Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Oral Microbiome of Oral Potentially Malignant and Malignant Disorders: Dysbiosis, Loss of Diversity, and Pathogens Enrichment

The role of dysbiosis in the development and progression of oral potentially malignant disorders (OPMDs) remains largely unknown. Here, we aim to characterize and compare the oral microbiome of homogeneous leucoplakia (HL), proliferative verrucous leukoplakia (PVL), oral squamous cell carcinoma (OSCC), and OSCC preceded by PVL (PVL-OSCC). Fifty oral biopsies from HL (n = 9), PVL (n = 12), OSCC (n = 10), PVL-OSCC (n = 8), and healthy (n = 11) donors were obtained. The sequence of the V3–V4 region of the 16S rRNA gene was used to analyze the composition and diversity of bacterial populations. In the cancer patients, the number of observed amplicon sequence variants (ASVs) was lower and Fusobacteriota constituted more than 30% of the microbiome. PVL and PVL-OSCC patients had a higher abundance of Campilobacterota and lower Proteobacteria than any other group analyzed. A penalized regression was performed to determine which species were able to distinguish groups. HL is enriched in Streptococcus parasanguinis, Streptococcus salivarius, Fusobacterium periodonticum, Prevotella histicola, Porphyromonas pasteri, and Megasphaera micronuciformis; PVL is enriched in Prevotella salivae, Campylobacter concisus, Dialister pneumosintes, and Schaalia odontolytica; OSCC is enriched in Capnocytophaga leadbetteri, Capnocytophaga sputigena, Capnocytophaga gingivalis, Campylobacter showae, Metamycoplasma salivarium, and Prevotella nanceiensis; and PVL-OSCC is enriched in Lachnospiraceae bacterium, Selenomonas sputigena, and Prevotella shahii. There is differential dysbiosis in patients suffering from OPMDs and cancer. To the best of our knowledge, this is the first study comparing the oral microbiome alterations in these groups; thus, additional studies are needed.
Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients

Glioblastoma (GBM) is a type of brain cancer that is typically very aggressive and difficult to treat. Glioblastoma cases have been reported to have increased during COVID-19. The mechanisms underlying this comorbidity, including genomic interactions, tumor differentiation, immune responses, and host defense, are not completely explained. Therefore, we intended to investigate the differentially expressed shared genes and therapeutic agents which are significant for these conditions by using in silico approaches. Gene expression datasets of GSE68848, GSE169158, and GSE4290 studies were collected and analyzed to identify the DEGs between the diseased and the control samples. Then, the ontology of the genes and the metabolic pathway enrichment analysis were carried out for the classified samples based on expression values. Protein–protein interactions (PPI) map were performed by STRING and fine-tuned by Cytoscape to screen the enriched gene module. In addition, the connectivity map was used for the prediction of potential drugs. As a result, 154 overexpressed and 234 under-expressed genes were identified as common DEGs. These genes were found to be significantly enriched in the pathways involved in viral diseases, NOD-like receptor signaling pathway, the cGMP-PKG signaling pathway, growth hormone synthesis, secretion, and action, the immune system, interferon signaling, and the neuronal system. STAT1, CXCL10, and SAMDL were screened out as the top 03 out of the top 10 most critical genes among the DEGs from the PPI network. AZD-8055, methotrexate, and ruxolitinib were predicted to be the possible agents for the treatment. The current study identified significant key genes, common metabolic signaling networks, and therapeutic agents to improve our perception of the common mechanisms of GBM–COVID-19.
Comparative Genomics of Legionella pneumophila Isolates from the West Bank and Germany Support Molecular Epidemiology of Legionnaires’ Disease

