion and elevated Cu/Pd ratios (up to 3.2×106) of the Panzhihua, Baima, Taihe and Hongge intrusions suggest PGE-depletion in their parental magmas due to early-stage sulfide removal. Sr-Nd isotopic compositions of the Panzhihua, Baima and Taihe intrusions suggest crustal contamination was insignificant and sulfide saturation produced mainly by crustal sulfur input was unlikely. MELTS modeling shows that extensive fractionation of chromite, olivine and clinopyroxene in deep-seated magma chambers may have induced early-stage sulfide saturation of the primary magmas. The relatively high sulfide contents in the Fe-Ti oxide layers at Panzhihua, Baima, Hongge and Taihe indicate a close relationship between the second-stage sulfide immiscibility and extensive Fe-Ti oxide crystallization. Positive correlations between sulfur and total Fe2O3, V and TiO2 suggest that Fe-Ti oxide (magnetite and ilmenite) crystallization may have triggered the second-stage sulfide saturation via sharply lowering the Fe concentration and oxygen fugacity of the magmas. Moderate degree of crustal contamination for the Xinjie Fe-Ti oxide-barren rocks may have induced sulfide saturation and accumulation at the lower part of the intrusion. Our calculations indicate that the Xinjie PGE-rich rocks have high R-factors (1000–10000), which are ascribed to PGE-upgrading of the sulfides via reaction with new replenishments of PGE-undepleted magmas. A few Panzhihua, Baima and Taihe samples that contain higher PGE concentrations suggest that the early-stage sulfide droplets at depths were entrained in later magma pulses delivered to shallower magma chambers. The very high R-factors determined by mass balance calculation, implies a good potential for discovering more PGE mineralization in the deep-seated intrusions of the magma plumbing system.
Effect of copper mill waste material on benthic invertebrates and zooplankton diversity and abundance in Lake Superior beaches

From 1900 to 1932 a copper (Cu) mill operated near Gay, Michigan, along the eastern shore of the Keweenaw Peninsula (Lake Superior, Michigan) and discharged waste material (stamp sands [SS]) to a nearby beach. These SS escaped containment structures and have been redeposited by wave action along the beaches in northern Grand Traverse Bay and onto Buffalo Reef, an important spawning area for native fish. Newly hatched fish move into nearby beach habitats where they grow during their first summer. Juvenile fish initially consume zooplankton before switching to benthic invertebrates once they are large enough. SS contain metals (especially Cu) that are toxic to many invertebrate taxa, and studies have observed few benthic taxa in areas covered by SS. We sampled the invertebrate community from four Lake Whitefish nursery areas: one near Buffalo Reef with high SS, one south of the Traverse River with moderate SS, one in nearby Little Traverse Bay with little SS, and a beach ∼58 km away with no SS (Big Bay). We also resampled the benthos at sites that had been sampled as part of an earlier Grand Traverse Bay study. Buffalo Reef (high SS) had fewer benthic taxa, and less density of several taxa than Little Traverse Bay (little SS), especially benthic copepods. All beaches had comparable zooplankton diversity, but the abundance was ∼2 orders of magnitude lower at Buffalo Reef (high SS) than other beaches. Cu and several other metals were elevated at beaches with more SS. We found support for associations between benthic density and diversity with depth (positive effect) and Cu concentration (negative effect). Cu concentration was a better predictor of declines in benthic invertebrate abundance and diversity than SS. We also observed that the relationship between Cu concentration and SS was non-linear, and highly variable. For example, 149 mg Cu/kg dry weight sediment is a consensus toxicity threshold used in the literature, but the prediction interval around that concentration from our model is 26-851 mg Cu/kg dry weight. A better predictive model of this relationship would be beneficial to develop to understand what level of SS reduction would prevent Cu impacts on invertebrates.
VASP phase separation with priming proteins of fast endophilin mediated endocytosis modulates actin polymerization

Actin polymerization is essential in several clathrin-independent endocytic pathways including fast endophilin mediated endocytosis (FEME), however the actin machinery involved in FEME has been elusive. Here, we show that the actin polymerase VASP, colocalizes and interacts directly with the FEME priming complex. We identify endophilin (EDP) as a VASP binding partner and establish novel non-canonical interactions between EDP and the EVH1 and EVH2 domains of VASP. The major FEME regulators EDP and lamellipodin (LPD) interact multivalently with VASP undergoing liquid-liquid phase separation both in solution and on lipid membranes. We show that priming complex mimicking condensates localise actin polymerization, with LPD-VASP promoting and EDP antagonising actin assembly, suggesting a novel role for EDP during the priming step of FEME. Finally, we show that LPD and EDP recruits and clusters VASP on lipid membranes mimicking the plasma membrane’s inner leaflet to locally assemble actin filaments. Our work supports a model where actin polymerization in FEME is spatiotemporally initiated by the depletion of EDP, mediated by receptor activation. Teaser Liquid-like condensates formed by actin polymerases and endocytic proteins, localise and regulate actin polymerization.
DNA damage drives antigen diversification through mosaic VSG formation in Trypanosoma brucei

