Glutathione <Emphasis Type="BoldItalic">S</Emphasis>-transferase P1 gene polymorphisms and susceptibility to coronary artery disease in a subgroup of north Indian population

The present study aimed to investigate the association of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) polymorphisms of GSTP1 with coronary artery disease (CAD) in a subgroup of north Indian population. In the present case–control study, CAD patients (\(n = 200\)) and age-matched, sex-matched and ethnicity-matched healthy controls (\(n = 200\)) were genotyped for polymorphisms in GSTP1 using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Genotype distribution of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) polymorphisms of GSTP1 gene was significantly different between cases and controls (\(P = 0.005\) and 0.024, respectively). Binary logistic regression analysis showed significant association of A/G (odds ratio (OR): 1.6, 95% CI: 1.08–2.49, \(P = 0.020\)) and G/G (OR: 3.1, 95% CI: 1.41–6.71, P \(=\) 0.005) genotypes of GSTP1 \(\hbox {g}.313\hbox {A}{\!>\!}\hbox {G}\), and C/T (OR: 5.8, 95% CI: 1.26–26.34, \(P = 0.024\)) genotype of GSTP1 \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) with CAD. The A/G and G/G genotypes of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and C/T genotype of \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) conferred 6.5-fold increased risk for CAD (OR: 6.5, 95% CI: 1.37–31.27, \(P = 0.018\)). Moreover, the recessive model of GSTP1 \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) is the best fit inheritance model to predict the susceptible gene effect (OR: 2.3, 95% CI: 1.11–4.92, \(P = 0.020\)). In conclusion, statistically significant associations of GSTP1 \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) (A/G, G/G) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) (C/T) genotypes with CAD were observed.     

Invasions Slow Down or Collapse in the Presence of Reactive Boundaries

Motivated by the propagation of thin bacterial films around planar obstacles, this paper considers the dynamics of travelling wave solutions to the Fisher–KPP equation \(u_t = u(1-u) + u_{xx} + u_{yy}\) in a planar strip \(-\infty< x < \infty \), \(0 \le y \le L\). We examine the propagation of fronts in the presence of a mixed boundary condition (also referred to as a ‘partially absorbing’ or ‘reactive’ boundary) \(u_y = \alpha u\), with \(\alpha >0\), at \(y=0\). The presence of boundary conditions of this kind leads to the development of front solutions that propagate in x but contain transverse structure in y. Motivated by the observation that the speed of propagation in the Fisher–KPP equation is determined (for exponentially decaying initial conditions) by the behaviour at the leading edge, we analyse the linearised Fisher–KPP equation in order to estimate the speed of the stable travelling front, a function of the width L and the imposed boundary conditions. For wide strips the speed estimate based on the linearised equation agrees well with the results of numerical simulations. For narrow channels numerical simulations indicate that the stable front propagates more slowly, and for sufficiently small L or sufficiently large \(\alpha \) the front speed falls to zero and the front collapses. The reason for the collapse is the non-existence, far behind the front, of a stable positive equilibrium solution u(x, y). While existence of these equilibrium states can be demonstrated via phase plane arguments, the investigation of stability is similar to calculations of critical patch sizes carried out in similar ecological models.     