Legionella pneumophila is an environmental bacterium and clinical pathogen that causes many life-threating outbreaks of an atypical pneumonia called Legionnaires’ disease (LD). Studies of this pathogen have focused mainly on Europe and the United States. A shortage in L. pneumophila data is clearly observed for developing countries. To reduce this knowledge gap, L. pneumophila isolates were studied in two widely different geographical areas, i.e., the West Bank and Germany. For this study, we sequenced and compared the whole genome of 38 clinical and environmental isolates of L. pneumophila covering different MLVA-8(12) genotypes in the two areas. Sequencing was conducted using the Illumina HiSeq 2500 platform. In addition, two isolates (A194 and H3) were sequenced using a Pacific Biosciences (PacBio) RSII platform to generate complete reference genomes from each of the geographical areas. Genome sequences from 55 L. pneumophila strains, including 17 reference strains, were aligned with the genome sequence of the closest strain (L. pneumophila strain Alcoy). A whole genome phylogeny based on single nucleotide polymorphisms (SNPs) was created using the ParSNP software v 1.0. The reference genomes obtained for isolates A194 and H3 consisted of circular chromosomes of 3,467,904 bp and 3,691,263 bp, respectively. An average of 36,418 SNPs (min. 8569, max. 70,708 SNPs) against our reference strain L. pneumophila str. Alcoy, and 2367 core-genes were identified among the fifty-five strains. An analysis of the genomic population structure by SNP comparison divided the fifty-five L. pneumophila strains into six branches. Individual isolates in sub-lineages in these branches differed by less than 120 SNPs if they had the same MLVA genotype and were isolated from the same location. A bioinformatics analysis identified the genomic islands (GIs) for horizontal gene transfer and mobile genetic elements, demonstrating that L. pneumophila showed high genome plasticity. Four L. pneumophila isolates (H3, A29, A129 and L10-091) contained well-defined plasmids. On average, only about half of the plasmid genes could be matched to proteins in databases. In silico phage findings suggested that 43 strains contained at least one phage. However, none of them were found to be complete. BLASTp analysis of proteins from the type IV secretion Dot/Icm system showed those proteins highly conserved, with less than 25% structural differences in the new L. pneumophila isolates. Overall, we demonstrated that whole genome sequencing provides a molecular surveillance tool for L. pneumophila at the highest conceivable discriminatory level, i.e., two to eight SNPs were observed for isolates from the same location but several years apart.
Essential dynamics: foundation and applications

Collective coordinates, as obtained by a principal component analysis of atomic fluctuations, are commonly used to predict a low‐dimensional subspace in which essential protein motion is expected to take place. The definition of such an essential subspace allows to characterize protein functional, and folding, motion, to provide insight into the (free) energy landscape, and to enhance conformational sampling in molecular dynamics simulations. Here, we provide an overview on the topic, giving particular attention to some methodological aspects, such as the problem of convergence, and mentioning possible new developments. © 2012 John Wiley & Sons, Ltd.
A simple and efficient fluorescent labeling method in Staphylococcus aureus for real-time tracking of invasive bacteria

Bacterial fluorescent labeling is a powerful tool for the diagnosis and treatment of bacterial infections. Here, we present a simple and efficient labeling strategy for Staphylococcus aureus. Intracellular labeling of bacteria was achieved by heat shock using Cyanine 5.5 (Cy5.5) near-infrared-I dyes in S. aureus (Cy5.5@S. aureus). Several key factors, such as Cy5.5 concentration and labeling time, were systematically evaluated. Further, the cytotoxicity of Cy5.5 and the stability of Cy5.5@S. aureus was evaluated by flow cytometry, inverted fluorescence microscopy, and transmission electron microscopy. In addition, Cy5.5@S. aureus were used to explore the phagocytic behavior of RAW264.7 macrophages. These results proved that Cy5.5@S. aureus had a uniform fluorescence intensity and high luminance; additionally, our method had no significant adverse effects on S. aureus compared to unlabeled S. aureus infections. Our method provides researchers with a useful option for analyzing the behavior of S. aureus as an infectious agent. This technique can be broadly applied to study host cell–bacteria interactions at the molecular level, and to in vivo tracing of bacterial infections.
Rise of Deep Learning Clinical Applications and Challenges in Omics Data: A Systematic Review

