Miracle-dz/UniFAR-FTUs huggingface dataset:
MoS2 as a co‐catalyst for photocatalytic hydrogen production from water

Solar‐to‐hydrogen conversion based on photocatalytic water splitting is a promising pathway for sustainable hydrogen production. The photocatalytic process requires highly active, inexpensive, and earth‐abundant materials as photocatalysts. As a presentative layer‐structured transition metal dichalcogenides, molybdenum disulfide (MoS2) is attracting intensive attention due to its unique electro and photo properties. In this article, we comprehensively review the recent research efforts of exploring MoS2 as a co‐catalyst for photocatalytic hydrogen production from water, with emphasis on its combination with CdS, CdSe, graphene, carbon nitride, TiO2, and others. It is shown that MoS2–semiconductor composites are promising photocatalysts for hydrogen evolution from water under visible light irradiation.
Stochastic simulation and calibration of organometallic photoresists for extreme ultraviolet lithography

Abstract. Organometallic photoresists are being pursued as an alternative photoresist material to push the current extreme ultraviolet lithography (EUVL) to the next generation of high-NA EUVL. In order to improve the photoresist performance, an understanding of the photoresist’s response to different process conditions is required. In this endeavor, a stochastic development model is implemented, integrated into full photoresist process steps, and applied for photoresist performance investigations. The model is applied to Inpria-YA photoresist, which works mainly by the process of aggregation. Previously published modeling approaches for metal-organic photoresists assume that the development characteristics of these materials depend only on the size of the created oxo-clusters. In contrast to that, we propose a modeling approach that provides a more detailed description of the interaction among the developer, ligands, and oxo-bonds. Further, the calibration procedures conducted to extract the model parameters to match experimental data are discussed. The model approximated the experimental data with CD RMSE and LWR RMSE of 0.60 and 0.40 nm, respectively. We also investigated the impact of photoresist parameters on the process metrics, line width roughness (LWR), critical dimension (CD), dose-to-size (DtS), and exposure latitude (EL) with the calibrated model. The investigation shows that details of the interaction of photoresist and developer, especially, the so-called development critical value, have a significant impact on the LWR and DtS.
Automatic Deception Detection using Multiple Speech and Language Communicative Descriptors in Dialogs

While deceptive behaviors are a natural part of human life, it is well known that human is generally bad at detecting deception. In this study, we present an automatic deception detection framework by comprehensively integrating prior domain knowledge in deceptive behavior understanding. Specifically, we compute acoustics, textual information, implicatures with non-verbal behaviors, and conversational temporal dynamics for improving automatic deception detection in dialogs. The proposed model reaches start-of-the-art performance on the Daily Deceptive Dialogues corpus of Mandarin (DDDM) database, 80.61% unweighted accuracy recall in deception recognition. In the further analyses, we reveal that (i) the deceivers’ deception behaviors can be observed from the interrogators’ behaviors in the conversational temporal dynamics features and (ii) some of the acoustic features (e.g. loudness and MFCC) and textual features are significant and effective indicators to detect deception behaviors.
Synthesis of magnetic ferrogels: a tool-box approach for finely tuned magnetic- and temperature-dependent properties

Abstract Multi responsive hydrogels have many potential applications in the field of medicine as well as technical fields and are of great interest in fundamental research. Here we present the synthesis and characterization of tailored magnetic hydrogels – micro- as well as macrogels – which consist of iron oxide and cobalt ferrite, varying in phase and morphology, embedded in a thermoresponsive polymer. We introduce new ways to synthesize magnetic particles and revisit some common strategies when dealing with particle synthesis. Subsequently we discuss the details of the thermoresponsive matrix and how we can influence and manipulate the thermoresponsive properties, i.e. the lower critical solution temperature. Ultimately, we present the particle-hydrogel composite and show two exemplary applications for particle matrix interactions, i.e. heat transfer and reorientation of the particles in a magnetic field.
Origins and mechanisms leading to aneuploidy in human eggs

