A fast and globally optimal solution for RNA-seq quantification.

Alignment-based RNA-seq quantification methods typically involve a time-consuming alignment process prior to estimating transcript abundances. In contrast, alignment-free RNA-seq quantification methods bypass this step, resulting in significant speed improvements. Existing alignment-free methods rely on the Expectation-Maximization (EM) algorithm for estimating transcript abundances. However, EM algorithms only guarantee locally optimal solutions, leaving room for further accuracy improvement by finding a globally optimal solution. In this study, we present TQSLE, the first alignment-free RNA-seq quantification method that provides a globally optimal solution for transcript abundances estimation. TQSLE adopts a two-step approach: first, it constructs a k-mer frequency matrix A for the reference transcriptome and a k-mer frequency vector b for the RNA-seq reads; then, it directly estimates transcript abundances by solving the linear equation ATAx = ATb. We evaluated the performance of TQSLE using simulated and real RNA-seq data sets and observed that, despite comparable speed to other alignment-free methods, TQSLE outperforms them in terms of accuracy. TQSLE is freely available at https://github.com/yhg926/TQSLE.

Globally Guided Deep V-Network-Based Motion Planning Algorithm for Fixed-Wing Unmanned Aerial Vehicles.

Fixed-wing UAVs have shown great potential in both military and civilian applications. However, achieving safe and collision-free flight in complex obstacle environments is still a challenging problem. This paper proposed a hierarchical two-layer fixed-wing UAV motion planning algorithm based on a global planner and a local reinforcement learning (RL) planner in the presence of static obstacles and other UAVs. Considering the kinematic constraints, a global planner is designed to provide reference guidance for ego-UAV with respect to static obstacles. On this basis, a local RL planner is designed to accomplish kino-dynamic feasible and collision-free motion planning that incorporates dynamic obstacles within the sensing range. Finally, in the simulation training phase, a multi-stage, multi-scenario training strategy is adopted, and the simulation experimental results show that the performance of the proposed algorithm is significantly better than that of the baseline method.

Conservation priorities for endangered trees facing multiple threats around the world.

Trees are vital to the survival of numerous species and to forest ecosystem functioning. However, the current distribution, vulnerability to extinction, and conservation priorities of globally endangered trees are not well known. We mapped the global distribution of 1686 tree species listed as endangered on the International Union for the Conservation of Nature Red List and identified conservation priority for them based on species richness, life-history traits, evolutionary distinctiveness, future climate change, and intensity of human activities. We also evaluated the impacts of various threats to these endangered tree species and evaluated the effectiveness of their protection based on the percentage of the species' range inside protected areas. The worldwide distribution of endangered trees, from the tropics through temperate zones, was uneven. Most endangered tree species were not protected in their native ranges, and only 153 species were fully protected. Hotspots of tree diversity occurred primarily in the tropics, and 79.06% of these were highly vulnerable to threats. We identified 253 areas of high priority for the conservation of endangered trees that are highly threatened and insufficiently protected. In particular, 43.42% of unprotected tree species in priority areas lacked recommended conservation measures or had no associated conservation plan. The priority conservation areas and unprotected trees we identified serve as a guideline for future management underpinning the post-2020 global biodiversity framework.

