Based on CDFT calculations, we study new features of surface electrostatic force (SEF) between two face-to-face overall neutral surfaces, each of which is comprised of atomic scale strip shape charge ...distribution and is immersed in +2:−1 electrolyte. Dielectric constant of near surface fluid is lower than that of distant fluid. Ion valence and dielectric constant heterogeneity effects are reflected in the following aspects. (i) For asymmetrical configuration of the strip shape charge distribution, if the coexistence bulk mole concentration
is high like
, one repulsion peak of the SEF appears at approximately two times the ion diameter and the peak height increases obviously with the ion valence and the strip shape domain width
; however, for low
value, like
, the ion valence almost does not cause any effect on the SEF shape and strength at small distances except that the higher valence ion causes a higher decaying rate of the SEF with the surface separation. (ii) For the case of the asymmetrical configuration and bivalent ion, strength of the small distance attractive SEF always reduces with the
value, and is positively correlated with the
value except when the
value is high and the domain surface charge strength
is low. (iii) The symmetrical strip shape charge distribution is an efficient way in inducing the attractive SEF in presence of bivalence ions even if the
value is low down to
; the attraction strength is positively correlated with the
value. (iv) The ion adsorption, playing a key role in influencing the SEF for the present overall neutral two-surface system, generally increases with the
value, and far higher than that relevant to two similarly charged surfaces with equal
value. (v) The lower surface fluid dielectric constant accords both the force and potential curves with new features like alternative mode of attraction and repulsion even in low bulk concentration, big strength in comparison with the average thermal energy, and large insensitivity to the surface charge distribution patterns and ion valence.
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Effects of relative arrangement of discrete surface charges and solvent granularity on the effective potential of mean force (EPMF) are studied. Main conclusions are summarized as follows: (i) With ...consideration of the solvent granularity the EPMF always becomes more attractive, and one like charge attraction always appears even if the counter-ion is univalent. Moreover, with transition from asymmetrical to symmetrical surface charge distributions of similar surface charge compactness, attraction strength of the EPMF always rises; with increase of the counter-ion valence the EPMF attraction strength rises unless the surface charge configuration is asymmetrical and less compact and the counter-ion high-valence. (ii) Whether the surface charge distribution is asymmetrical or symmetrical, the EPMF tends to become more attractive in the compactness charge configuration than in the non-compactness charge configuration. (iii) The correlation between the EPMF attraction strength and bulk mole concentration can be positive or negative depending on the counter-ion valence, compactness of surface charge distribution, and average surface charge strength. Highly taking value of each of the three quantities helps in inducing one negative correlation and vice versa. (iv) Co-ion size has almost no influence on the EPMF, increasing or decreasing the counter-ion size inhibits or enhances the solvent granularity effect.
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The present study is performed on the way and mechanism by which ion size changes curves of differential electrical capacitance (C d) vs surface charge strength |σ| and energy storage density E vs ...applied voltage U of an electrical double layer (EDL) formed inside a cylindrical pore electrode. Several valuable findings are made. (i) The C d–|σ| curve generally rises as a result of solvent granularity, which combined with simultaneous higher ion (whether counter- or co-ion) size and higher electrolyte bulk concentration, causing obvious overall morphology change of the curve. (ii) Smaller counterion always raises greatly both C d and E, whereas the co-ion size only has a very weak influence on C d over a range of |σ| around zero, and has almost no influence on E. (iii) One higher counterion electrical valence helps in raising both C d and E, but the electrolyte bulk concentration has no obvious influence on both C d and E in the presence of a higher valence counterion. (iv) The change rate of E with σ exhibits an inflection point at an appropriately large value of |σ| if the counterion valence is not too high (for example, bivalence), and simultaneously the counterion diameter increases. The above findings and relevant mechanisms can be explained reasonably by the changes of ions local distributions in the EDL and their adsorption capacities.
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IJS, KILJ, NUK, PNG, UL, UM
Scarcity of annotated images hampers the building of automated solution for reliable COVID-19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein present a ...label-free approach for segmenting COVID-19 lesions in CT via voxel-level anomaly modeling that mines out the relevant knowledge from normal CT lung scans. Our modeling is inspired by the observation that the parts of tracheae and vessels, which lay in the high-intensity range where lesions belong to, exhibit strong patterns. To facilitate the learning of such patterns at a voxel level, we synthesize 'lesions' using a set of simple operations and insert the synthesized 'lesions' into normal CT lung scans to form training pairs, from which we learn a normalcy-recognizing network (NormNet) that recognizes normal tissues and separate them from possible COVID-19 lesions. Our experiments on three different public datasets validate the effectiveness of NormNet, which conspicuously outperforms a variety of unsupervised anomaly detection (UAD) methods.