The gain or loss of a chromosome—or aneuploidy—acts as one of the major triggers for infertility and pregnancy loss in humans. These chromosomal abnormalities affect more than 40% of eggs in women at both ends of the age spectrum, that is, young girls as well as women of advancing maternal age. Recent studies in human oocytes and embryos using genomics, cytogenetics, and in silico modeling all provide new insight into the rates and potential genetic and cellular factors associated with aneuploidy at varying stages of development. Here, we review recent studies that are shedding light on potential molecular mechanisms of chromosome missegregation in oocytes and embryos across the entire female reproductive life span.
Chemotherapy induces a YAP1-dependent fetal conversion to human Colorectal Cancer cells that is predictive of poor patient outcome

Current therapy against colorectal cancer is based on DNA-damaging agents that eradicate highly proliferative malignant cells. Whether sublethal chemotherapy affects tumor cell behavior and impacts on patient outcome is primarily unstudied. We now show that sublethal chemotherapy imposes a quiescent-like state to p53 wildtype human colorectal cancer (CRC) cells that is linked to the acquisition of a fetal phenotype downstream of YAP1, similar to that observed after intestinal damage. CRC cells displaying this fetal phenotype exhibit tumor- initiating activity comparable to untreated cells but superior metastatic capacity. Notably, nuclear YAP1 accumulation, or detection of the fetal signature in tumors predict poor prognosis in CRC patients carrying p53 wildtype tumors. Collectively, our results uncover a potential adverse response of tumor cells to suboptimal chemotherapy, and identify nuclear YAP1 and fetal conversion of colorectal tumors as biomarkers for prognosis and therapy prescription. Statement of significance Chemotherapy induces a quiescent-like phenotype to colorectal cancer cells that is linked to the acquisition of a YAP1-dependent fetal signature. Notably, this signature is predictive of patient outcome in different cohorts of human colorectal cancer.
Portrait of a genus: the genetic diversity of Zea

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in the wild relatives of maize. Here, we characterize a high-density genomic variation map from ~700 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 65 million single nucleotide polymorphisms (SNPs), 8 million Insertion/Deletion (InDel) polymorphisms, and over one thousand novel inversions. The variation map reveals evidence of selection within taxa displaying novel adaptations such as perenniality and regrowth. We focus in detail on evidence of convergent adaptation in highland teosinte and temperate maize. This study not only indicates the key role of hormone related pathways in highland adaptation and flowering time related pathways in high latitude adaptation, but also identifies significant overlap in the genes underlying adaptations to both environments. To show how this data can identify useful genetic variants, we generated and characterized novel mutant alleles for two flowering time candidate genes. This work provides the most extensive sampling to date of the genetic diversity inherent in the genus Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.
Novel antiviral interferon sensitive genes unveiled by correlation-driven gene selection and integrated systems biology approaches

Interferons (IFNs) are key cytokines involved in alerting the immune system to viral infection. After IFN stimulation, cellular transcriptional profile critically changes, leading to the expression of several IFN stimulated genes (ISGs) that exert a wide variety of antiviral activities. Despite many ISGs have been already identified, a comprehensive network of coding and non-coding genes with a central role in IFN-response still needs to be elucidated. We performed a global RNA-Seq transcriptome profile of the HCV permissive human hepatoma cell line Huh7.5 and its parental cell line Huh7, upon IFN treatment, to define a network of genes whose coordinated modulation plays a central role in IFN-response. Our study adds molecular actors, coding and non-coding genes, to the complex molecular network underlying IFN-response and shows how systems biology approaches, such as correlation networks, network’s topology and gene ontology analyses can be leveraged to this aim.
DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

