Oncomelania hupensis (O. hupensis), the sole intermediate host of Schistosoma japonicum, greatly influence the prevalence and distribution of schistosomiasis japonica. The distribution area of O. hupensis has remained extensive for numerous years. This study aimed to establish a valid agent-based model of snail density and further explore the environmental conditions suitable for snail breeding. A marshland with O. hupensis was selected as a study site in Dongting Lake Region, and snail surveys were monthly conducted from 2007 to 2016. Combined with the data from historical literature, an agent-based model of snail density was constructed in NetLogo 6.2.0 and validated with the collected survey data. BehaviorSpace was used to identify the optimal ranges of soil temperature, pH, soil water content, and vegetation coverage for snail growth, development and reproduction. An agent-based model of snail density was constructed and showed a strong agreement with the monthly average snail density from the field surveys. As soil temperature increased, the snail density initially rose before declining, reaching its peak at around 21°C. There were similar variation patterns for other environmental factors. The findings from the model suggested that the optimum ranges of soil temperature, pH, soil water content and vegetation coverage were 19°C to 23 °C, 6.4 to 7.6, 42% to 75%, and 70% to 93%, respectively. A valid agent-based model of snail density was constructed, providing more objective information about the optimum ranges of environmental factors for snail growth, development and reproduction.

Environmental exposures are known to be associated with pathogen transmission and immune impairment, but the association of exposures with aetiology and severity of community-acquired pneumonia (CAP) are unclear. A retrospective observational study was conducted at nine hospitals in eight provinces in China from 2014 to 2019. CAP patients were recruited according to inclusion criteria, and respiratory samples were screened for 33 respiratory pathogens using molecular test methods. Sociodemographic, environmental and clinical factors were used to analyze the association with pathogen detection and disease severity by logistic regression models combined with distributed lag nonlinear models. A total of 3323 CAP patients were included, with 709 (21.3%) having severe illness. 2064 (62.1%) patients were positive for at least one pathogen. More severe patients were found in positive group. After adjusting for confounders, particulate matter (PM) 2.5 and 8-h ozone (O3-8h) were significant association at specific lag periods with detection of influenza viruses and Klebsiella pneumoniae respectively. PM10 and carbon monoxide (CO) showed cumulative effect with severe CAP. Pollutants exposures, especially PM, O3-8h, and CO should be considered in pathogen detection and severity of CAP to improve the clinical aetiological and disease severity diagnosis.

Understanding historical environmental determinants associated with the risk of elevated marine water contamination could enhance monitoring marine beaches in a Canadian setting, which can also inform predictive marine water quality models and ongoing climate change preparedness efforts. This study aimed to assess the combination of environmental factors that best predicts Escherichia coli (E. coli) concentration at public beaches in Metro Vancouver, British Columbia, by combining the region’s microbial water quality data and publicly available environmental data from 2013 to 2021. We developed a Bayesian log-normal mixed-effects regression model to evaluate predictors of geometric E. coli concentrations at 15 beaches in the Metro Vancouver Region. We identified that higher levels of geometric mean E. coli levels were predicted by higher previous sample day E. coli concentrations, higher rainfall in the preceding 48 h, and higher 24-h average air temperature at the median or higher levels of the 24-h mean ultraviolet (UV) index. In contrast, higher levels of mean salinity were predicted to result in lower levels of E. coli. Finally, we determined that the average effects of the predictors varied highly by beach. Our findings could form the basis for building real-time predictive marine water quality models to enable more timely beach management decision-making.

Phenotypic variation is the result of gene expression based on complex interaction between genetic and environmental factors. It is well known that genetic and environmental factors influence gene expression, but our understanding of their relative importance remains limited. To obtain a hint for the understanding of their contributions, we took advantage of monozygotic twins, as they share genetic and shared environmental factors but differ in nonshared factors, such as environmental differences and stochastic factors. In this study, we performed cap analysis of gene expression on three pairs of twins and clustered each individual based on their expression profiles of annotated genes. The dendrogram of annotated gene transcripts showed a monophyletic clade for each twin pair. We also analyzed the expression of retrotransposons, such as human endogenous retroviruses (HERVs) and long interspersed nuclear elements (LINEs), given their abundance in the genome. Clustering analyses demonstrated that HERV and LINE expression diverged even within monozygotic twin pairs. Thus, HERVs and LINEs are more susceptible to nonshared factors than annotated genes. Motif analysis of differentially expressed annotated genes suggests that specificity protein/Krüppel-like factor family transcription factors are involved in the expression divergence of annotated gene influenced by nonshared factors. Collectively, our findings suggest that expressions of annotated genes and retrotransposons are differently regulated, and that the expression of retrotransposons is more susceptible to nonshared factors than annotated genes.