Optimal Therapy Scheduling Based on a Pair of Collaterally Sensitive Drugs

Despite major strides in the treatment of cancer, the development of drug resistance remains a major hurdle. One strategy which has been proposed to address this is the sequential application of drug therapies where resistance to one drug induces sensitivity to another drug, a concept called collateral sensitivity. The optimal timing of drug switching in these situations, however, remains unknown. To study this, we developed a dynamical model of sequential therapy on heterogeneous tumors comprised of resistant and sensitive cells. A pair of drugs (DrugA, DrugB) are utilized and are periodically switched during therapy. Assuming resistant cells to one drug are collaterally sensitive to the opposing drug, we classified cancer cells into two groups, \(A_\mathrm{R}\) and \(B_\mathrm{R}\), each of which is a subpopulation of cells resistant to the indicated drug and concurrently sensitive to the other, and we subsequently explored the resulting population dynamics. Specifically, based on a system of ordinary differential equations for \(A_\mathrm{R}\) and \(B_\mathrm{R}\), we determined that the optimal treatment strategy consists of two stages: an initial stage in which a chosen effective drug is utilized until a specific time point, T, and a second stage in which drugs are switched repeatedly, during which each drug is used for a relative duration (i.e., \(f \Delta t\)-long for DrugA and \((1-f) \Delta t\)-long for DrugB with \(0 \le f \le 1\) and \(\Delta t \ge 0\)). We prove that the optimal duration of the initial stage, in which the first drug is administered, T, is shorter than the period in which it remains effective in decreasing the total population, contrary to current clinical intuition. We further analyzed the relationship between population makeup, \(\mathcal {A/B} = A_\mathrm{R}/B_\mathrm{R}\), and the effect of each drug. We determine a critical ratio, which we term \(\mathcal {(A/B)}^{*}\), at which the two drugs are equally effective. As the first stage of the optimal strategy is applied, \(\mathcal {A/B}\) changes monotonically to \(\mathcal {(A/B)}^{*}\) and then, during the second stage, remains at \(\mathcal {(A/B)}^{*}\) thereafter. Beyond our analytic results, we explored an individual-based stochastic model and presented the distribution of extinction times for the classes of solutions found. Taken together, our results suggest opportunities to improve therapy scheduling in clinical oncology.     

Analysis of two susceptibility SNPs in HLA region and evidence of interaction between rs6457617 in <Emphasis Type="BoldItalic">HLA-DQB1</Emphasis> and <Emphasis Type="BoldItalic">HLA-DRB1</Emphasis>*04 locus on Tunisian rheumatoid arthritis

Previous genomewide association studies (GWAS) and meta-analyses have enumerated several genes/loci in major histocompatibility complex region, which are consistently associated with rheumatoid arthritis (RA) in different ethnic populations. Given the genetic heterogeneity of the disease, it is necessary to replicate these susceptibility loci in other populations. In this case, we investigate the analysis of two SNPs, rs13192471 and rs6457617, from the human leukocyte antigen (HLA) region with the risk of RA in Tunisian population. These SNPs were previously identified to have a strong RA association signal in several GWAS studies. A case–control sample composed of 142 RA patients and 123 healthy controls was analysed. Genotyping of rs13192471 and rs6457617 was carried out using real-time PCR methods by TaqMan allelic discrimination assay. A trend of significant association was found in rs6457617 TT genotype with susceptibility to RA (\(P = 0.04\), \(p_{c} = 0.08\), \(\hbox {OR} = 1.73\)). Moreover, using multivariable analysis, the combination of rs6457617*TT–HLA-DRB1*\(04^{+}\) increased risk of RA (\(\hbox {OR} = 2.38\)), which suggest a gene–gene interaction event between rs6457617 located within the HLA-DQB1 and HLA-DRB1. Additionally, haplotypic analysis highlighted a significant association of rs6457617*T–HLA-DRB1*\(04^{+}\) haplotype with susceptibility to RA (\(P = 0.018\), \(p_{c} = 0.036\), \(\hbox {OR} = 1.72\)). An evidence of association was shown subsequently in \(\hbox {antiCCP}^{+}\) subgroup with rs6457617 both in T allele and TT genotype (\(P = 0.01\), \(p_{c} = 0.03\), \(\hbox {OR} = 1.66\) and \(P = 0.008\), \(p_{c} = 0.024\), \(\hbox {OR} = 1.28\), respectively). However, no association was shown for rs13192471 polymorphism with susceptibility and severity to RA. This study suggests the involvement of rs6457617 locus as risk variant for susceptibility/severity to RA in Tunisian population. Secondly, it highlights the gene–gene interaction between HLA-DQB1 and HLA-DRB1.     