Motivation Drug combination therapy has become a increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experiments. Therefore, computational screening has become an important way to prioritize drug combinations. Graph neural network have recently shown remarkable performance in the prediction of compound-protein interactions, but it has not been applied to the screening of drug combinations. Results In this paper, we proposed a deep learning model based on graph neural networks and attention mechanism to identify drug combinations that can effectively inhibit the viability of specific cancer cells. The feature embeddings of drug molecule structure and gene expression profiles were taken as input to multi-layer feedforward neural network to identify the synergistic drug combinations. We compared DeepDDS with classical machine learning methods and other deep learning-based methods on benchmark data set, and the leave-one-out experimental results showed that DeepDDS achieved better performance than competitive methods. Also, on an independent test set released by well-known pharmaceutical enterprise AstraZeneca, DeepDDS was superior to competitive methods by more than 16% predictive precision. Furthermore, we explored the interpretability of the graph attention network, and found the correlation matrix of atomic features revealed important chemical substructures of drugs. We believed that DeepDDS is an effective tool that prioritized synergistic drug combinations for further wet-lab experiment validation. Availability and implementation Source code and data are available at https://github.com/Sinwang404/DeepDDS/tree/master
Caspar, an adapter for VAP and TER94 delays progression of disease by regulating glial inflammation in a Drosophila model of ALS8

Amyotrophic Lateral Sclerosis (ALS) is a fatal, late onset, progressive motor neurodegenerative disorder. We have been studying cellular and molecular mechanisms involved in ALS using a vesicle-associated membrane protein-associated protein B (VAPB/ALS8) Drosophila model, which mimics many systemic aspects of the human disease. Here, we show that the ER resident VAPB interacts with Caspar, an ortholog of human fas associated factor 1 (FAF1). Caspar, in turn, interacts with transitional endoplasmic reticulum ATPase (TER94), a fly ortholog of ALS14 (VCP/p97, Valosin-containing protein), via its UBX domain and poly-ubiqutinated proteins with its UBA domain. Caspar overexpression in the glia extends lifespan and also slows the progression of motor dysfunction in the ALS8 model, a phenomenon that we ascribe to its ability to restrain age-dependant inflammation, modulated by Relish/NFκB signalling. We hypothesize that Caspar is a key molecule in the pathogenesis of ALS. Caspar connects the plasma membrane (PM) localized immune signalosome to the ER based VAPB degradative machinery, presumably at PM:ER contact sites. The Caspar:TER94:VAPB complex appears to be a strong candidate for regulating both protein homeostasis and NFκB signalling. These, in turn, regulate glial inflammation and determine progression of disease. Our study projects human FAF1 as an important protein target to alleviate the progression of motor neuron disease.
Facile synthesis of g-C3N4 nanosheets loaded with WO3 nanoparticles with enhanced photocatalytic performance under visible light irradiation

Graphitic carbon nitride (g-C3N4) nanosheets loaded with WO3 nanoparticles were prepared via heat treatment of g-C3N4 together with WOx-EDA nanobelts. The thermal treatment temperature and WOx-EDA precursor play the key role in enhancing the interaction between WO3 nanoparticles and g-C3N4 nanosheets, because the temperature of thermal decomposition of WOx-EDA (∼400 °C) is close to the thermal exfoliation temperature of g-C3N4. The structure evolution and promotion effect of the nanocomposites in photocatalytic performance were well studied. It is found that WO3 nanoparticles uniformly dispersed on the surface of the g-C3N4 nanosheets, and the close integration of WO3 and g-C3N4 lead to the high photocatalytic activity in the degradation of RhB under visible light irradiation. Meanwhile, a larger specific area and increase of visible light absorption are also of benefit to speed up the degradation of organic dye. Also, the mechanism of the photocatalytic reaction and its reutilization properties were investigated.
Active Microbiome Structure and Functional Analyses of Freshwater Benthic Biofilm Samples Influenced by RNA Extraction Methods

