bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multi-scale fusion CNN model based on adaptive transfer learning for multi-class MI-classification in BCI system
Authors: Roy Arunabha M. 
Published: March 2022

AbstractDeep learning-based brain-computer interface (BCI) in motor imagery (MI) has emerged as a powerful method for establishing direct communication between the brain and external electronic devices. However, due to inter-subject variability, inherent complex properties, and low signal-to-noise ratio (SNR) in electroencephalogram (EEG) signal are major challenges that significantly hinders the accuracy of the MI classifier. To overcome this, the present work proposes an efficient transfer learning-based multi-scale feature fused CNN (MSFFCNN) which can capture the distinguishable features of various non-overlapping canonical frequency bands of EEG signals from different convolutional scales for multi-class MI classification. In order to account for inter-subject variability from different subjects, the current work presents 4 different model variants including subject-independent and subject-adaptive classification models considering different adaptation configurations to exploit the full learning capacity of the classifier. Each adaptation configuration has been fine-tuned in an extensively trained pre-trained model and the performance of the classifier has been studied for vast range of learning rates and degrees of adaptation which illustrates the advantages of using an adaptive transfer learning-based model. The model achieves an average classification accuracy of 94.06% (±2.29%) and kappa value of 0.88 outperforming several baseline and current state-of-the-art EEG-based MI classification models with fewer training samples. The present research provides an effective and efficient transfer learning-based end-to-end MI classification framework for designing a high-performance robust MI-BCI system.
Toxicological Analysis of Poly-Lactide Co-Glycolide Microparticles, Chitosan Nanoparticles and Poly(Anhydride) Nanoparticles in Vero Cell
Authors: Hazarika Dipankar , Borah Durlabh Prasad , Boruah Jayanta Sarma , Begum Yasmin , Sultana Anisha , Tamuly Shantanu , Nath Rita , Chowdhury Devasish , Dutta Biswajit , Borah Probodh , Kalita Dhruba Jyoti 
Published: March 2022

ABSTRACTThe present study was carried out to evaluate in-vitro toxicity associated with chitosan nanoparticles, poly(anhydride) nanoparticles and poly-lactide co-glycolide (PLG) microparticle in Vero cell line. The cytotoxicity of all three micro/nano-particles was assessed using different concentration. For each concentration, the confluent monolayer was treated for a period of 36-48 hours and studied for morphological alteration, live and death count etc. after the treatment. It was observed that the different concentrations of chitosan nanoparticles and Gantrez® nanoparticles did not have significant effect on the cell viability as evident from the non-significant difference between the OD540 of formazan product formed from MTT in treated and untreated cells. The concentration of chitosan nanoparticles and Gantrez® nanoparticles up to 1000 μg/ml did not have any influence in cellular metabolic activities and viability. However, a reduction in the cellular viability and metabolic activities were observed when PLG microparticles were used at 1000 μg/ml. At concentrations below 1000 μg/ml, all the nanoparticles/microparticles were found to be safe in terms of cytotoxicity.
Generalized Method of Moments improves parameter estimation in biochemical signaling models of time-stamped single-cell snapshot data
Authors: John Wu , Stewart William CL , Ciriyam Jayaprakash , Jayajit Das 
Published: March 2022

AbstractMotivationOrdinary differential equations are commonly used to model the sub-cellular dynamics of average values of proteins and mRNAs. New single-cell technologies provide cell-to-cell differences in protein/mRNA abundances that allow for the evaluation of higher order moments. However, using this additional information to improve parameter estimation can be challenging since the magnitudes of single-cell abundances can vary widely between proteins/mRNA.ResultsWe employ Generalized Method of Moments (GMM) and Particle Swarm Optimization to address the above challenges in mechanistic modeling of signaling kinetics data. Using synthetic data from linear and non-linear models, we show that the proposed method improves parameter estimation and enables construction of approximate confidence intervals. Furthermore, our approach exploits parallel computation to scale with increasing data size and dimensions. We apply our software CyGMM to estimate parameters in a linear ODE model for publicly available longitudinal single-cell cytometry data for CD8+ T cells. Our results demonstrate substantial improvements for modeling data from single-cell cytometry and RNA-seq experiments.AvailabilityWe also make freely available our estimation software CyGMM written in C++ on github (https://github.com/jhnwu3/CyGMM).Contactjayajit@gmail.comSupplementary informationSupplementary data are available at Bioinformatics online.
A novel PLS1 c.981+1G>A variant causes autosomal-dominant hereditary hearing loss in a family via up-regulation of the PI3K-Akt signaling pathway
Authors: Xu Liangpu , Wang Xinrui , Li Jia , Chen Lingji , Wang Haiwei , Xu Shiyi , Zhang Yanhong , Li Wei , Yao Pengcheng , Tan Meihua , Zhou Si , Chen Meihuan , Pan Yali , Chen Xuemei , Chen Xiaolan , Liu Yunliang , Lin Na , Huang Hailong , Cao Hua 
Published: March 2022

