Despite the success of the United States (US) Boll Weevil Eradication Program, the boll weevil, Anthonomus grandis Boheman (Coleoptera: Curculionidae), remains a threat to cotton production in the southern US and is arguably the most important cotton pest in Central and South America. Management of this species is complicated by the existence of morphologically similar variants and re-infestations of areas where eradication had been successful. To date, no study has applied a high-throughput sequencing approach to better understand the population genetic structure of the boll weevil. Furthermore, only a single study has investigated genetic relationships between populations in North and South America. Here, we used double digest restriction site-associated DNA sequencing (ddRADseq) to resolve the population genomic structure of the boll weevil in the southern US, northern Mexico, and Argentina, test the two-form and three-form hypotheses of boll weevil variation in North America using a phylogeographic approach, and determine the relationship of the South American populations to the North. Our results supported the two-form hypothesis of boll weevil variation in North America wherein there are two major genetic lineages – one consisting of populations found geographically west of the Sierra Madre Occidental mountain range and the second consisting of populations found to the east – both are highly sub-structured across space and time. Boll weevil populations from Argentina were more closely related to the eastern lineage, suggesting a range expansion by the eastern lineage, but additional sampling across Central and South America is needed to determine a probable origin.
Telomeres, the short repetitive DNA sequences that cap the ends of linear chromosomes, shorten during cell division and are implicated in senescence in most species. Telomerase can rebuild telomeres but is repressed in many mammals that exhibit replicative senescence, presumably as a tumor suppression mechanism. It is therefore important that we have an accurate understanding of the co-evolution of telomere biology and life-history traits that has shaped the diversity of senescence patterns across species. Gomes et al. (2011) produced a large data set on telomere length (TL), telomerase activity, body mass and lifespan among 57 mammal species. We re-analyzed their data using the same phylogenetic multiple regressions and with several additional analyses to test the robustness of findings. We found substantial inconsistencies in our results compared to Gomes et al.’s. Consistent with Gomes et al. we found an inverse association between TL and lifespan. Contrary to the analyses in Gomes et al., we found a generally robust inverse association between TL and mass, and only weak non-robust evidence for an association between telomerase activity and mass. These results suggest that shorter TL may have been selected for in larger and longer-lived species–likely as a mechanism to suppress cancer. We support this hypothesis by showing that longer telomeres predict higher cancer risk across 22 species. Furthermore, we find that domesticated species have longer telomeres. Our results call into question past interpretations of the co-evolution of telomere biology and life-history traits and stress the need for careful attention to model construction.
Background AF in HCM is associated with high stroke risk despite low CHA2DS2-VASc scores. Hence, there is need to understand AF pathophysiology and predict AF in HCM. We develop/apply a data-driven, machine learning-based method to identify AF cases and clinical features associated with AF in HCM, using electronic health record (EHR) data. Methods Patients with documented paroxysmal/ persistent/permanent AF (n=191) were considered AF cases, and the remaining patients in sinus rhythm (n=640) were tagged as No-AF. We evaluated 93 clinical variables; the most informative variables useful for distinguishing AF from No-AF cases were selected based on the 2-sample t-test and information gain criterion. Results We identified 18 highly informative clinical variables: 11 are positively associated (e.g. LA-diameter, LV-diastolic dysfunction, LV-LGE), and 7 are negatively correlated (e.g. several exercise parameters) with AF in HCM. Next, patient records were represented via these 18 variables. Data imbalance resulting from the relatively low number of AF cases was addressed via a combination of over- and under-sampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. Specifically, an ensemble of logistic regression and naïve Bayes classifiers, trained based on the 18 variables and corrected for data imbalance, proved most effective for separating AF from No-AF cases (sensitivity=0.74, specificity=0.72, C-index=0.80). Conclusions Our model (HCM-AF-Risk Model), the first machine learning-based method for identification of AF cases in HCM, demonstrates good performance, and suggests that AF is associated with a more severe cardiac HCM-phenotype.