Advances in high-throughput sequencing technologies have enabled extensive studies of freshwater biofilms and significant breakthroughs in biofilm meta-omics. To date, however, no standardized protocols have been developed for the effective isolation of RNA from freshwater benthic biofilms. In this study, we compared column-based kit RNA extraction with five RNAzol-based extractions, differentiated by various protocol modifications. The RNA products were then evaluated to determine their integrity, purity and yield and were subjected to meta-transcriptomic sequencing and analysis. Significant discrepancies in the relative abundance of active communities and structures of eukaryotic, bacterial, archaebacterial, and viral communities were observed as direct outcomes of the tested RNA extraction methods. The column isolation-based group was characterized by the highest relative abundance of Archaea and Eukaryota, while the organic isolation-based groups commonly had the highest relative abundances of Prokaryota (bacteria). Kit extraction methods provided the best outcomes in terms of high-quality RNA yield and integrity. However, these methods were deemed questionable for studies of active bacterial communities and may contribute a significant degree of bias to the interpretation of downstream meta-transcriptomic analyses.
The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data

1 International Maize and Wheat Improvement Center (CIMMYT), Carretera México-Veracruz, de Mexico, Mexico, Colegio de Postgraduados, Montecillo, Edo. de Mexico, Mexico, Department of Genetics, “Luiz de Queiroz” Agriculture College, University of São Paulo, São Paulo, Brazil, 4 Facultad de Telemática, Universidad de Colima, Colima, Mexico, Departamento de Matemáticas, Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara, Mexico
Structural basis for human T-cell leukemia virus type 1 Gag targeting to the plasma membrane for assembly

During the late phase of retroviral replication, the virally encoded Gag polyprotein is targeted to the plasma membrane (PM) for assembly. Gag–PM binding is mediated by the N-terminal matrix (MA) domain of Gag. For many retroviruses, Gag binding to the PM was found to be dependent on phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]. However, it was shown that for human T-cell leukemia virus type 1 (HTLV-1), Gag binding to membranes is less dependent on PI(4,5)P2, suggesting that other factors may modulate Gag assembly. To elucidate the mechanism by which HTLV-1 Gag binds to the PM, we employed NMR techniques to solve the structure of unmyristoylated MA (myr(–)MA) and to characterize its interactions with lipids and liposomes. The MA structure consists of four α-helices and unstructured N- and C-termini. We show that myr(–)MA binds to PI(4,5)P2 via the polar head and that myr(–)MA binding to inositol phosphates (IPs) is significantly enhanced by increasing the number of phosphate groups on the inositol ring, indicating that the MA–IP binding is governed by charge–charge interactions. The IP binding site was mapped to a well-defined basic patch formed by lysine and arginine residues. Using a sensitive NMR-based liposome binding assay, we show that myr(–)MA binding to membranes is significantly enhanced by phosphatidylserine (PS). Confocal microscopy data show that Gag is localized to the inner leaflet of the PM of infected cells, while the Gag G2A mutant, lacking myristoylation, is diffuse and cytoplasmic. These findings advance our understanding of a key mechanism in retroviral assembly.
Serotoninergic Modulation of Phototactic Variability Underpins a Bet-Hedging Strategy in Drosophila melanogaster

When organisms’ environmental conditions vary unpredictably in time, it can be advantageous for individuals to hedge their phenotypic bets. It has been shown that a bet-hedging strategy possibly underlies the high inter-individual diversity of phototactic choice in Drosophila melanogaster. This study shows that fruit flies from a population living in a boreal and relatively unpredictable climate have more variable variable phototactic biases than fruit flies from a more stable tropical climate, consistent with bet-hedging theory. We experimentally show that phototactic variability of D. melanogaster is regulated by the neurotransmitter serotonin (5-HT), which acts as a suppressor of the variability of phototactic choices. When fed 5-HT precursor, boreal flies exhibited lower variability, and they were insensitive to 5-HT inhibitor. The opposite pattern was seen in the tropical flies. Thus, the reduction of 5-HT in fruit flies’ brains may be the mechanistic basis of an adaptive bet-hedging strategy in a less predictable boreal climate.
Propelling and perturbing appendages together facilitate strenuous ground self-righting