AbstractBackgroundThe fimbrin protein family contains a variety of proteins, of which Plastin1 (PLS1) is an important member. The latest researches show that variations in the coding region of PLS1 gene is related to the development of deafness.However, it remains unknown about the molecular mechanism of deafness caused by PLS1 gene variants.Methodswhole exome sequencing was performed on the affected family members and healthy ones to identify the pathogenic variants, followed by sanger sequencing. Minigene assay was conducted to investigate the impact of the variant on PLS1 mRNA splicing. The pathogenicity of the variant was further investigated in zebrafish. RNA-sequencing (RNA-seq) was done for analyzing the dysregulated downstream signaling pathways caused by knockdown of PLS1 expression.ResultsWe identified a novel variant PLS1 c.981+1G>A in a large Chinese family with hearing loss and demonstrated that the variant is responsible for the occurrence of hearing loss by inducing Exon8 skipping or deletion of Exon8 (47bp). The variant caused abnormal inner ear phenotypes, characterized by decreased mean otolith distance, anterior otolith diameter, posterior otolith diameter, and cochlear diameter, swimming speed and distance in zebrafish. Furthermore, silencing PLS1 expression significantly upregulated genes in the PI3K-Akt signaling pathway, including Col6a3, Spp1, Itgb3 and Hgf.ConclusionsPLS1 c.981+1G>A is a novel pathogenic variant for hearing loss by inducing Exon8 skipping or deletion of Exon8 (47bp). Up-regulation of the PI3K-Akt signaling pathway plays an important role in the pathogenesis of PLS-1 gene.
Fragment-Based Ligand Generation Guided By Geometric Deep Learning On Protein-Ligand Structure
Authors: Powers Alexander S. , Yu Helen H. , Suriana Patricia , Dror Ron O. 
Published: March 2022

AbstractComputationally-aided design of novel molecules has the potential to accelerate drug discovery. Several recent generative models aimed to create new molecules for specific protein targets. However, a rate limiting step in drug development is molecule optimization, which can take several years due to the challenge of optimizing multiple molecular properties at once. We developed a method to solve a specific molecular optimization problem in silico: expanding a small, fragment-like starting molecule bound to a protein pocket into a larger molecule that matches that physiochemical properties of known drugs. Using data-efficient E(3) equivariant based neural networks and a 3D atomic point cloud representation, our model learns how to attach new molecular fragments to a growing structure by recognizing realistic intermediates generated en route to a final ligand. This approach always generates chemically valid molecules and incorporates all relevant 3D spatial information from the protein pocket. This framework produces promising molecules as assessed by multiple properties that address binding affinity, ease of synthesis, and solubility. Overall, we demonstrate the feasibility of 3D molecular structure expansion conditioned on protein pockets while maintaining desirable drug-like physiochemical properties and developed a tool that could accelerate the work of medicinal chemists.
Single-nucleotide substitution determines pollen production in Japanese cedar
Authors: Kakui Hiroyuki , Ujino-Ihara Tokuko , Hasegawa Yoichi , Tsurisaki Eriko , Futamura Norihiro , Iwai Junji , Higuchi Yuumi , Fujino Takeshi , Suzuki Yutaka , Kasahara Masahiro , Yamaguchi Katsushi , Shigenobu Shuji , Otani Masahiro , Nakano Masaru , Ueno Saneyoshi , Moriguchi Yoshinari 
Published: March 2022

