Honey bee queen health is unaffected by contact exposure to pesticides commonly found in beeswax

Collective decision-making during reproduction in social insects: a conceptual model for queen supersedure in honey bees (Apis mellifera)

Insect societies have served as excellent examples for co-ordinated decision-making. The production of sexuals is the most important group decision that social insects face since it affects both direct and indirect fitness. The behavioral processes by which queens are selected have been of particular interest since they are the primary egg layers that enable colony function. As a model system, previous research on honey bee reproduction has focused on swarming behavior and nest site selection. One significant gap in our knowledge of the collective decision-making process over reproduction is how daughter queens simply replace old or failing queens (=supersedure) rather than being reared for the purposes of colony fission (=swarming) or queen loss (=emergency queen rearing). Here, I present a conceptual model that provides a framework for understanding the collective decisions by colonies to supersede their mother queens, as well as provide some key recommendations on future empirical work.

Systematic approaches to machine learning models for predicting pesticide toxicity

Pesticides play an important role in modern agriculture by protecting crops from pests and diseases. However, the negative consequences of pesticides, such as environmental contamination and adverse effects on human and ecological health, underscore the importance of accurate toxicity predictions. To address this issue, artificial intelligence models have emerged as valuable methods for predicting the toxicity of organic compounds. In this review article, we explore the application of machine learning (ML) for pesticide toxicity prediction. This review provides a detailed summary of recent developments, prediction models, and datasets used for pesticide toxicity prediction. In this analysis, we compared the results of several algorithms that predict the harmfulness of various classes of pesticides. Furthermore, this review article identified emerging trends and areas for future direction, showcasing the transformative potential of machine learning in promoting safer pesticide usage and sustainable agriculture.

Exposure of chlorothalonil and acetamiprid reduce the survival and cause multiple internal disturbances in Apis mellifera larvae reared in vitro

Background: Chlorothalonil and acetamiprid are chemical pesticides commonly used in agricultural production and have been shown to have negative effects on bee's fitness. Despite many studies have revealed that honey bee (Apis mellifera L.) larvae are posting a high risk on exposure to pesticides, but the toxicology information of chlorothalonil and acetamiprid on bee larvae remain limited. Results: The no observed adverse effect concentration (NOAEC) of chlorothalonil and acetamiprid for honey bee larvae were 4 μg/mL and 2 μg/mL, respectively. Except for CarE, the enzymic activities of GST and P450 were not influenced by chlorothalonil at NOAEC, while chronic exposure to acetamiprid slightly increased the activities of the three tested enzymes at NOAEC. Further, the exposed larvae showed significantly higher expression of genes involved in a series of different toxicologically relevant process following, including caste development (Tor (GB44905), InR-2 (GB55425), Hr4 (GB47037), Ac3 (GB11637) and ILP-2 (GB10174)), immune system response (abaecin (GB18323), defensin-1 (GB19392), toll-X4 (GB50418)), and oxidative stress response (P450, GSH, GST, CarE). Conclusion: Our results suggest that the exposure to chlorothalonil and acetamiprid, even at concentrations below the NOAEC, showed potentially effects on bee larvae's fitness, and more important synergistic and behavioral effects that can affect larvae fitness should be explored in the further.

