Miracle-dz/UniFAR-FTUs huggingface dataset:
Graphene in wearable textile sensor devices for healthcare

Abstract Current advances in flexible, textile wearable device manufacturing are being made through a new generation of materials and nanotechnology. These recent advances make integrating functional sensors into textiles easier and allow for widespread application, including healthcare. Through improving the materials and integration techniques used, wearable sensors can be used to create personalised healthcare products that can monitor vital physical and biological signals. One material that is leading the way for future healthcare systems is graphene. Graphene has superior electrical and thermal conductivity, high chemical stability, and extreme mechanical properties. It also offers a variety of hybrid types that are useful when designing cost-effective and scalable electronic devices for textile applications. This review will outline how graphene and textile-based materials are being used to manufacture wearable health-monitoring devices as well as the challenges and opportunities of graphene and textile-based materials.
A comprehensive review on effective medium theories to find effective dielectric constant of composites

We present here a selective and focused review of various Effective Medium Theories (EMT) with their progressive developments, and different mixture formulae used to calculate one of the most important optical constants, i.e. effective permittivity, for different composites. First, we visit the well-known Maxwell Garnett (MG) EMT and its variants. Thereafter, we discuss MG-EMT for the inclusions such as bi-anisotropic materials, carbon nanotube, uniaxial, and anisotropic materials. Then we emphasise the Bruggeman (Br) EMT and its variants. We have also discussed Br-EMT for uniaxial inclusions. In the next section, we analyse Bragg-Pippard (BP) EMT for anisotropic dielectric homogenized composite medium and for bi-anisotropic system. Next, we discuss on Strong Property Fluctuation Theory (SPFT) for bi-anisotropic ellipsoidal inclusions. Following this, we consider EMT for dielectric-magnetic materials, and for thin multilayer structures. Finally, we discuss different mixture formulae used for colloidal solutions, gas mixtures, solvent mixtures, and electrolyte solutions.
Effect of alkali treatment on the mechanical properties and water resistance of bamboo scraps/magnesium oxychloride composites

Abstract Alkali treatment of bamboo scraps was adopted to improve the interface compatibility between the organic-phase bamboo scraps of the composite material and the inorganic-phase magnesium oxychloride. Scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, and other techniques were used to characterize bamboo scraps before and after alkali treatment. The bamboo scraps treated with alkali exhibited improved bonding properties to cementitious materials. The mechanical properties and water resistance of the composite material were evaluated. The results indicated that the mechanical strength first increased and then decreased with an increase in alkali concentration. After treatment with 3wt% NaOH solution, the composite exhibited the highest compressive strength and bending strength. The softening coefficient also reached 0.57. Alkali treatment resulted in improved bonding of bamboo scraps with magnesium oxychloride cementitious material, as confirmed by mechanical property and water resistance tests, and SEM image analysis.
Identification and Characterization of an HtrA Sheddase Produced by Coxiella burnetii

Having previously shown that soluble E-cadherin (sE-cad) is found in sera of Q fever patients, and that infection of BeWo cells by C. burnetii leads to modulation of the E-cad/β-cat pathway, our purpose was to identify which sheddase(s) might catalyze the cleavage of E-cad. Here, we searched for a direct mechanism of cleavage initiated by the bacterium itself, assuming the possible synthesis of a sheddase encoded in the genome of C. burnetii or an indirect mechanism based on the activation of a human sheddase. Using a straightforward bioinformatics approach to scan the complete genomes of four laboratory strains of C. burnetii, we demonstrate that C. burnetii encodes a 451 amino acid sheddase (CbHtrA) belonging to the HtrA family and differently expressed according to the bacterial virulence. An artificial CbHtrA gene (CoxbHtrA) was expressed and the CoxbHtrA recombinant protein was found to have sheddase activity. We also found evidence that the C. burnetii infection triggers an over-induction of the human HuHtrA gene expression. Finally, we demonstrate that cleavage of E-cad by CoxbHtrA on THP-1-cells leads to an M2 polarization of the target cells and the induction of their secretion of IL-10, which ‘disarms’ the target cells and improves C. burnetii replication. Taken together these results demonstrate that the genome of C. burnetii encodes a functional HtrA sheddase and establish a link between the HtrA sheddase-induced cleavage of E-cad, the M2 polarization of the target cells and their secretion of IL-10, and the intracellular replication of C. burnetii.
Molecular portraits of colorectal cancer morphological regions

