Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive Analysis of the Functions and Prognostic Value of RNA-Binding Proteins in Thyroid Cancer

RNA binding proteins (RBPs) have been proved to play pivotal roles in a variety types of tumors. However, there is no convincible evidence disclosing the functions of RBPs in thyroid cancer (THCA) thoroughly and systematically. Integrated analysis of the functional and prognostic effect of RBPs help better understanding tumorigenesis and development in thyroid and may provide a novel therapeutic method for THCA. In this study, we obtained a list of human RBPs from Gerstberger database, which covered 1,542 genes encoding RBPs. Gene expression data of THCA was downloaded from The Cancer Genome Atlas (TCGA, n = 567), from which we extracted 1,491 RBPs’ gene expression data. We analyzed differentially expressed RBPs using R package “limma”. Based on differentially expressed RBPs, we constructed protein-protein interaction network and the GO and KEGG pathway enrichment analyses were carried out. We found six RBPs (AZGP1, IGF2BP2, MEX3A, NUDT16, NUP153, USB1) independently associated with prognosis of patients with thyroid cancer according to univariate and multivariate Cox proportional hazards regression models. The survival analysis and risk score analysis achieved good performances from this six-gene prognostic model. Nomogram was constructed to guide clinical decision in practice. Finally, biological experiments disclosed that NUP153 and USB1 can significantly impact cancer cell proliferation and migration. In conclusion, our research provided a new insight of thyroid tumorigenesis and development based on analyses of RBPs. More importantly, the six-gene model may play an important role in clinical practice in the future.
Antibodies Targeting the Transferrin Receptor 1 (TfR1) as Direct Anti-cancer Agents

The transferrin receptor 1 (TfR1), also known as cluster of differentiation 71 (CD71), is a type II transmembrane glycoprotein that binds transferrin (Tf) and performs a critical role in cellular iron uptake through the interaction with iron-bound Tf. Iron is required for multiple cellular processes and is essential for DNA synthesis and, thus, cellular proliferation. Due to its central role in cancer cell pathology, malignant cells often overexpress TfR1 and this increased expression can be associated with poor prognosis in different types of cancer. The elevated levels of TfR1 expression on malignant cells, together with its extracellular accessibility, ability to internalize, and central role in cancer cell pathology make this receptor an attractive target for antibody-mediated therapy. The TfR1 can be targeted by antibodies for cancer therapy in two distinct ways: (1) indirectly through the use of antibodies conjugated to anti-cancer agents that are internalized by receptor-mediated endocytosis or (2) directly through the use of antibodies that disrupt the function of the receptor and/or induce Fc effector functions, such as antibody-dependent cell-mediated cytotoxicity (ADCC), antibody-dependent cell-mediated phagocytosis (ADCP), or complement-dependent cytotoxicity (CDC). Although TfR1 has been used extensively as a target for antibody-mediated cancer therapy over the years, interest continues to increase for both targeting the receptor for delivery purposes and for its use as direct anti-cancer agents. This review focuses on the developments in the use of antibodies targeting TfR1 as direct anti-tumor agents.
Rapid and Efficient Generation of Myelinating Human Oligodendrocytes in Organoids

Human stem cell derived brain organoids are increasingly gaining attention as an ideal model system for investigating neurological diseases, particularly those that involve myelination defects. However, current protocols for generating brain organoids with sufficiently mature oligodendrocytes that deposit myelin on endogenously produced neurons are lengthy and complicated. Taking advantage of a human pluripotent stem cell line that reports on SOX10 expression, we developed a protocol that involves a 42 day exposure of neuroectoderm-derived organoids to a cocktail of growth factors and small molecules that collectively foster oligodendrocyte specification and survival. Importantly, the resulting day 42 brain organoids contain both myelinating oligodendrocytes, cortical neuronal cells and astrocytes. These oligodendrocyte brain organoids therefore constitute a valuable and tractable platform for functional neurogenomics and drug screening for white matter diseases.
Exosomal LncRNA LBX1-AS1 Derived From RBPJ Overexpressed-Macrophages Inhibits Oral Squamous Cell Carcinoma Progress via miR-182-5p/FOXO3

