Pathogenetic aspects of alcoholic encephalopathy treatment

Alcohol is considered to be the most common exogenous toxins, causing encephalopathy. The defeat of almost all parts of the nervous system should be assigned to the special features of ethanol. Neurophysiological mechanisms of development of substance dependence are based in the stem and limbic structures of the brain that are involved in ensuring the regulation of emotional state, mood, motivation sphere, psychophysical tone of human behavior in general and its adaptation to the environment. Stress or disruption of the normal functioning of these structures can lead to the formation of abstinence syndrome, affective disorders in remission and craving for alcohol. Dopaminergic and opioid (endorphin) system play an important role in the genesis of various mental and motor disorders. In some way alcohol dependence can be regarded as an endorfinodefitsitnoe disease with a pathogenetic point of view. Activating of opioidereal system by trans-cranial electrical stimulation promotes the restoration of disturbed emotional, cognitive and autonomic functions, reduces craving for alcohol and in that way increases the effectiveness of rehabilitation treatmen

Superposition effect and clan structure in forward-backward multiplicity correlations

The main purpose of this paper is to discuss the link between forward-backward multiplicity correlations properties and the shape of the corresponding final charged particle multiplicity distribution in various classes of events in different collisions. It is shown that the same mechanism which explains the shoulder effect and the H_n vs. n oscillations in charged particle multiplicity distributions, i.e., the weighted superposition of different classes of events with negative binomial properties, reproduces within experimental errors also the forward-backward multiplicity correlation strength in e+e- annihilation at LEP energy and allows interesting predictions for pp collisions in the TeV energy region, to be tested at LHC, for instance with the ALICE detector. We limit ourselves at present to study substructures properties in hadron-hadron collisions and e+e- annihilation; they are examined as ancillary examples in the conviction that their understanding might be relevant also in other more complex cases.Comment: 16 page

Effective Electromagnetic Lagrangian at Finite Temperature and Density in the Electroweak Model

Using the exact propagators in a constant magnetic field, the effective electromagnetic Lagrangian at finite temperature and density is calculated to all orders in the field strength B within the framework of the complete electroweak model, in the weak coupling limit. The partition function and free energy are obtained explicitly and the finite temperature effective coupling is derived in closed form. Some implications of this result, potentially interesting to astrophysics and cosmology, are discussed.Comment: 14 pages, Revtex

A search for ferromagnetism in transition-metal-doped piezoelectric ZnO

We present the results of a computational study of ZnO in the presence of Co and Mn substitutional impurities. The goal of our work is to identify potential ferromagnetic ground states within the (Zn,Co)O or (Zn,Mn)O material systems that are also good candidates for piezoelectricity. We find that, in contrast to previous results, robust ferromagnetism is not obtained by substitution of Co or Mn on the Zn site, unless additional carriers (holes) are also incorporated. We propose a practical scheme for achieving such $p$-type doping in ZnO

IL11 activates pancreatic stellate cells and causes pancreatic inflammation, fibrosis and atrophy in a mouse model of pancreatitis

Interleukin-11 (IL11) is important for fibrosis and inflammation, but its role in the pancreas is unclear. In pancreatitis, fibrosis, inflammation and organ dysfunction are associated with pancreatic stellate cell (PSC)-to-myofibroblast transformation. Here, we show that IL11 stimulation of PSCs, which specifically express IL11RA in the pancreas, results in transient STAT3 phosphorylation, sustained ERK activation and PSC activation. In contrast, IL6 stimulation of PSCs caused sustained STAT3 phosphorylation but did not result in ERK activation or PSC transformation. Pancreatitis factors, including TGFβ, CTGF and PDGF, induced IL11 secretion from PSCs and a neutralising IL11RA antibody prevented PSC activation by these stimuli. This revealed an important ERK-dependent role for autocrine IL11 activity in PSCs. In mice, IL11 was increased in the pancreas after pancreatic duct ligation, and in humans, IL11 and IL11RA levels were elevated in chronic pancreatitis. Following pancreatic duct ligation, administration of anti-IL11RA to mice reduced pathologic (ERK, STAT, NF-κB) signalling, pancreatic atrophy, fibrosis and pro-inflammatory cytokine (TNFα, IL6 and IL1β) levels. This is the first description of IL11-mediated activation of PSCs, and the data suggest IL11 as a stromal therapeutic target in pancreatitis

Targeting endogenous kidney regeneration using anti-IL11 therapy in acute and chronic models of kidney disease