Access to prairie pollen affects honey bee queen fecundity in the field and lab

Beekeepers experience high annual losses of colonies, with environmental stressors like pathogens, reduced forage, and pesticides as contributors. Some factors, like nutritional stress from reduced flower abundance or diversity, are more pronounced in agricultural landscapes where extensive farming limits pollen availability. In addition to affecting other aspects of colony health, quantity and quality of pollen available are important for colony brood production and likely for queen egg laying. While some US beekeepers report >50% of colony loss due to queen failure, the causes of poor-quality queens are poorly understood. Access to resources from native prairie habitat is suggested as a valuable late-season resource for honey bees that can reverse colony growth declines, but it is not clear how prairie forage influences queen egg laying. We hypothesized that the pollen resources present in an extensive Midwestern corn/soybean agroecosystem during the critical late season period affect honey bee queen egg laying and that access to native prairies can increase queen productivity. To test this, we designed a field experiment in Iowa, keeping colonies in either soybean or prairie landscapes during a critical period of forage dearth, and we quantified queen egg laying as well as pollen collection (quantity and species). Then, using pollen collected in the field experiments, we created representative dietary mixtures, which we fed to bees using highly controlled laboratory cages to test how consumption of these diets affected the egg laying of naive queens. In two out of three years, queens in prairies laid more eggs compared to those in soybean fields. Pollen quantity did not vary between the two landscapes, but composition of species did, and was primarily driven by collection of evening primrose (Oenothera biennis). When pollen representative of the two landscapes was fed to caged bees in the laboratory queens fed prairie pollen laid more eggs, suggesting that pollen from this landscape plays an important role in queen productivity. More work is needed to tease apart the drivers of these differences, but understanding how egg laying is regulated is useful for designing landscapes for sustainable pollinator management and can inform feeding regimes for beekeepers.

Safety and efficacy of totally minimally invasive right colectomy in the obese patients: a multicenter propensity score-matched analysis

Despite the well-known benefits of the minimally invasive approach for the right colon cancer treatment, less is known about its feasibility and advantages in morbid obese patients. The aim of this study is to compare the postoperative outcomes after totally minimally invasive right colectomy between the obese and non-obese population. Data derived from a prospectively maintained multicenter colorectal database were analysed, dividing the enrolled patients into two groups: obese (BMI > 29.99) patient group and non-obese patient group. Data about gender, age, American Society of Anesthesiologists (ASA) Score, tumor characteristics, operative time, anastomosis time, extraction site, incision length, intraoperative complications, postoperative complications, postoperative recovery, specimen length and retrieved nodes were taken to assess the achievement of the oncologic standards. After a propensity score matching, a total of 184 patients was included, 92 in each group. No differences were found in terms of demographic data and tumor characteristics. Intraoperative data showed a significant difference in terms of anastomosis time in favour of non-obese group (p < 0.0001). No intraoperative complications were recorded and no conversion was needed in both groups. No differences were found in terms of postoperative complications. There were no differences in terms of first mobilization (p = 0.745), time to first flatus (p = 0.241) time to tolerance to liquid and solid diet (p = 0.241 and p = 0.06) and length of hospital stay (p = 0.817). The analysis of oncologic outcomes demonstrated adequate results in both groups. The results obtained by our study confirmed the feasibility and safety of the totally minimally invasive approach even in obese population.

Drone honey bees are disproportionately sensitive to abiotic stressors despite expressing high levels of stress response proteins

Drone honey bees (Apis mellifera) are the obligate sexual partners of queens, and the availability of healthy, high-quality drones directly affects a queen's fertility and productivity. Yet, our understanding of how stressors affect adult drone fertility, survival, and physiology is presently limited. Here, we investigated sex biases in susceptibility to abiotic stressors (cold stress, topical imidacloprid exposure, and topical exposure to a realistic cocktail of pesticides). We found that drones (haploid males) were more sensitive to cold and imidacloprid exposure than workers (sterile, diploid females), but the cocktail was not toxic at the concentrations tested. We corroborated this lack of cocktail toxicity with in-hive exposures via pollen feeding. We then used quantitative proteomics to investigate protein expression profiles in the hemolymph of topically exposed workers and drones, and found that 34 proteins were differentially expressed in exposed drones relative to controls, but none were differentially expressed in exposed workers. Contrary to our hypothesis, we show that drones express surprisingly high baseline levels of putative stress response proteins relative to workers. This suggests that drones' stress tolerance systems are fundamentally rewired relative to workers, and susceptibility to stress depends on more than simply gene dose or allelic diversity.