Antigenic variation, using large genomic repertoires of antigen-encoding genes, allows pathogens to evade host antibody. Many pathogens, including the African trypanosome Trypanosoma brucei, extend their antigenic repertoire through genomic diversification. While evidence suggests that T. brucei relies heavily on the generation of new variant surface glycoprotein (VSG) genes to maintain a chronic infection, a lack of experimentally tractable tools for studying this process has obscured its underlying mechanisms. Here, we present a highly sensitive targeted RNA sequencing approach for measuring VSG diversification. Using this method, we demonstrate that a Cas9-induced DNA double-strand break within the VSG coding sequence can induce VSG recombination with patterns identical to those observed during infection. These newly generated VSGs are antigenically distinct from parental clones and thus capable of facilitating immune evasion. Together, these results provide insight into the mechanisms of VSG diversification and an experimental framework for studying the evolution of antigen repertoires in pathogenic microbes.
Base composition at the start of the coding sequence controls the balance between translation initiation and mRNA degradation in E. coli

Protein synthesis efficiency is highly dependent on mRNA coding sequence. Furthermore, there is extensive evidence of a correlation between mRNA stability and protein expression level, though the mechanistic determinants remain unclear. Using yellow fluorescent protein (YFP) as a reporter gene, we herein demonstrate that adenosine (A) abundance in the first six codons is a critical determinant for achieving high protein synthesis in E. coli. Increasing A and/or decreasing guanosine (G) content in this region results in substantial increases in protein expression level both in vivo and in vitro that are correlated with steady-state mRNA concentration in vivo, and this effect is attributable to changes in the stability of the mRNA that are directly coupled to its translation efficiency. Increasing A content promotes mRNA incorporation into the functional 70S ribosomal initiation complex without altering its affinity for the 30S ribosomal subunit. These results support a model in which base composition in the first six codons modulates local mRNA folding energy to control the balance between productive translation initiation versus degradation of mRNAs bound to the 30S ribosomal subunit. Based on these findings, we developed a short N-terminal coding sequence that optimizes translation initiation efficiency for protein production in E. coli.
Modeling springtime shallow frontal clouds with cloud-resolving and single-column models

This modeling study compares the performance of eight single-column models (SCMs) and four cloud-resolving models (CRMs) in simulating shallow frontal cloud systems observed during a subperiod of the March 2000 ARM intensive operational period (IOP). Except for the passage of a cold front at the beginning of this subperiod, frontal cloud systems are driven by a persistent frontogenesis over the Southern Great Plains and moisture transport from northwestern part of the Gulf of Mexico. This study emphasizes quantitative comparisons among model simulations and with data, focusing on a 27 h period when only shallow frontal clouds were observed. All CRMs and SCMs qualitatively simulated clouds in the observed shallow cloud layer. Significantly different cloud amounts and cloud microphysical properties are, however, found in the model simulations. All CRMs do not produce any clouds above the observed shallow cloud layer, but most SCMs produce clouds in the middle and upper troposphere. Possible causes are discussed in this study. One is the strong decoupling between cloud condensate and cloud fraction in nearly all SCM parameterizations. Clouds are produced whenever the relative humidity (RH) reaches its threshold although the cloud water content is almost nonexistent. The other is the weak upper tropospheric subsidencemore » that has been averaged over both descending and ascending regions, i.e., the unresolved upper-level dynamical forcings. The intermodel differences are also analyzed and related to the detailed formulations of cloud microphysical processes and fractional cloud parameterizations in the SCMs and possibly to the dynamical framework in the CRMs. The underestimate of cloud liquid water content (LWC) in some SCMs is related to the Sundqvist-type formulation of the autoconversion process or the small threshold value for autoconversion, based upon the comparison between the observed and simulated LWCs. Although two of the CRMs with anelastic dynamics simulate the shallow frontal cloud much better than the SCMs, the CRMs do not necessarily perform much better than the SCMs for the entire subperiod when deep frontal clouds are presents. For the simulations of the entire subperiod, the CRM results show a vertical phase tilting in the cloud fractions while the SCM results show a vertical phase tilting in the LWCs. The observed cloud property profiles do not have any vertical phase tilting. The peak magnitudes of the simulated cloud properties are underestimated in most models and the life cycles of the simulated frontal cloud systems are much longer than those observed. These results suggest the importance of the horizontal advection of hydrometeors, which are currently not available, to drive model simulations and to adequately evaluate the performance of the models in the future. « less
Using CSP to Detect Errors in the TMN Protocol

