Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Annotation of Narrative Radiology Reports

Narrative texts in electronic health records can be efficiently utilized for building decision support systems in the clinic, only if they are correctly interpreted automatically in accordance with a specified standard. This paper tackles the problem of developing an automated method of labeling free-form radiology reports, as a precursor for building query-capable report databases in hospitals. The analyzed dataset consists of 1295 radiology reports concerning the condition of a knee, retrospectively gathered at the Clinical Hospital Centre Rijeka, Croatia. Reports were manually labeled with one or more labels from a set of 10 most commonly occurring clinical conditions. After primary preprocessing of the texts, two sets of text classification methods were compared: (1) traditional classification models—Naive Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), and Random Forests (RF)—coupled with Bag-of-Words (BoW) features (i.e., symbolic text representation) and (2) Convolutional Neural Network (CNN) coupled with dense word vectors (i.e., word embeddings as a semantic text representation) as input features. We resorted to nested 10-fold cross-validation to evaluate the performance of competing methods using accuracy, precision, recall, and F1 score. The CNN with semantic word representations as input yielded the overall best performance, having a micro-averaged F1 score of 86.7%. The CNN classifier yielded particularly encouraging results for the most represented conditions: degenerative disease (95.9%), arthrosis (93.3%), and injury (89.2%). As a data-hungry deep learning model, the CNN, however, performed notably worse than the competing models on underrepresented classes with fewer training instances such as multicausal disease or metabolic disease. LR, RF, and SVM performed comparably well, with the obtained micro-averaged F1 scores of 84.6%, 82.2%, and 82.1%, respectively.
Effects of UV Stabilizers on Polypropylene Outdoors

Hindered amine light stabilizers (HALSs) and nano ZnO were used to stabilize polypropylene (PP) film-based formulations that were exposed to ultraviolet (UV) light for different lengths of time, simulating the harsh outdoor weather of Dallas, Texas, USA. UV doses applied in our laboratory are 121 times larger than the UV dose provided by the sunlight in Texas. 15 different compositions were studied. Tensile behavior, UV transmittance, thermal stability (by thermogravimetric analysis) and dynamic friction of the so exposed PP-based films were determined. Scanning electron micrographs of fracture surfaces were obtained. Nano-ZnO-containing stabilizers impart strong UV resistance to our films. The combination of HALSs and nano-ZnO stabilizers makes the PP films harder—which is important for some PP applications, such as toy manufacturing.
Enhanced serotonin availability amplifies fatigue perception and modulates the TMS‐induced silent period during sustained low‐intensity elbow flexions

During maximal effort contractions, intense serotonin release via the raphe‐spinal pathway spills over from the somato‐dendritic compartment to activate inhibitory 5‐HT1A receptors on the axon initial segment of motoneurons to reduce motoneuronal output. We investigated whether the same mechanism of central fatigue is present for low‐intensity contractions, whereby weak serotonergic drive over an extended period may cause accumulation of serotonin and exacerbate central fatigue. Enhanced availability of serotonin did not directly influence motor pathways or motor performance during prolonged submaximal contraction. However, perceptions of muscle fatigue were greater, and the fatigue‐induced lengthening of the silent period elicited via motor cortical stimulation was reduced with enhanced availability of serotonin. We propose that sustained low‐intensity serotonergic neurotransmission influences supraspinal processes associated with fatigue, without directly influencing the output of the motor system during submaximal exercise.
Leucocyte typing IV : white cell differentiation antigens

What next? , C.Milstein statistical analysis, W.Gilks et al. Part 1 B-cells: B-cell section report, B.Dorken et al cluster reports and B-cell papers. Part 2 T-cells: T-cell section report, P.Rieber et al cluster reports and T-cell papers. Part 3 Activation antigens: Activation antigens section report, H.Stein and R.Schwarting cluster reports and activation papers. Part 4 NK-and non-lineage antigens: NK- and non-lineage antigens section report, R.E. Schmidt et al cluster reports and NK- and non-lineage papers. Part 5 Myeloid cells: Myeloid cells section report, W.Knapp et al cluster reports and myeloid papers. Part 6 Platelets: Platelets section report, AEG Kr von dem Borne et al cluster reports and platelet papers. Part 7 Plenary papers.
In Vivo Biodistribution of Respirable Solid Lipid Nanoparticles Surface-Decorated with a Mannose-Based Surfactant: A Promising Tool for Pulmonary Tuberculosis Treatment?

