Epidemiology of yellow fever virus in humans,arthropods, and non-human primates in sub-Saharan Africa: A systematic review and meta-analysis

Yellow fever (YF) has re-emerged in the last two decades causing several outbreaks in endemic countries and spreading to new receptive regions. This changing epidemiology of YF creates new challenges for global public health efforts. Yellow fever is caused by the yellow fever virus (YFV) that circulates between humans, the mosquito vector, and non-human primates (NHP). In this systematic review and meta-analysis, we review and analyse data on the case fatality rate (CFR) and prevalence of YFV in humans, and on the prevalence of YFV in arthropods, and NHP in sub-Saharan Africa (SSA). We performed a comprehensive literature search in PubMed, Web of Science, African Journal Online, and African Index Medicus databases. We included studies reporting data on the CFR and/or prevalence of YFV. Extracted data was verified and analysed using the random effect meta-analysis. We conducted subgroup, sensitivity analysis, and publication bias analyses using the random effect meta-analysis while I² statistic was employed to determine heterogeneity. This review was registered with PROSPERO under the identification CRD42021242444. The final meta-analysis included 55 studies. The overall case fatality rate due to YFV was 31.1% (18.3–45.4) in humans and pooled prevalence of YFV infection was 9.4% (6.9–12.2) in humans. Only five studies in West and East Africa detected the YFV in mosquito species of the genus Aedes and in Anopheles funestus. In NHP, YFV antibodies were found only in members of the Cercopithecidae family. Our analysis provides evidence on the ongoing circulation of the YFV in humans, Aedes mosquitoes and NHP in SSA. These observations highlight the ongoing transmission of the YFV and its potential to cause large outbreaks in SSA. As such, strategies such as those proposed by the WHO’s Eliminate Yellow Fever Epidemics (EYE) initiative are urgently needed to control and prevent yellow fever outbreaks in SSA.     

SARS-CoV-2-specific T cells associate with inflammation and reduced lung function in pulmonary post-acute sequalae of SARS-CoV-2

As of January 2022, at least 60 million individuals are estimated to develop post-acute sequelae of SARS-CoV-2 (PASC) after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While elevated levels of SARS-CoV-2-specific T cells have been observed in non-specific PASC, little is known about their impact on pulmonary function which is compromised in the majority of these individuals. This study compares frequencies of SARS-CoV-2-specific T cells and inflammatory markers with lung function in participants with pulmonary PASC and resolved COVID-19 (RC). Compared to RC, participants with respiratory PASC had between 6- and 105-fold higher frequencies of IFN-γ- and TNF-α-producing SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells in peripheral blood, and elevated levels of plasma CRP and IL-6. Importantly, in PASC participants the frequency of TNF-α-producing SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells, which exhibited the highest levels of Ki67 indicating they were activity dividing, correlated positively with plasma IL-6 and negatively with measures of lung function, including forced expiratory volume in one second (FEV¹), while increased frequencies of IFN-γ-producing SARS-CoV-2-specific T cells associated with prolonged dyspnea. Statistical analyses stratified by age, number of comorbidities and hospitalization status demonstrated that none of these factors affect differences in the frequency of SARS-CoV-2 T cells and plasma IL-6 levels measured between PASC and RC cohorts. Taken together, these findings demonstrate elevated frequencies of SARS-CoV-2-specific T cells in individuals with pulmonary PASC are associated with increased systemic inflammation and decreased lung function, suggesting that SARS-CoV-2-specific T cells contribute to lingering pulmonary symptoms. These findings also provide mechanistic insight on the pathophysiology of PASC that can inform development of potential treatments to reduce symptom burden.     

