An extension of Gauss's principle of least constraint

International audienceGauss's principle of least constraint is reformulated to cover cases in which the constraint forces may do positive or negative work on a system in a virtual displacement. This is needed to deal conveniently with cases in which, for example, friction is significant

The peroxisome counteracts oxidative stresses by suppressing catalase import via Pex14 phosphorylation

Most of peroxisomal matrix proteins including a hydrogen peroxide (H2O2)-decomposing enzyme, catalase, are imported in a peroxisome-targeting signal type-1 (PTS1)-dependent manner. However, little is known about regulation of the membrane-bound protein import machinery. Here, we report that Pex14, a central component of the protein translocation complex in peroxisomal membrane, is phosphorylated in response to oxidative stresses such as H2O2 in mammalian cells. The H2O2-induced phosphorylation of Pex14 at Ser232 suppresses peroxisomal import of catalase in vivo and selectively impairs in vitro the interaction of catalase with the Pex14-Pex5 complex. A phosphomimetic mutant Pex14-S232D elevates the level of cytosolic catalase, but not canonical PTS1-proteins, conferring higher cell resistance to H2O2. We thus suggest that the H2O2-induced phosphorylation of Pex14 spatiotemporally regulates peroxisomal import of catalase, functioning in counteracting action against oxidative stress by the increase of cytosolic catalase

Morphological study of the arterial supply to the menisci in pigs with special reference to creating meniscus injury model

Background: Some reports have used pigs to establish models of meniscus injury. However, accurate information on the origin, course, and access of the arteries supplying the menisci remains unclear. This information is important to avoid damaging vital arteries when creating the meniscus injury model. Materials and methods: In this study, fetal and adult pigs were employed to investigate the arterial supply of the menisci in pigs using gross anatomical and histological methods. Results: Macro-anatomically, the anterior horn, body, and posterior horn of the medial meniscus were found to be supplied by the medial superior genicular artery, medial inferior genicular artery, and posterior middle genicular artery. The anterior and posterior horns of the lateral meniscus were supplied by the cranial tibial recurrent artery and the middle genicular artery, respectively. Anastomosis was observed in some cases, but appeared to be infrequent and too thin to expect the anastomotic branches to provide adequate blood flow. The histological examination showed that the arteries entered the meniscus along the tie-fiber. The access process of the artery was the same irrespective of whether it was in fetal or mature pigs, the medial or lateral meniscus, or the anterior horn or body or posterior horn. The medial inferior genicular artery ran along the medial meniscus in the circumferential direction. Therefore, the clinical longitudinal incision should take into account the characteristics of the vessel course in order to protect the blood vessels from damage. Conclusions: Based on the results of this study, the protocol for creating a pig meniscus injury model should be reconsidered

Gyrification patterns in first-episode, drug-naïve major depression: Associations with plasma levels of brain-derived neurotrophic factor and psychiatric symptoms

Background and objectivesCortical structural changes in major depressive disorder (MDD) are usually studied using a voxel-based morphometry approach to delineate the cortical gray matter volume. Among cortical structures, gyrification patterns are considered a relatively stable indicator. In this study, we investigated differences in gyrification patterns between MDD patients and healthy controls (HCs) and explored the association of gyrification patterns with plasma brain-derived neurotrophic factor (BDNF) levels and depressive symptoms in MDD patients.MethodsWe evaluated 79 MDD patients and 94 HCs and assessed depression severity in the patients using the 17-item Hamilton Depression Rating Scale (HAM-D). Blood samples of both groups were collected to measure plasma BDNF levels. Magnetic resonance imaging (MRI) data were obtained using three-dimensional fast-spoiled gradient-recalled acquisition. Differences in plasma BDNF levels between groups were examined using the Mann–Whitney U test. Principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to investigate the gyrification patterns which were significantly different between the groups, i.e., those with variable importance in projection (VIP) scores of >1.5 and p-value < 0.05 in multiple regression analyses adjusted for age and sex. Finally, multiple regression analysis was performed on the selected gyrification patterns to examine their association with BDNF levels in the two groups and HAM-D in the patients.ResultsThere were no significant differences in plasma BDNF levels between the groups. We found that 108 (71.0%) of 152 total local gyrification indices were MDD < HC. We identified 10 disease-differentiating factors based on critical gyrification features (VIP > 1.5 and p-value adjusted for age and sex < 0.05). However, we found no significant correlations between the 10 gyrification patterns and plasma BDNF levels and no interaction with group. Moreover, no significant correlations were observed between the local gyrification indices and HAM-D total scores.ConclusionThese results suggest that abnormal early cortical neurodevelopment may mediate vulnerability to MDD, independent of plasma BDNF levels and depressive symptoms

The estimation of parameters in time-dependent transport problems: Dynamic programming and associative memories

AbstractTime-dependent radiation and energy transport problems are important in atmospheric science, medicine, biochemistry, and other areas. To determine external energy fields, direct problems (in which parameters are known) can be solved computationally by numerical integration followed by the numerical inversion of Laplace transforms. On the other hand, this paper treats inverse problems of estimating transport parameters on the basis of external observations of radiant intensity. These problems are approached using associative memory neural networks whose associated least squares problem is solved using a new dynamic programming algorithm. The quality of the estimates in the presence of noise in measurements is studied