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Objective(s): The present study aims to establish and evaluate a rat model for hangover headaches caused by alcoholic drinks.Materials and Methods: Chronic migraine (CM) model rats were divided into 3 groups, and intragastrically administered alcoholic drinks (sample A, B, or C) to simulate hangover headache attacks. The withdrawal threshold for the hind paw/face and the thermal latency of hind paw withdrawal were detected after 24 hr. Serum was collected from the periorbital venous plexus of rats in each group, and enzymatic immunoassays were used to determine the serum levels of calcitonin gene-related peptide (CGRP), substance P (SP), and nitric oxide (NO).Results: Compared with the control group, the mechanical hind paw pain threshold was significantly lower in rats administered Samples A and B after 24 hr; however, no significant difference was observed across groups for the thermal pain threshold. The mechanical threshold for periorbital pain was only significantly reduced in rats administered Sample A. Immunoassays further indicated that serum levels of SP in the group administered Sample A were significantly higher than those in the control group; the serum levels of NO and CGRP were significantly higher in the group of rats receiving Sample B.Conclusion: We successfully developed an effective and safe rat model for investigating alcohol drink induced hangover headaches. This model could be used to investigate the mechanisms associated with hangover headaches for the development of novel and promising candidates for the future treatment or prophylaxis of hangover headaches.

Objective: To investigate differences in infection control awareness, and related implementation of measures between anti-epidemic medical staff and workers during the outbreak of novel coronavirus (COVID-19) infection, and to propose corresponding countermeasures. Methods: A self-designed questionnaire on the practice of infection control and implement were conducted, and 250 medical staff and workers participating in the anti-epidemic work in our hospital from March to April 2022 were investigated online. Results: A total of 208 valid questionnaires were recovered, of which 192 were valid questionnaires, including 158 medical staff (82.3%) and 34 (17.7%) workers. Before entering the isolation point, the proportion of workers vs medical staff who knew the knowledge about COVID-19, hospital infection control procedures, standardized use of masks, awareness of occupational post-exposure disposal procedures, awareness of sensory control and implementation of sensory control in living areas were 58.8% vs 89.2%, 67.6% vs 91.1%, 82.4% vs 98.7%, (58.8% vs 98.7%), (47.1% vs 98.7%), (47.1% vs 94.3%) (P

Abstract Background Pelvic girdle pain (PGP) is a multifactorial condition with a partly unknown etiology. This condition can be mentally and physically compromising both during and after pregnancy. To provide all-around preventive measures to improve the recovery from PGP, it is a necessity for obstetricians and orthopaedists to develop predictive studies about the worse prognosis for this condition. Therefore, this study aims to determine whether personality traits can predict the consequences of long-term pregnancy-related PGP. Methods This was a prospective study conducted from January 2015 to August 2018. A total of 387 pregnant women were enrolled in this study. According to whether they had experienced PGP during the past 4 weeks, the subjects were classified into no PGP and PGP groups. Persistent PGP after the pregnancy was defined as a recurrent or continuous visual analog score (VAS) pain rating of ≥3 for more than 1 week. The Quick Big Five Personality Test (QBFPT) was used to assess personality traits. Data were obtained by mail or in the clinic. The authors collected data including age, BMI, educational level, annual household income, cesarean delivery, breastfeeding, unexpected sex of the baby, parity, sick leave, no or rare ability to take rest breaks at work, and PGP in the previous pregnancy. Results Of 387 included women, 264 subjects experienced PGP during the pregnancy with a mean age of 26.3 ± 4.5 years. A total of 80 of 264 (30.3%) women experienced persistent PGP after the pregnancy. Persistent PGP after the pregnancy was associated with higher levels of neuroticism (OR = 2.12, P = 0.001). Comparing women with persistent PGP, those who reported higher levels of extraversion and conscientiousness were more likely to recover from this condition (OR = 0.65, P = 0.001; OR = 0.78, P = 0.010, respectively). Besides, neuroticism was positively associated with higher pain scores (r = 0.52, P = 0.005). However, extraversion and conscientiousness domains showed negative correlations with pain score (r = − 0.48, P = 0.003; r = − 0.36, P = 0.001). Conclusions Personality traits were significantly associated with the outcomes of PGP.

The AMEOS (Assimilating Multi-source Earth Observation Satellite data for crop pests and diseases monitoring and forecasting) project aims to bring together cutting edge research to provide pest and disease monitoring and forecast information, integrating multi-source information (Earth Observation, meteorological, entomological and plant pathological, etc.) to support decision making in the sustainable management of insect pests and diseases in agriculture. The main objective of the project, that is, improving crop diseases and pests monitoring and forecasting, will be achieved by utilizing EO data, developing new algorithms, and combining new and existing data from multi-source EO sensors to produce high spatial and temporal land surface information. The project foresees the assessment of the possibility of using available satellite images datasets to assess the evolution of diseases on permanent (olive groves, vineyards), or row crops (wheat) in Italy and China. The paper describes the results of the research activity which focused on: ① improving the classification of the agricultural areas devoted to winter wheat and olive trees, starting from what has been made available from the Corine Land Cover initiative; ② developing an approach suitable to be automated for estimating trees by using Sentinel 2 images; ③ developing a new index, REDSI (consisting of Red, Re1, and Re3 bands), for detecting and monitoring yellow rust infection of winter wheat at the canopy and regional scale. The research activity covers the: Province of Lecce, that is the Italian area strongly affected, since 2015, by the Xylella fastidiosa disease which causes a rapid decline in olive plantations. Province of Anyang, Neihuang county, which was affected by the yellow rust disease in the spring 2017.

In the space rendezvous and docking, real-time measurement of the position and attitude between the visual sensor on the tracking spacecraft and the characteristic target on the target spacecraft is needed, and the premise is to quickly and accurately identify the feature targets. In this paper, a fast recongnition algorithm of four concentric ring feature targets is proposed. Firstly, the algorithm uses the optimized Otsu for image segmentation. Then the contour is extracted by the connected region recognition method. Finally, according to the relationship between the circumference and the area of the circle, the circle is determined, and the least square method is used to fit the circle and extract the center of the feature circle. The experimental results show that the method can recognize feature targets accurately and quickly within 2 m distance, and the computational efficiency to the method is improved by nearly 10 times compared with the pre-optimization algorithm.