1. P-glycoprotein (P-gp/MDR1), one of the most clinically important transmembrane transporters in humans, is encoded by the ABCB1/MDR1 gene. Recent insights into the structural features of P-gp/MDR1 ...enable a re-evaluation of the biochemical evidence on the binding and transport of drugs by P-gp/MDR1.
2. P-gp/MDR1 is found in various human tissues in addition to being expressed in tumours cells. It is located on the apical surface of intestinal epithelial cells, bile canaliculi, renal tubular cells, and placenta and the luminal surface of capillary endothelial cells in the brain and testes.
3. P-gp/MDR1 confers a multi-drug resistance (MDR) phenotype to cancer cells that have developed resistance to chemotherapy drugs. P-gp/MDR1 activity is also of great clinical importance in non-cancer-related drug therapy due to its wide-ranging effects on the absorption and excretion of a variety of drugs.
4. P-gp/MDR1 excretes xenobiotics such as cytotoxic compounds into the gastrointestinal tract, bile and urine. It also participates in the function of the blood-brain barrier.
5. One of the most interesting characteristics of P-gp/MDR1 is that its many substrates vary greatly in their structure and functionality, ranging from small molecules such as organic cations, carbohydrates, amino acids and some antibiotics to macromolecules such as polysaccharides and proteins.
6. Quite a number of single nucleotide polymorphisms have been found for the MDR1 gene. These single nucleotide polymorphisms are associated with altered oral bioavailability of P-gp/MDR1 substrates, drug resistance, and a susceptibility to some human diseases.
7. Altered P-gp/MDR1 activity due to induction and/or inhibition can cause drug-drug interactions with altered drug pharmacokinetics and response.
8. Further studies are warranted to explore the physiological function and pharmacological role of P-gp/MDR1.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Abstract We investigated the effective interaction potential (EIP) between charged surfaces in solvent comprised of dipole dimer molecules added with a certain amount of ionic liquid. Using classical ...density functional theory, the EIP is calculated and decoupled into entropic and energy terms. Unlike the traditional Asakura–Oosawa (AO) depletion model, the present entropic term can be positive or negative, depending on the entropy change associated with solvent molecule migration from bulk into slit pore. This is determined by pore congestion and disruption of the bulk dipole network. The energy term is determined by the free energy associated with hard-core repulsion and electrostatic interactions between surface charges, ion charges, and polarized charges carried by the dipole dimer molecules. The calculations in this article clearly demonstrate the variability of the entropy term, which contrasts sharply with the traditional AO depletion model, and the corrective effects of electrostatic and spatial hindrance interactions on the total EIP; we revealed several non-monotonic behaviors of the EIP and its entropic and energy terms concerning solvent bulk concentration and solvent molecule dipole moment; additionally, we demonstrated the promoting effect of dipolar solvent on the emergence of like-charge attraction, even in 1:1 electrolyte solutions. The microscopic origin of the aforementioned phenomena was analyzed to be due to the non-monotonic change of dipolar solvent adsorption with dipole moment under conditions of low solution dielectric constant. The present findings offer novel approaches and molecular-level guidance for regulating the EIP. This insight has implications for understanding fundamental processes in various fields, including biomolecule-ligand binding, activation energy barriers, ion tunneling transport, as well as the formation of hierarchical structures, such as mesophases, micro-, and nanostructures, and beyond.
•A novel loss function for multi-organ segmentation.•Handling both input and output class imbalance.•Smoothing dice (or similar discrete) loss function(s).•Preventing potential gradient ...vanishing/exploding problem caused by Dice or similar loss functions.•First deep network for PET multi-organ segmentation.•Tested on various data-sets: MRI, PET, and CT.