The active targeting to alveolar macrophages (AM) is an attractive strategy to improve the therapeutic efficacy of ‘old’ drugs currently used in clinical practice for the treatment of pulmonary tuberculosis. Previous studies highlighted the ability of respirable solid lipid nanoparticle assemblies (SLNas), loaded with rifampicin (RIF) and functionalized with a novel synthesized mannose-based surfactant (MS), both alone and in a blend with sodium taurocholate, to efficiently target the AM via mannose receptor-mediated mechanism. Here, we present the in vivo biodistribution of these mannosylated SLNas, in comparison with the behavior of both non-functionalized SLNas and bare RIF. SLNas biodistribution was assessed, after intratracheal instillation in mice, by whole-body real-time fluorescence imaging in living animals and RIF quantification in excised organs and plasma. Additionally, SLNas cell uptake was determined by using fluorescence microscopy on AM from bronchoalveolar lavage fluid and alveolar epithelium from lung dissections. Finally, histopathological evaluation was performed on lungs 24 h after administration. SLNas functionalized with MS alone generated the highest retention in lungs associated with a poor spreading in extra-pulmonary regions. This effect could be probably due to a greater AM phagocytosis with respect to SLNas devoid of mannose on their surface. The results obtained pointed out the unique ability of the nanoparticle surface decoration to provide a potential more efficient treatment restricted to the lungs where the primary tuberculosis infection is located.
The Role of Dorsal Raphe Serotonin Neurons in the Balance between Reward and Aversion

Background: Reward processing is fundamental for animals to survive and reproduce. Many studies have shown the importance of dorsal raphe nucleus (DRN) serotonin (5-HT) neurons in this process, but the strongly correlative link between the activity of DRN 5-HT neurons and rewarding/aversive potency is under debate. Our primary objective was to reveal this link using two different strategies to transduce DRN 5-HT neurons. Methods: For transduction of 5-HT neurons in wildtype mice, adeno-associated virus (AAV) bearing the mouse tryptophan hydroxylase 2 (TPH2) gene promoter was used. For transduction in Tph2-tTA transgenic mice, AAVs bearing the tTA-dependent TetO enhancer were used. To manipulate the activity of 5-HT neurons, optogenetic actuators (CheRiff, eArchT) were expressed by AAVs. For measurement of rewarding/aversive potency, we performed a nose-poke self-stimulation test and conditioned place preference (CPP) test. Results: We found that stimulation of DRN 5-HT neurons and their projections to the ventral tegmental area (VTA) increased the number of nose-pokes in self-stimulation test and CPP scores in both targeting methods. Concomitantly, CPP scores were decreased by inhibition of DRN 5-HT neurons and their projections to VTA. Conclusion: Our findings indicate that the activity of DRN 5-HT neurons projecting to the VTA is a key modulator of balance between reward and aversion.
Flow Interactions Between Low Aspect Ratio Hydrofoils in In-line and Staggered Arrangements