We use FDR (Failures Divergence Refinement), a model checker for CSP, to detect errors in the TMN protocol (M. Tatebayashi et al., 1990). We model the protocol and a very general intruder as CSP processes, and use the model checker to test whether the intruder can successfully attack the protocol. We consider three variants on the protocol, and discover a total of 10 different attacks leading to breaches of security.
Glyphosate Effects on Growth and Biofilm Formation in Bee Gut Symbionts and Diverse Associated Bacteria

Biofilm formation is a common adaptation enabling bacteria to thrive in various environments and to withstand external pressures. In the context of host-microbe interactions, biofilms play vital roles in establishing microbiomes associated with animals and plants and are used by opportunistic microbes to facilitate proliferation within hosts. Investigating biofilm dynamics, composition, and responses to environmental stressors is crucial for understanding microbial community assembly and biofilm regulation in health and disease. In this study, we explore the independent gut colonization and in vitro biofilm formation abilities of core members of the honey bee (Apis mellifera) gut microbiota. Additionally, we assess the impact of glyphosate, a widely used herbicide with antimicrobial properties, and a glyphosate-based formulation on growth and biofilm formation in bee gut symbionts as well as in other biofilm-forming bacteria associated with diverse animals and plants. Our results demonstrate that several strains of core bee gut bacterial species can independently colonize the bee gut, which probably depends on their ability to form biofilms. Furthermore, glyphosate exposure has varying effects on bacterial growth and biofilm formation. These findings imply specific impacts of environmental stressors on microbial biofilms with both ecological and host health-related implications. Importance Biofilms are essential for microbial communities to establish and thrive in diverse environments. In the honey bee gut, the core microbiota member Snodgrassella alvi forms biofilms, potentially aiding the establishment of other members and promoting interactions with the host. In this study, we show that specific strains of other core members, including Bifidobacterium, Bombilactobacillus, Gilliamella, and Lactobacillus, also form biofilms. We then examine the impact of glyphosate, a widely used herbicide that disrupts the bee microbiota, on their growth and biofilm formation. Our findings demonstrate diverse effects of glyphosate on biofilm formation, ranging from inhibition to enhancement, reflecting observations in other beneficial or pathogenic bacteria associated with animals and plants. Thus, glyphosate exposure may influence bacterial growth and biofilm formation, potentially shaping microbial establishment on host surfaces and impacting health outcomes.
Talin-Null Cells of Dictyostelium Are Strongly Defective in Adhesion to Particle and Substrate Surfaces and Slightly Impaired in Cytokinesis

Dictyostelium discoideum contains a full-length homologue of talin, a protein implicated in linkage of the actin system to sites of cell-to-substrate adhesion in fibroblasts and neuronal growth cones. Gene replacement eliminated the talin homologue in Dictyostelium and led to defects in phagocytosis and cell-to-substrate interaction of moving cells, two processes dependent on a continuous cross talk between the cell surface and underlying cytoskeleton. The uptake rate of yeast particles was reduced, and only bacteria devoid of the carbohydrate moiety of cell surface lipopolysaccharides were adhesive enough to be recruited by talin-null cells in suspension and phagocytosed. Cell-to-cell adhesion of undeveloped cells was strongly impaired in the absence of talin, in contrast with the cohesion of aggregating cells mediated by the phospholipid-anchored contact site A glycoprotein, which proved to be less talin dependent. The mutant cells were still capable of moving and responding to a chemoattractant, although they attached only loosely to a substrate via small areas of their surface. With their high proportion of binucleated cells, the talin-null mutants revealed interactions of the mitotic apparatus with the cell cortex that were not obvious in mononucleated cells.
CycleVTON: A Cycle Mapping Framework for Parser-Free Virtual Try-On