Background. Substrate analysis of the left atrium in patients undergoing atrial fibrillation ablation has limitations when performed by means of simple bipolar acquisition. Objective. To evaluate the incidence of low-voltages (LV) through maps constructed by means of various catheters:multipoltar (MC), omnipolar (OC) and circular catheters (CMC) with the 3D electro-anatomical systems (3d-S) CARTO3 and Ensite-Precision. Methods. To assess LV we acquired maps by means of CMC and MC in the voltage range 0.05-0.5 mV in 70 patients in sinus rhythm. In case of OC only, we made an intra-patient comparison of bipolar maps constructed in along, across and HD-Wave configurations by means of Ensite-Precision in the ranges of 0.05-0.5 mV and 0.5-1.0 mV. Basing on this comparison, we chose the range that best identified LV and characterized patchy fibrosis by analyzing a set of different colors (qualitative analysis). Finally, we performed a quantitative analysis of LV by applying the qualitative characteristics described above. Results. Basing on our settings, the optimal range for OC was 0.3-0.6 mV. OC revealed smaller LV areas than MC (p <0.05 or p <0.001), except in the lateral wall. No significant differences were observed between CMCs. The same rates of AF recurrence were found for OC and MC during the follow-up period. Conclusions.In our experience, OC does not present the limits of bipolar HD maps, though further studies are needed in order to confirm that 0.3-0.6 mV as LV optimal voltage range.
We describe the anaesthetic management of a 4-day-old premature infant presenting for urgent resection of a massive posterior intrapericardial teratoma. Anaesthetic challenges include anticipating cardiopulmonary collapse upon induction and hemodynamic instability associated with blood loss or tumor manipulation. Premature infants present unique challenges due to patient-to-tumor size discrepancy.
The benefits of opioid use in older adults to manage chronic non-cancer pain must outweigh the risks as these individuals are more susceptible to the side effects and drug interactions associated with opioids. Pharmacogenomic testing supports clinicians to select an appropriate opioid therapy while minimizing these risks.
Stevens-Johnson Syndrome (SJS) happen as a result of infection, side effects to medications or of unknown etiology. Carbamazepine is a common cause (SJS). Good history taking is crucial if clinically indicated treatment with carbamazepine. carbamazepine should be avoided with previous history of severe drug reaction like mast cell activation syndrome.
Community detection decomposes large-scale, complex networks ‘optimally’ into sets of smaller sub-networks. It finds sub-networks that have the least inter-connections and the most intra-connections. This article presents an efficient community detection algorithm that detects community structures in a weighted network by solving a multi-objective optimization problem. The whale optimization algorithm is extended to enabe it to handle multi-objective optimization problems with discrete variables and to solve the problems on parallel processors. To this end, the population’s positions are discretized using a transfer function that maps real variables to discrete variables, the initialization steps for the algorithm are modified to prevent generating unrealistic connections between variables, and the updating step of the algorithm is redefined to produce integer numbers. To identify the community configurations that are Pareto optimal, the non-dominated sorting concept is adopted. The proposed algorithm is tested on the Tennessee Eastman process to show its application and performance.
A spatially resolved 1-D pressure filtration model was developed for a slurry of edible fat crystals. The model focuses on the expression step in which a cake is compressed to force the liquid through a filter cloth. The model describes the local oil flow in the shrinking cake modeled as a porous nonlinear elastic medium existing of two phases, viz. porous aggregates and inter-aggregate liquid. Conservation equations lead to a set of two differential equations (vs time and vs a material coordinate ) for two void ratios, which are solved numerically by exploiting a finite-difference scheme. A simulation with this model results in a spatially resolved cake composition and in the outflow velocity, both as a function of time, as well as the final solid fat contents of the cake. Simulation results for various filtration conditions are compared with experimental data collected in a pilot-plant scale filter press.
