Impaired fasting glucose as an independent risk factor for hypertension among healthy middle-aged Japanese subjects with optimal blood pressure: the Yuport Medical Checkup Centre retrospective cohort study

BACKGROUND: This study aimed at investigating whether impaired fasting glucose (IFG) is an independent risk factor for incident hypertension among middle-aged Japanese subjects with optimal blood pressure (OBP). FINDINGS: This retrospective cohort study was conducted in 2943 non-diabetic and non-hypertensive subjects aged 40–64 years, who participated in a voluntary health check-up program during the baseline (1998–2002) and follow-up periods (2002–2006). A multiple logistic regression model was utilized to calculate the odds ratio (OR) of incident hypertension among men and women with IFG and OBP. OBP was defined as systolic blood pressure (SBP) <120 mmHg and diastolic blood pressure (DBP) <80 mmHg, with no known history of hypertension. In this study, hypertension was defined as SBP ≥140 mmHg and DBP ≥90 mmHg or by a self-reported clinical diagnosis of hypertension. After the mean follow-up period of 5.6 years, the incidence of hypertension in men and women was 5.7% (73/1270) and 3.8% (62/1673), respectively. The age-adjusted ORs for incident hypertension in men and women with IFG were 1.95 (95% CI, 1.21–3.15) and 3.54 (95% CI, 2.00–6.27), respectively. After adjusting for age, systolic blood pressure, body mass index, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and uric acid, the ORs for hypertension were 1.66 (95% CI; 1.02–2.70) for men and 2.62 (95% CI, 1.45–4.73) for women. CONCLUSION: The study results show that IFG may act as an independent risk factor for developing hypertension in individuals with OBP

A Hypergraph Approach for Estimating Growth Mechanisms of Complex Networks

Temporal datasets that describe complex interactions between individuals over time are increasingly common in various domains. Conventional graph representations of such datasets may lead to information loss since higher-order relationships between more than two individuals must be broken into multiple pairwise relationships in graph representations. In those cases, a hypergraph representation is preferable since it can preserve higher-order relationships by using hyperedges. However, existing hypergraph models of temporal complex networks often employ some data-independent growth mechanism, which is the linear preferential attachment in most cases. In principle, this pre-specification is undesirable since it completely ignores the data at hand. Our work proposes a new hypergraph growth model with a data-driven preferential attachment mechanism estimated from observed data. A key component of our method is a recursive formula that allows us to overcome a bottleneck in computing the normalizing factors in our model. We also treat an often-neglected selection bias in modeling the emergence of new edges with new nodes. Fitting the proposed hypergraph model to 13 real-world datasets from diverse domains, we found that all estimated preferential attachment functions deviates substantially from the linear form. This demonstrates the need of doing away with the linear preferential attachment assumption and adopting a data-driven approach. We also showed that our model outperformed conventional models in replicating the observed first-order and second-order structures in these real-world datasets

Molecular cloning and bacterial expression of a cDNA encoding furostanol glycoside 26-O-β-glucosidase of Costus speciosus

AbstractFurostanol glycoside 26-O-β-glucosidase (F26G) purified from Costus speciosus rhizomes was digested with endoproteinase, and several internal peptide fragments were obtained. Degenerate oligonucleotide primers based on amino acid sequences of the peptides were used for amplification of F26G cDNA fragments by applying nested polymerase chain reactions to cDNAs from in vitro cultured plantlets of C. speciosus. Using primers based on sequences of the cDNA fragments, the 5′- and 3′-end clones were isolated by rapid amplification of cDNA ends (RACE) methods. Finally, the entire coding portion of F26G cDNA was cloned by using primers designed from sequences of the RACE products. The deduced amino acid sequence of CSF26G1, the protein encoded by the cloned cDNA, consists of 562 amino acids and shows high homology to a widely distributed family of β-glucosidases (BGA family). Cell-free homogenate of Escherichia coli expressing CSF26G1 cDNA showed β-glucosidase activity specific for cleavage of the C-26 glucosidic bond of furostanol glycosides

Formation and Thermal Stability of Amorphous Phase in Transition Metal-Phosphorus Binary Alloys

