A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.

Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system-related diseases are diagnosed by the differential count of white blood cells, which is one of the common laboratory tests. Data is one of the most important ingredients in the development and testing of many commercial and successful automatic or semi-automatic systems. To this end, this study introduces a free access dataset of normal peripheral white blood cells called Raabin-WBC containing about 40,000 images of white blood cells and color spots. For ensuring the validity of the data, a significant number of cells were labeled by two experts. Also, the ground truths of the nuclei and cytoplasm are extracted for 1145 selected cells. To provide the necessary diversity, various smears have been imaged, and two different cameras and two different microscopes were used. We did some preliminary deep learning experiments on Raabin-WBC to demonstrate how the generalization power of machine learning methods, especially deep neural networks, can be affected by the mentioned diversity. Raabin-WBC as a public data in the field of health can be used for the model development and testing in different machine learning tasks including classification, detection, segmentation, and localization.

Experimental verification of the standard model of particle physics.

The history concerning an experimental verification of the standard model of particle physics is reviewed with special emphasis on results from experiments using the highest-energy particle colliders, namely, PETRA, LEP and LHC. This article covers physics subjects from discovering the gluon and precise measurements at LEP, to discovering the Higgs boson. It also covers some searches for physics beyond the standard model, particularly supersymmetry, as well as recent developments of some particle detectors that were used in those experiments.

Machine learning to determine optimal conditions for controlling the size of elastin-based particles.

This paper evaluates the aggregation behavior of a potential drug and gene delivery system that combines branched polyethyleneimine (PEI), a positively-charged polyelectrolyte, and elastin-like polypeptide (ELP), a recombinant polymer that exhibits lower critical solution temperature (LCST). The LCST behavior of ELP has been extensively studied, but there are no quantitative ways to control the size of aggregates formed after the phase transition. The aggregate size cannot be maintained when the temperature is lowered below the LCST, unless the system exhibits hysteresis and forms irreversible aggregates. This study shows that conjugation of ELP with PEI preserves the aggregation behavior that occurs above the LCST and achieves precise aggregate radii when the solution conditions of pH (3, 7, 10), polymer concentration (0.1, 0.15, 0.3 mg/mL), and salt concentration (none, 0.2, 1 M) are carefully controlled. K-means cluster analyses showed that salt concentration was the most critical factor controlling the hydrodynamic radius and LCST. Conjugating ELP to PEI allowed crosslinking the aggregates and achieved stable particles that maintained their size below LCST, even after removal of the harsh (high salt or pH) conditions used to create them. Taken together, the ability to control aggregate sizes and use of crosslinking to maintain stability holds excellent potential for use in biological delivery systems.

The Sun, neutrinos and Super-Kamiokande.

In the standard model of elementary particle physics neutrinos are massless, and therefore the actuality of finite neutrino mass indicates a theory beyond the standard model. The Sun produces abundant neutrinos due to nuclear fusion reactions. A pioneering experiment in the early '70s detected neutrinos from the Sun, but found that the observed flux was smaller than expected, which was then called the missing solar neutrino problem. Tremendous efforts were made both experimentally and theoretically to solve this problem. In 2001, almost 30 years after the first indication, data from Super-Kamiokande in Japan and SNO in Canada together provided evidence that neutrino oscillation effectively converts the solar (electron) neutrinos to non-electron type neutrinos. Neutrino oscillation can occur only for those neutrinos with finite neutrino mass.

First benchmarking of the BIANCA model for cell survival prediction in a clinical hadron therapy scenario.

In the framework of RBE modelling for hadron therapy, the BIANCA biophysical model was extended to O-ions and was used to construct a radiobiological database describing the survival of V79 cells as a function of ion type (1 ⩽ Z ⩽ 8) and energy. This database allowed performing RBE predictions in very good agreement with experimental data. A method was then developed to construct analogous databases for different cell lines, starting from the V79 database as a reference. Following interface to the FLUKA Monte Carlo radiation transport code, BIANCA was then applied for the first time to predict cell survival in a typical patient treatment scenario, consisting of two opposing fields of range-equivalent protons or C-ions. The model predictions were found to be in good agreement with CHO cell survival data obtained at the Heidelberg ion-beam therapy (HIT) centre, as well as predictions performed by the local effect model (version LEM IV). This work shows that BIANCA can be used to predict cell survival and RBE not only for V79 and AG01522 cells, as shown previously, but also, in principle, for any cell line of interest. Furthermore, following interface to a transport code like FLUKA, BIANCA can provide predictions of 3D biological dose distributions for hadron therapy treatments, thus laying the foundations for future applications in clinics.

