Distinct Distribution of Archaea From Soil to Freshwater to Estuary: Implications of Archaeal Composition and Function in Different Environments.

In addition to inhabiting extreme territories, Archaea are widely distributed in common environments spanning from terrestrial to aquatic environments. This study investigated and compared archaeal community structures from three different habitats (representing distinct environments): agriculture soils (from farming system trials FST, PA, United States), freshwater biofilms (from White Clay Creek, PA, United States), and estuary water (Chesapeake Bay, United States). High-throughput sequencing of 16S rRNA genes indicated that Thaumarchaeota, Euryarchaeota, Nanoarchaeota, Crenarchaeota, and Diapherotrites were the commonly found dominant phyla across these three environments. Similar to Bacteria, distinct community structure and distribution patterns for Archaea were observed in soils vs. freshwater vs. estuary. However, the abundance, richness, evenness, and diversity of archaeal communities were significantly greater in soils than it was in freshwater and estuarine environments. Indicator species (or amplicon sequence variants, ASVs) were identified from different nitrogen and carbon cycling archaeal groups in soils (Nitrososphaerales, Nitrosotaleales, Nitrosopumilales, Methanomassiliicoccales, Lainarchaeales), freshwater biofilms (Methanobacteria, Nitrososphaerales) and Chesapeake Bay (Marine Group II, Nitrosopumilales), suggesting the habitat-specificity of their biogeochemical contributions to different environments. Distinct functional aspects of Archaea were also confirmed by functional predictions (PICRUSt2 analysis). Further, co-occurrence network analysis indicated that only soil Archaea formed stable modules. Keystone species (ASVs) were identified mainly from Methanomassiliicoccales, Nitrososphaerales, Nitrosopumilales. Overall, these results indicate a strong habitat-dependent distribution of Archaea and their functional partitions within the local environments.

Managing acute respiratory tract infections in children.

Respiratory tract infections (RTIs), including community-acquired pneumonia (CAP), bronchiolitis, viral-induced wheeze and croup, account for more primary care consultations than any other illness group and are the most likely reason for a parent or carer to contact a health professional. The majority of RTIs in fully immunised children are usually self-limiting. However, in a small percentage of children RTIs may become life threatening and it is crucial that all front-line health professionals are able to recognise and identify these children who are at risk of deterioration. To ensure this, fast recognition of symptoms is important, with care taken to exclude any 'red flag' features that may prompt a referral to secondary care. Nurses are well placed to reassure and support families, and to provide education regarding the facts about fever, the appropriate use of a single antipyretic medication, how to avoid dehydration in children with RTIs, and the beneficial role of immunisation in preventing infection. It is also important to explain in cases of CAP where antibiotics are necessary about how soon to expect a response, any side effects from antibiotics, and to provide 'safety net advice' on when to consider reassessment for the child. An illustrative case study is included to highlight some of the challenges that are likely to be encountered in clinical practice.

Comparison of soil quality index using three methods.

Assessment of management-induced changes in soil quality is important to sustaining high crop yield. A large diversity of cultivated soils necessitate identification development of an appropriate soil quality index (SQI) based on relative soil properties and crop yield. Whereas numerous attempts have been made to estimate SQI for major soils across the World, there is no standard method established and thus, a strong need exists for developing a user-friendly and credible SQI through comparison of various available methods. Therefore, the objective of this article is to compare three widely used methods to estimate SQI using the data collected from 72 soil samples from three on-farm study sites in Ohio. Additionally, challenge lies in establishing a correlation between crop yield versus SQI calculated either depth wise or in combination of soil layers as standard methodology is not yet available and was not given much attention to date. Predominant soils of the study included one organic (Mc), and two mineral (CrB, Ko) soils. Three methods used to estimate SQI were: (i) simple additive SQI (SQI-1), (ii) weighted additive SQI (SQI-2), and (iii) statistically modeled SQI (SQI-3) based on principal component analysis (PCA). The SQI varied between treatments and soil types and ranged between 0-0.9 (1 being the maximum SQI). In general, SQIs did not significantly differ at depths under any method suggesting that soil quality did not significantly differ for different depths at the studied sites. Additionally, data indicate that SQI-3 was most strongly correlated with crop yield, the correlation coefficient ranged between 0.74-0.78. All three SQIs were significantly correlated (r = 0.92-0.97) to each other and with crop yield (r = 0.65-0.79). Separate analyses by crop variety revealed that correlation was low indicating that some key aspects of soil quality related to crop response are important requirements for estimating SQI.