Discrete modeling for integration and analysis of large-scale signaling networks

Most biological processes are orchestrated by large-scale molecular networks which are described in large-scale model repositories and whose dynamics are extremely complex. An observed phenotype is a state of this system that results from control mechanisms whose identification is key to its understanding. The Biological Pathway Exchange (BioPAX) format is widely used to standardize the biological information relative to regulatory processes. However, few modeling approaches developed so far enable for computing the events that control a phenotype in large-scale networks.Here we developed an integrated approach to build large-scale dynamic networks from BioPAX knowledge databases in order to analyse trajectories and to identify sets of biological entities that control a phenotype. The Cadbiom approach relies on the guarded transitions formalism, a discrete modeling approach which models a system dynamics by taking into account competition and cooperation events in chains of reactions. The method can be applied to every BioPAX (large-scale) model thanks to a specific package which automatically generates Cadbiom models from BioPAX files.The Cadbiom framework was applied to the BioPAX version of two resources (PID, KEGG) of the Pathway Commons database and to the Atlas of Cancer Signalling Network (ACSN). As a case-study, it was used to characterize sets of biological entities implicated in the epithelial-mesenchymal transition. Our results highlight the similarities between the PID and ACSN resources in terms of biological content, and underline the heterogeneity of usage of the BioPAX semantics limiting the fusion of models that require curation. Causality analyses demonstrate the smart complementarity of the databases in terms of combinatorics of controllers that explain a phenotype. From a biological perspective, our results show the specificity of controllers for epithelial and mesenchymal phenotypes that are consistent with the literature and identify a novel signature for intermediate states.     

Demographic responses to climate‐driven variation in habitat quality across the annual cycle of a migratory bird species

The demography and dynamics of migratory bird populations depend on patterns of movement and habitat quality across the annual cycle. We leveraged archival GPS‐tagging data, climate data, remote‐sensed vegetation data, and bird‐banding data to better understand the dynamics of black‐headed grosbeak (Pheucticus melanocephalus) populations in two breeding regions, the coast and Central Valley of California (Coastal California) and the Sierra Nevada mountain range (Sierra Nevada), over 28 years (1992–2019). Drought conditions across the annual cycle and rainfall timing on the molting grounds influenced seasonal habitat characteristics, including vegetation greenness and phenology (maturity dates). We developed a novel integrated population model with population state informed by adult capture data, recruitment rates informed by age‐specific capture data and climate covariates, and survival rates informed by adult capture–mark–recapture data and climate covariates. Population size was relatively variable among years for Coastal California, where numbers of recruits and survivors were positively correlated, and years of population increase were largely driven by recruitment. In the Sierra Nevada, population size was more consistent and showed stronger evidence of population regulation (numbers of recruits and survivors negatively correlated). Neither region showed evidence of long‐term population trend. We found only weak support for most climate–demographic rate relationships. However, recruitment rates for the Coastal California region were higher when rainfall was relatively early on the molting grounds and when wintering grounds were relatively cool and wet. We suggest that our approach of integrating movement, climate, and demographic data within a novel modeling framework can provide a useful method for better understanding the dynamics of broadly distributed migratory species.     

Species specificity and intraspecific variation in the chemical profiles of Heliconius butterflies across a large geographic range

In many animals, mate choice is important for the maintenance of reproductive isolation between species. Traits important for mate choice and behavioral isolation are predicted to be under strong stabilizing selection within species; however, such traits can also exhibit variation at the population level driven by neutral and adaptive evolutionary processes. Here, we describe patterns of divergence among androconial and genital chemical profiles at inter‐ and intraspecific levels in mimetic Heliconius butterflies. Most variation in chemical bouquets was found between species, but there were also quantitative differences at the population level. We found a strong correlation between interspecific chemical and genetic divergence, but this correlation varied in intraspecific comparisons. We identified “indicator” compounds characteristic of particular species that included compounds already known to elicit a behavioral response, suggesting an approach for identification of candidate compounds for future behavioral studies in novel systems. Overall, the strong signal of species identity suggests a role for these compounds in species recognition, but with additional potentially neutral variation at the population level.     