Objectives Macrophage-derived exosomes (Mφ-Exos) are involved in tumor onset, progression, and metastasis, but their regulation in oral squamous cell carcinoma (OSCC) is not fully understood. RBPJ is implicated in macrophage activation and plasticity. In this study, we assessed the role of Mφ-Exos with RBPJ overexpression (RBPJ-OE Mφ-Exos) in OSCC. Materials and Methods The long non-coding RNA (lncRNA) profiles in RBPJ-OE Mφ-Exos and THP-1-like macrophages (WT Mφ)-Exos were evaluated using lncRNA microarray. Then the functions of Mφ-Exo-lncRNA in OSCC cells were assessed via CCK-8, EdU, and Transwell invasion assays. Besides, luciferase reporter assay, RNA immunoprecipitation, and Pearson’s correlation analysis were adopted to confirm interactions. Ultimately, a nude mouse model of xenografts was used to further analyze the function of Mφ-Exo-lncRNAs in vivo. Results It was uncovered that lncRNA LBX1-AS1 was upregulated in RBPJ-OE Mφ-Exos relative to that in WT Mφ-Exos. RBPJ-OE Mφ-Exos and LBX1-AS1 overexpression inhibited OSCC cells to proliferate and invade. Meanwhile, LBX1-AS1 knockdown boosted the tumor to grow in vivo. The effects of RBPJ-OE Mφ-Exos on OSCC cells can be reversed by the LBX1-AS1 knockdown. Additionally, mechanistic investigations revealed that LBX1-AS1 acted as a competing endogenous RNA of miR-182-5p to regulate the expression of FOXO3. Conclusion Exo-LBX1-AS1 secreted from RBPJ-OE Mφ inhibits tumor progression through the LBX1-AS1/miR-182-5p/FOXO3 pathway, and LBX1-AS1 is probably a diagnostic biomarker and potential target for OSCC therapy.
Active^2 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

While deep learning is a powerful tool for natural language processing (NLP) problems, successful solutions to these problems rely heavily on large amounts of annotated samples. However, manually annotating data is expensive and time-consuming. Active Learning (AL) strategies reduce the need for huge volumes of labeled data by iteratively selecting a small number of examples for manual annotation based on their estimated utility in training the given model. In this paper, we argue that since AL strategies choose examples independently, they may potentially select similar examples, all of which may not contribute significantly to the learning process. Our proposed approach, Active\mathbf{^2} Learning (A\mathbf{^2}L), actively adapts to the deep learning model being trained to eliminate such redundant examples chosen by an AL strategy. We show that A\mathbf{^2}L is widely applicable by using it in conjunction with several different AL strategies and NLP tasks. We empirically demonstrate that the proposed approach is further able to reduce the data requirements of state-of-the-art AL strategies by \approx \mathbf{3-25\%} on an absolute scale on multiple NLP tasks while achieving the same performance with virtually no additional computation overhead.
Implementation of Neural Network on FPGA

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Deep neural networks and their application is rapidly changing many of the fields by bringing a different way of solution to the problems. In fact, it is being applied in every field right from Signal processing to the communication. Although it solves many problems easily, training and deploying it is limited due to various reasons. These deep neural networks require most powerful computational devices like GPU in order to train them and large RAM, memory is required for its operation limiting its usage in many of the applications. Even if these resources are provided through cloud the deployment of system faces problems like more latency as there is round trip to the server, connectivity, privacy as the data needs to leave the system. All these problems could be overcome using the FPGA’s for the deployment of the neural network as they are low cost and reconfigurable. In fact, FPGA’s are faster than GPU during inference in many of the cases making it suitable for the deployment in the real time application. FPGA’s are faster than GPU’s as the neural network is implemented as a hardware in case of FPGA’s, where only hardware delays are introduced but in case of CPU or GPU large number of floating-point operations needs to be done using ALU. We will implement a trained neural network of TensorFlow on FPGA using Verilog HDL to perform a regression task.
A Broader Range for ‘Meaning the Same Thing’: Human Against Machine on Hard Paraphrase Detection Tasks