Terrestrial animals must self-right when overturned on the ground, but this locomotor task is strenuous. To do so, the discoid cockroach often pushes its wings against the ground to begin a somersault which rarely succeeds. As it repeatedly attempts this, the animal probabilistically rolls to the side to self- right. During winged self-righting, the animal flails its legs vigorously. Here, we studied whether wing opening and leg flailing together facilitate strenuous ground self-righting. Adding mass to increase hind leg flailing kinetic energy increased the animal’s self-righting probability. We then developed a robot with similar strenuous self-righting behavior and used it as a physical model for systematic experiments. The robot’s self-righting probability increased with wing opening and leg flailing amplitudes. A potential energy landscape model revealed that, although wing opening did not generate sufficient kinetic energy to overcome the high pitch potential energy barrier to somersault, it reduced the barrier for rolling, facilitating the small kinetic energy from leg flailing to probabilistically overcome it to self-right. The model also revealed that the stereotyped body motion during self-righting emerged from physical interaction of the body and appendages with the ground. Our work demonstrated the usefulness of potential energy landscape for modeling self-righting transitions. Impact statement Animals can, and robots should, use different types of appendages together to propel and perturb themselves to self-right when overturned, a strenuous yet crucial locomotor task.
Electrocatalytic performance comparison of Pt/V and Pd/V electrocatalysts for ethanol oxidation reaction

Direct ethanol fuel cells (DEFCs) operate at low temperature, which makes the oxidation and reduction reactions slower, requiring electrocatalysts able to accelerate these reactions. In the present work, commercial Vulcan carbon (V) supported Pt and Pd catalysts were compared as electrocatalysts for ethanol oxidation reaction (EOR) in acidic and alkaline medium, respectively. Cyclic voltammetries obtained in presence of ethanol showing a better catalytic performance for the Pd/V electroctalyst compared to the Pt/V electrocatalyst. The maximum current density related with the EOR in a 1.0 mol L -1 ethanol + 1.0 mol L -1 NaOH solution was 236.9 A g Pd -1 for Pd/V. The better performance of the Pd/V electrocatalyst can be associated with a lower Pd nanoparticles sizes and higher particles dispersion onto the Vulcan carbon surface in the Pd/V electrocatalyst. The onset potential for the EOR was 0.2 V vs. SCE for the Pt/V sample and -0.6 V vs. Hg/HgO for the Pd/V sample.
Discovery and Validation of a Three-Cytokine Plasma Signature as a Biomarker for Diagnosis of Pediatric Tuberculosis

Pediatric TB poses challenge in diagnosis due to the paucibacillary nature of the disease. We conducted a prospective diagnostic study to identify immune biomarkers of pediatric TB and controls (discovery cohort) and obtained a separate “validation” cohort of confirmed cases of pediatric TB and controls. Multiplex ELISA was performed to examine the plasma levels of cytokines. Discovery and validation cohorts revealed that baseline plasma levels of IFNγ, TNFα, IL-2, and IL-17A were significantly higher in active TB (confirmed TB and unconfirmed TB) in comparison to unlikely TB children. Receiver operating characteristics (ROC) curve analysis revealed that IFNγ, IL-2, TNFα, and IL-17A (in the discovery cohort) and TNFα and IL-17A (in the validation cohort) could act as biomarkers distinguishing confirmed or unconfirmed TB from unlikely TB with the sensitivity and specificity of more than 90%. In the discovery cohort, cytokines levels were significantly diminished following anti-tuberculosis treatment. In both the cohorts, combiROC models offered 100% sensitivity and 98% to 100% specificity for a three-cytokine signature of TNFα, IL-2, and IL-17A, which can distinguish confirmed or unconfirmed TB children from unlikely TB. Thus, a baseline cytokine signature of TNFα, IL-2, and IL-17A could serve as an accurate biomarker for the diagnosis of pediatric tuberculosis.