This research aims to review and evaluate the most relevant scientific studies about deep learning (DL) models in the omics field. It also aims to realize the potential of DL techniques in omics data analysis fully by demonstrating this potential and identifying the key challenges that must be addressed. Numerous elements are essential for comprehending numerous studies by surveying the existing literature. For example, the clinical applications and datasets from the literature are essential elements. The published literature highlights the difficulties encountered by other researchers. In addition to looking for other studies, such as guidelines, comparative studies, and review papers, a systematic approach is used to search all relevant publications on omics and DL using different keyword variants. From 2018 to 2022, the search procedure was conducted on four Internet search engines: IEEE Xplore, Web of Science, ScienceDirect, and PubMed. These indexes were chosen because they offer enough coverage and linkages to numerous papers in the biological field. A total of 65 articles were added to the final list. The inclusion and exclusion criteria were specified. Of the 65 publications, 42 are clinical applications of DL in omics data. Furthermore, 16 out of 65 articles comprised the review publications based on single- and multi-omics data from the proposed taxonomy. Finally, only a small number of articles (7/65) were included in papers focusing on comparative analysis and guidelines. The use of DL in studying omics data presented several obstacles related to DL itself, preprocessing procedures, datasets, model validation, and testbed applications. Numerous relevant investigations were performed to address these issues. Unlike other review papers, our study distinctly reflects different observations on omics with DL model areas. We believe that the result of this study can be a useful guideline for practitioners who look for a comprehensive view of the role of DL in omics data analysis.
Formal Foundations for Research Methods: The Matching of Methodological Needs

Summary ‘Research methods’ is a universal component of the sociology course, and it is also often uninspiring, ill thought‐out and defined as marginal to sociological concerns. The ‘theory‐methods divide’ has arisen in part because theory construction and model building have not been seen as basically identical enterprises. A basic reorientation and restructuring of research methods (and allied) courses is advocated, and this would be based on establishing formal modes of representation, analysis and explanation as an inherently sociological enterprise and one to which all students would be exposed from the start of their courses.
A risk-sensitive maximum principle: the case of imperfect state observation

The risk-sensitive maximum principle for optimal stochastic control derived by the author in an earlier work (System Control Letters, vol.15, 1990) is restated. This is an immediate generalization of the classic Pontryagin principle, to which it reduces in the deterministic case, and is expressed immediately in terms of observables. It is derived on the assumption that the criterion function is the exponential of an additive cost function, and is exact under linear-quadratic Gaussian assumptions, but is otherwise valid as a large deviation approximation. The principle is extended to the case of imperfect state observation after preliminary establishment of a certainty-equivalence principle. The derivation yields as byproduct a large-deviation version of the updating equation for nonlinear filtering. The development is heuristic. It is believed that the mathematical arguments given are the essential ones, and provide a self-contained treatment at this level. >
Evaluating environmental controls on the exoskeleton density of larval Dungeness crab via micro computed tomography

Dungeness crab (Metacarcinus magister) have significant socioeconomic value, but are threatened by ocean acidification (OA) and other environmental stressors that are driven by climate change. Despite evidence that adult harvests are sensitive to the abundance of larval populations, relatively little is known about how Dungeness megalopae will respond to these stressors. Here we evaluate the ability to use micro-computed tomography (μCT) to detect variations in megalope exoskeleton density and how these measurements reflect environmental variables and calcification mechanisms. We use a combination of field data, culture experiments, and model simulations to suggest resolvable differences in density are best explained by minimum pH at the time zoeae molt into megalopae. We suggest that this occurs because more energy must be expended on active ion pumping to reach a given degree of calcite supersaturation at lower pH. Energy availability may also be reduced due to its diversion to other coping mechanisms. Alternate models based on minimum temperature at the time of the zoea-megalope molt are nearly as strong and complicate the ability to conclusively disentangle pH and temperature influences. Despite this, our results suggest that carryover effects between life stages and short-lived extreme events may be particularly important controls on exoskeleton integrity. μCT-based estimates of exoskeleton density are a promising tool for evaluating the health of Dungeness crab populations that will likely provide more nuanced information than presence-absence observations, but future in situ field sampling and culture experiments are needed to refine and validate our results.
Modelling the dust and gas outflows from IRC+10 216 - I. Ground-based and airborne observations