Oestrogen regulates the expression of cathepsin E-A-like gene through ER$$\upbeta $$ in liver of chicken ( Gallus gallus)

The cathepsin E-A-like, also known as ‘similar to nothepsin’, is a new member of the aspartic protease family, which may take part in processing of egg yolk macromolecules, due to it was identified in the chicken egg-yolk. Previously, studies have suggested that the expression of cathepsin E-A-like increased gradually during sexual maturation of pullets, but the exact regulation mechanism is poorly understood. In this study, to gain insight into the function and regulation mechanism of the gene in egg-laying hen, we cloned the cathepsin E-A-like gene and evaluated its evolutionary origin by using both phylogenetic and syntenic methods. The mode of the gene expression regulation was analysed through stimulating juvenile hens with \(17\upbeta \)-estradiol and chicken embryo hepatocytes with \(17\upbeta \)-estradiol combined with oestrogen receptor antagonists including MPP, ICI 182,780 and tamoxifen. Our results showed that cathepsin E-A-like was an orthologoues gene with nothepsin, which is present in birds but not in mammals. The expression of cathepsin E-A-like significantly increased in a dose-dependent manner after the juvenile hens were treated with \(17\upbeta \)-estradiol (\(P~<~0.05\)). Compared with the \(17\upbeta \)-estradiol treatment group, the expression of cathepsin E-A-like was not significantly changed when the hepatocytes were treated with \(17\upbeta \)-estradiol combined with MPP (\(P~<~0.05\)). In contrast, compared with the \(17\upbeta \)-estradiol combined with MPP treatment group, the expression of cathepsin E-A-like was significantly downregulated when the hepatocytes were treated with \(17\upbeta \)-estradiol combined with tamoxifen or ICI 182,780 (\(P~<~0.05\)). These results demonstrated that cathepsin E-A-like shared the same evolutionary origin with nothepsin. The expression of cathepsin E-A-like was regulated by oestrogen, and the regulative effect was predominantly mediated through ER-\(\upbeta \) in liver of chicken.     

An improved Four-Russians method and sparsified Four-Russians algorithm for RNA folding

Background

The basic RNA secondary structure prediction problem or single sequence folding problem (SSF) was solved 35 years ago by a now well-known \(O(n^3)\)-time dynamic programming method. Recently three methodologies—Valiant, Four-Russians, and Sparsification—have been applied to speedup RNA secondary structure prediction. The sparsification method exploits two properties of the input: the number of subsequence Z with the endpoints belonging to the optimal folding set and the maximum number base-pairs L. These sparsity properties satisfy \(0 \le L \le n / 2\) and \(n \le Z \le n^2 / 2\), and the method reduces the algorithmic running time to O(LZ). While the Four-Russians method utilizes tabling partial results.

Results

In this paper, we explore three different algorithmic speedups. We first expand the reformulate the single sequence folding Four-Russians \(\Theta \left(\frac{n^3}{\log ^2 n}\right)\)-time algorithm, to utilize an on-demand lookup table. Second, we create a framework that combines the fastest Sparsification and new fastest on-demand Four-Russians methods. This combined method has worst-case running time of \(O(\tilde{L}\tilde{Z})\), where \(\frac{{L}}{\log n} \le \tilde{L}\le min\left({L},\frac{n}{\log n}\right)\) and \(\frac{{Z}}{\log n}\le \tilde{Z} \le min\left({Z},\frac{n^2}{\log n}\right)\). Third we update the Four-Russians formulation to achieve an on-demand \(O( n^2/ \log ^2n )\)-time parallel algorithm. This then leads to an asymptotic speedup of \(O(\tilde{L}\tilde{Z_j})\) where \(\frac{{Z_j}}{\log n}\le \tilde{Z_j} \le min\left({Z_j},\frac{n}{\log n}\right)\) and \(Z_j\) the number of subsequence with the endpoint j belonging to the optimal folding set.

Conclusions

The on-demand formulation not only removes all extraneous computation and allows us to incorporate more realistic scoring schemes, but leads us to take advantage of the sparsity properties. Through asymptotic analysis and empirical testing on the base-pair maximization variant and a more biologically informative scoring scheme, we show that this Sparse Four-Russians framework is able to achieve a speedup on every problem instance, that is asymptotically never worse, and empirically better than achieved by the minimum of the two methods alone.