The ability to recognize that pairs or sets of language expressions “mean the same thing” is a cognitive task for which meaning representation is clearly a central issue. This paper uses the task of paraphrasing to study meaning representation in a cognitive system. The main claim of this paper is that a consequential part of the meaning representation for a natural language expression is a set of language-free structures and processes that are not part of the expression in question. To support our claims, we construct a corpus of paraphrase pairs using a system that has a non-linguistic meaning representation decoupled from the linguistic system that generates natural language from it. This corpus of paraphrase pairs is special in that it represents a full range of syntactic and lexical difference in their constituent sentences. We conduct an extensive analysis comparing the performance of a state-of-the-art neural network model against humans performing the paraphrase detection task. We ﬁnd that the model deviates signiﬁcantly from human classiﬁcation performance, particularly on sentence pairs that conveyed the same meaning while exhibiting signiﬁcant differences lexically and syntactically. As the neural network model is trained only on linguistic items, the discrepancy points to the existence and necessity of a signiﬁcant non-linguistic part of meaning formation.
Using Deep Learning Approach in Flight Exceedance Event Analysis

Causal analysis of flight exceedance events, e.g. hard-landing, is a key task for modern airlines performing Flight Operation Quality Assurance (FOQA) programs. The main objective of the program is to learn from experience: detect early signs of major problems and correct them before accidents occur. It has been found that flare operation would greatly influence the landing performance. According to the finding, we proposed a deep learning approach to assist airlines performing causal analysis for hard landing events. Experimental results confirm that compared with the other state-of-the-art techniques, the proposed approach provides a more reliable results. The technique can be the basis of developing advanced models for further revealing the relationships between pilot operations and flight exceedance events.
Optimizing Read Operations of Hadoop Distributed File System on Heterogeneous Storages

The key challenge in big data processing frameworks such as Hadoop distributed ﬁle system (HDFS) is to optimize the throughput for read operations. Toward this goal, several studies have been conducted to enhance read performance on heterogeneous storages. Recently, although HDFS has supported several storage policies for placing data blocks in heterogeneous storages, it fails to fully utilize the potential of fast storages ( e.g. , SSD). The primary reason for its suboptimal read performance is that, while distributing read requests, existing HDFS only considers the network distance between the client and datanodes, thereby incurring more read requests to slower storages with more data ( e.g. , HDD). In this paper, we propose a new data retrieval policy for distributing read requests on heterogeneous stor-ages in HDFS. Speciﬁcally, the proposed policy considers both the unique characteristics of storages in datanodes and the network environments, to efﬁciently distribute read requests. We develop several policies including the proposed policy to balance these two factors such as random selection, storage type selection, weighted round-robin selection, and dynamic round-robin selection. Our experimental results show that the throughput of the proposed method outperforms those of the existing policies by up to six times in extensive benchmark datasets.
Synthesis of 16-fluoroestrogens by unusually facile fluoride ion displacement reactions: prospects for the preparation of fluorine-18 labeled estrogens

16.cap alpha. -Fluoroestradiol and 16.beta. -fluoroestradiol can be prepared by the reaction of fluoride ion with the opposite corresponding epimeric (((trifluoromethyl)sulfonyl)oxy)estrone precursors, followed by stereoselective reduction to the 17.beta. -estradiols. The related 17.beta. -ethynyl compounds can be prepared by ethynylation of the fluoroestrones. Stereochemical assignments, suggested by known reaction stereoselectivities, are supported by extensive /sup 1/H and /sup 19/F NMR analyses. The fluoride ion displacement reactions operate rapidly and efficiently at room temperature, even with low concentrations of fluoride ion. This rapid and convenient fluorination method is adaptable to the preparation of fluorine-18 labeled estrogens that may be useful as breast tumor imaging agents. 18 references, 1 tables.
Structural and Electronic Properties of Monolayer 1T-MoS2 Phase, and Its Interaction with Water Adsorbed on Perfect, Single S-Vacated and MoS2-Unit-Vacated Surface: Density Functional Theory Calculations