We have developed a model for the dust and gas envelope of the C star IRC+10 216. Spherical symmetry is assumed, and the model consistently solves the full radiative transfer problem for the rotationally excited far-infrared and submillimetre wavelength CO lines and for the dust continuum. New observations of the CO J=9--8 and 12--11 lines, made with the Kuiper Airborne Observatory, are presented. The model accounts for the first 32 rotational states in the lowest two vibrational levels of CO, and is shown to yield satisfactory fits to both line profiles and spatial maps of the CO J=1--0, 2--1, 3--2, 4--3, 6--5, 7--6, 9--8 and 12--11 lines. The dust model yields a good fit to the spectral energy distribution from the near-IR to millimetre wavelengths, assuming a distance to the star of 170 pc. From the CO model we are able to confirm previous findings that the gas in the outer envelope is heated by the photoelectric effect, and we also find that the mass-loss rate must be of order 5 × 10-5 Mo˙ yr-1, with a gas-to-dust ratio of approximately 220, in order to fit all the CO observations and the spectral energy distribution simultaneously, and to predict accurately the observed wind terminal velocity via radiative acceleration of the dust grains which are momentum-coupled to the gas. The gas temperature distribution is found to be lower than predicted by a simple three-level molecule approach which has been found to work for the envelopes of O-rich asymptotic giant branch stars, but is in good agreement with some previously published models for this source. In contrast with some previously published models, we find no evidence for a recent change in mass-loss rate.
The Travelling Wave Scheme for The Navier--Stokes Equations

A new scheme is developed for the one-dimensional, compressible Navier--Stokes equations. The method is a deviation from traditional explicit methods in that the hyperbolic and parabolic parts are treated as a single entity and travelling waves are used as approximating tools. The scheme is used mainly for computation in the regime where the mesh size is of the same order as the ratio of the viscosity $\varepsilon$ to the characteristic speed. A viscous Riemann solver is designed that solves the local Riemann problems.
Carrier depletion based silicon optical modulators

Silicon optical modulators have generated an increasing interest in the recent years, as their performances are crucial to achieve high speed optical links. Among possibilities to achieve optical modulation in silicon-based materials, index variation by free carrier concentration variation has demonstrated good potentiality. High speed and low loss silicon modulators can be obtained by carrier depletion inside lateral PN or PIPIN diodes. When the diode is reverse biased, refractive index variations are obtained and then phase modulation of the guided wave is obtained. Mach-Zehnder interferometers are used to convert phase modulation into intensity modulation. Experimental results are presented for both PN and PIPIN diodes.
Thermal Lensing and Optical Bistability in Ferroelectrics

In a recently developed theory of thermal lensing by ferroelectrics under laser illumination, the sample temperature as a function of radius and time was expressed as an integral. It is now shown that this integral can be approximated by known functions in a form which is accurate to within 1% for practical experimental situations. The theory is extended to explain asymmetric thermal focusing by BNN (barium sodium niobate, Ba2NaNb5O15). The presence of optical bistability in PMN (lead magnesium niobate, Pb(Mg1/3Nb2/3)O3), and PLZT (lanthanum doped lead zirconium titanate, Pb(Zr1-xTix)O3:La) and its absence in BNN and Ce:SBN (cerium doped strontium barium niobate, Ce3+:SrxBa1-xNb2O6) is explained by the presence or absence of Fabry-Pérot resonance. Possible sustained periodic relaxation oscillations are discussed.
Terahertz radiation as a bunch diagnostic for laser-wakefield-accelerated electron bunches

Experimental results are reported from two measurement techniques (semiconductor switching and electro-optic sampling) that allow temporal characterization of electron bunches produced by a laser-driven plasma-based accelerator. As femtosecond electron bunches exit the plasma-vacuum interface, coherent transition radiation (at THz frequencies) is emitted. Measuring the properties of this radiation allows characterization of the electron bunches. Theoretical work on the emission mechanism is presented, including a model that calculates the THz wave form from a given bunch profile. It is found that the spectrum of the THz pulse is coherent up to the 200 μm thick crystal (ZnTe) detection limit of 4THz, which corresponds to the production of sub-50fs (rms) electron bunch structure. The measurements demonstrate both the shot-to-shot stability of bunch parameters that are critical to THz emission (such as total charge and bunch length), as well as femtosecond synchronization among bunch, THz pulse, and laser beam.
How fair is our air? The injustice of procedure, distribution, and recognition within the discourse of air pollution in Delhi, India