Prioridades de conservación para los árboles amenazados que enfrentan múltiples amenazas en todo el mundo Resumen Los árboles son vitales para la supervivencia de numerosas especies y para el funcionamiento de los ecosistemas forestales. Sin embargo, no se conoce muy bien la distribución actual, vulnerabilidad a la extinción y prioridades de conservación de los árboles amenazados a nivel mundial. Mapeamos la distribución global de 1686 especies de árboles catalogadas como en peligro por la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza e identificamos su prioridad de conservación con base en la riqueza de especies, características de historia de vida, singularidad evolutiva, cambio climático futuro e intensidad de las actividades humanas. También evaluamos el impacto de varias amenazas sobre estas especies y analizamos la efectividad de su protección con base en el porcentaje de la distribución de la especie ubicado dentro de un área protegida. La distribución mundial de árboles en peligro, desde los trópicos y hasta las zonas templadas, fue desigual. La mayoría de las especies no estaban protegidas dentro de su distribución nativa y sólo 153 especies contaban con protección completa. Los puntos calientes de diversidad de árboles se ubicaron principalmente en los trópicos, y el 79.06% de estos tenían una vulnerabilidad alta ante las amenazas. Identificamos 253 áreas de gran prioridad para la conservación de los árboles en peligro que están amenazados y con poca protección. En particular, el 43.42% de las áreas sin protección dentro de las áreas prioritarias no contaban con las medidas recomendadas de conservación o no tenían asociado un plan de conservación. Las áreas prioritarias de conservación y los árboles sin protección que identificamos son una pauta para futuros manejos que apuntalan el marco de trabajo post-2020 para la biodiversidad.

Effect of rotavirus genetic diversity on vaccine impact.

Group A rotaviruses (RVAs) are the leading cause of gastroenteritis, causing 0.2 million deaths and several million hospitalisations globally each year. Four rotavirus vaccines (RotarixTM , RotaTeqTM , Rotavac® and ROTASIIL® ) have been pre-qualified by the World Health Organization (WHO), but the two newly pre-qualified vaccines (Rotavac® and ROTASIIL® ) are currently only in use in Palestine and India, respectively. In 2009, WHO strongly proposed that rotavirus vaccines be included in the routine vaccination schedule of all countries around the world. By the end of 2019, a total of 108 countries had administered rotavirus vaccines, and 10 countries have currently been approved by Gavi for the introduction of rotavirus vaccine in the near future. With 39% of global coverage, rotavirus vaccines have had a substantial effect on diarrhoeal morbidity and mortality in different geographical areas, although efficacy appears to be higher in high income settings. Due to the segmented RNA genome, the pattern of RVA genotypes in the human population is evolving through interspecies transmission and/or reassortment events for which the vaccine might be less effective in the future. However, despite the relative increase in some particular genotypes after rotavirus vaccine use, the overall efficacy of rotavirus mass vaccination worldwide has not been affected. Some of the challenges to improve the effect of current rotavirus vaccines can be solved in the future by new rotavirus vaccines and by vaccines currently in progress.

Globally Adaptive Longitudinal Quantile Regression with High Dimensional Compositional Covariates.

In this work, we propose a longitudinal quantile regression framework that enables a robust characterization of heterogeneous covariate-response associations in the presence of high-dimensional compositional covariates and repeated measurements of both response and covariates. We develop a globally adaptive penalization procedure, which can consistently identify covariate sparsity patterns across a continuum set of quantile levels. The proposed estimation procedure properly aggregates longitudinal observations over time, and ensures the satisfaction of the sum-zero coefficient constraint that is needed for proper interpretation of the effects of compositional covariates. We establish the oracle rate of uniform convergence and weak convergence of the resulting estimators, and further justify the proposed uniform selector of the tuning parameter in terms of achieving global model selection consistency. We derive an efficient algorithm by incorporating existing R packages to facilitate stable and fast computation. Our extensive simulation studies confirm the theoretical findings. We apply the proposed method to a longitudinal study of cystic fibrosis children where the association between gut microbiome and other diet-related biomarkers is of interest.

The global prevalence of burnout among general practitioners: a systematic review and meta-analysis.