Many species of fish gather in dense collectives or schools where there are significant flow interactions from their shed wakes. Commonly, these swimmers shed a classic reverse von Kármán wake, however, schooling eels produce a bifurcated wake topology with two vortex rings shed per oscillation cycle. To examine the schooling interactions of a hydrofoil with a bifurcated wake topology, we present tomographic particle image velocimetry (tomo PIV) measurements of the flow interactions and direct force measurements of the performance of two low-aspect-ratio hydrofoils (AR=0.5) in an in-line and a staggered arrangement. Surprisingly, when the leader and follower are interacting in either arrangement there are only minor alterations to the flowfields beyond the superposition of the flowfields produced by the isolated leader and follower. Motivated by this finding, Garrick’s linear theory, a linear unsteady hydrofoil theory based on a potential flow assumption, was adapted to predict the lift and thrust performance of the follower. Here, the follower hydrofoil interacting with the leader’s wake is considered as the superposition of an isolated pitching foil with a time-varying cross-stream velocity derived from the wake flow measurements of the isolated leader. Linear theory predictions accurately capture the time-averaged lift force and some of the major peaks in thrust derived from the follower interacting with the leader’s wake in a staggered arrangement. The thrust peaks that are not predicted by linear theory are likely driven by spatial variations in the flowfield acting on the follower or nonlinear flow interactions; neither of which are accounted for in the simple theory. This suggests that unsteady potential flow theory that does account for spatial variations in the flowfield acting on a hydrofoil can provide a relatively simple framework to understand and model the flow interactions that occur in schooling fish. Additionally, schooling eels can derive thrust and efficiency increases of 63-80% in either a in-line or a staggered arrangement where the follower is between two branched momentum jets or with one momentum jet branch directly impinging on it, respectively.
Topical Delivery of Meloxicam using Liposome and Microemulsion Formulation Approaches

The aim of this study is to develop, characterize and compare conventional liposome, deformable liposome (transfersome) and microemulsion formulations as potential topical delivery systems for meloxicam. Liposomes were characterized in terms of vesicle size, zeta potential and entrapment efficiency. For microemulsions, particle size, electrical conductivity and viscosity studies were performed to assess the structure of the investigated systems. An ex vivo skin permeation study has been conducted to compare these formulations. The dermal and transdermal delivery of meloxicam using these formulations can be a promising alternative to conventional oral delivery of non-steroidal anti-inflammatory drugs (NSAIDs) with enhanced local and systemic onset of action and reduced side effects.
Hericium Erinaceus Prevents DEHP-Induced Mitochondrial Dysfunction and Apoptosis in PC12 Cells

Hericium Erinaceus (HE) is a medicinal plant known to possess anticarcinogenic, antibiotic, and antioxidant activities. It has been shown to have a protective effect against ischemia-injury-induced neuronal cell death in rats. As an extending study, here we examined in pheochromocytoma 12 (PC12) cells, whether HE could exert a protective effect against oxidative stress and apoptosis induced by di(2-ethylhexyl)phthalate (DEHP), a plasticizer known to cause neurotoxicity. We demonstrated that pretreatment with HE significantly attenuated DEHP induced cell death. This protective effect may be attributed to its ability to reduce intracellular reactive oxygen species levels, preserving the activity of respiratory complexes and stabilizing the mitochondrial membrane potential. Additionally, HE pretreatment significantly modulated Nrf2 and Nrf2-dependent vitagenes expression, preventing the increase of pro-apoptotic and the decrease of anti-apoptotic markers. Collectively, our data provide evidence of new preventive nutritional strategy using HE against DEHP-induced apoptosis in PC12 cells.
The Missing Lnc: The Potential of Targeting Triple-Negative Breast Cancer and Cancer Stem Cells by Inhibiting Long Non-Coding RNAs

Treatment decisions for breast cancer are based on staging and hormone receptor expression and include chemotherapies and endocrine therapy. While effective in many cases, some breast cancers are resistant to therapy, metastasize and recur, leading to eventual death. Higher percentages of tumor-initiating cancer stem cells (CSCs) may contribute to the increased aggressiveness, chemoresistance, and worse outcomes among breast cancer. This may be particularly true in triple-negative breast cancers (TNBCs) which have higher percentages of CSCs and are associated with worse outcomes. In recent years, increasing numbers of long non-coding RNAs (lncRNAs) have been identified as playing an important role in breast cancer progression and some of these have been specifically associated within the CSC populations of breast cancers. LncRNAs are non-protein-coding transcripts greater than 200 nucleotides which can have critical functions in gene expression regulation. The preclinical evidence regarding lncRNA antagonists for the treatment of cancer is promising and therefore, presents a potential novel approach for treating breast cancer and targeting therapy-resistant CSCs within these tumors. Herein, we summarize the lncRNAs that have been identified as functionally relevant in breast CSCs. Furthermore, our review of the literature and analysis of patient datasets has revealed that many of these breast CSC-associated lncRNAs are also enriched in TNBC. Together, this suggests that these lncRNAs may be playing a particularly important role in TNBC. Thus, certain breast cancer-promoting/CSC-associated lncRNAs could be targeted in the treatment of TNBCs and the CSCs within these tumors should be susceptible to anti-lncRNA therapy.
Cloning, Molecular Characterization and Expression Patterns of DMRTC2 Implicated in Germ Cell Development of Male Tibetan Sheep