The coronavirus disease 2019 (COVID-19) pandemic has presented unique challenges to international health care systems. Management of the current pandemic puts a huge strain on health care sectors and leads to new strategies conducting by health care systems in countries across the world. In the present article, we review the epidemiologic data, Iranian health care system response, as well as the effects of COVID-19 pandemic on cardiac surgery practice in Iran
Embolism spreading in dehydrating angiosperm xylem is driven by gas movement between embolised and sap-filled conduits. Here, we examine how proximity to pre-existing embolism and hydraulic segmentation affect embolism propagation. Based on the optical method, we compared xylem embolism resistance between detached leaves and leaves attached to branches, and between intact leaves and leaves with minor veins cut (n = 6 species). Moreover, we directly compared the optical and pneumatic method on detached leaves. Embolism resistance of detached leaves was significantly lower than leaves attached to stems, except for two species with all vessels ending in their petioles. Cutting of minor veins showed embolism spreading in narrow vessels near the cuts prior to wide vessels in major veins. Moreover, embolism spreading between open and intact vessels occurred at largely similar xylem water potentials than embolism spreading between intact vessels, resulting in strong similarity between the optical and pneumatic method. We conclude that embolism spreading may depend on a direct connection to pre-existing embolism as gas source, is not exclusively pressure-driven, and indirectly related to conduit size. Hydraulic segmentation, however, can minimise embolism spreading due to confined and/or poorly interconnected conduits, which may increase hydraulic safety by slowing down gas diffusion.
A patient with heart failure due to dilated ischemic cardiomyopathy presented in cardiogenic shock for institution of veno-arterial extracorporeal membrane oxygenation as a bridge to cardiac transplantation. To provide adequate venous drainage and simultaneous decompression of the left atrium (indirect left ventricular venting) a single venous cannula was placed across the interatrial septum so the distal orifice and side ports were located within the left atrium and the proximal set of side ports at the cavoatrial junction. Three-dimensional transesophageal echocardiography demonstrated utility in guiding cannula placement and appropriate positioning within the left atrium.
The aim of our study is to know the rate of restoration, the reconstitution of the forest landscape and the impact of fires on the resilience of the soils of the Tenira forest. The frequent fires in the latter are one of the main major disruptive factors for the various components of the soil, regeneration and their dynamics. The uses of remote sensing data reduce the cost and time required to assess damage in the forest. It periodically and automatically provides information on very large areas and on several spectral bands. Our approach is based on the chronic study of this forest through the use of landsat sensor data, after collecting real field data. A supervised classification was applied to the selected images in order to identify the types of soils and the vegetation. The analysis of the results obtained showed remarkable of dominance agricultural soils of the type calcisols, calcaric fluvisols and the regeneration of the forest cover in the study area. There is also an increase areas cleared for agriculture which has accelerated soil erosion in this region. Indeed, the intensification of crops requires an increase in inputs which can lead to a decrease in the biological activities of the soil, in particular earthworms. This type of vegetation existing after this fire; indicates the low water storage capacity and the high risk of erosion. The final results generally showed that the rate of recovery of land use and type of soils in the Tenira forest has changed considerably.
The current COVID-19 pandemic offers a unique opportunity to examine the utility of Internet search data in disease modelling across multiple countries. Google Trends data (GTD) indicating the volume of Internet searching on ‘Coronavirus’ were obtained for a range of European countries along with corresponding incident case numbers. Significant positive correlations between GTD with incident case numbers occurred across European countries, with the strongest correlations being obtained using contemporaneous data for most countries. GTD was then integrated into a lag distributed model; this improved model quality for both the increasing and decreasing epidemic phases.
Background Many people are used to administering their drugs with food, beverages, or herbs, which may contain chemicals that interfere with the prescribed drugs that could potentially lead to changes in their efficacy or safety and alteration in their pharmacokinetic properties. Objective To assess the extent of perception and use of food, beverages and herbs alongside with conventional drugs and their potential interactions among Jordanian society. Methods This descriptive cross-sectional survey was conducted in Jordan (20 April - 5 May 2020). The survey was developed using Google forms, validated and distributed via social media platforms. Data was analyzed using Statistical Package for Social Sciences-24. Main outcome measure Use and perception of food, beverages, herbs and their drug interactions among Jordanians. Results Of all participants (n = 789), 77.8% were females, 46.2% were 50-year-old, 69.7% were married, 70.8% were medically insured, and 51.1% had a bachelor’s degrees. Seventy percent of the study participants reported use of medicinal plants. About 66% of participants agreed that medicinal plants or herbs could treat diseases and 58.6% thought that medications could interact with drugs. In general, the participants’ knowledge about food/beverage/herb-drug interactions was considered poor. However, linear regression analysis illustrated that the level of knowledge was significantly affected (p-value <0.05) by gender, marital status, social status, the educational level, and employment sector. Conclusion Jordanians have a positive perception towards herbs and their ability to treat diseases. However, their knowledge about food/beverage-drug interactions was poor. This call needs to enhance the community awareness on food/beverage/herb-drug interactions.