BACKGROUND: Burnout among general practitioners (GPs) has attracted the attention of more and more researchers. An adequate understanding the prevalence and related factors of burnout to prevent and reduce burnout is necessary. This study systematically measured the global prevalence of burnout among GPs. METHODS: Eligible original studies were identified from the PubMed, Ovid Embase, Ovid Medline (R), and Web of science databases. We searched the full-time period available for each database, up to 30 September 2021. The adjusted prevalence rate was estimated using a random-effects meta-analysis. The heterogeneity was evaluated using I2 statistic. Differences by study-level characteristics were estimated via subgroup analyses and meta-regression. RESULTS: A total of 16 cross-sectional studies with 7,595 participants were included. The pooled burnout rate showed 37%, 28%, and 26% of general GPs suffer from high emotional exhaustion (EE), high depersonalization (DP), and low personal exhaustion (PA), respectively. Groups comparisons found that high EE, high DP, and low PA rate data obtained from 2001 to 2009, high DP rate data obtained from Europe, low PA rate data obtained from high-quality studies had much higher rates. CONCLUSIONS: This study demonstrated the prevalence of burnout in the GPs and alert health managers to tailor their strategies to retain this community. Targeted initiatives are needed to provide adequate GPs' well-being and maintain primary health care.

Constructing Grith Eight GC-LDPC Codes Based on the GCD FLRM Matrix with a New Lower Bound.

By connecting multiple short, local low-density parity-check (LDPC) codes with a global parity check, the globally coupled (GC) LDPC code can attain high performances with low complexities. The typical design of a local code is a quasi-cyclic (QC) LDPC for which the code length is proportional to the size of circulant permutation matrix (CPM). The greatest common divisor (GCD)-based full-length row multiplier (FLRM) matrix is constrained by a lower bound of CPM size to avoid six length cycles. In this paper, we find a new lower bound for the CPM size and propose an algorithm to determine the minimum CPM size and the corresponding FLRM matrix. Based on the new lower bound, two methods are proposed to construct the GC-QC-LDPC code of grith 8 based on the GCD based FLRM matrix. With the proposed algorithm, the CPM size can be 45% less than that given by sufficient condition of girth 8. Compared with the conventional GC-LDPC construction, the codes constructed with the proposed method have improved performance and are more flexible in code length and code rate design.

Assessing dynamic covariate effects with survival data.

Dynamic (or varying) covariate effects often manifest meaningful physiological mechanisms underlying chronic diseases. However, a static view of covariate effects is typically adopted by standard approaches to evaluating disease prognostic factors, which can result in depreciation of some important disease markers. To address this issue, in this work, we take the perspective of globally concerned quantile regression, and propose a flexible testing framework suited to assess either constant or dynamic covariate effects. We study the powerful Kolmogorov-Smirnov (K-S) and Cramér-Von Mises (C-V) type test statistics and develop a simple resampling procedure to tackle their complicated limit distributions. We provide rigorous theoretical results, including the limit null distributions and consistency under a general class of alternative hypotheses of the proposed tests, as well as the justifications for the presented resampling procedure. Extensive simulation studies and a real data example demonstrate the utility of the new testing procedures and their advantages over existing approaches in assessing dynamic covariate effects.

Quorum-sensing induced transitions between bistable steady-states for a cell-bulk ODE-PDE model with lux intracellular kinetics.

Intercellular signaling and communication are used by bacteria to regulate a variety of behaviors. In a type of cell-cell communication known as quorum sensing (QS), which is mediated by a diffusible signaling molecule called an autoinducer, bacteria can undergo sudden changes in their behavior at a colony-wide level when the density of cells exceeds a critical threshold. In mathematical models of QS behavior, these changes can include the switch-like emergence of intracellular oscillations through a Hopf bifurcation, or sudden transitions between bistable steady-states as a result of a saddle-node bifurcation of equilibria. As an example of this latter type of QS transition, we formulate and analyze a cell-bulk ODE-PDE model in a 2-D spatial domain that incorporates the prototypical LuxI/LuxR QS system for a collection of stationary bacterial cells, as modeled by small circular disks of a common radius with a cell membrane that is permeable only to the autoinducer. By using the method of matched asymptotic expansions, it is shown that the steady-state solutions for the cell-bulk model exhibit a saddle-node bifurcation structure. The linear stability of these branches of equilibria are determined from the analysis of a nonlinear matrix eigenvalue problem, called the globally coupled eigenvalue problem. The key role on QS behavior of a bulk degradation of the autoinducer field, which arises from either a Robin boundary condition on the domain boundary or from a constant bulk decay, is highlighted. With bulk degradation, it is shown analytically that the effect of coupling identical bacterial cells to the bulk autoinducer diffusion field is to create an effective bifurcation parameter that depends on the population of the colony, the bulk diffusivity, the membrane permeabilities, and the cell radius. QS transitions occur when this effective parameter passes through a saddle-node bifurcation point of the Lux ODE kinetics for an isolated cell. In the limit of a large but finite bulk diffusivity, it is shown that the cell-bulk system is well-approximated by a simpler ODE-DAE system. This reduced system, which is used to study the effect of cell location on QS behavior, is easily implemented for a large number of cells. Predictions from the asymptotic theory for QS transitions between bistable states are favorably compared with full numerical solutions of the cell-bulk ODE-PDE system.