ABSTRACT The risk profile of air pollution generates multiple meanings of justice for diverse stakeholders. We examined 535 articles from two Indian newspapers published between 2017 and 2020 and obtained 13 concepts of justice pertinent to ambient air pollution in Delhi. Employing the theoretical perspective of environmental justice, we observed the prevalence of procedural and distributive justice discourses with dominant participation from non-governmental organizations and academic institutions. Recognition justice emerged the most underrepresented of all discourses. We used Discourse Network Analysis to reveal the prominence of Indian citizens, the Supreme Court of India, and farmers in the justice debate, and an overall restricted participation of the government bodies. Our findings highlight polarization among the academic and the non-academic actors on the disproportionate effect of air pollution. For air pollution mitigation in Delhi, we suggest organized and inclusive participation by diverse stakeholders in decision-making, acknowledging socio-cultural differences among populations.
Bayesian inference in hierarchical non‐negative matrix factorisation models of musical sounds

There has been a surge of interest to efficient audio and music modeling using tools from statistical machine learning. One such technique, that has been particularly successful, is non‐negative matrix factorisation (NMF). However, a detailed theoretical understanding of this success is missing, as well as links to other modeling strategies such as sinusoidal or harmonic models. To fill this gap, we describe NMF in a statistical framework, as a hierarchical generative model consisting of an observation and a prior component. We show that particular choices lead to standard NMF algorithms as special cases, where parameter estimation is carried out via maximum likelihood. Starting from this view, we develop extensions that facilitate more realistic acoustic modeling (such as spectral smoothness or harmonicity of natural sounds) and alternative inference techniques via Gibbs sampling and variational Bayes, which allow us to do principled comparisons between alternative models via Bayesian model selection. Ou.
On properties of the approximate Peano derivatives

The notion of fcth approximate Peano differentiation not only generalizes fcth ordinary differentiation but also fcth Peano differentiation and fcth L„ differentiation. Recently, M. Evans has shown that a fcth approximate Peano derivative at least shares with these other derivatives the property of belonging to Baire class one. In this paper the author extends the properties possessed by a fcth approximate Peano derivative by showing that it is like the above derivatives in that it also possesses the following properties: Darboux, Denjoy, Zahorski, and a new property stronger than the Zahorski property, Property Z.
Effect of externally imposed and self-generated flows on turbulence and magnetohydrodynamic activity in tokamak plasmas

The effects of externally imposed and self-generated poloidal flows on turbulence and magnetohydrodynamic (MHD) activity are examined in the context of the possible Electric Tokamak (ET) [Phys. Plasmas 6, 4722 (1999)] plasmas and (circularized) DIII-D-like [Fusion Technol. 8, 441 (1985)] discharges. Global gyrokinetic particle simulations and reduced MHD calculations respectively show that ion temperature gradient driven turbulence (ITGDT) and resistive internal kink MHD activity can be reduced and/or suppressed with experimentally achievable externally imposed flows for possible ET start-up plasmas. Global gyrokinetic particle simulations of ITGDT also serve to demonstrate that self-generated flows are necessary to yield experimentally relevant radial correlation lengths in the case of DIII-D-like discharges.
Comparing apples with oranges

'If two men lay bricks to build a wall, we may quite fairly measure their contributions by counting the number laid by each; but if one mixes the mortar and the other lays the bricks, it would be absurd to measure their relative quantitative contributions by measuring the volumes of bricks and of mortar' (Richard Lewontin). Thus: 'For it to make sense to ask what (or how much) a cause contributes to an effect, the various causes must be commensurable in the way they produce their effects' (Elliott Sober). These claims sound reasonable but I show on the contrary that, for their contributions to be comparable, it is neither necessary nor sufficient that two causes also be commensurable. Rather, in a sense that I discuss, what really matters is that they be separable.