AbstractPollinosis, also known as pollen allergy or hay fever, is a global problem caused by pollen produced by various plant species1–6. The wind-pollinated Japanese cedar (Cryptomeria japonica) is the largest contributor to severe pollinosis in Japan, where increasing proportions of people have been affected in recent decades7. TheMS4(MALE STERILITY 4) locus of Japanese cedar controls pollen production, and its homozygous mutants (ms4/ms4) show abnormal pollen development after the tetrad stage and produce no mature pollen. In this study, we narrowed down theMS4locus by fine mapping in Japanese cedar and foundTKPR1(TETRAKETIDE α-PYRONE REDUCTASE) gene in this region. Transformation experiments usingArabidopsis thalianashowed that single-nucleotide substitution ofCjTKPR1determines pollen production. Broad conservation of TKPR1 beyond plant division could lead to the creation of pollen-free plant not only for Japanese cedar but also for broader plant species.
Harnessing the power of technical and natural variation in 116 yeast datasets to benchmark long read assembly pipelines
Authors: Gettle Noah , Gallone Brigida , Verstrepen Kevin J. , Stelkens Rike 
Published: March 2022

AbstractWith increases in throughput and reductions in cost, long read sequencing has become the standard for most genome assembly projects and has opened up new avenues for large-scale genomic research. While more amenable to assembly than short-read sequence data, long-read datasets tend to have higher error rates. To address this problem numerous tools have been developed to correct reads before assembly and polish assembled contigs. Although, numerous studies have been conducted to assess or benchmark these tools, few capture the real variance in long read sequence data that might affect tool performance much less full pipeline performance. To address these shortcomings, we compiled a dataset containing long-read sequences of 116 different strains of brewers’ yeast, S. cerevisiae, gathered largely from public databases and evaluated different assembly-related tools as well as their interactions. We found that pre-assembly short-read error correction of long reads combined with post-assembly short-read polishing provided the best assemblies. We also found that correction/polishing steps with uncorrected long reads often lead to degradation of assembly quality. Finally, we show which tools and pipelines work best with different types of input data.
Diminished distractor filtering with increased perceptual load and sustained effort explains attention deficit in post-stroke fatigue
Authors: Kuppuswamy Annapoorna , Harris Anthony , De Doncker William , Alexander Adrian , Lavie Nilli 
Published: March 2022

AbstractObjectivesPost-stroke fatigue (PSF) is a prevalent symptom associated with attention deficits. However, it is currently unclear what drives these. Here we applied Load Theory of Attention to investigate the role of perceptual load in the relationship between attention, distraction, and fatigue levels in PSF.MethodsThirty-two chronic stroke survivors performed a selective attention task under different perceptual load levels. Neural responses to targets and distractors were measured with frequency-tagged EEG responses.ResultsWe showed that Fatigue Severity Scale-7 (FSS-7) scores are predictive of slower responses, irrespective of the task level of perceptual load. Although average distractor frequency (10Hz) power was reduced with higher perceptual load, the reduction in 10Hz power with increasing task load, was smaller in those with higher FSS-7 scores. Higher FSS-7 scores were also associated with increased 10Hz distractor response as time progressed, both within task-trials and across the experiment duration.ConclusionThe results are consistent with previous reports of slower processing speed and sustained selective attention deficits. Importantly they demonstrate that higher fatigue severity is associated with a reduced ability to suppress neural response to irrelevant distractors stimuli when the task demands more attention due to its increased perceptual load. An account for attention deficit in PSF based on a distractor filtering deficit that emerges with increased perceptual load and sustained effort can explain a myriad of PSF symptoms (e.g. sensory perceptual overload, and difficulties to concentrate).Key messagesWhat is already known on this topic➢Post-stroke fatigue involves mental fatigue which is exacerbated in cognitively demanding task, as well as difficulties in concentrating and sustaining attention on a task.➢However previous research has not converged on a clear account of the nature of attention deficits in post-stroke fatigue, as well as on how these relate to the level of perceptual demand in a cognitive taskWhat this study adds➢The study suggests that attention deficits in post-stroke fatigue are attributed to a failure to attenuate neural responses to distractors with increased perceptual load in the task, as well as with increased demands on sustained attention with a longer task engagement➢This pattern points to a distractor filtering deficit that is magnified by perceptual load and sustained mental effort as main drivers of attention deficits in post-stroke fatigueHow this study might affect research, practice or policy➢This study enhances our understanding of attentional deficit in post-stroke fatigue, within an integrative account that explains mental fatigue symptomology
Plasmid characterization in bacterial isolates of public health relevance in a tertiary healthcare facility in Kilimanjaro, Tanzania
Authors: Sengeruan Lameck Pashet , van Zwetselaar Marco , Kumburu Happiness , Aarestrup Frank M. , Kreppel Katharina , Sauli Elingarami , Sonda Tolbert 
Published: March 2022