This study examines the influence of founding conditions and decisions on new companies' performance, analysing how both environmental context and organisational dynamics interact to determine their success. It distinguishes between two different success indicators: survival and profitable growth. An empirical study conducted using a sample of 3,722 new agri-food companies in two different periods, one of economic stability and the other of recession, showed that founding conditions had long-lasting effects on post-entry performance. The economic context acted as a moderator of the relationship between individual factors and success. Adverse environmental conditions were also a determinant of success, making surviving firms more competitive and resilient. The results reflect the survival of the fitter principle by showing that early profitability reduced the risk of failure and made firms more likely to become profitable in the medium term. Internationalisation strategies developed organisational capabilities that created an imprint for adaptability and growth.

The world is experiencing a global push toward smart agriculture to help feed the burgeoning population by increasing food security while reducing the carbon footprint of food production. The guidelines for healthy eating have increased globally from five to seven servings of vegetables a day and this had led to the quest for a sustainable form of vegetable production that will reduce the carbon footprint and still provide consumers with the required nutrients. Microgreens contain more nutrients than some mature vegetables and can be cultivated on vertical farms, offering a different approach with the potential to resolve environmental and health challenges. Microgreens are young plantlets grown from the seeds of edible leafy vegetables and are usually eaten raw. They contain high levels of bioactive compounds and can be processed into oils to create valuable cosmetic products. Microgreens have become well-known to chefs and are gaining popularity in upmarket grocery outlets. Consequently, growing microgreens are presenting huge market opportunities worldwide. Their nutritional benefits, easy production methods and short production cycle are some of the reasons they are attractive to growers. The most important factors affecting the growth of microgreens are micro and macro-climates. One challenge to producing microgreens is that the growing environment is ideal for microbial organisms to thrive. As such, microgreens are prone to foodborne pathogens such as E. coli, Listeria and Salmonella. Consequently, the microgreens industry is facing various setbacks including product recalls from Salmonella and Listeria food poisoning outbreaks. In addition, the short shelf-life of microgreens is a serious challenge for getting microgreens to market, this is driving studies in several post-harvest treatments. This review examines the nutrient content and health benefits of microgreens and factors affecting microgreens' growth: temperature, humidity, photoperiod, fertilization, etc. and post-harvest treatments, all of which can potentially impact microbial growth, the phytochemical content and the physical appearance of microgreens bound for the market.

The myxozoan Ceratonova shasta was described from hatchery rainbow trout over 70 years ago. The parasite continues to cause severe disease in salmon and trout, and is recognized as a barrier to salmon recovery in some rivers. This review incorporates changes in our knowledge of the parasite's life cycle, taxonomy and biology and examines how this information has expanded our understanding of the interactions between C. shasta and its salmonid and annelid hosts, and how overarching environmental factors affect this host–parasite system. Development of molecular diagnostic techniques has allowed discrimination of differences in parasite genotypes, which have differing host affinities, and enabled the measurement of the spatio-temporal abundance of these different genotypes. Establishment of the C. shasta life cycle in the laboratory has enabled studies on host–parasite interactions and the availability of transcriptomic data has informed our understanding of parasite virulence factors and host defences. Together, these advances have informed the development of models and management actions to mitigate disease.

Metazoan parasite communities can experience temporal structural changes related to seasonal and/or local variations in several biotic and abiotic environmental factors. However, few studies have addressed this issue in tropical regions, where changes in water temperature are less extreme than in temperate regions, so the factors or processes that can generate variations in these parasite communities are as yet unclear. We quantified and analysed the parasite communities of 421 Lutjanus peru (Nichols & Murphy, 1922) collected from Acapulco Bay in Guerrero, Mexico, over a four-year period (August 2018 to April 2021), to identify any interannual variation due to local biotic and abiotic factors influenced by natural oceanographic phenomena, such as El Niño–Southern Oscillation, or La Niña. Twenty-five metazoan parasite taxa were recovered and identified: seven Digenea species; two Monogenea; one Cestoda; one Acanthocephala; four Nematoda; and ten of Crustacea (seven Copepoda and three Isopoda). The digeneans and copepods were the best represented parasite groups. The parasite communities were characterized by a high numerical dominance of helminth larvae. Species richness at the component community level (13 to 19 species) was similar to reported richness in other Lutjanus spp. The parasite communities of L. peru had a high variability in species composition, but low aggregate variability (e.g. species diversity), suggesting that structure of these communities may be quite stable over time. A clear interannual variation pattern was not observed, suggesting that parasite species of this host may respond differently to variations in environmental factors. Interannual variations were possibly caused by a combination of biotic (i.e. host feeding behaviour and body size) and local abiotic factors (influenced by climatic anomalies) which generated notable changes in the infection levels of several component species.

