Comparative transcriptomics reveals commonalities and differences in the genetic underpinnings of a floral dimorphism

Distyly, a floral dimorphism associated with heteromorphic self-incompatibility and controlled by the S-locus supergene, evolved independently multiple times. Comparative analyses of the first transcriptome atlas for the main distyly model, Primula veris, with other distylous species produced the following findings. A set of 53 constitutively expressed genes in P. veris did not include any of the housekeeping genes commonly used to normalize gene expression in qPCR experiments. The S-locus gene CYP$^{T}$ acquired its role in controlling style elongation via a change in expression profile. Comparison of genes differentially expressed between floral morphs revealed that brassinosteroids and auxin are the main hormones controlling style elongation in P. veris and Fagopyrum esculentum, respectively. Furthermore, shared biochemical pathways might underlie the expression of distyly in the distantly related P. veris, F. esculentum and Turnera subulata, suggesting a degree of correspondence between evolutionary convergence at phenotypic and molecular levels. Finally, we provide the first evidence supporting the previously proposed hypothesis that distyly supergenes of distantly related species evolved via the recruitment of genes related to the phytochrome-interacting factor (PIF) signaling network. To conclude, this is the first study that discovered homologous genes involved in the control of distyly in distantly related taxa

Startup’s critical failure factors dynamic modeling using FCM

The emergence of startups and their influence on a country's economic growth has become a significant concern for governments. The failure of these ventures leads to substantial depletion of financial resources and workforce, resulting in detrimental effects on a country's economic climate. At various stages of a startup's lifecycle, numerous factors can affect the growth of a startup and lead to failure. Numerous scholars and authors have primarily directed their attention toward studying the successes of these ventures. Previous research review of critical failure factors (CFFs) reveals a dearth of research that comprehensively investigates the introduction of all failure factors and their interdependent influences. This study investigates and categorizes the failure factors across various stages of a startup's life cycle to provide a deeper insight into how they might interact and reinforce one another. Employing expert perspectives, the authors construct fuzzy cognitive maps (FCMs) to visualize the CFFs within entrepreneurial ventures and examine these factors' influence across the four growth stages of a venture. Our primary aim is to construct a model that captures the complexities and uncertainties surrounding startup failure, unveiling the concealed interconnections among CFFs. The FCMs model empowers entrepreneurs to anticipate potential failures under diverse scenarios based on the dynamic behavior of these factors. The proposed model equips entrepreneurs and decision-makers with a comprehensive understanding of the collective influence exerted by various factors on the failure of entrepreneurial ventures

Combining population genomics and ecological niche modeling to assess taxon limits between Carex jemtlandica and C. lepidocarpa

Carex section Ceratocystis (Cyperaceae) is a group of recently evolved plant species, in which hybridization is frequent, introgression is documented, taxonomy is complex, and morphological boundaries are vague. Within this section, a unified taxonomic treatment of the Carex jemtlandica-Carex lepidocarpa species complex does not exist, and Norway may currently be the sole country accepting species rank for both. Carex jemtlandica is mainly confined to Fennoscandia and is thus a Fennoscandian conservation responsibility. This motivated us to test the principal hypothesis that both C. jemtlandica and C. lepidocarpa represent evolutionary significant units, and that both deserve their current recognition at species level. We investigated their evolutionary distinctiveness in Norway, using restriction site-associated DNA sequencing and ecological niche modeling. Our genomic results reveal two genetic clusters, largely corresponding to C. jemtlandica and C. lepidocarpa that also remain distinct in sympatry, despite clear indications of ongoing hybridization and introgression. The ecological niche modeling suggests that they occupy different environmental niches. Jointly, our results clearly show that C. jemtlandica and C. lepidocarpa represent separately evolving entities that should qualify recognition as evolutionary significant units. Given the high level of introgression compared to other hybridizing species pairs in Carex we recommend treating C. jemtlandica as a subspecies of C. lepidocarpa.Peer reviewe

The Relationship between Spiritual Well-being and Family Cohesion in Patients with Thalassemia Major

Introduction: This study was conducted to investigate the relationship between spiritual well-being and family cohesion among people with thalassemia Major. Methods: This cross-sectional study was conducted on 101 patients with thalassemia major of Dezful Large Hospital in 2015. Data were collected by three questionnaires: demographic data, Standard Spiritual Well-being Scale by Daaleman and Frey and Moos Family Cohesion Scale. The data was analyzed using SPSS version 18 statistical test, Pearson correlation and linear regression with a significance level of p< 0.05. Results: The average score of spiritual well-being and self-efficacy subscales were 9.66 +/- 34.58 and 9.66 +/- 14.68, respectively; which indicates the average level of these variables. Linear regression test results also showed that there was a statistically significant (p< 0.05) relationship between spiritual well-being and family cohesion (B=0.25) and between selfefficacy and family cohesion (B=0.24); but there was no significant relationship between life scheme and family cohesion (B=0.16) (p=0.10). Conclusion: In this study it was observed that a significant direct correlation exists between spiritual well-being and family cohesion. The role of the family as the main supportive institution against the challenges of life is undeniable. Hence, by increasing the level of spiritual well-being of the patients some steps can be taken to promote the cohesion of patients' families in order to decrease their spiritual and physical problems

The genomes of Darwin's primroses reveal chromosome-scale adaptive introgression and differential permeability of species boundaries

Introgression is an important source of genetic variation that can determine species adaptation to environmental conditions. Yet, definitive evidence of the genomic and adaptive implications of introgression in nature remains scarce. The widespread hybrid zones of Darwin's primroses (Primula elatior, Primula veris, and Primula vulgaris) provide a unique natural laboratory for studying introgression in flowering plants and the varying permeability of species boundaries. Through analysis of 650 genomes, we provide evidence of an introgressed genomic region likely to confer adaptive advantage in conditions of soil toxicity. We also document unequivocal evidence of chloroplast introgression, an important precursor to species-wide chloroplast capture. Finally, we provide the first evidence that the S-locus supergene, which controls heterostyly in primroses, does not introgress in this clade. Our results contribute novel insights into the adaptive role of introgression and demonstrate the importance of extensive genomic and geographical sampling for illuminating the complex nature of species boundaries

Whole-genome analyses disentangle reticulate evolution of primroses in a biodiversity hotspot

Biodiversity hotspots, such as the Caucasus mountains, provide unprecedented opportunities for understanding the evolutionary processes that shape species diversity and richness. Therefore, we investigated the evolution of Primula sect. Primula, a clade with a high degree of endemism in the Caucasus. We performed phylogenetic and network analyses of whole-genome resequencing data from the entire nuclear genome, the entire chloroplast genome, and the entire heterostyly supergene. The different characteristics of the genomic partitions and the resulting phylogenetic incongruences enabled us to disentangle evolutionary histories resulting from tokogenetic vs cladogenetic processes. We provide the first phylogeny inferred from the heterostyly supergene that includes all species of Primula sect. Primula. Our results identified recurrent admixture at deep nodes between lineages in the Caucasus as the cause of non-monophyly in Primula. Biogeographic analyses support the 'out-of-the-Caucasus' hypothesis, emphasizing the importance of this hotspot as a cradle for biodiversity. Our findings provide novel insights into causal processes of phylogenetic discordance, demonstrating that genome-wide analyses from partitions with contrasting genetic characteristics and broad geographic sampling are crucial for disentangling the diversification of species-rich clades in biodiversity hotspots

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation