Influence of SLC22A1 gene polymorphisms on gastrointestinal adverse effects with metformin therapy in South Indian type 2 diabetes mellitus patients

Background: Metformin, a first-line agent in Type 2 diabetes mellitus, causes gastrointestinal adverse effects in 20-30% of patients, leading to discontinuation in 5-10% of them. Organic cation transporter 1 (OCT1) encoded by SLC22A1, transports metformin from the enterocytes into the bloodstream. Reduced function OCT1 variants could lead to increased luminal concentration of metformin leading to gastrointestinal adverse effects. Two single nucleotide polymorphisms in the SLC22A1 gene were studied in this cross-sectional study with cases and controls. Objective was to determine the association between genetic polymorphisms rs628031 (1222A>G) and rs622342 (1386C>A) in SLC22A1 gene and gastrointestinal adverse effects to metformin therapy in South Indian type 2 diabetes mellitus patients. Methods: The study was conducted in JIPMER, Puducherry, India in T2DM patients (n=300) of South Indian origin, who were categorized into case (N=100) and control (N=200) groups, based on their gastrointestinal tolerance to metformin. DNA was extracted from the patients using whole blood by phenol-chloroform method and genotyping was done using real-time PCR. Results: Minor allele frequency of rs628031 (A allele) and rs622342 (C allele) were 33.8% and 26.5% respectively. Genotype frequencies did not differ significantly between the case and control groups (rs628031, p=0.45, rs622342, p=0.28). Female gender (AOR 3.77; 95% CI 2.07, 6.85; p<0.001) and proton pump inhibitor usage (AOR 7.66; 95% CI 3.01, 19.47; p<0.001) had higher association with metformin intolerance. Conclusions: No significant association was found between the genotypes of single nucleotide polymorphisms (rs628031 and rs622342) in the SLC22A1 gene and gastrointestinal adverse effects to metformin therapy in South Indian type 2 diabetes mellitus patients

Remarks on the Formulation of Quantum Mechanics on Noncommutative Phase Spaces

We consider the probabilistic description of nonrelativistic, spinless one-particle classical mechanics, and immerse the particle in a deformed noncommutative phase space in which position coordinates do not commute among themselves and also with canonically conjugate momenta. With a postulated normalized distribution function in the quantum domain, the square of the Dirac delta density distribution in the classical case is properly realised in noncommutative phase space and it serves as the quantum condition. With only these inputs, we pull out the entire formalisms of noncommutative quantum mechanics in phase space and in Hilbert space, and elegantly establish the link between classical and quantum formalisms and between Hilbert space and phase space formalisms of noncommutative quantum mechanics. Also, we show that the distribution function in this case possesses 'twisted' Galilean symmetry.Comment: 25 pages, JHEP3 style; minor changes; Published in JHE

A Weakly-Robust PTAS for Minimum Clique Partition in Unit Disk Graphs

We consider the problem of partitioning the set of vertices of a given unit disk graph (UDG) into a minimum number of cliques. The problem is NP-hard and various constant factor approximations are known, with the current best ratio of 3. Our main result is a {\em weakly robust} polynomial time approximation scheme (PTAS) for UDGs expressed with edge-lengths, it either (i) computes a clique partition or (ii) gives a certificate that the graph is not a UDG; for the case (i) that it computes a clique partition, we show that it is guaranteed to be within (1+\eps) ratio of the optimum if the input is UDG; however if the input is not a UDG it either computes a clique partition as in case (i) with no guarantee on the quality of the clique partition or detects that it is not a UDG. Noting that recognition of UDG's is NP-hard even if we are given edge lengths, our PTAS is a weakly-robust algorithm. Our algorithm can be transformed into an O(\frac{\log^* n}{\eps^{O(1)}}) time distributed PTAS. We consider a weighted version of the clique partition problem on vertex weighted UDGs that generalizes the problem. We note some key distinctions with the unweighted version, where ideas useful in obtaining a PTAS breakdown. Yet, surprisingly, it admits a (2+\eps)-approximation algorithm for the weighted case where the graph is expressed, say, as an adjacency matrix. This improves on the best known 8-approximation for the {\em unweighted} case for UDGs expressed in standard form.Comment: 21 pages, 9 figure

Rare association of turner syndrome with neurofibromatosis type 1 and tuberous sclerosis complex

We report a rare association of Turner syndrome with both Neurofibromatosis type I and Tuberous Sclerosis. The patient had XO karyotype with Turners stigmata and also had features of Neurofibromatosis 1 in the form of significant cafe-au-lait spots and Plexiform neurofibroma along with typical features of Tuberous Sclerosis complex. Pedigree analysis revealed that the elder brother of the proband in the family also suffered from Tuberous Sclerosis without the manifestation of Neurofibromatosis or any other genetic disorders. We hypothesize that these associations could be due to new independent mutations and also increased maternal and paternal age in a pre-disposition of Turner syndrome