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole- tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.
Investigating variant and expression of CVD genes associated phenotypes among high-risk Heart Failure patients

Cardiovascular disease (CVD) is a leading cause of premature mortality in the US and the world. CVD comprises of several complex and mostly heritable conditions, which range from myocardial infarction to congenital heart disease. Here, we report our findings from an integrative analysis of gene expression, disease-causing gene variants, and associated phenotypes among CVD populations, with a focus on high-risk Heart Failure (HF) patients. We built a cohort using electronic health records (EHR) of consented patients with available samples, and then performed high-throughput whole-genome and RNA sequencing (RNA-seq) of key genes responsible for HF and other CVD pathologies. We also incorporated a translational aspect to our study by integrating genomics findings with patient medical records. This involved linking ICD-10 codes with our gene expression and variant data to identify associations with HF and other CVDs. Our in-depth gene expression analysis revealed differentially expressed genes associated with HF (41 genes) and other CVDs (23 genes). Furthermore, a variant analysis of whole-genome sequence data of CVD patients identified genes with altered gene expression (FLNA, CST3, LGALS3, and HBA1) with functional and nonfunctional mutations in these genes. Our study highlights the importance of an integrative approach that leverages gene expression, genetic mutations, and clinical data that will allow the prioritization of key driver genes for complex diseases to improve personalized healthcare.
DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals

Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling sound elements in recordings of animal sounds and demonstrate its utility on recordings of beetle courtships and whale songs. The software, DISCO, computes sensible confidence estimates and produces labels with high precision and accuracy. In addition to the core labeling software, it provides a simple tool for labeling training data, and a visual system for analysis of resulting labels. DISCO is open-source and easy to install, it works with standard file formats, and it presents a low barrier of entry to use.
Single-cell RNA sequencing unravels the transcriptional network underlying zebrafish retina regeneration

In the lesioned zebrafish retina, Müller glia produce multipotent retinal progenitors that generate all retinal neurons, replacing lost cell types. To study the molecular mechanisms linking Müller glia reactivity to progenitor production and neuronal differentiation, we used single cell RNA sequencing of Müller glia, progenitors and regenerated progeny from uninjured and light-lesioned retinae. We discover an injury-induced Müller glia differentiation trajectory that leads into a cell population with a hybrid identity expressing marker genes of Müller glia and progenitors. A glial self-renewal and a neurogenic trajectory depart from the hybrid cell population. We further observe that neurogenic progenitors progressively differentiate to generate retinal ganglion cells first and bipolar cells last, similar to the events observed during retinal development. Our work provides a comprehensive description of Müller glia and progenitor transcriptional changes and fate decisions in the regenerating retina, which are key to tailor cell differentiation and replacement therapies for retinal dystrophies in humans.
The circadian clock is required for rhythmic lipid transport in the Drosophila hemolymph in interaction with diet, photic condition and feeding

Modern lifestyle often is at odds with endogenously driven rhythmicity, which can lead to circadian disruption and metabolic syndrome. One signature for circadian disruption is a diminished or altered cycling of metabolites in the circulating tissue reflecting the current metabolic status. Drosophila is a well-established model in chronobiology, but day-time dependent variations of transport metabolites in the fly circulation are poorly characterized. Here, we sampled fly hemolymph throughout the day and analysed diacylglycerols (DGs), phosphoethanolamines (PEs) and phosphocholines (PCs) using LC-MS. In wildtype flies kept on sugar-only medium under a light-dark cycle, all transport lipid species showed a synchronized bimodal oscillation pattern with maxima at the beginning and end of the light phase which were impaired in period01 clock mutants. In wildtype flies under constant dark conditions, the oscillation became monophasic with a maximum in the middle of the subjective day. In strong support of clock-driven oscillations, levels of DGs, PEs and PCs peaked once in the middle of the light phase under time-restricted feeding independent of the time of food intake. Rearing of wildtype flies on lipid-containing standard medium masked the rhythmic alterations of hemolymph lipid levels. Our data suggest that the circadian clock aligns daily oscillations of DGs, PEs and PCs in the hemolymph to the anabolic siesta phase, whith a strong influence of light on phase and modality. This finding opens the question whether and to what extent the circadian regulation of transport lipid levels in the hemolymph contributes to the health of the fly.
Rapid and highly efficient morphogenic gene-mediated hexaploid wheat transformation