     

Self-complementary circular codes in coding theory

Self-complementary circular codes are involved in pairing genetic processes. A maximal \(C^3\) self-complementary circular code X of trinucleotides was identified in genes of bacteria, archaea, eukaryotes, plasmids and viruses (Michel in Life 7(20):1–16 2017, J Theor Biol 380:156–177, 2015; Arquès and Michel in J Theor Biol 182:45–58 1996). In this paper, self-complementary circular codes are investigated using the graph theory approach recently formulated in Fimmel et al. (Philos Trans R Soc A 374:20150058, 2016). A directed graph \(\mathcal {G}(X)\) associated with any code X mirrors the properties of the code. In the present paper, we demonstrate a necessary condition for the self-complementarity of an arbitrary code X in terms of the graph theory. The same condition has been proven to be sufficient for codes which are circular and of large size \(\mid X \mid \ge 18\) trinucleotides, in particular for maximal circular codes (\(\mid X \mid = 20\) trinucleotides). For codes of small-size \(\mid X \mid \le 16\) trinucleotides, some very rare counterexamples have been constructed. Furthermore, the length and the structure of the longest paths in the graphs associated with the self-complementary circular codes are investigated. It has been proven that the longest paths in such graphs determine the reading frame for the self-complementary circular codes. By applying this result, the reading frame in any arbitrary sequence of trinucleotides is retrieved after at most 15 nucleotides, i.e., 5 consecutive trinucleotides, from the circular code X identified in genes. Thus, an X motif of a length of at least 15 nucleotides in an arbitrary sequence of trinucleotides (not necessarily all of them belonging to X) uniquely defines the reading (correct) frame, an important criterion for analyzing the X motifs in genes in the future.     

Study of biological communities subject to imperfect detection: bias and precision of community <Emphasis Type="Italic">N</Emphasis>-mixture abundance models in small-sample situations

Community N-mixture abundance models for replicated counts provide a powerful and novel framework for drawing inferences related to species abundance within communities subject to imperfect detection. To assess the performance of these models, and to compare them to related community occupancy models in situations with marginal information, we used simulation to examine the effects of mean abundance \((\bar{\lambda }\): 0.1, 0.5, 1, 5), detection probability \((\bar{p}\): 0.1, 0.2, 0.5), and number of sampling sites (n _site : 10, 20, 40) and visits (n _visit : 2, 3, 4) on the bias and precision of species-level parameters (mean abundance and covariate effect) and a community-level parameter (species richness). Bias and imprecision of estimates decreased when any of the four variables \((\bar{\lambda }\), \(\bar{p}\), n _site , n _visit ) increased. Detection probability \(\bar{p}\) was most important for the estimates of mean abundance, while \(\bar{\lambda }\) was most influential for covariate effect and species richness estimates. For all parameters, increasing n _site was more beneficial than increasing n _visit . Minimal conditions for obtaining adequate performance of community abundance models were n _site  ≥ 20, \(\bar{p}\) ≥ 0.2, and \(\bar{\lambda }\) ≥ 0.5. At lower abundance, the performance of community abundance and community occupancy models as species richness estimators were comparable. We then used additive partitioning analysis to reveal that raw species counts can overestimate β diversity both of species richness and the Shannon index, while community abundance models yielded better estimates. Community N-mixture abundance models thus have great potential for use with community ecology or conservation applications provided that replicated counts are available.     

Transmission Fitness in Co-colonization and the Persistence of Bacterial Pathogens

Humans are often colonized by polymorphic bacteria such as Streptococcus pneumoniae, Bordetella pertussis, Staphylococcus Aureus, and Haemophilus influenzae. Two co-colonizing pathogen clones may interact with each other upon host entry and during within-host dynamics, ranging from competition to facilitation. Here we examine the significance of these exploitation strategies for bacterial spread and persistence in host populations. We model SIS epidemiological dynamics to capture the global behavior of such multi-strain systems, focusing on different parameters of single and dual colonization. We analyze the impact of heterogeneity in clearance and transmission rates of single and dual colonization and find the criteria under which these asymmetries enhance endemic persistence. We obtain a backward bifurcation near \(R_0 = 1\) if the reproductive value of the parasite in dually infected hosts is sufficiently higher than that in singly infected ones. In such cases, the parasite is able to persist even in sub-threshold conditions, and reducing the basic reproduction number below 1 would be insufficient for elimination. The fitness superiority in co-colonized hosts can be attained by lowering net parasite clearance rate (\(\gamma _\mathrm{{d}}\)), by increasing transmission rate (\(\beta _\mathrm{{d}}\)), or both, and coupling between these traits critically constrains opportunities of pathogen survival in the \(R_0<1\) regime. Finally, using an adaptive dynamics approach, we verify that despite their importance for sub-threshold endemicity, traits expressed exclusively in coinfection should generally evolve independently of single infection traits. In particular, for \(\beta _\mathrm{{d}}\) a saturating parabolic or hyperbolic function of \(\gamma _\mathrm{{d}}\), co-colonization traits evolve to an intermediate optimum (evolutionarily stable strategy, ESS), determined only by host lifespan and the trade-off parameters linking \(\beta _\mathrm{{d}}\) and \(\gamma _\mathrm{{d}}\). Our study invites more empirical attention to the dynamics and evolution of parasite life-history traits expressed exclusively in coinfection.     