Image-based virtual try-on aims to transfer a target clothing onto a specific person. A significant challenge is arbitrarily matched clothing and person lack corresponding ground truth to supervised learning. A recent pioneering work leveraged an improved cycleGAN to enable one network to generate the desired image for another network during training. However, there is no difference in the result distribution before and after the clothing changes. Therefore, using two different networks is unnecessary and may even increase the difficulty of convergence. Furthermore, the introduced human parsing used to provide body structure information in the input also have a negative impact on the try-on result. How to employ a single network for supervised learning while eliminating human parsing? To tackle these issues, we present a Cycle mapping Virtual Try-On Network (CycleVTON), which can produce photo-realistic try-on results by using a cycle mapping framework without the parser. In particular, we introduce a flow constraint loss to achieve supervised learning of arbitrarily matched clothing and person as inputs to the deformer, thus naturally mimicking the interaction between clothing and the human body. Additionally, we design a skin generation strategy that can adapt to the shape of the target clothing by dynamically adjusting the skin region, i.e., by first removing and then filling skin areas. Extensive experiments conducted on challenging benchmarks demonstrate that our proposed method exhibits superior performance compared to state-of-the-art methods.
Stop the dicing in hematopoiesis

MicroRNAs (miRNAs) belong to an abundant class of highly conserved small (22nt) non-coding RNAs. MiRNA profiling studies indicate that their expression is highly cell type-dependent. DICER1 is an essential RNase III endoribonuclease for miRNA processing. Hematopoietic cell type- and developmental stage-specific Dicer1 deletion models show that miRNAs are essential regulators of cellular survival, differentiation and function. For instance, miRNA deficiency in hematopoietic stem cells and progenitors of different origins results in decreased cell survival, dramatic developmental aberrations or dysfunctions in mice. We recently found that homozygous Dicer1 deletion in myeloid-committed progenitors results in an aberrant expression of stem cell genes and induces a regained self-renewal capacity. Moreover, Dicer1 deletion causes a block in macrophage development and myeloid dysplasia, a cellular condition that may be considered as a preleukemic state. However, Dicer1-null cells do not develop leukemia in mice, indicating that depletion of miRNAs is not enough for tumorigenesis. Surprisingly, we found that heterozygous Dicer1 deletion in myeloid-committed progenitors, but not Dicer1 knockout, collaborates with p53 deletion in leukemic progression and results in various types of leukemia. Our data indicate that Dicer1 is a haploinsufficient tumorsuppressor in hematopoietic neoplasms, which is consistent with the observed downregulation of miRNA expression in human leukemia samples. Here, we review the various hematopoietic specific Dicer1 deletion mouse models and the phenotypes observed within the different hematopoietic lineages and cell developmental stages. Finally, we discuss the role for DICER1 in mouse and human malignant hematopoiesis.
Dual-Channel Learning Framework for Drug-Drug Interaction Prediction via Relation-Aware Heterogeneous Graph Transformer

Identifying novel drug-drug interactions (DDIs) is a crucial task in pharmacology, as the interference between pharmacological substances can pose serious medical risks. In recent years, several network-based techniques have emerged for predicting DDIs. However, they primarily focus on local structures within DDI-related networks, often overlooking the significance of indirect connections between pairwise drug nodes from a global perspective. Additionally, effectively handling heterogeneous information present in both biomedical knowledge graphs and drug molecular graphs remains a challenge for improved performance of DDI prediction. To address these limitations, we propose a Transformer-based relatIon-aware Graph rEpresentation leaRning framework (TIGER) for DDI prediction. TIGER leverages the Transformer architecture to effectively exploit the structure of heterogeneous graph, which allows it direct learning of long dependencies and high-order structures. Furthermore, TIGER incorporates a relation-aware self-attention mechanism, capturing a diverse range of semantic relations that exist between pairs of nodes in heterogeneous graph. In addition to these advancements, TIGER enhances predictive accuracy by modeling DDI prediction task using a dual-channel network, where drug molecular graph and biomedical knowledge graph are fed into two respective channels. By incorporating embeddings obtained at graph and node levels, TIGER can benefit from structural properties of drugs as well as rich contextual information provided by biomedical knowledge graph. Extensive experiments conducted on three real-world datasets demonstrate the effectiveness of TIGER in DDI prediction. Furthermore, case studies highlight its ability to provide a deeper understanding of underlying mechanisms of DDIs.
Incorporating Generalization Heuristics into Verification of Prolog Programs

This paper is concerned with the problem of generalization heuristics, which are incorporated into our verification system for Prolog programs. Two kinds of generalization are discussed, that is, a mechanical generalisation and an intelligent generalization. We show that the mechanical generalization used in Boyer-Moore*s theorem prover (BMTP) can be performed by the simplification rule of our verification system, as well as in the case of cross-fertilization. To the intelligent generalization heuristic, which is not employed in BMTP, we give a generalization scheme which is naturally incorporated into our inference system of the extended-execution style of the Prolog interpreter, and which proves to be effective also for flawed induction schemes.