Undernutrition in children is a challenging problem in developing countries, including Ethiopia. Stunting is the most prevalent form of undernutrition. The majority of studies on childhood stunting and its associated factors focused on children, maternal and socioeconomic components. However, a few studies reported poor WaSH status and antibiotic exposure as environmental risk factors for child stunting, and the case of socio-demographic factors also lacks consistency. Concerning this, there is a lack of information in Ethiopia. Therefore, the present study assessed the association of socio-demographic, WaSH, and antibiotic exposure with stunting among under-five children. A cross-sectional study was conducted involving 340 mother–child pairs. Anthropometric data were collected using standard and calibrated height and weight scales. For factorial data, an interviewer-guided standard questionnaire was used. Logistic regression analyses were used to identify factors determining childhood stunting. In the present study, the prevalence of stunting, underweight and wasting was 14⋅7 % (95 % CI 10⋅9, 18⋅5), 4⋅4 % (95 % CI 2⋅4, 6⋅8) and 2⋅1 % (95 % CI 0⋅6, 3⋅5), respectively. Low dietary diversity, being born from a mother with an education level of secondary school, and belonging to a female-headed household were positively associated (P < 0⋅05) with stunting. The prevalence of overall undernutrition was lower (21⋅2 %) in the study area. Stunting was significantly associated with dietary diversity, maternal educational level and sex of households head. The government policy should focus on enhancing the dietary diversity of households, and encouraging women's education.

Invasive species face new selective pressures and low genetic variation caused by genetic bottlenecks and founder effects when they are introduced into novel environments. Epigenetic variation may help them to cope with these problems. Mile-a-minute (Mikania micrantha Kunth) is a highly invasive exotic weed that has seriously damaged biodiversity and agricultural ecosystems. We first adopted methylation-sensitive amplified polymorphism (MSAP) markers to investigate epigenetic variation of 21 M. micrantha populations in southern China, and further explored the effects of environmental factors on population epigenetic differentiation by correlating epigenetic and climate and soil data. Adaptive epiloci positively correlated with climate/soil variables were identified. Minimum temperature of the coldest month and mean temperature of the coldest quarter were considered as decisive factors for its distribution. Climate is presumed to play a relatively more important role than soil in shaping the adaptive epigenetic differentiation in M. micrantha. Under ongoing global warming, populations of M. micrantha are predicted to expand northward. In addition, the weed also presented higher epigenetic variation compared with genetic variation. Leaf shape variation was detected related to methylation-state change at the population level.

Research has emphasized the genetic basis of individual differences in body mass index (BMI); however, genetic factors cannot explain the rapid rise of obesity. Eating behaviors have been stipulated to be the behavioral expression of genetic risk in an obesogenic environment. In this study, we decompose variation and covariation between three key eating behaviors and BMI in a sample of 698 participants, consisting of 167 monozygotic, 150 dizygotic complete same-sex female twins and 64 incomplete pairs from a population-based twin registry in the southeast of Spain, The Murcia Twin Registry. Phenotypes were emotional eating, uncontrolled eating and cognitive restraint, measured by the Three Factor Eating Questionnaire and objectively measured BMI. Variation in eating behaviors was driven by nonshared environmental factors (range: 56%−65%), whereas shared environmental and genetic factors were secondary. All three eating behaviors were correlated with BMI (r = .19–.25). Nonshared environmental factors explained the covariations (Emotional eating–Uncontrolled eating: rE = .54, 95% CI [.43, .64]; BMI–Cognitive restraint: rE = .15, 95% CI [.01, .28]). In contrast to BMI, individual differences in eating behaviors are mostly explained by nonshared environmental factors, which also accounted for the phenotypic correlation between eating behaviors and BMI. Due to the sample size, analyses were underpowered to detect contributions of additive genetic or shared environmental factors to variation and covariation of the phenotypes. Although more research is granted, these results support that eating behaviors could be viable intervention targets to help individuals maintain a healthy weight.