Equipping teachers with globally competent practices: A mixed methods study on integrating global competence and teacher education.

Education leaders recommend that global competence-global citizenship mentality and knowledge development for global participation-be incorporated into school curricula. This mixed methods study examined teacher's perceptions and self-reported practices of globally competent teaching. Data was collected from teachers taking a graduate education course infused with global learning. Results suggest teachers value and desire to enact globally competent teaching but need practical direction for classroom effectuation. Data manifest all four dimensions of the Global Teaching Model (i.e., situated relevant practice, integrated global learning, critical and cultural consciousness raising, and intercultural collaboration for transformative action) to differing degrees. This study provides evidence for the Global Teaching Model as a prospective framework and emphasizes the critical dimension when internationalizing teacher education.

Energy-Level Jumping Algorithm for Global Optimization in Compressive Sensing-Based Target Localization.

Target localization is one of the essential tasks in almost applications of wireless sensor networks. Some traditional compressed sensing (CS)-based target localization methods may achieve low-precision target localization because of using locally optimal sparse solutions. Solving global optimization for the sparse recovery problem remains a challenge in CS-based target localization. In this paper, we propose a novel energy-level jumping algorithm to address this problem, which achieves high-precision target localization by solving the globally optimal sparse solution of l p -norm ( 0 < p < 1 ) minimization. By repeating the process of energy-level jumping, our proposed algorithm establishes a global convergence path from an initial point to the global minimizer. Compared with existing CS-based target localization methods, the simulation results show that our localization algorithm obtain more accurate locations of targets with the significantly reduced number of measurements.

Global Pediatric Drug Development.

BACKGROUND: The EU Paediatric Regulation was introduced in 2007. In the United States, specific paediatric legislation has existed for even longer. This overview describes the similarities and differences in the legislation and provides input on how to achieve a global, harmonized pediatric development plan. OBJECTIVES: The overview aims to investigate, through discussions and case examples, how to achieve pediatric medicines development fulfilling the expectations of the authorities as well as sponsors. METHODS: The pediatric legislation used in the European Union and United States are compared, and case studies for pediatric development plans where a global harmonized plan was eventually achieved are discussed. RESULTS: The case studies demonstrate some difficulties in getting to the goal of globally aligned pediatric plan development; however, recent initiatives from EMA and FDA are to a large degree addressing such challenges. CONCLUSIONS: Global pediatric drug development is a evolving field, and with recent initiatives from the European Medicines Agency and US Food and Drug Administration, this goal is definitively attainable. (Curr Ther Res Clin Exp. 2019; 80:XXX-XXX).

A rapid 3D fat-water decomposition method using globally optimal surface estimation (R-GOOSE).

