ProNormz – An integrated approach for human proteins and protein kinases normalization

AbstractThe task of recognizing and normalizing protein name mentions in biomedical literature is a challenging task and important for text mining applications such as protein–protein interactions, pathway reconstruction and many more. In this paper, we present ProNormz, an integrated approach for human proteins (HPs) tagging and normalization. In Homo sapiens, a greater number of biological processes are regulated by a large human gene family called protein kinases by post translational phosphorylation. Recognition and normalization of human protein kinases (HPKs) is considered to be important for the extraction of the underlying information on its regulatory mechanism from biomedical literature. ProNormz distinguishes HPKs from other HPs besides tagging and normalization. To our knowledge, ProNormz is the first normalization system available to distinguish HPKs from other HPs in addition to gene normalization task. ProNormz incorporates a specialized synonyms dictionary for human proteins and protein kinases, a set of 15 string matching rules and a disambiguation module to achieve the normalization. Experimental results on benchmark BioCreative II training and test datasets show that our integrated approach achieve a fairly good performance and outperforms more sophisticated semantic similarity and disambiguation systems presented in BioCreative II GN task. As a freely available web tool, ProNormz is useful to developers as extensible gene normalization implementation, to researchers as a standard for comparing their innovative techniques, and to biologists for normalization and categorization of HPs and HPKs mentions in biomedical literature. URL: http://www.biominingbu.org/pronormz

Spray pyrolisis deposition and characterization of Cd-TiO2 thin film for photocatalytic and photovoltaic applications

In the present paper, an innovative approach to enhance the photocatalytic efficiency and energy of photovoltaics by modifying the surface morphology of a TiO2 is demonstrated.The photovoltaic device provides sustainable power efficiency in TiO2 (TO) and Cd-TiO2 (CTO) thin films grown through spray pyrolysis. The structural and optical properties of the prepared undoped and Cd doped TiO2 thin films were studied. The morphology and content of the pro­duced samples were studied using scanning electron microscopy (SEM with EDAX). A UV-Vis spectrophotometer was used to record the optical absorption spectra of TiO2 nanoparticles. XRD analysis showed that TO and CTO had anatase structure, and the average crystalline size was calculated as 132.0 nm.The photocatalytic efficiency of TO and CTO for degradation of Rodhamine B (RhB) dye was examined. Also, power-voltage (P-V) and photocurrent-voltage (I-V) output current intensity relations were discussed

Large language models in biomedical natural language processing: benchmarks, baselines, and recommendations

Biomedical literature is growing rapidly, making it challenging to curate and extract knowledge manually. Biomedical natural language processing (BioNLP) techniques that can automatically extract information from biomedical literature help alleviate this burden. Recently, large Language Models (LLMs), such as GPT-3 and GPT-4, have gained significant attention for their impressive performance. However, their effectiveness in BioNLP tasks and impact on method development and downstream users remain understudied. This pilot study (1) establishes the baseline performance of GPT-3 and GPT-4 at both zero-shot and one-shot settings in eight BioNLP datasets across four applications: named entity recognition, relation extraction, multi-label document classification, and semantic similarity and reasoning, (2) examines the errors produced by the LLMs and categorized the errors into three types: missingness, inconsistencies, and unwanted artificial content, and (3) provides suggestions for using LLMs in BioNLP applications. We make the datasets, baselines, and results publicly available to the community via https://github.com/qingyu-qc/gpt_bionlp_benchmark

Functional implications of glycans and their curation:insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy

Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes. A workshop titled "Functional impact of glycans and their curation" was held in conjunction with the 16th Annual International Biocuration Conference to discuss ongoing worldwide activities related to glycan function curation. This workshop brought together subject matter experts, tool developers, and biocurators from over 20 projects and bioinformatics resources. Participants discussed four key topics for each of their resources: (i) how they curate glycan function-related data from publications and other sources, (ii) what type of data they would like to acquire, (iii) what data they currently have, and (iv) what standards they use. Their answers contributed input that provided a comprehensive overview of state-of-the-art glycan function curation and annotations. This report summarizes the outcome of discussions, including potential solutions and areas where curators, data wranglers, and text mining experts can collaborate to address current gaps in glycan and glycosylation annotations, leveraging each other's work to improve their respective resources and encourage impactful data sharing among resources. Database URL: https://wiki.glygen.org/Glycan_Function_Workshop_2023