Simultaneous segmentation of multiple organs from different medical imaging modalities is a crucial task as it can be utilized for computer-aided diagnosis, computer-assisted surgery, and therapy planning. Thanks to the recent advances in deep learning, several deep neural networks for medical image segmentation have been introduced successfully for this purpose. In this paper, we focus on learning a deep multi-organ segmentation network that labels voxels. In particular, we examine the critical choice of a loss function in order to handle the notorious imbalance problem that plagues both the input and output of a learning model. The input imbalance refers to the class-imbalance in the input training samples (i.e., small foreground objects embedded in an abundance of background voxels, as well as organs of varying sizes). The output imbalance refers to the imbalance between the false positives and false negatives of the inference model. In order to tackle both types of imbalance during training and inference, we introduce a new curriculum learning based loss function. Specifically, we leverage Dice similarity coefficient to deter model parameters from being held at bad local minima and at the same time gradually learn better model parameters by penalizing for false positives/negatives using a cross entropy term. We evaluated the proposed loss function on three datasets: whole body positron emission tomography (PET) scans with 5 target organs, magnetic resonance imaging (MRI) prostate scans, and ultrasound echocardigraphy images with a single target organ i.e., left ventricular. We show that a simple network architecture with the proposed integrative loss function can outperform state-of-the-art methods and results of the competing methods can be improved when our proposed loss is used.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Using Monte Carlo results as a reference, a classical density functional theory (
CDFT
) is shown to reliably predict the forces between two heterogeneously charged surfaces immersed in an ...electrolyte solution, whereas the Poisson–Boltzmann (
PB
) theory is demonstrated to deteriorate obviously for the same system even if the system parameters considered fall within the validity range of the
PB
theory in the homogeneously charged surfaces. By applying the tested
CDFT
, we study the effective electrostatic potential of mean force (
EPMF
) between two face–face planar and hard surfaces of zero net charge on which positive and negative charges are separated and considered to present as discontinuous spots on the inside edges of the two surfaces. Main conclusions are summarized as follows: (i) strength of the
EPMF
in the surface charge separation case is very sensitively and positively correlated with the surface charge separation level and valency of the salt ion. Particularly, the charge separation level and the salt ion valency have a synergistic effect, which makes high limit of the
EPMF
strength in the surface charge separation case significantly go beyond that of the ideal homogeneously charged surface counterpart at average surface charge density similar to the average surface positive or negative charge density in the charge separation case. (ii) The surface charge distribution patterns mainly influence sign of the
EPMF
: symmetrical and asymmetrical patterns induce repulsive and attractive (at small distances)
EPMF
, respectively; but with low valency salt ions and low charge separation level the opposite may be the case. With simultaneous presence of both higher valency cation and anion, the
EPMF
can be repulsive at intermediate distances for asymmetrical patterns. (iii) Salt ion size has a significant impact, which makes the
EPMF
tend to become more and more repulsive with the ion diameter regardless of the surface charge distribution patterns and the valency of the salt ion; whereas if the 1:1 type electrolyte and the symmetrical patterns are considered, then the opposite may be the case. All of these findings can be explained self-consistently from several perspectives: an excess adsorption of the salt ions (induced by the surface charge separation) serving to raise the osmotic pressure between the plates, configuration fine-tuning in the thinner ion adsorption layer driven by the energy decrease principle, direct Coulombic interactions operating between charged objects on the two face-to-face plates involved, and net charge strength in the ion adsorption layer responsible for the net electrostatic repulsion.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The three central phenomena of cuprate (copper oxide) superconductors are linked by a common doping level p*-at which the enigmatic pseudogap phase ends and the resistivity exhibits an anomalous ...linear dependence on temperature, and around which the superconducting phase forms a dome-shaped area in the phase diagram
. However, the fundamental nature of p* remains unclear, in particular regarding whether it marks a true quantum phase transition. Here we measure the specific heat C of the cuprates Eu-LSCO and Nd-LSCO at low temperature in magnetic fields large enough to suppress superconductivity, over a wide doping range
that includes p*. As a function of doping, we find that C
/T is strongly peaked at p* (where C
is the electronic contribution to C) and exhibits a log(1/T) dependence as temperature T tends to zero. These are the classic thermodynamic signatures of a quantum critical point
, as observed in heavy-fermion
and iron-based
superconductors at the point where their antiferromagnetic phase comes to an end. We conclude that the pseudogap phase of cuprates ends at a quantum critical point, the associated fluctuations of which are probably involved in d-wave pairing and the anomalous scattering of charge carriers.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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