Genomewide identification of PPR gene family and prediction analysis on restorer gene in <Emphasis Type="BoldItalic">Gossypium</Emphasis>

Pentatricopeptide repeat (PPR) gene family plays an essential role in the regulation of plant growth and organelle gene expression. Some PPR genes are related to fertility restoration in plant, but there is no detailed information in Gossypium. In the present study, we identified 482 and 433 PPR homologues in Gossypium raimondii (\(\hbox {D}_{5}\)) and G. arboreum (\(\hbox {A}_{2}\)) genomes, respectively. Most PPR homologues showed an even distribution on the whole chromosomes. Given an evolutionary analysis to PPR genes from G. raimondii (\(\hbox {D}_{5}\)), G. arboreum (\(\hbox {A}_{2}\)) and G. hirsutum genomes, eight PPR genes were clustered together with restoring genes of other species. Most cotton PPR genes were qualified with no intron, high proportion of \(\upalpha \)-helix and classical tertiary structure of PPR protein. Based on bioinformatics analyses, eight PPR genes were targeted in mitochondrion, encoding typical P subfamily protein with protein binding activity and organelle RNA metabolism in function. Further verified by RNA-seq and quantitative real-time PCR (qRT-PCR) analyses, two PPR candidate genes, Gorai.005G0470 (\(\hbox {D}_{5}\)) and Cotton_A_08373 (\(\hbox {A}_{2}\)), were upregulated in fertile line than sterile line. These results reveal new insights into PPR gene evolution in Gossypium.     

Backbone resonance assignments for the SET domain of the human methyltransferase NSD2

Aberrant NSD2 methyltransferase activity is implicated as the oncogenic driver in multiple myeloma, suggesting opportunities for novel therapeutic intervention. The methyltransferase activity of NSD2 resides in its catalytic SET domain, which is conserved among most lysine methyltransferases. Here we report the backbone \(\hbox {H}^{\mathrm{N}}\), N, C\(^{\prime }\), \(\hbox {C}^\alpha\) and side-chain \(\hbox {C}^\beta\) assignments of a 25 kDa NSD2 SET domain construct, spanning residues 991–1203. A chemical shift analysis of C\(^{\prime }\), \(\hbox {C}^\alpha\) and \(\hbox {C}^\beta\) resonances predicts a secondary structural pattern that is in agreement with homology models.     

Optimal foraging behavior with an explicit consideration of within-individual behavioral variation: an example of predation

Animal behavior is flexible, and the same individual can exhibit variable expressions under the equivalent ecological situations (i.e., within-individual behavioral variation). This study examines the evolution of within-individual behavioral variation using an individual-based model. A common predation scenario is considered where a predator spends a period h to handle and consume a captured prey. The model assumes the handling time of the predator to be a random variable. The average and within-individual variance of handling time are described by \(\mu _h\) and \(\sigma _h^2\), respectively, where each individual has its own unique \(\mu _h\) and \(\sigma _h^2\). Using a genetic algorithm, the evolution of \(\sigma _h^2\) is traced. The results show that natural selection acts on both \(\mu _h\) and \(\sigma _h^2\), and the optimal behavioral variation depends on the density of prey. In particular, individuals with high behavioral variance \(\sigma _h^2\) are more likely selected when prey density is low. Individual based modeling can be a useful tool for studying the ultimate significance of within-individual behavioral variation and generating empirically testable predictions. The mechanisms of the evolution of within-individual behavioral variation and their ecological implications are discussed.     

