Annals of The Entomological Society of America最新文献

Bee monitoring, or widespread efforts to document bee community biodiversity, can involve data collection using lethal (specimen collections) or non-lethal methods (observations, photographs). Additionally, data can be collected by professional scientists or by volunteer participants from the general public. Collection-based methods presumably produce more reliable data with fewer biases against certain taxa, while photography-based approaches, such as data collected from public natural history platforms like iNaturalist, can involve more people and cover a broader geographic area. Few efforts have been made to quantify the pros and cons of these different approaches. We established a community science monitoring program to assess bee biodiversity across the state of Pennsylvania (USA) using specimen collections with nets, blue vane traps, and bowl traps. We recruited 26 participants, mostly Master Gardeners, from across the state to sample bees after receiving extensive training on bee monitoring topics and methods. The specimens they collected were identified to species, stored in museum collections, and the data added to public databases. Then, we compared the results from our collections to research-grade observations from iNaturalist during the same time period (2021 and 2022). At state and county levels, we found collections data documented over twice as much biodiversity and novel baseline natural history data (state and county records) than data from iNaturalist. iNaturalist data showed strong biases toward large-bodied and non-native species. This study demonstrates the value of highly trained community scientists for collections-based research that aims to document patterns of bee biodiversity over space and time.

Background: Obstructive Sleep Apnea Syndrome (OSAS) is a breathing disorder during sleep. The work was to evaluate the relationship between vasoactive and oxidative stress indicators and cardiac function in Obstructive Sleep Apnea Syndrome (OSAS) patients.

Methods: OSAS patients (n=120) were treated with CPAP from May 2021 to June 2022. According to the clinical efficacy, the patients were divided into effective and ineffective groups. Vasoactive factors and oxidative stress indices were compared between the two groups to evaluate their clinical efficacy. The changes in cardiac function indices in the two groups were tested, and the correlation between vasoactive factors and oxidative stress indices and cardiac function was analysed.

Results: The effective rate of CPAP was 63.33% (76/120). Ang II, ET-1, and MDA levels were lower, and the SOD level was higher in the effective group than in the ineffective group after treatment. The AUC of the four indicators was all greater than 0.75. LPWT and IVST values of the effective group were lower than the ineffective group. A positive correlation was identified between the levels of Ang II, ET-1, and MDA with LPWT, between levels of ET-1 and MDA with IVST, and a negative correlation between SOD with LPWT and IVST.

Conclusions: CPAP treatment can effectively improve vascular activity and reduce the oxidative stress response in OSAS patients, and the combined detection of vasoactive factors and oxidative stress indicators is valuable for evaluating the efficacy of CPAP and is related to the cardiac function of patients.

Pollinators are critical for agricultural production and food security, leading to many ongoing surveys of pollinators (especially bees) in crop and adjacent landscapes. These surveys have become increasingly important to better understand the community of potential pollinators, quantify relative insect abundance, and secure crop ecosystem services. However, as some bee populations are declining, there is a need to align and improve bee survey efforts, so that they can best meet research and conservation goals, particularly in light of the logistical and financial constraints of conducting such studies. Here, we mined the existing literature on bee surveys in or around agricultural lands to better understand how sampling methods can be optimized to maximize estimates of 2 key measures of bee communities (abundance and richness). After reviewing 72 papers spanning 20 yr of publication, we found that study duration, number of sites, sampling time, and sampling method most significantly influenced abundance, while the number of trips per year and collection method significantly influenced richness. Our analysis helps to derive thresholds, priorities, and recommendations that can be applied to future studies describing bee communities in agroecosystems.