PURPOSE: To improve the graph model of our previous work GOOSE for fat-water decomposition with higher computational efficiency and quantitative accuracy. METHODS: A modification of the GOOSE fat water decomposition algorithm is introduced while the global convergence guarantees of GOOSE are still inherited to minimize fat-water swaps and phase wraps. In this paper, two non-equidistant graph optimization frameworks are proposed as a single-step framework termed as rapid GOOSE (R-GOOSE), and a multi-step framework termed as multi-scale R-GOOSE (mR-GOOSE). Both frameworks contain considerably less graph connectivity than GOOSE, resulting in a great computation reduction thus making it readily applicable to multidimensional fat water applications. The quantitative accuracy and computational time of the novel frameworks are compared with GOOSE on the 2012 ISMRM Challenge datasets to demonstrate the improvement in performance. RESULTS: Both frameworks accomplish the same level of high accuracy as GOOSE among all datasets. Compared to 100 layers in GOOSE, only 8 layers were used in the new graph model. Computational time is lowered by an order of magnitude to around 5 s for each dataset in (mR-GOOSE), R-GOOSE achieves an average run-time of 8 s. CONCLUSION: The proposed method provides fat-water decomposition results with a lower run-time and higher accuracy compared to the previously proposed GOOSE algorithm. Magn Reson Med 79:2401-2407, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Biometrical evaluation of the performance of the revised OECD Test Guideline 402 for assessing acute dermal toxicity.

A comprehensive biometrical assessment was conducted to compare the performance of multiple test designs for acute dermal systemic toxicity to support the animal welfare update to the original OECD Test Guideline (TG) 402 for acute dermal toxicity. The test designs evaluated included: (1) two, three, or five animals per dose group (2) evident toxicity or lethality endpoints and (3) absence or presence of a one-animal sighting study. The revision of TG 402 respected the 3R principles (replace, reduce, refine) of animal testing. The results demonstrate that the TG 402 test design can be optimised with reduced animal numbers per test group, such that a scenario of two animals per group following a sighting study at a starting dose of 200 mg/kg bw (unless further information is available to better define the starting dose) would provide a classification which in most cases is conservative, without compromising both the statistical ability of the study to assess dermal toxicity, or the relevant classification outcome.

On Optimal Cooperative Sensing with Energy Detection in Cognitive Radio.

In this paper, we propose an optimal cooperative sensing technique for cognitive radio to maximize sensing performance based on energy detection. In most spectrum sensing research, many cooperation methods have been proposed to overcome the sensitivity of energy detection so that both primary and secondary users are better off in terms of spectral efficiency. However, without assigning a proper sensing threshold to each sensing node, cooperation may not be effective unless the received average primary user signal-to-noise ratio (SNR) is identical. We show that equal threshold energy detection severely degrades sensing performance when cooperative sensing nodes experience diverse average SNRs, and it is not unusual for even single-node sensing to be better than cooperative sensing. To this end, based on the Neyman-Pearson criterion we formulate an optimization problem to maximize sensing performance by using optimized thresholds. Since this is a non-convex optimization problem, we provide a condition that convexifies the problem and thus serves as a sufficient optimality condition. We find that, perhaps surprisingly, in all practical cases one may consider this condition satisfied, and thus optimal sensing performance can be obtained. Through extensive simulations, we demonstrate that the proposed technique achieves a globally optimal solution, i.e., it maximizes the probability of detection under practical operating parameters such as the target probability of false alarm, different SNRs, and the number of cooperative sensing nodes.

Hazard banding in compliance with the new Globally Harmonised System (GHS) for use in control banding tools.

Many control banding tools use hazard banding in risk assessments for the occupational handling of hazardous substances. The outcome of these assessments can be combined with advice for the required risk management measures (RMMs). The Globally Harmonised System of Classification and Labelling of Chemicals (GHS) has resulted in a change in the hazard communication elements, i.e. Hazard (H) statements instead of Risk-phrases. Hazard banding schemes that depend on the old form of safety information have to be adapted to the new rules. The purpose of this publication is to outline the rationales for the assignment of hazard bands to H statements under the GHS. Based on this, this publication proposes a hazard banding scheme that uses the information from the safety data sheets as the basis for assignment. The assignment of hazard bands tiered according to the severity of the underlying hazards supports the important principle of substitution. Additionally, the set of assignment rules permits an exposure-route-specific assignment of hazard bands, which is necessary for the proposed route-specific RMMs. Ideally, all control banding tools should apply the same assignment rules. This GHS-compliant hazard banding scheme can hopefully help to establish a unified hazard banding strategy in the various control banding tools.