This paper deals with the amorphous-forming ability of Mn-P, Fe-P, Co-P, Ni-P, Cu-P, Pd-P and Pt-P binary alloys quenched rapidly from the melt and the stability and structural change of the amorphous phases on heating. A melt-quenching technique yields the formation of an amorphous phase only for Fe_P_, Ni_P_, Pd_P_ and Pt_P_ alloys. The critical cooling rate for the formation of an amorphous phase is calculated to be of the order 10^5-10^6 K/s for these amorphous-forming alloys from the transformation theories of crystal nucleation and growth kinetics in the liquid. Therefore, it may be stated that the binary alloys with the critical cooling rates lower than about 10^7 K/s can be melt-quenched to the amorphous state by the centrifugal quenching apparatus used in the present work. Further, it has been demonstrated that the crystallization of these amorphous phases occurs through the two stages of Am.→Am.+Crys-I→Crys-I+Crys-II→Stable Phases near the temperatures of about 620 K for Fe_P_, 600 K for Ni_P_, 535 K for Pd_P_ and 470 K for Pt_P_ alloy

International Competition on Graph Counting Algorithms 2023

This paper reports on the details of the International Competition on Graph Counting Algorithms (ICGCA) held in 2023. The graph counting problem is to count the subgraphs satisfying specified constraints on a given graph. The problem belongs to #P-complete, a computationally tough class. Since many essential systems in modern society, e.g., infrastructure networks, are often represented as graphs, graph counting algorithms are a key technology to efficiently scan all the subgraphs representing the feasible states of the system. In the ICGCA, contestants were asked to count the paths on a graph under a length constraint. The benchmark set included 150 challenging instances, emphasizing graphs resembling infrastructure networks. Eleven solvers were submitted and ranked by the number of benchmarks correctly solved within a time limit. The winning solver, TLDC, was designed based on three fundamental approaches: backtracking search, dynamic programming, and model counting or #SAT (a counting version of Boolean satisfiability). Detailed analyses show that each approach has its own strengths, and one approach is unlikely to dominate the others. The codes and papers of the participating solvers are available: https://afsa.jp/icgca/.Comment: https://afsa.jp/icgca

Solution structure of multi-domain protein ER-60 studied by aggregation-free SAXS and coarse-grained-MD simulation

Multi-domain proteins (MDPs) show a variety of domain conformations under physiological conditions, regulating their functions through such conformational changes. One of the typical MDPs, ER-60 which is a protein folding enzyme, has a U-shape with four domains and is thought to have different domain conformations in solution depending on the redox state at the active centres of the edge domains. In this work, an aggregation-free small-angle X-ray scattering revealed that the structures of oxidized and reduced ER-60 in solution are different from each other and are also different from those in the crystal. Furthermore, structural modelling with coarse-grained molecular dynamics simulation indicated that the distance between the two edge domains of oxidized ER-60 is longer than that of reduced ER-60. In addition, one of the edge domains has a more flexible conformation than the other

Statins Activate Human PPARα Promoter and Increase PPARα mRNA Expression and Activation in HepG2 Cells

Statins increase peroxisome proliferator-activated receptor α (PPARα) mRNA expression, but the mechanism of this increased PPARα production remains elusive. To examine the regulation of PPARα production, we examined the effect of 7 statins (atorvastatin, cerivastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin) on human PPARα promoter activity, mRNA expression, nuclear protein levels, and transcriptional activity. The main results are as follows. (1) Majority of statins enhanced PPARα promoter activity in a dose-dependent manner in HepG2 cells transfected with the human PPARα promoter. This enhancement may be mediated by statin-induced HNF-4α. (2) PPARα mRNA expression was increased by statin treatment. (3) The PPARα levels in nuclear fractions were increased by statin treatment. (4) Simvastatin, pravastatin, and cerivastatin markedly enhanced transcriptional activity in 293T cells cotransfected with acyl-coenzyme A oxidase promoter and PPARα/RXRα expression vectors. In summary, these data demonstrate that PPARα production and activation are upregulated through the PPARα promoter activity by statin treatment