A viscoplastic model for the active component in cardiac muscle

The HMK model (Hunter et al. in Prog Biophys Mol Biol 69:289–331, 1998) proposes mechanobiological equations for the influence of intracellular calcium concentration \(\hbox {Ca}_\mathrm{i}\) on the evolution of bound calcium concentration \(\hbox {Ca}_\mathrm{b}\) and the tropomyosin kinetics parameter z, which model processes in the active component of the tension in cardiac muscle. The inelastic response due to actin-myosin crossbridge kinetics is modeled in the HMK model with a function Q that depends on the history of the rate of total stretch of the muscle fiber. Here, an alternative model is proposed which models the active component of the muscle fiber as a viscoplastic material. In particular, an evolution equation is proposed for the elastic stretch \(\lambda _\mathrm{a} \) in the active component. Specific forms of the constitutive equations are proposed and used to match experimental data. The proposed viscoplastic formulation allows for separate modeling of three processes: the high rate deactivation of crossbridges causing rapid reduction in active tension; the high but lower rate reactivation of crossbridges causing recovery of active tension; and the low rate relaxation effects characterizing the Hill model of muscles.     

Association of <Emphasis Type="BoldItalic">lactase</Emphasis> 13910 C/T polymorphism with bone mineral density and fracture risk: a meta-analysis

A number of studies have investigated the association of lactase (LCT, C/T-13910) gene polymorphism with bone mineral density (BMD) and fracture risk, but previous results were inconclusive. In this study, a meta-analysis was performed to quantify the association of LCT (C/T-13910) polymorphism with BMD and fracture risk. Eligible publications were searched in the PubMed, Web of Science, Embase databases, Google Scholar, Yahoo and Baidu. Pooled weighed mean difference (WMD) or odds ratio (OR) with their 95% confidence interval (CI) were calculated using a fixed-effects or random-effects model. A total of nine articles with 8871 subjects were investigated in the present meta-analysis. Overall, the TT/TC genotypes of LCT 13910 C/T polymorphism showed significantly higher BMD than those with the CC genotype at femur neck (FN) (\(\hbox {WMD} = 0.011\,\hbox {g/cm}^{2}\), 95% CI \(=\) 0.004–0.018, \(P = 0.003\)). Besides, LCT 13910 C/T polymorphism may decrease the risk of any site fractures (for TT versus TC \(+\) CC, OR \(=\) 0.813, 95% CI \(=\) 0.704–0.938, \(P = 0.005\); for T allele versus C allele, OR \(=\) 0.885, 95% CI \(=\) 0.792–0.989, \(P = 0.032\)). However, there was no significant association of LCT 13910 C/T polymorphism with BMD at lumbar spine and risk of vertebral fractures under all genetic contrast models (all P values were \({>}0.05\)). The meta-analysis suggests that there are significant effects of LCT 13910 C/T polymorphism on BMD and fracture risk. Large-scale studies with different ethnic populations will be needed to further investigate the possible race-specific effect of LCT 13910 C/T polymorphism on BMD and fracture risk.     

Stability of a Stochastic Model of an SIR Epidemic with Vaccination

We prove almost sure exponential stability for the disease-free equilibrium of a stochastic differential equations model of an SIR epidemic with vaccination. The model allows for vertical transmission. The stochastic perturbation is associated with the force of infection and is such that the total population size remains constant in time. We prove almost sure positivity of solutions. The main result concerns especially the smaller values of the diffusion parameter, and describes the stability in terms of an analogue \(\mathcal{R}_\sigma\) of the basic reproduction number \(\mathcal{R}_0\) of the underlying deterministic model, with \(\mathcal{R}_\sigma \le \mathcal{R}_0\). We prove that the disease-free equilibrium is almost sure exponentially stable if \(\mathcal{R}_\sigma <1\).     