The double sex and mab-3-related transcription factors like family C2 (DMRTC2) gene is indispensable for mammalian testicular function and spermatogenesis. Despite its importance, what expression and roles of DMRTC2 possesses and how it regulates the testicular development and spermatogenesis in sheep, especially in Tibetan sheep, remains largely unknown. In this study, DMRTC2 cDNA from testes of Tibetan sheep was firstly cloned by the RT-PCR method, and its molecular characterization was identified. Subsequently, the expression and localization patterns of DMRTC2 were evaluated by quantitative real-time PCR (qPCR), Western blot, and immunofluorescence. The cloning and sequence analysis showed that the Tibetan sheep DMRTC2 cDNA fragment contained 1113 bp open reading frame (ORF) capable of encoding 370 amino acids, and displayed high identities with some other mammals, which shared an identical DM domain sequence of 47 amino acids ranged from residues 38 to 84. qPCR and Western blot results showed that DMRTC2 was expressed in testes throughout the development stages while not in epididymides (caput, corpus, and cauda), with higher mRNA and protein abundance in Tibetan sheep testes of one- and three-year-old (post-puberty) compared with that of three-month-old (pre-puberty). Immunofluorescence results revealed that immune staining for DMRTC2 protein was observed in spermatids and spermatogonia from post-puberty Tibetan sheep testes, and gonocytes from pre-puberty Tibetan sheep testes. Together, these results demonstrated, for the first time, in sheep, that DMRTC2, as a highly conserved gene in mammals, is essential for sheep spermatogenesis by regulating the proliferation or differentiation of gonocytes and development of spermatids in ram testes at different stages of maturity.
The Influence of Local Habitat and Microclimate on the Levels of Secondary Metabolites in Slovak Bilberry (Vaccinium myrtillus L.) Fruits

The berries of Vaccinium myrtillus L. are usually collected in the wild for the purpose of being a food source. They are naturally high in phenolic compounds, which possess antioxidative properties, so the berries are therefore often labeled as “functional foods”. This study evaluated seven samples of bilberry fruits from different locations in Slovakia for the content of the main phenolic compounds (anthocyanins, flavonoids and tannins) using European Pharmacopoeia 9 spectrophotometric methods. A thorough analysis of environmental factors showed that several phenolic constituents are closely corresponding with their respective environments, as well as with each other. The environmental factors with statistically significant correlations in this study are altitude, habitat type, sunlight exposure, and soil carbon content. Our findings suggest that the berries collected at sunny sites with no topsoil damage contain more phenolic compounds. The lowest amounts of phenolic compounds were found in samples from dense forests or with visible soil erosion and windthrow damage. The negative effect of windthrow damage on the levels of secondary metabolites in bilberry fruits has been described for the first time. This study observed no relationship between the amount of phenolic compounds and soil pH, soil nitrogen levels, or slope exposition.
A Theoretical Study on Trehalose + Water Mixtures for Dry Preservation Purposes

