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Objective To assess the efficacy of selective salpingography (SSG) with additional tubal catheterization (TC) among infertile patients diagnosed with PTO and analysis of reproductive outcome. Study Design Retrospective cohort study. Results Of a total of 399 tubes with confirmed proximal tubal occlusion, 383 successfully restored their patency resulting in 96 % technical success rate. Thirty-five percent of oviducts that had their patency restored was treated with SSG and 65% required additional TC. Reproductive outcomes at minimum 12 months following the treatment were collected by a telephone survey. 21/221 women were lost to follow up. Out of remaining 200 patients with at least one patent tube, 80 patients conceived which resulted in 40 % overall pregnancy rate. Conclusion Selective salpingography and tubal canalization offer patient-friendly, minimally invasive and cost-effective alternatives to tubal microsurgery and IVF-ET in women with tubal occlusion with very high technical success rate and promising clinical results which depend also on the complexity of couple infertility. Specific indications and limitations make a careful assessment of fallopian tubes and comprehensive evaluation of partners' reproductive situation prior to therapy an absolute requirement.

An increase in the intracellular Ca2+ level in neurons is one of the main steps in the memory formation cascade. The increase results from extracellular Ca2+ influx by activation of ionotropic glutamate receptors and release from intracellular stores by the stimulation of IP3 receptors (IP3Rs) via group I metabotropic glutamate receptors (mGluR1/5). Recent data indicate an additional mechanism resulting in Ca2+ influx into neurons, triggered by intracellular signals that are directly connected to the activation of group I mGluRs. This influx occurs through transient receptor potential (TRP) channels, which are permeable to Na+, K+ and, mainly, Ca2+. These channels are activated by increases in intracellular Ca2+, diacylglycerol (DAC) and inositol 1,4,5-triphosphate (IP3) level resulting from a group I mGluR activation. The aim of the present study was to investigate the participation of TRP channels, especially from TRPC and TRPV groups, in memory consolidation and reconsolidation and memory retrieval processes in a passive avoidance task in one-day old chicks. TRP channels were blocked by the injection of the unspecific channel modulators SKF 96365 (2.5 µl 30 µM/hemisphere) and 2-APB (2.5 µl 10 µM/hemisphere) directly into the intermediate medial mesopallium (IMM) region of the chick brain immediately after initial training or after a reminder. The inhibition of specific TRP channels (TRPV1, TRPV3 or TRPC3) was achieved by the application of selective antibodies. Our results demonstrate that the inhibition of TRP channels by the application of both modulators disrupted memory consolidation, resulting in permanent task amnesia. The inhibition of the TRPV1, TRPC3 and TRPV3 channels by specific antibodies resulted in similar amnesia. Moreover, the inhibition of TRP channels by SKF 96365 and 2-APB at different time points after initial training or after the reminder also resulted in amnesia, indicating the role of TRP channels in memory retrieval. The inhibition of calcium influx through these channels resulted in permanent memory disruption, which suggests that the calcium signal generated by TRP channels is crucial for memory formation and retrieval processes. For the first time, the important role of TRPV3 channels in memory formation was demonstrated.

Given an edge-weighted graph G with a set $$Q$$ of k terminals, a mimicking network is a graph with the same set of terminals that exactly preserves the size of minimum cut between any partition of the terminals. A natural question in the area of graph compression is to provide as small mimicking networks as possible for input graph G being either an arbitrary graph or coming from a specific graph class. We show an exponential lower bound for cut mimicking networks in planar graphs: there are edge-weighted planar graphs with k terminals that require $$2^{k-2}$$ edges in any mimicking network. This nearly matches an upper bound of $$\mathcal {O}(k 2^{2k})$$ of Krauthgamer and Rika (in: Khanna (ed) Proceedings of the twenty-fourth annual ACM-SIAM symposium on discrete algorithms, SODA 2013, New Orleans, 2013) and is in sharp contrast with the upper bounds of $$\mathcal {O}(k^2)$$ and $$\mathcal {O}(k^4)$$ under the assumption that all terminals lie on a single face (Goranci et al., in: Pruhs and Sohler (eds) 25th Annual European symposium on algorithms (ESA 2017), 2017, arXiv:1702.01136 ; Krauthgamer and Rika in Refined vertex sparsifiers of planar graphs, 2017, arXiv:1702.05951 ). As a side result we show a tight example for double-exponential upper bounds given by Hagerup et al. (J Comput Syst Sci 57(3):366–375, 1998), Khan and Raghavendra (Inf Process Lett 114(7):365–371, 2014), and Chambers and Eppstein (J Gr Algorithms Appl 17(3):201–220, 2013).

Arthritis is the second most commonly reported chronic condition and the leading cause of disability among older adults in the United States. Previous studies of aquatic-based interventions for arthritis have focused on physical benefits. In this study, some psychosocial benefits as well as physiological benefits are examined. The purpose of this study was to examine the perceived leisure satisfaction of participants who were involved in the Arthritis Foundation Aquatic Program in order to determine some factors that might be associated with persistence of participation in this program. Forty-nine subjects participated in the six-week program and completed the Leisure Satisfaction Measure (LSM) both at the beginning and at the end of the six weeks. There was no significant difference found for the overall scores of the LSM. However, there were significant mean differences at the 0.05 level found for three of the subscales on the LSM (ie, psychological, relaxation, and physiological), indicating that participating in the six-week aquatic exercise program increased the participants’ perceived leisure satisfaction levels in those three areas.

In this paper we study the Steiner tree problem over a dynamic set of terminals. We consider the model where we are given an $n$-vertex graph $G=(V,E,w)$ with positive real edge weights, and our goal is to maintain a tree which is a good approximation of the minimum Steiner tree spanning a terminal set $S \subseteq V$, which changes over time. The changes applied to the terminal set are either terminal additions (incremental scenario), terminal removals (decremental scenario), or both (fully dynamic scenario). Our task here is twofold. We want to support updates in sublinear $o(n)$ time, and keep the approximation factor of the algorithm as small as possible. We show that we can maintain a $(6+\varepsilon)$-approximate Steiner tree of a general graph in $\tilde{O}(\sqrt{n} \log D)$ time per terminal addition or removal. Here, $D$ denotes the stretch of the metric induced by $G$. For planar graphs we achieve the same running time and the approximation ratio of $(2+\varepsilon)$. Moreover, we show faster algorithms for incremental and decremental scenarios. Finally, we show that if we allow higher approximation ratio, even more efficient algorithms are possible. In particular we show a polylogarithmic time $(4+\varepsilon)$-approximate algorithm for planar graphs. One of the main building blocks of our algorithms are dynamic distance oracles for vertex-labeled graphs, which are of independent interest. We also improve and use the online algorithms for the Steiner tree problem., Full version of the paper accepted to STOC'15

A reoptimization problem describes the following scenario: given an instance of an optimization problem together with an optimal solution for it, we want to find a good solution for a locally modified instance. In this paper, we deal with reoptimization variants of the shortest common superstring problem (SCS) where the local modifications consist of adding or removing a single string. We show the NP-hardness of these reoptimization problems and design several approximation algorithms for them. First, we use a technique of iteratively using any SCS algorithm to design an approximation algorithm for the reoptimization variant of adding a string whose approximation ratio is arbitrarily close to 8/5 and another algorithm for deleting a string with a ratio tending to 13/7. Both algorithms significantly improve over the best currently known SCS approximation ratio of 2.5. Additionally, this iteration technique can be used to design an improved SCS approximation algorithm (without reoptimization) if the input instance contains a long string, which might be of independent interest. However, these iterative algorithms are relatively slow. Thus, we present another, faster approximation algorithm for inserting a string which is based on cutting the given optimal solution and achieves an approximation ratio of 11/6. Moreover, we give some lower bounds on the approximation ratio which can be achieved by algorithms that use such cutting strategies., Algorithmica, 61 (2), ISSN:0178-4617, ISSN:1432-0541

Given an instance of an optimization problem together with an optimal solution for it, a reoptimization problem asks for a solution for a locally modified input instance. In this paper we develop new reoptimization techniques and apply them to the Steiner Tree Problem. Our techniques significantly improve the previous results and apply to a variety of reoptimization problems.