Conserved roles of Sam50 and metaxins in VDAC biogenesis

Voltage-dependent anion-selective channel (VDAC) is a β-barrel protein in the outer mitochondrial membrane that is necessary for metabolite exchange with the cytosol and is proposed to be involved in certain forms of apoptosis. We studied the biogenesis of VDAC in human mitochondria by depleting the components of the mitochondrial import machinery by using RNA interference. Here, we show the importance of the translocase of the outer mitochondrial membrane (TOM) complex in the import of the VDAC precursor. The deletion of Sam50, the central component of the sorting and assembly machinery (SAM), led to both a strong defect in the assembly of VDAC and a reduction in the steady-state level of VDAC. Metaxin 2-depleted mitochondria had reduced levels of metaxin 1 and were deficient in import and assembly of VDAC and Tom40, but not of three matrix-targeted precursors. We also observed a reduction in the levels of metaxin 1 and metaxin 2 in Sam50-depleted mitochondria, implying a connection between these three proteins, although Sam50 and metaxins seemed to be in different complexes. We conclude that the pathway of VDAC biogenesis in human mitochondria involves the TOM complex, Sam50 and metaxins, and that it is evolutionarily conserved

Increase in degraded collagen type II in synovial fluid early in the rabbit meniscectomy model of osteoarthritis

SummaryObjectiveThe objective of this study was to determine whether collagen type II breakdown products in synovial fluid (SF), detected by an enzyme-linked immunoassay, represent a useful marker for early events in osteoarthritis (OA) in the rabbit medial meniscectomy model.DesignComplete medial meniscectomy was performed on the right knee joints of 32 rabbits. Balanced groups of rabbits were then sacrificed at 2, 4, 8, and 12 weeks post-surgery. An additional 8 unoperated and 11 sham-operated animals served as controls. SF lavages were performed on right and left knee joints of the same animals at sacrifice. The proteolytic epitope of type II collagen was monitored using an enzyme-linked immunoassay.ResultsMacroscopically visible surface fibrillation and focal erosions appeared as early as 2 weeks after meniscectomy in the femorotibial joint (P<0.01). OA developed gradually during the later observation period, and then predominantly on the medial tibial plateau and medial femur. Significant histological alterations in cartilage, including a loss of proteoglycans, surface irregularities, and clefts, were detected at 2 weeks after meniscectomy (P<0.01). Collagen type II epitope levels in SF lavage samples were elevated peaking at 2 weeks after meniscectomy (P<0.02). Levels decreased at later time points, but they were still raised at 12 weeks (P≤0.05). Highly significant correlations were found between the SF collagen type II epitope levels and the macroscopic and microscopic scoring results (Spearman rho correlation coefficient, macroscopy—collagen type II epitope r=0.222, P=0.025; microscopy—collagen type II epitope r=0.436, P≤0.01).ConclusionIn this rabbit model of medial meniscectomy, levels of type II collagen fragments in SF appear to provide a useful marker of the early degenerative changes

No differences in value-based decision-making due to use of oral contraceptives

Fluctuating ovarian hormones have been shown to affect decision-making processes in women. While emerging evidence suggests effects of endogenous ovarian hormones such as estradiol and progesterone on value-based decision-making in women, the impact of exogenous synthetic hormones, as in most oral contraceptives, is not clear. In a between-subjects design, we assessed measures of value-based decision-making in three groups of women aged 18 to 29 years, during (1) active oral contraceptive intake (N = 22), (2) the early follicular phase of the natural menstrual cycle (N = 20), and (3) the periovulatory phase of the natural menstrual cycle (N = 20). Estradiol, progesterone, testosterone, and sex-hormone binding globulin levels were assessed in all groups via blood samples. We used a test battery which measured different facets of value-based decision-making: delay discounting, risk-aversion, risk-seeking, and loss aversion. While hormonal levels did show the expected patterns for the three groups, there were no differences in value-based decision-making parameters. Consequently, Bayes factors showed conclusive evidence in support of the null hypothesis. We conclude that women on oral contraceptives show no differences in value-based decision-making compared to the early follicular and periovulatory natural menstrual cycle phases. Copyright © 2022 Lewis, Kimmig, Kroemer, Pooseh, Smolka, Sacher and Derntl

Probabilistic (logic) programming concepts

A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions. Each of these languages employs its own probabilistic primitives, and comes with a particular syntax, semantics and inference procedure. This makes it hard to understand the underlying programming concepts and appreciate the differences between the different languages. To obtain a better understanding of probabilistic programming, we identify a number of core programming concepts underlying the primitives used by various probabilistic languages, discuss the execution mechanisms that they require and use these to position and survey state-of-the-art probabilistic languages and their implementation. While doing so, we focus on probabilistic extensions of logic programming languages such as Prolog, which have been considered for over 20 years

Generating Random Logic Programs Using Constraint Programming

Testing algorithms across a wide range of problem instances is crucial to ensure the validity of any claim about one algorithm's superiority over another. However, when it comes to inference algorithms for probabilistic logic programs, experimental evaluations are limited to only a few programs. Existing methods to generate random logic programs are limited to propositional programs and often impose stringent syntactic restrictions. We present a novel approach to generating random logic programs and random probabilistic logic programs using constraint programming, introducing a new constraint to control the independence structure of the underlying probability distribution. We also provide a combinatorial argument for the correctness of the model, show how the model scales with parameter values, and use the model to compare probabilistic inference algorithms across a range of synthetic problems. Our model allows inference algorithm developers to evaluate and compare the algorithms across a wide range of instances, providing a detailed picture of their (comparative) strengths and weaknesses.Comment: This is an extended version of the paper published in CP 202