A genetic algorithm

Castelli, M., Dondi, R., Manzoni, S., Mauri, G., & Zoppis, I. (2019). Top k 2-clubs in a network: A genetic algorithm. In J. J. Dongarra, J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, R. Lam, V. V. Krzhizhanovskaya, M. H. Lees, ... P. M. A. Sloot (Eds.), Computational Science. ICCS 2019: 19th International Conference, 2019, Proceedings (Vol. 5, pp. 656-663). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11540 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22750-0_63The identification of cohesive communities (dense sub-graphs) is a typical task applied to the analysis of social and biological networks. Different definitions of communities have been adopted for particular occurrences. One of these, the 2-club (dense subgraphs with diameter value at most of length 2) has been revealed of interest for applications and theoretical studies. Unfortunately, the identification of 2-clubs is a computationally intractable problem, and the search of approximate solutions (at a reasonable time) is therefore fundamental in many practical areas. In this article, we present a genetic algorithm based heuristic to compute a collection of Top k 2-clubs, i.e., a set composed by the largest k 2-clubs which cover an input graph. In particular, we discuss some preliminary results for synthetic data obtained by sampling Erdös-Rényi random graphs.authorsversionpublishe

Investigation of the presence of an aliphatic biopolymer in cyanobacteria: Implications for kerogen formation

Algaenan has been suggested to be one of the main precursors of certain kerogens. It is a non-hydrolysable and insoluble biomolecule of high molecular weight. It has been found in a limited number of microalgae species. There is considerable uncertainty about its formation and preservation, as well as its role in kerogen formation and the implications for the global C cycle. We tested whether the cyanobacterium Chlorogloeopsis fritschii can synthesise a biomacromolecule similar to algaenan with potential to contribute to kerogen via selective preservation. Two freshwater green microalgae, Pseudochoricystis ellipsoidea and Scenedesmus obliquus, as well as C. fritschii, were subjected to harsh solvent extraction and hydrolysis steps to obtain an insoluble and non-hydrolysable macromolecule. The residues from all three species were analysed using pyrolysis–gas chromatography–mass spectrometry and solid-state nuclear magnetic resonance spectroscopy. The analysis revealed that C. fritschii indeed contains a resistant biomacromolecule exhibiting the characteristic aliphatic structure of algaenan, similar to the algaenan residues from the two microalgae. Due to the robust nature of Chlorogloeopsis compared with eukaryotes, it can prevail in extreme environmental conditions such as freezing, thawing, desiccation and overheating – conditions prevalent on the primeval earth. The presence of a resistant aliphatic biopolymer in Chlorogloeopsis suggests that cyanobacteria could have contributed to kerogen via selective preservation

On Structural Parameterizations of the Bounded-Degree Vertex Deletion Problem

We study the parameterized complexity of the Bounded-Degree Vertex Deletion problem (BDD), where the aim is to find a maximum induced subgraph whose maximum degree is below a given degree bound. Our focus lies on parameters that measure the structural properties of the input instance. We first show that the problem is W[1]-hard parameterized by a wide range of fairly restrictive structural parameters such as the feedback vertex set number, pathwidth, treedepth, and even the size of a minimum vertex deletion set into graphs of pathwidth and treedepth at most three. We thereby resolve an open question stated in Betzler, Bredereck, Niedermeier and Uhlmann (2012) concerning the complexity of BDD parameterized by the feedback vertex set number. On the positive side, we obtain fixed-parameter algorithms for the problem with respect to the decompositional parameter treecut width and a novel problem-specific parameter called the core fracture number

Long COVID clinical severity types based on symptoms and functional disability: A longitudinal evaluation

Background: Long COVID (LC) is a multisystem clinical syndrome with functional disability and compromised overall health. Information on LC clinical severity types is emerging in cross-sectional studies. This study explored the pattern and consistency of long COVID (LC) clinical severity types over time in a prospective sample. Methods: Participants with LC completed the condition-specific outcome measure C19-YRSm (Yorkshire Rehabilitation Scale modified version) at two assessment time points. A cluster analysis for clinical severity types was undertaken at both time points using the k-means partition method. Results: The study included cross-sectional data for 759 patients with a mean age of 46.8 years (SD = 12.7), 69.4% females, and a duration of symptoms of 360 days (IQR 217 to 703 days). The cluster analysis at first assessment revealed three distinct clinical severity type clusters: mild (n = 96), moderate (n = 422), and severe (n = 241). Longitudinal data on 356 patients revealed that the pattern of three clinical severity types remained consistent over time between the two assessments, with 51% of patients switching clinical severity types between the assessments. Conclusions: This study is the first of its kind to demonstrate that the pattern of three clinical severity types is consistent over time, with patients also switching between severity types, indicating the fluctuating nature of LC