While most attention in cardiovascular disease has been traditionally focused on the morphology, function and prognostic role of the left ventricle, during the last decade studies have raised awareness of the crucial role that the right ventricle plays in a variety of cardiovascular settings, including diseases primarily linked to the left ventricle. The assessment of right ventricular performance with conventional echocardiography is challenging. Novel echocardiographic techniques improve the functional assessment of the right ventricle and they showed good correlation with the gold standard represented by cardiovascular magnetic resonance. However, there is no single universally accepted parameter that accurately defines right ventricular function; hence a thorough evaluation of the right ventricle needs an integrative, multi-parametric approach. This review summarizes the traditional and innovative echocardiographic techniques used in the functional assessment of the right ventricle, focusing on the role of right ventricular dysfunction in heart failure with reduced ejection fraction and providing a perspective on recent evidence from literature.
Ischemic mitral regurgitation (IMR) is one of the common complications of coronary heart disease. The primary underlying mechanism is ventricular myopathy rather than disease of the valve itself. The decrease of myocardial blood supply will lead to myocardial damage, which will lead to the left ventricular remodeling, left ventricular enlargement, annular dilation, papillary muscle displacement and limited leaflet activity, resulting in mitral regurgitation. IMR has a certain effect on the prognosis of coronary heart disease, and the incidence rate of IMR has been increasing in recent years. IMR is a complex dynamic process, and it is a great challenge to deal with IMR. For patients with moderate or severe IMR, there are still many challenges and controversies in the choice of surgical methods. This article reviews the pathological process of left ventricular remodeling, the evaluation of IMR, the choice of mitral valve (MV) repair or replacement, and the reserve of MV function. Our review suggests that assessment of MV reserve function may be a predictor of IMR. In the future, assessment of MV reserve function may provide further useful information for evaluating MV function and determining MV repair or replacement in patients with IMR.
Objective To examine early and late pregnancy loss in women with and without polycystic ovary syndrome (PCOS) undergoing IVF/ICSI transfers. Design Retrospective cohort study. Setting Reproductive medicine center at a tertiary hospital. Population Records were reviewed for women with a positive β-hCG after IVF/ICSI treatment from May 2014 to April 2019. Methods Odds ratios (ORs) for early (13 ≤weeks) and late (13-24 weeks) pregnancy loss were calculated among women with and without PCOS for plurality of the pregnancy with adjustment for confounding factors. Main outcomes measures Early and late pregnancy loss. Results A total of 21,820 charts identified with a positive β-hCG, 2,357 (10.8%) subjects had PCOS, and 19,463 (89.2%) controls did not. Early pregnancy loss occurred in 12.4% of women with PCOS versus 12.8% in women with non-PCOS. Women with PCOS demonstrated a higher rate of late pregnancy loss (5.4% in PCOS vs 3.1% in non-PCOS, OR 1.79, 95%CI, 1.46-2.19, P<.001), regardless of the plurality of the pregnancy (one gestational sac: 4.1 vs. 2.7 percent, OR 1.56, 95%CI,1.18-2.05; ≥ two gestational sacs: 8.1 vs. 4.1 percent, OR 2.08, 95%CI,1.54-2.82, PCOS vs. Non-PCOS, respectively). Potential negative impact of PCOS was reduced to marginal level once BMI were taken into account (aOR 1.42, 95% CI, .99-2.03). BMI and maternal comorbidities were independently associated with late pregnancy loss (aOR 1.65, 95%CI, 1.26-2.17 and aOR 2.07,95%CI,1.43-3.00). Conclusions PCOS women with overweight and preexisting comorbidities would benefit from lifestyle intervention and close surveillance throughout the whole pregnancy.