The properties of trehalose + water mixtures are studied as a function of mixture composition and temperature using molecular dynamics simulations. As trehalose disaccharide has been proposed for dry preservation purposes, the objective of this work is to analyse the nanoscopic properties of the considered mixtures, in terms of aggregation, clustering, interactions energies, and local dynamics, and their relationships with hydrogen bonding. The reported results allow a detailed characterization of hydrogen bonding and its evolution with mixture composition and thus inferring the effects of trehalose on water structuring providing results to justify the mechanisms of trehalose acting as preservation agent.
Hybridized Love Waves in a Guiding Layer Supporting an Array of Plates with Decorative Endings

This study follows from Maurel et al., Phys. Rev. B 98, 134311 (2018), where we reported on direct numerical observations of out-of-plane shear surface waves propagating along an array of plates atop a guiding layer, as a model for a forest of trees. We derived closed form dispersion relations using the homogenization procedure and investigated the effect of heterogeneities at the top of the plates (the foliage of trees). Here, we extend the study to the derivation of a homogenized model accounting for heterogeneities at both endings of the plates. The derivation is presented in the time domain, which allows for an energetic analysis of the effective problem. The effect of these heterogeneous endings on the properties of the surface waves is inspected for hard heterogeneities. It is shown that top heterogeneities affect the resonances of the plates, hence modifying the cut-off frequencies of a wave mathematically similar to the so-called Spoof Plasmon Polariton (SPP) wave, while the bottom heterogeneities affect the behavior of the layer, hence modifying the dispersion relation of the Love waves. The complete system simply mixes these two ingredients, resulting in hybrid surface waves accurately described by our model.
The shape of things to come: Topological data analysis and biology, from molecules to organisms

Shape is data and data is shape. Biologists are accustomed to thinking about how the shape of biomolecules, cells, tissues, and organisms arise from the effects of genetics, development, and the environment. Less often do we consider that data itself has shape and structure, or that it is possible to measure the shape of data and analyze it. Here, we review applications of topological data analysis (TDA) to biology in a way accessible to biologists and applied mathematicians alike. TDA uses principles from algebraic topology to comprehensively measure shape in data sets. Using a function that relates the similarity of data points to each other, we can monitor the evolution of topological features—connected components, loops, and voids. This evolution, a topological signature, concisely summarizes large, complex data sets. We first provide a TDA primer for biologists before exploring the use of TDA across biological sub‐disciplines, spanning structural biology, molecular biology, evolution, and development. We end by comparing and contrasting different TDA approaches and the potential for their use in biology. The vision of TDA, that data are shape and shape is data, will be relevant as biology transitions into a data‐driven era where the meaningful interpretation of large data sets is a limiting factor.
Motion correction of respiratory-gated PET images using deep learning based image registration framework

Artifacts caused by patient breathing and movement during PET data acquisition affect image quality. Respiratory gating is commonly used to gate the list-mode PET data into multiple bins over a respiratory cycle. Non-rigid registration of respiratory-gated PET images can reduce motion artifacts and preserve count statistics, but it is time consuming. In this work, we propose an unsupervised non-rigid image registration framework using deep learning for motion correction. Our network uses a differentiable spatial transformer layer to warp the moving image to the fixed image and uses a stacked structure for deformation field refinement. Estimated deformation fields were incorporated into an iterative image reconstruction algorithm to perform motion compensated PET image reconstruction. We validated the proposed method using simulation and clinical data and implemented an iterative image registration approach for comparison. Motion compensated reconstructions were compared with ungated images. Our simulation study showed that the motion compensated methods can generate images with sharp boundaries and reveal more details in the heart region compared with the ungated image. The resulting normalized root mean square error (NRMS) was 24.3 ± 1.7% for the deep learning based motion correction, 31.1 ± 1.4% for the iterative registration based motion correction, and 41.9 ± 2.0% for ungated reconstruction. The proposed deep learning based motion correction reduced the bias compared with the ungated image without increasing the noise level and outperformed the iterative registration based method. In the real data study, both motion compensated images provided higher lesion contrast and sharper liver boundaries than the ungated image and had lower noise than the reference gate image. The contrast of the proposed method based on the deep neural network was higher than the ungated image and iterative registration method at any matched noise level.