Signs of stabilisation and stable coexistence

Many empirical studies motivated by an interest in stable coexistence have quantified negative density dependence, negative frequency dependence, or negative plant–soil feedback, but the links between these empirical results and ecological theory are not straightforward. Here, we relate these analyses to theoretical conditions for stabilisation and stable coexistence in classical competition models. By stabilisation, we mean an excess of intraspecific competition relative to interspecific competition that inherently slows or even prevents competitive exclusion. We show that most, though not all, tests demonstrating negative density dependence, negative frequency dependence, and negative plant–soil feedback constitute sufficient conditions for stabilisation of two‐species interactions if applied to data for per capita population growth rates of pairs of species, but none are necessary or sufficient conditions for stable coexistence of two species. Potential inferences are even more limited when communities involve more than two species, and when performance is measured at a single life stage or vital rate. We then discuss two approaches that enable stronger tests for stable coexistence‐invasibility experiments and model parameterisation. The model parameterisation approach can be applied to typical density‐dependence, frequency‐dependence, and plant–soil feedback data sets, and generally enables better links with mechanisms and greater insights, as demonstrated by recent studies.     

Environmental Supply Chain Cooperation and Its Effect on the Circular Economy Practice‐Performance Relationship Among Chinese Manufacturers

Due to resource scarcity and environmental degradation, a new development concept emphasizing environmental concerns, called the circular economy (CE), has been enacted in legislation in China. This environmental management concept can be implemented at three levels, namely, region, industrial zone, and individual enterprise, with the objective of boosting economic development while lessening environmental and resource challenges. Environmental supply chain cooperation (ESCC), an approach that utilizes customer and supplier cooperation in environmental management, has been initiated among Chinese enterprises. Using survey data collected from 396 Chinese manufacturers, we examine the role of ESCC practices in influencing the relationship between implementing CE practices and the achievement of performance outcomes by testing the moderation and mediation effects of ESCC practices on the CE practice‐performance relationship through hierarchical regression analysis. Our data analyses indicate that ESCC practices are useful by moderation and, in some cases, essential by mediation, for Chinese manufacturers seeking to realize the performance targets desired in CE practices. The results highlight the need for Chinese manufacturers to improve supply chain coordination in their implementation of CE. On the policy side, our research findings suggest that ESCC practices are beneficial and, in some cases, necessary for the development of CE in China.     

Inhibition of mitochondrial complex I improves glucose metabolism independently of AMPK activation

Accumulating evidences showed metformin and berberine, well‐known glucose‐lowering agents, were able to inhibit mitochondrial electron transport chain at complex I. In this study, we aimed to explore the antihyperglycaemic effect of complex I inhibition. Rotenone, amobarbital and gene silence of NDUFA13 were used to inhibit complex I. Intraperitoneal glucose tolerance test and insulin tolerance test were performed in db/db mice. Lactate release and glucose consumption were measured to investigate glucose metabolism in HepG2 hepatocytes and C2C12 myotubes. Glucose output was measured in primary hepatocytes. Compound C and adenoviruses expressing dominant negative AMP‐activated protein kinase (AMPK) α1/2 were exploited to inactivate AMPK pathway. Cellular NAD⁺/NADH ratio was assayed to evaluate energy transforming and redox state. Rotenone ameliorated hyperglycaemia and insulin resistance in db/db mice. It induced glucose consumption and glycolysis and reduced hepatic glucose output. Rotenone also activated AMPK. Furthermore, it remained effective with AMPK inactivation. The enhanced glycolysis and repressed gluconeogenesis correlated with a reduction in cellular NAD⁺/NADH ratio, which resulted from complex I suppression. Amobarbital, another representative complex I inhibitor, stimulated glucose consumption and decreased hepatic glucose output in vitro, too. Similar changes were observed while expression of NDUFA13, a subunit of complex I, was knocked down with gene silencing. These findings reveal mitochondrial complex I emerges as a key drug target for diabetes treatment. Inhibition of complex I improves glucose homoeostasis via non‐AMPK pathway, which may relate to the suppression of the cellular NAD⁺/NADH ratio.