Hexyl cinnamal: consideration of skin-sensitizing properties and suitability as a positive control.

BACKGROUND: Hexyl cinnamal (HCA) is a widely used fragrance chemical, the low skin-sensitizing potency of which has made it a common choice for the use as a positive control for predictive toxicology assays. However, HCA is commonly negative in current candidate in vitro alternatives test methods. OBJECTIVE: To review the evidence that HCA is a classifiable skin sensitizer against the standards set by the Globally Harmonized Scheme (GHS), and determine whether it represents an appropriate choice for a positive control substance for predictive testing. METHODS: Using the GHS criteria, mechanistic data, and in vitro, in vivo and human evidence relating to HCA and skin sensitization have been reviewed. RESULTS: The chemistry of HCA is consistent with potential for skin sensitization and predictive in vivo test data support this conclusion. However, the human data are relatively sparse, consistent with HCA possessing a low capacity to induce skin sensitization under conditions of consumer exposures. CONCLUSIONS: Using GHS criteria (and applying a precautionary approach) HCA would classify as a weaker skin sensitizer than predicted by the local lymph node assay (LLNA). However, given the human experience, it is necessary to consider whether HCA is the most appropriate choice for use as a positive regulatory control.

Estimating the Size of the Hidden Population of COVID-19.

INTRODUCTION: An asymptomatic population has the same infection as symptomatic individuals, so these individuals can unknowingly spread the virus. It is not possible to predict the rate of epidemic growth by considering only the identified isolated or hospitalized population. In this study, we want to estimate the size of the COVID-19 population, based on information derived from patients visiting medical centers. So, individuals who do not receive a formal diagnosis in those medical centers can be considered as hidden. METHODOLOGY: To estimate the Bayesian size of the hidden population of COVID-19 a respondentdriven sampling (RDS) method was used. Twenty-three people infected with COVID-19 seeds and who had positive PCR test results were selected as seeds. These participants were asked whether any of their friends and acquaintances who had COVID-19 did not visit a medical center or hid their illness. Access to other patients was gained through friendship and kinship, hence allowing the sampling process to proceed. RESULTS: Out of 23 selected seeds, only 15 seeds remained in the sample and the rest were excluded due to not participating in the further sampling process. After 5 waves, 50 people with COVID-19 who had hidden their disease and were not registered in the official statistics were included in the sample. It was estimated that 12,198 people were infected with COVID-19 in Khalkhal city in 2022. This estimate was much higher than recorded in the official COVID-19 statistics. CONCLUSIONS: The study findings indicate that the estimated 'true' numbers of COVID-19 patients in one town in Iran were significantly higher compared to the official numbers. The RDS method can help capture the potential size of infections in further pandemics or outbreaks globally.

A GHS-consistent approach to health hazard classification of petroleum substances, a class of UVCB substances.

The process streams refined from petroleum crude oil for use in petroleum products are among those designated by USEPA as UVCB substances (unknown or variable composition, complex reaction products and biological materials). They are identified on global chemical inventories with unique Chemical Abstract Services (CAS) numbers and names. The chemical complexity of most petroleum substances presents challenges when evaluating their hazards and can result in differing evaluations due to the varying level of hazardous constituents and differences in national chemical control regulations. Global efforts to harmonize the identification of chemical hazards are aimed at promoting the use of consistent hazard evaluation criteria. This paper discusses a systematic approach for the health hazard evaluation of petroleum substances using chemical categories and the United Nations (UN) Globally Harmonized System (GHS) of classification and labeling. Also described are historical efforts to characterize the hazard of these substances and how they led to the development of categories, the identification of potentially hazardous constituents which should be considered, and a summary of the toxicology of the major petroleum product groups. The use of these categories can increase the utility of existing data, provide better informed hazard evaluations, and reduce the amount of animal testing required.