The kidney has large regenerative capacity, but this is compromised when kidney damage is excessive and renal tubular epithelial cells (TECs) undergo SNAI1-driven growth arrest. Here we investigate the role of IL11 in TECs, kidney injury and renal repair. IL11 stimulation of TECs induces ERK- and p90RSK-mediated GSK3β inactivation, SNAI1 upregulation and pro-inflammatory gene expression. Mice with acute kidney injury upregulate IL11 in TECs leading to SNAI1 expression and kidney dysfunction, which is not seen in Il11 deleted mice or in mice administered a neutralizing IL11 antibody in either preemptive or treatment modes. In acute kidney injury, anti-TGFβ reduces renal fibrosis but exacerbates inflammation and tubule damage whereas anti-IL11 reduces all pathologies. Mice with TEC-specific deletion of Il11ra1 have reduced pathogenic signaling and are protected from renal injury-induced inflammation, fibrosis, and failure. In a model of chronic kidney disease, anti-IL11 therapy promotes TEC proliferation and parenchymal regeneration, reverses fibroinflammation and restores renal mass and function. These data highlight IL11-induced mesenchymal transition of injured TECs as an important renal pathology and suggest IL11 as a therapeutic target for restoring stalled endogenous regeneration in the diseased kidney

Thermal Casimir effect in ideal metal rectangular boxes

The thermal Casimir effect in ideal metal rectangular boxes is considered using the method of zeta functional regularization. The renormalization procedure is suggested which provides the finite expression for the Casimir free energy in any restricted quantization volume. This expression satisfies the classical limit at high temperature and leads to zero thermal Casimir force for systems with infinite characteristic dimensions. In the case of two parallel ideal metal planes the results, as derived previously using thermal quantum field theory in Matsubara formulation and other methods, are reproduced starting from the obtained expression. It is shown that for rectangular boxes the temperature-dependent contribution to the electromagnetic Casimir force can be both positive and negative depending on side lengths. The numerical computations of the scalar and electromagnetic Casimir free energy and force are performed for cubesComment: 10 pages, 4 figures, to appear in Europ. Phys. J.

Search for sterile neutrino oscillation using RENO and NEOS data

We present a reactor model independent search for sterile neutrino oscillation using 2\,509\,days of RENO near detector data and 180 days of NEOS data. The reactor related systematic uncertainties are significantly suppressed as both detectors are located at the same reactor complex of Hanbit Nuclear Power Plant. The search is performed by electron antineutrino\,($\overline{\nu}_e$) disappearance between six reactors and two detectors with baselines of 294\,m\,(RENO) and 24\,m\,(NEOS). A spectral comparison of the NEOS prompt-energy spectrum with a no-oscillation prediction from the RENO measurement can explore reactor $\overline{\nu}_e$ oscillations to sterile neutrino. Based on the comparison, we obtain a 95\% C.L. excluded region of $0.1<|\Delta m_{41}^2|<7$\,eV$^2$. We also obtain a 68\% C.L. allowed region with the best fit of $|\Delta m_{41}^2|=2.41\,\pm\,0.03\,$\,eV$^2$ and $\sin^2 2\theta_{14}$=0.08$\,\pm\,$0.03 with a p-value of 8.2\%. Comparisons of obtained reactor antineutrino spectra at reactor sources are made among RENO, NEOS, and Daya Bay to find a possible spectral variation.Comment: 6 pages, 5 figures: This manuscript has been significantly revised by the joint reanalysis by RENO and NEOS Collaborations. (In the previous edition, the RENO collaboration used publicly available NEOS data to evaluate the expected neutrino spectrum at NEOS.

Prediction of major depressive disorder following beta-blocker therapy in patients with cardiovascular diseases

Incident depression has been reported to be associated with poor prognosis in patients with cardiovascular disease (CVD), which might be associated with beta-blocker therapy. Because early detection and intervention can alleviate the severity of depression, we aimed to develop a machine learning (ML) model predicting the onset of major depressive disorder (MDD). A model based on L1 regularized logistic regression was trained against the South Korean nationwide administrative claims database to identify risk factors for the incident MDD after beta-blocker therapy in patients with CVD. We identified 50,397 patients initiating beta-blockers for CVD, with 774 patients developing MDD within 365 days after initiating beta-blocker therapy. An area under the receiver operating characteristic curve (AUC) of 0.74 was achieved. A history of non-selective beta-blockers and factors related to anxiety disorder, sleeping problems, and other chronic diseases were the most strong predictors. AUCs of 0.62–0.71 were achieved in the external validation conducted on six independent electronic health records and claims databases in the USA and South Korea. In conclusion, an ML model that identifies patients at high-risk for incident MDD was developed. Application of ML to identify susceptible patients for adverse events of treatment may serve as an important approach for personalized medicine