Quantum critical behaviour at the many-body localization transition.

Phase transitions are driven by collective fluctuations of a system's constituents that emerge at a critical point1. This mechanism has been extensively explored for classical and quantum systems in equilibrium, whose critical behaviour is described by the general theory of phase transitions. Recently, however, fundamentally distinct phase transitions have been discovered for out-of-equilibrium quantum systems, which can exhibit critical behaviour that defies this description and is not well understood1. A paradigmatic example is the many-body localization (MBL) transition, which marks the breakdown of thermalization in an isolated quantum many-body system as its disorder increases beyond a critical value2-11. Characterizing quantum critical behaviour in an MBL system requires probing its entanglement over space and time4,5,7, which has proved experimentally challenging owing to stringent requirements on quantum state preparation and system isolation. Here we observe quantum critical behaviour at the MBL transition in a disordered Bose-Hubbard system and characterize its entanglement via its multi-point quantum correlations. We observe the emergence of strong correlations, accompanied by the onset of anomalous diffusive transport throughout the system, and verify their critical nature by measuring their dependence on the system size. The correlations extend to high orders in the quantum critical regime and appear to form via a sparse network of many-body resonances that spans the entire system12,13. Our results connect the macroscopic phenomenology of the transition to the system's microscopic structure of quantum correlations, and they provide an essential step towards understanding criticality and universality in non-equilibrium systems1,7,13.

X-Ray Fluorescence Computed Tomography Induced by Photon, Electron, and Proton Beams.

X-ray fluorescence CT (XFCT) has shown promise for molecular imaging of gold nanoparticles. To date, XFCT has been induced by kilovoltage photon beams due to the high photoelectric interaction probability. We compare K-shell and L-shell XFCT induced by photon, electron, and proton beams for two phantom sizes. A 2.5 and 5.0-cm diameter phantom with four 5 mm and 10 mm vials, respectively, with gold-solutions of 0.1%-2% by weight were built in TOPAS, a GEANT4-based Monte Carlo simulation tool. The 2.5-cm phantom was imaged with XFCT induced by beams of 7.45×104 81 keV- and 5 MeV-photons, 220 kVp- and 6 MV-photons, 10 MeV- and 100 MeV-electrons, and 100 MeV- and 250 MeV-protons. The doses between each phantom size were equal. First-generation CT geometry with 0.5 mm × 0.5 mm pencil beams with 0.5 mm-translation and 2°-rotation steps over each phantom was modeled. The scattered x-rays were detected on an idealized spherical detector from which the K-shell and L-shell fluorescent x-rays were extracted in 0.5 keV and 0.2 keV bins. XFCT images were generated using iterative reconstruction algorithms. The highest gold sensitivity was seen in the 81 keV-photon K-shell and L-shell images (0.004% and 0.007%) of the 5.0 cm-phantom at 30 mGy. For the 2.5 cm-phantom, the detection limits were 0.006%, 0.62%, and 0.28% for 81 keV-photon K-shell, 100 MeV-electron K-shell, and 100 MeV-proton L-shell images, respectively. The mean imaging dose was approximately 2-3 orders of magnitude higher in electron- and proton-XFCT compared to 81keV-photon XFCT. Our MC study demonstrates that the small-object XFCT imaging achieves the best performance when induced with kilovoltage-photon beams. Due to high imaging doses, electron- and proton-induced XFCT might be feasible for guiding nanoparticle-enhanced charged-particle radiotherapy.

Alterations in synaptic density and myelination in response to exposure to high-energy charged particles.

High-energy charged particles are considered particularly hazardous components of the space radiation environment. Such particles include fully ionized energetic nuclei of helium, silicon, and oxygen, among others. Exposure to charged particles causes reactive oxygen species production, which has been shown to result in neuronal dysfunction and myelin degeneration. Here we demonstrate that mice exposed to high-energy charged particles exhibited alterations in dendritic spine density in the hippocampus, with a significant decrease of thin spines in mice exposed to helium, oxygen, and silicon, compared to sham-irradiated controls. Electron microscopy confirmed these findings and revealed a significant decrease in overall synapse density and in nonperforated synapse density, with helium and silicon exhibiting more detrimental effects than oxygen. Degeneration of myelin was also evident in exposed mice with significant changes in the percentage of myelinated axons and g-ratios. Our data demonstrate that exposure to all types of high-energy charged particles have a detrimental effect, with helium and silicon having more synaptotoxic effects than oxygen. These results have important implications for the integrity of the central nervous system and the cognitive health of astronauts after prolonged periods of space exploration.