AbstractPlasmids are infectious double stranded DNA molecules that are found within bacteria. Horizontal gene transfer promotes successful spread of different types of plasmids within or among bacteria species, making their detection an important task for guiding clinical treatment. We used whole genome sequenced data to determine the prevalence of plasmid replicons in clinical bacterial isolates, the presence of resistance and virulence genes in plasmids, and the relationship between resistance and virulence genes within each plasmid. All bacterial sequences were de novo assembled using Unicycler before extraction of plasmids. Assembly graphs were submitted to Gplas+plasflow for plasmid prediction. The predicted plasmid components were validated using PlasmidFinder.A total of 159 (56.2%) out of 283 bacterial isolates were found to carry plasmids, with E. coli, K. pneumoniae and S. aureus being the most prevalent plasmid carriers. A total of 27 (87.1%) combined plasmids were found to carry both resistance and virulence genes compared to 4 (12.9%) single plasmids. No statistically significant correlation was found between the number of antimicrobial resistance and virulence genes in plasmids (r =-0.25, p > 0.05). Our findings show a relatively high proportion of plasmid-carrying isolates suggesting selection pressure due to antibiotic use in the hospital. Co-occurrence of antibiotic resistance and virulence genes in clinical isolates is a public health relevant problem needing attention.
The MAPK/ERK channel capacity exceeds 6 bit/hour
Authors: Nałęcz-Jawecki Paweł , Gagliardi Paolo Armando , Kochańczyk Marek , Dessauges Coralie , Pertz Olivier , Lipniacki Tomasz 
Published: March 2022

AbstractLiving cells utilize signaling pathways to sense, transduce, and process information. As the extracellular stimulation often has rich temporal characteristics which may govern dynamic cellular responses, it is important to quantify the rate of information flow through the signaling pathways. In this study, we used an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter to assess the ability of the MAPK/ERK pathway to transduce signal encoded in a sequence of pulses. By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour. The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence. The high information transmission rate may enable the pathway to coordinate multiple processes including cell movement and respond to rapidly varying stimuli such as chemoattracting gradients created by other cells.Author summaryTo respond to external stimulation, living cells need to transfer information from membrane receptors to downstream proteins that regulate physiological outcomes. In this study we used cells expressing a light-activatable receptor that transmits signals to MAPK/ERK transduction pathway, which regulates numerous physiological processes including proliferation, differentiation and cell motility. By stimulating these cells with various sequences of short light pulses we found that ERK, the last component of the considered signal transduction pathway, may receive at least 6 bits per hour. This bitrate allows 6 binary decisions per hour, enabling rapid responses to varied extracellular stimuli.
Distribution and frequency of salivary gland tumours: an international multicenter study
Authors: Alsanie Ibrahim , Rajab Shahad , Cottom Hannah , Adegun Oluyori , Agarwal Reshma , Jay Amrita , Graham Laura , James Jacqueline , Barrett A William , van Heerden Willie , de Vito Mariano , Canesso Alessandra , Adisa Akinyele Olumuyiwa , Akinshipo Abdul-Warith Olaitan , Ajayi Oluseyi Folake , Nwoga Mark Chukwuemeka , Okwuosa Chukwubuzor Udokwu , Omitola Olufemi Gbenga , Orikpete Efetobo Victor , Soluk-Tekkesin Merva , Bello Ibrahim , Qannam Ahmed , Gonzalez Wilfredo , de Oliveira Maria Eduard Perez , Santos-Silva Alan Roger , Vargas Pablo Agustin , Toh Eu-Wing , Khurram Syed Ali 
Published: March 2022