Forecasting next season’s <Emphasis Type="Italic">Ixodes ricinus</Emphasis> nymphal density: the example of southern Germany 2018

The castor bean tick, Ixodes ricinus (L.) (Ixodida: Ixodidae), is the principal vector of pathogens causing tick-borne encephalitis or Lyme borreliosis in Europe. It is therefore of general interest to make an estimate of the density of I. ricinus for the whole year at the beginning of the tick season. There are two necessary conditions for making a successful prediction: a long homogeneous time series of observed tick density and a clear biological relationship between environmental predictors and tick density. A 9-year time series covering the period 2009–2017 of nymphal I. ricinus flagged at monthly intervals in southern Germany has been used. With the hypothesis that I. ricinus density is triggered by the fructification of the European beech 2 years before, the mean annual temperature of the previous year, and the current mean winter temperature (December–February), a forecast of the annual nymphal tick density has been made. Therefore, a Poisson regression model was generated resulting in an explained variance of 93.4% and an error of \(\hbox {RMSE} = 21\) ticks per \(100\,\hbox {m}^2\) (annual \(\hbox {MEAN} = 260\) collected ticks/\(100\,\hbox {m}^2\)). An independent verification of the forecast for the year 2017 resulted in 187 predicted versus 180 observed nymphs per \(100\,\hbox {m}^2\). For the year 2018 a relatively high number of 443 questing I. ricinus nymphs per \(100\,\hbox {m}^2\) is forecasted, i.e., a “good” tick year.     

Cell Volume Regulation in the Proximal Tubule of Rat Kidney

We developed a dynamic model of a rat proximal convoluted tubule cell in order to investigate cell volume regulation mechanisms in this nephron segment. We examined whether regulatory volume decrease (RVD), which follows exposure to a hyposmotic peritubular solution, can be achieved solely via stimulation of basolateral K\(^+\) and \(\hbox {Cl}^-\) channels and \(\hbox {Na}^+\)–\(\hbox {HCO}_3^-\) cotransporters. We also determined whether regulatory volume increase (RVI), which follows exposure to a hyperosmotic peritubular solution under certain conditions, may be accomplished by activating basolateral \(\hbox {Na}^+\)/H\(^+\) exchangers. Model predictions were in good agreement with experimental observations in mouse proximal tubule cells assuming that a 10% increase in cell volume induces a fourfold increase in the expression of basolateral K\(^+\) and \(\hbox {Cl}^-\) channels and \(\hbox {Na}^+\)–\(\hbox {HCO}_3^-\) cotransporters. Our results also suggest that in response to a hyposmotic challenge and subsequent cell swelling, \(\hbox {Na}^+\)–\(\hbox {HCO}^-_3\) cotransporters are more efficient than basolateral K\(^+\) and \(\hbox {Cl}^-\) channels at lowering intracellular osmolality and reducing cell volume. Moreover, both RVD and RVI are predicted to stabilize net transcellular \(\hbox {Na}^+\) reabsorption, that is, to limit the net \(\hbox {Na}^+\) flux decrease during a hyposmotic challenge or the net \(\hbox {Na}^+\) flux increase during a hyperosmotic challenge.     

A novel real-time driving fatigue detection system based on wireless dry EEG

Development of techniques for detection of mental fatigue has varied applications in areas where sustaining attention is of critical importance like security and transportation. The objective of this study is to develop a novel real-time driving fatigue detection methodology based on dry Electroencephalographic (EEG) signals. The study has employed two methods in the online detection of mental fatigue: power spectrum density (PSD) and sample entropy (SE). The wavelet packets transform (WPT) method was utilized to obtain the \(\theta \) (4–7 Hz), \(\alpha \) (8–12 Hz) and \(\beta \) (13–30 Hz) bands frequency components for calculating corresponding PSD of the selected channels. In order to improve the fatigue detection performance, the system was individually calibrated for each subject in terms of fatigue-sensitive channels selection. Two fatigue-related indexes: (\(\theta +\alpha \))/\(\beta \) and \(\theta \)/\(\beta \) were computed and then fused into an integrated metric to predict the degree of driving fatigue. In the case of SE extraction, the mean of SE averaged across two EEG channels (‘O1h’ and ‘O2h’) was used for fatigue detection. Ten healthy subjects participated in our study and each of them performed two sessions of simulated driving. In each session, subjects were required to drive simulated car for 90 min without any break. The results demonstrate that our proposed methods are effective for fatigue detection. The prediction of fatigue is consistent with the observation of reaction time that was recorded during simulated driving, which is considered as an objective behavioral measure.