Using density functional theory calculations with van der Waals dispersion corrections, we studied the structural and electronic properties of monolayer 1T-MoS2, and how it interacts with water on perfect and vacancy-doped cases, which include single sulfur and MoS2-unit vacancies. We first optimized and calculated its structural parameters and electronic properties and confirmed earlier reports suggesting its metastable state and metallic electronic structure. Results show that adsorption sites on perfect surface bind water weakly while the opposite is true for vacancy sites adsorption. Climbing nudged elastic band calculations revealed that sulfur vacancy site could favorably dissociate water and evolve hydrogen with moderate energy cost, while significantly high energies are required for the same processes on MoS2 unit vacancy. The results are important in supplementing efforts to find clean and renewable energy sources.
In vivo Assessment of Nanomaterials Toxicity

The concern regarding the safety of nanomaterials for the human body is constantly raising. On one hand, there is an increase in the production of nanomaterials for technological applications, which raises the risk of accidental exposure of the workers during the technological manipulation. On the other hand, nanomaterials can be designed for medical applications and their faith in the human body, along with their interactions with different tissues, becomes of vital importance. The mechanisms involved in nanomaterials toxicity are discussed, including oxidative stress and inflammation. In vivo toxicity evaluation includes different routes of administration or interaction between the nanomaterial and the organism, as well as a short-term or a long-term exposure or evaluation. Also, the characteristics of nanomaterials, including size, shape, impurities, function, surface coating in relation to their toxicity, were discussed. A particular attention has been given to the evalua‐ tion of the toxicity of dendrimers, silver nanoparticles, gold nanoparticles and carbon nanotubes.
Electrochemically active biofilm-mediated synthesis of silver nanoparticles in water

Silver nanoparticles 1–7 nm in size were synthesized within 2 h in water by challenging an electrochemically active biofilm (EAB) with a solution containing AgNO3 as precursor and sodium acetate as an electron donor. The electrochemically active bacteria present on the anaerobic biofilm act as a catalyst to oxidise the sodium acetate by producing electrons for the reduction of Ag+ ions. The high monodispersity, rapidity, and extracellular nature of this synthesis, together with the production of smaller nanoparticles that are easily separated, make this protocol highly significant in the area of nanoparticle synthesis.
Hydrothermal synthesis of ZnO@polysiloxane microspheres and their application in preparing optical diffusers

In this study, optical diffusers based on ZnO@polysiloxane microsphere fillers were successfully prepared by a solvent-free UV curing process. ZnO@polysiloxane microspheres were synthesized via a highly efficient and facile hydrothermal synthetic method. The microscope analysis revealed that the ZnO@polysiloxane microspheres were about 6–8 μm in diameter. The optical properties of the diffusers were also measured for the first time. The results suggest that the novel diffuser based on ZnO@polysiloxane microsphere fillers possessed suitable light transmittance, good diffusion capacity, and low incident angle dependence. In addition, its tunable optical diffusing capacity relied on the amount of ZnO@polysiloxane microsphere fillers. When the concentration of the ZnO@polysiloxane microspheres was as high as 15 wt%, the diffusing properties of the novel diffusers reached the level of a commercially available diffuser. Therefore, the new fillers can be widely used for the preparation of multifunctional diffusion materials such as touch-panel functions, monitors, military projectors, and TVs.
Investigation on Semantic Role Labeling of Chinese

Semantic roles (AGENT, THEME, LOCATION, etc) provide a natural level of shallow semantic representation for a sentence. In the natural language processing field, researchers have experienced a growth of interest in semantic role labeling by applying statistical and machine-learning methods. So far much of the research has been focused on English due to the lack of semantically annotated resources in other languages. In this paper we will report the method and state on semantic role labeling using a pre-release version of the Chinese Proposition Bank.
Experimental and Theoretical Studies on the Interaction between Isonicotinic Acid Molecules and Silver Nanoclusters