AbstractBackgroundSalivary gland tumours (SGT) are a relatively rare group of neoplasms with a wide range of histopathological appearance and clinical features. To date, most of the epidemiological studies on salivary gland tumours are limited for a variety of reason including being out of date, extrapolated from either a single centre or country studies, or investigating either major or minor glands only.MethodsThis study aimed to mitigate these shortcomings by analysing epidemiological data including demographic, anatomical location and histological diagnoses of SGT from multiple centres across the world. The analysed data included age, gender, location and histological diagnosis from fifteen centres covering the majority of the world health organisation (WHO) geographical regions between 2006 and 2019.ResultsA total of 5798 cases were analysed including 65% benign and 35% malignant tumours. A slight female predilection (54%) and peak incidence between the fourth and seventh decade for both benign and malignant tumours was observed. The majority (69%) of the SGT presented in major and 31% in the minor glands. The parotid gland was the most common location (70%) for benign and minor glands (46%) for malignant tumours. Pleomorphic adenoma (70%), and Warthin’s tumour (17%), were the most common benign tumours whereas mucoepidermoid carcinoma (25%) and adenoid cystic carcinoma (16%) were the most frequent malignant tumours.ConclusionsThis multicentre investigation presents the largest cohort study to date analysing salivary gland tumour data from tertiary centres scattered across the globe. These findings should serve as a baseline for future studies evaluating the epidemiological landscape of these tumours.
Standardization of cytological behavior of pollens in sorghum by Image analysis
Authors: Narkhede Gopal W. , Mehtre Shivaji P , Deshpande Santosh P 
Published: March 2022

ABSTRACTThe development of iso-nuclear male sterile (A) and maintainer (B) line along with male fertile (R) lines, referred to as fertility restorers, helped in cost-effective seed production and deployment of hybrids. The pollen viability/fertility for maintenance (B-line) and restoration (R-line) remains a significant phenotyping hurdle in developing new lines. We carried out the present investigation to evaluate the pollen fertility status of Cytoplasmic Genetic Male Sterility (CGMS) based hybrids in sorghum. The experimental material consisted of 238 CGMS based hybrids developed from the crossing of individuals of (296B ×IS 188551) - based Recombinant Inbred Line (RIL) population (F7:F8) with male-sterile line (296A). The experiment was conducted in the rainy and post-rainy seasons during 2016 to evaluate pollen fertility. The authors illustrated the pollen fertility status by counting pollen counts using two methods: viz., visual counting by the naked eye, and image analysis using ImageJ (NIH, USA) software. We compared results between counts recorded visually and ImageJ reads for randomly selected 50 individuals each during the rainy and post-rainy seasons. The pollen counts from ImageJ were 95% efficient in detecting sterile vs. fertile counts. These results provide a better, efficient, and quick tool for characterizing the pollen behavior and also add value to the genetics studies by accounting for the quantitative variation encoded by multiple loci.
Isoform-specific mutation in Dystonin-b gene causes late-onset protein aggregate myopathy and cardiomyopathy
Authors: Yoshioka Nozomu , Kurose Masayuki , Yano Masato , Tran Dang Minh , Okuda Shujiro , Mori-Ochiai Yukiko , Horie Masao , Nagai Toshihiro , Nishino Ichizo , Shibata Shinsuke , Takebayashi Hirohide 
Published: March 2022

AbstractDystonin (DST), which encodes cytoskeletal linker proteins, express three tissue-selective isoforms: neural DST-a, muscular DST-b, and epithelial DST-e. DST mutations cause different disorders including hereditary sensory and autonomic neuropathy 6 (HSAN-VI) and epidermolysis bullosa simplex; however, etiology of the muscle phenotype in DST-related diseases has been unclear. Because DST-b contains all of the DST-a-encoding exons, known HSAN-VI mutations could affect both DST-a and DST-b isoforms. To investigate the specific function of DST-b in striated muscles, we generated a Dst-b-specific mutant mouse model harboring a nonsense mutation. Dst-b mutant mice exhibited late-onset protein aggregate myopathy and cardiomyopathy without neuropathy. We observed desmin aggregation, focal myofibrillar dissolution, and mitochondrial accumulation in striated muscles, which are common characteristics of myofibrillar myopathy. We also found nuclear inclusions containing p62, ubiquitin, and SUMO proteins with nuclear envelope invaginations as a unique pathological hallmark in Dst-b mutation-induced cardiomyopathy. RNA sequencing analysis revealed changes in expression of genes responsible for cardiovascular functions. In silico analysis identified DST-b alleles with nonsense mutations in populations worldwide, suggesting that some unidentified hereditary myopathy and cardiomyopathy are caused by DST-b mutations. Here, we demonstrate that the Dst-b isoform is essential for long-term maintenance of striated muscles.