Integrated Approaches to Identify miRNA Biomarkers Associated with Cognitive Dysfunction in Multiple Sclerosis Using Text Mining, Gene Expression, Pathways, and GWAS

Multiple sclerosis (MS), a chronic autoimmune disorder, affects the central nervous system of many young adults. More than half of MS patients develop cognition problems. Although several genomic and transcriptomic studies are currently reported in MS cognitive impairment, a comprehensive repository dealing with all the experimental data is still underdeveloped. In this study, we combined text mining, gene regulation, pathway analysis, and genome-wide association studies (GWAS) to identify miRNA biomarkers to explore the cognitive dysfunction in MS, and to understand the genomic etiology of the disease. We first identified the dysregulated miRNAs associated with MS and cognitive dysfunction using PubTator (text mining), HMDD (experimental associations), miR2Disease, and PhenomiR database (differentially expressed miRNAs). Our results suggest that miRNAs such as hsa-mir-148b-3p, hsa-mir-7b-5p, and hsa-mir-7a-5p are commonly associated with MS and cognitive dysfunction. Next, we retrieved GWAS signals from GWAS Catalog, and analyzed the enrichment analysis of association signals in genes/miRNAs and their association networks. Then, we identified susceptible genetic loci, rs17119 (chromosome 6; p = 1 × 10−10), rs1843938 (chromosome 7; p = 1 × 10−10), and rs11637611 (chromosome 15; p = 1.00 × 10−15), associated with significant genetic risk. Lastly, we conducted a pathway analysis for the susceptible genetic variants and identified novel risk pathways. The ECM receptor signaling pathway (p = 3.98 × 10−8) and PI3K/Akt signaling pathway (p = 5.98 × 10−5) were found to be associated with differentially expressed miRNA biomarkers

Electrocopolymerization of poly(o-toludine-co-metanilic acid) on mild steel surfaces and their physico-electrochemical characterizations

For the first time, poly(o-toludine-co-metanilic acid) (POM) layers have been deposited on mild steel (MS) substrate by galvanostatic (GS), potentiostatic (PS) and potentiodynamic (PD) methods. AC impedance of the electrodes has been analyzed. The shape and impedance parameters of galvanostatically prepared electrodes are similar to those of potentiostatically grown electrodes. The impedance spectra of potentiodynamically prepared electrode, however, are different. The redox behavior of POM copolymer has been studied using cyclicvoltammetric technique. Also, the copolymer prepared by potentiodynamic method has been characterized by UV–vis spectroscopy, Fourier Transform Infrared spectroscopy (FTIR) and Thermogravimetric analysis. It has been observed that polymerization of POM are greatly influenced by the method of preparation

Potentiodynamic deposition of poly (o-anisidine-co-metanilic acid)on mild steel and its application as corrosion inhibitor

For the first time, poly (o-anisidine-co-metanilic acid) (PASM) was deposited on mild steel substrate by electrochemical polymerization of o-anisidine and metanilic acid monomers in aqueous solution of 0.1M H2SO4. The electrochemical polymerization of o-anisidine takes place in the presence of metanilic acid monomer and uniform, strongly adherent coating was obtained on the substrate. The electroactivity of copolymerwas studied by cyclic voltammetry and AC impedance techniques. There is an increasing anodic current due to oxidation of metanilic acid monomer at the surface of the electrode when the applied potential is cycled from −0.2V to 0.8 V. These deposits were characterized by Fourier transform infrared (FTIR) spectroscopy, UV–vis and TG/DTA techniques. The effect of various concentrations of PASM copolymer solution in acid rain corrosive media has been studied through potentiodynamic polarization, AC impedance and I–E curvemethods. The soluble form of polymeric solution provided better anti-corrosive behavior in artificial acid rain solution