ABSTRACT The present paper describes the studies on the adsorption behavior and charge transfer from isonicotinic acid to silver nanoparticles with experiment and theory. Compared with UV–Visible adsorption spectrum, the adsorption spectrum of Ih-Ag13 cluster was quite good agreed with that of silver colloidal nanoparticle. So that one Ag13 cluster as a substrate was used to simulate Raman frequencies of the adsorption configuration. Here, it is demonstrated the calculated Raman spectra are in good agreement with experimental results. The analysis of Mulliken charge was obtained by density functional theory, which indicated the charge characteristics of Ag13 nanoparticle. Once isonicotinic acid molecules were adsorbed on sliver clusters, the charges transfer from isonicotinic acid to silver clusters, so that the surface charges of silver clusters are uneven.
Reaction of nitriles under acidic conditions. Part VI. Synthesis of condensed 4-chloro- and 4-aminopyrimidines from ortho-aminonitriles

Condensation of a nitrile with benzene, furan and thiophene ortho-aminonitriles in the presence of dry hydrogen chloride yields condensed 4-chloropyrimidines, condensed 4-aminopyrimidines or a mixture of the two condensed pyrimidines in varying proportions depending upon the nature of the nitrile and the substrate, ortho-aminonitrile.
Conflict of interest declaration

David Ames has undertaken research with cholinesterase inhibitor drugs supported by Eisai, Janssen, Parke-Davis and Pfizer. He has received honoraria for talks and consultancies and some financial support to enable conference attendance from those four companies and from Novartis, the other pharmaceutical company to market a cholinesterase inhibitor in Australia.
New neutral cesium evaporation chamber and UHV suitcase

It is well known that the use of Cs+ primary ions results in an important increase of the negative ionization probability during SIMS analyses. Moreover, Cs+ bombardment allows working in the MCsx+ mode, which is a widely used technique to reduce the matrix effect. A major drawback of Cs+ primary ion bombardment is that the Cs+ beam serves both for the incorporation of Cs and for the sputtering of the surface. Therefore, the sputtering yield, and consequently the cesium surface concentration, are constricted by the primary bombardment conditions.
Potential of harvesting atmospheric water over urban cities in Kenya

Most urban areas in Kenya are facing water crisis due to rapid population growth, industrialization and climate change. This study investigates potential of harvesting water from fog and air humidity over urban cities in Kenya. Daily air temperature, dew point temperature, wind direction and speed were used. Parameters including atmospheric water vapor pressure, saturated vapor pressure and the absolute and relative humidity of the atmosphere were derived. Air temperatures ranged between 18.2 and 27.6°C in urban areas. Mean annual foggy days was higher at Jomo Kenyatta International Airport (JKIA) with a maximum of 17 foggy days compared to other stations. However, mean annual harvesting days was higher at Moi International Airport (MIA) with a maximum of 350 days. Based on device efficiency of 10%, stations in Nairobi city (JKIA/Dagorretti Corner/Wilson Airport) indicated maximum water harvesting potential of 3.2/1.4/2.9 litres/m 2 /day in direction d6 (225 -270°) while Kisumu station
Solid-Phase Synthesis of Lidocaine and Procainamide Analogues Using Backbone Amide Linker (BAL) Anchoring1

New solid-phase strategies have been developed for the synthesis of lidocaine (1) and procainamide (2) analogues, using backbone amide linker (BAL) anchoring. Both sets were prepared starting from a common resin-bound intermediate, followed by four general steps: (i) attachment of a primary aliphatic or aromatic amine to the solid support via reductive amination (as monitored by a novel test involving reaction of 2,4-dinitrophenylhydrazine with residual aldehyde groups); (ii) acylation of the resultant secondary amine; (iii) displacement of halide with an amine; and (iv) trifluoroacetic acid-mediated release from the support. A manual parallel strategy was followed to provide 60 novel compounds, of which two dozen have not been previously described. In most cases, initial crude purities were >80%, and overall isolated yields were in the 40−88% range.