Combinatorial characterization of bacterial taxa-driven differences in the microbiome of oyster reefs.

Oyster reefs are invaluable ecosystems that provide a wide array of critical ecosystem services, including water filtration, coastal protection, and habitat provision for various marine species. However, these essential habitats face escalating threats from climate change and anthropogenic stressors. To combat these challenges, numerous oyster restoration initiatives have been undertaken, representing a global effort to preserve and restore these vital ecosystems. A significant, yet poorly understood, component of oyster reefs is the microbial communities. These communities account for a substantial proportion of marine reefs and are pivotal in driving key biogeochemical processes. Particularly, the environmental microbiome plays a crucial role in supporting the health and resilience of oyster populations. In our study, we sought to shed light on the microbiome within oyster reef ecosystems by characterizing the abundance, and diversity of microorganisms in the soil, biofilm, and oysters in 4 sites using a combinatorial approach to identify differentially abundant microbes by sample type and by sampling location. Our investigation revealed distinct microbial taxa in oysters, sediment and biofilm. The maximum Shannon Index indicated a slightly increased diversity in Heron's Head (5.47), followed by Brickyard park (5.35), Dunphy Park (5.17) and Point Pinole (4.85). This is likely to be driven by significantly higher oyster mortality observed at Point Pinole during routine monitoring and restoration efforts. Interestingly Ruminococcus, Streptococcus, Staphylococcus, Prevotella, Porphyromonas, Parvimonas, Neisseria, Lactococcus, Haemophilus, Fusobacterium, Dorea, Clostridium, Campylobacter, Bacteroides, and Akkermansia were positively associated with the biofilm. Yet we have limited understanding of their beneficial and/or detrimental implications to oyster growth and survival. By unraveling the intricate relationships in microbial composition across an oyster reef, our study contributes to advancing the knowledge needed to support effective oyster reef conservation and restoration efforts.

SARS-CoV-2 RNA and N Antigen Quantification via Wastewater at the Campus Level, Building Cluster Level, and Individual-Building Level.

Monitoring wastewater for SARS-CoV-2 from populations smaller than those served by wastewater treatment plants may help identify small spatial areas (subsewersheds) where COVID-19 infections are present. We sampled wastewater from three nested locations with different sized populations within the same sewer network at a university campus and quantified SARS-CoV-2 RNA using reverse transcriptase droplet digital polymerase chain reaction (PCR). SARS-CoV-2 RNA concentrations and/or concentrations normalized by PMMoV were positively associated with laboratory-confirmed COVID-19 cases for both the sewershed level and the subsewershed level. We also used an antigen-based assay to detect the nucleocapsid (N) antigen from SARS-CoV-2 in wastewater samples at the sewershed level. The N antigen was regularly detected at the sewershed level, but the results were not associated with either laboratory-confirmed COVID-19 cases or SARS-CoV-2 RNA concentrations. The results of this study indicate that wastewater monitoring based on quantification of SARS-CoV-2 RNA using PCR-based methods is associated with COVID-19 cases at multiple geographic scales within the subsewershed level and can serve to aid the public health response.

Internet addiction in students: a cause of concern.

The Internet was originally designed to facilitate communication and research activities. However, the dramatic increase in the use of the Internet in recent years has led to pathological use (Internet addiction). This study is a preliminary investigation of the extent of Internet addiction in school children 16-18 years old in India. The Davis Online Cognition Scale (DOCS) was used to assess pathological Internet use. On the basis of total scores obtained (N = 100) on the DOCS, two groups were identified--dependents (18) and non-dependents (21), using mean +/- 1/2 SD as the criterion for selection. The UCLA loneliness scale was also administered to the subjects. Significant behavioral and functional usage differences were revealed between the two groups. Dependents were found to delay other work to spend time online, lose sleep due to late-night logons, and feel life would be boring without the Internet. The hours spent on the Internet by dependents were greater than those of non-dependents. On the loneliness measure, significant differences were found between the two groups, with the dependents scoring higher than the non-dependents.