The successful employment of morphogenic regulator genes, Zm-Baby Boom (ZmBbm) and Zm-Wuschel2 (ZmWus2), for Agrobacterium-mediated transformation of maize (Zea mays L.) and sorghum (Sorghum bicolor L.) has been reported to improve transformation by inducing rapid somatic embryo formation. Here, we report two morphogenic gene-mediated wheat transformation methods, either with or without morphogenic and marker gene excision. These methods yield independent-transformation efficiency up to 58% and 75%, respectively. In both cases, the tissue culture duration for generating transgenic plants was significantly reduced from 80 to nearly 50 days. In addition, the transformation process was significantly simplified to make the procedure less labor-intensive, higher-throughput and more cost-effective, by eliminating the requirement for embryonic axis excision, bypassing the necessity for prolonged dual-selection steps for callus formation, and obviating the prerequisite of cytokinin for shoot regeneration. Furthermore, we have demonstrated the flexibility of the methods and generated high-quality transgenic events across multiple genotypes using herbicide (phosphinothricin, ethametsulfuron)- and antibiotic (G418)-based selections.
Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, as differences can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.
Ensemble Processing and Synthetic Image Generation for Abnormally Shaped Nuclei Segmentation

Abnormalities in biological cell nuclei morphology are correlated with cell cycle stages, disease states, and various external stimuli. There have been many deep learning approaches that have described nuclei segmentation and analysis of nuclear morphology. One problem with many deep learning methods is acquiring large amounts of annotated nuclei data, which is generally expensive to obtain. In this paper, we propose a system to segment abnormally shaped nuclei with a limited amount of training data. We first generate specific shapes of synthetic nuclei groundtruth. We randomly sample these synthetic groundtruth images into training sets to train several Mask R-CNNs. We design an ensemble strategy to combine or fuse segmentation results from the Mask R-CNNs. We also design an oval nuclei removal by StarDist to reduce the false positives and improve the overall segmentation performance. Our experiments indicate that our method outperforms other methods in segmenting abnormally shaped nuclei.
New tools to study the interaction between integrins and latent TGFβ1

Transforming growth factor beta (TGFβ) 1 regulates cell differentiation and proliferation in different physiological settings, but is also involved in fibrotic progression and protects tumors from the immune system. Integrin αVβ6 has been shown to activate latent TGFβ1 by applying mechanical forces onto the latency-associated peptide (LAP). While the extracellular binding between αVβ6 and LAP1 is well characterized, less is known about the cytoplasmic adaptations that enable αVβ6 to apply such forces. Here, we generated new tools to facilitate the analysis of this interaction. We combined the integrin-binding part of LAP1 with a GFP and the Fc chain of human IgG. This chimeric protein, sLAP1, revealed a mechanical rearrangement of immobilized sLAP1 by αVβ6 integrin. This unique interaction was not observed between sLAP1 and other integrins. We also analyzed αVβ6 integrin binding to LAP2 and LAP3 by creating respective sLAPs. Compared to sLAP1, integrin αVβ6 showed less binding to sLAP3 and no rearrangement. These observations indicate differences in the binding of αVβ6 to LAP1 and LAP3 that have not been appreciated so far. Finally, αVβ6-sLAP1 interaction was maintained even at strongly reduced cellular contractility, highlighting the special mechanical connection between αVβ6 integrin and latent TGFβ1.
Slow-rising and fast-falling dopaminergic dynamics jointly adjust negative prediction error in the ventral striatum

The greater the reward expectations are, the more different the brain’s physiological response will be. Although it is well-documented that better-than-expected outcomes are encoded quantitatively via midbrain dopaminergic (DA) activity, it has been less addressed experimentally whether worse-than-expected outcomes are expressed quantitatively as well. We show that larger reward expectations upon unexpected reward omissions are associated with the preceding slower rise and following larger decrease (DA dip) in the DA concentration at the ventral striatum of mice. We set up a lever press task on a fixed ratio (FR) schedule requiring five lever presses as an effort for a food reward (FR5). The mice occasionally checked the food magazine without a reward before completing the task. The percentage of this premature magazine entry (PME) increased as the number of lever presses approached five, showing rising expectations with increasing proximity to task completion, and hence greater reward expectations. Fiber photometry of extracellular DA dynamics in the ventral striatum using a fluorescent protein (genetically encoded GPCR-activation-based-DA sensor: GRABDA2m) revealed that the slow increase and fast decrease in DA levels around PMEs were correlated with the PME percentage, demonstrating a monotonic relationship between the DA dip amplitude and degree of expectations. Computational modeling of the lever press task implementing temporal difference errors and state transitions replicated the observed correlation between the PME frequency and DA dip amplitude in the FR5 task. Taken together, these findings indicate that the DA dip amplitude represents the degree of reward expectations monotonically, which may guide behavioral adjustment.
Investigation of interactions of intense plasma streams with tungsten and carbon fibre composite targets in the PF-1000 facility

This paper presents the results of research on interactions of pulsed plasma streams, as generated by the PF-1000 facility, with solid targets made of tungsten or carbon fibre composite. The device was equipped with a modified inner electrode with a central tungsten insert of 50 mm in diameter. The PF-1000 experimental chamber was filled with pure deuterium at p0 = 1.47 hPa. At the charging voltage U0 = 24 kV, the maximum current amounted to 1.8 MA in about 5.5 μs after the discharge initiation. The investigated targets were located on the z-axis, at a distance of 9 cm from the inner electrode end. For plasma diagnostics, optical emission spectroscopy, 16-frame laser interferometry and a soft x-ray measuring system of four silicon pin diodes were used. It was observed that plasma streams reached the target about 100 ns after the maximum compression and generated a plasma pillow at the sample surface, as proved from time-resolved optical spectra.
High-resolution calorimetric study of critical behaviour at the smectic-C*–smectic- phase transition

Precise heat-capacity measurements have been made around the smectic-–smectic- phase transition in the R–S mixture of liquid crystal MHPOBC ([1,1′-biphenyl]-4-carboxylic acid, 4′-(octyloxy)-, 4-[[(1-methylheptyl)oxy]carbonyl]phenyl ester) which exhibits ferro- and antiferroelectric phases. Ultra-low frequency ac calorimeter and high-sensitivity differential scanning calorimeter have been used. The measurements revealed the existence of quite slow relaxation near the transition. The heat-capacity anomaly accompanying the transition showed a significant increase as decreasing heat frequency in the ac method. The excess heat capacity observed for a mixture that is closest to the critical point has been analysed quantitatively.
Numerical modelling of landscape evolution: geomorphological perspectives

A resurgence of interest in landscape evolution has occurred as computational technology has made possible spatially and temporally extended numerical modelling. We review elements of a structured approach to model development and testing. It is argued that natural breaks in landscape process and morphology define appropriate spatial domains for the study of landscape evolution. The concept of virtual velocity is used to define appropriate timescales for the study of landscape change. Process specification in numerical modelling requires that the detail incorporated into equations be commensurable with the particular scale being considered. This may entail a mechanistic approach at small (spatial) scales, whereas a generalized approach to process definition may be preferred in large-scale studies. The distinction is illustrated by parameterizations for hillslope and fluvial transport processes based on scale considerations. Issues relevant to model implementation, including validation, verification, calibration and confirmation, are discussed. Finally, key developments and characteristics associated with three approaches to the study of landscape modelling:(i) conceptual; (ii) quasi-mechanistic; and (iii) generalized physics, are reviewed.