Purpose: In this qualitative descriptive study, we aimed to explore the experiences of nurses providing end-of-life (EOL) care in an emergency department (ED) setting and identify the associated challenges and implications for clinical practice. Methods: Twelve nurses with over 1 year of EOL care experience in the ED were interviewed. The collected data were analyzed using thematic analysis, as outlined by Braun and Clarke. Results: Five main themes with corresponding subthemes were identified: (1) Inadequate Environment for EOL Care, including physical environment barriers for a dignified death and emotional restraint in a chaotic setting; (2) Impact of Life-Sustaining Treatment Decision Complexity, encompassing complicated dynamics of family decision-making and compromised care quality in the decision-making process; (3) Managing Care Relationships in Physician-Limited Settings, manifested as navigating limited physician communication and bearing the emotional weight of EOL care; (4) Challenges in Protecting Patients’ Rights, characterized by powerlessness in the face of silent patients and confusion from reversed decisions by families; and (5) Actualizing Compassionate EOL Care, ensuring dignity through purposeful actions and navigating environmental barriers to dignified care. Conclusion: We highlight the need for systematic changes in the ED to better support EOL care, including the development of culturally sensitive communication protocols, shared guidelines for decision-making, and improved collaboration between healthcare professionals. These findings provide valuable insights into enhancing EOL care in EDs. Future efforts should focus on policy changes, tailored education programs, and support systems that address the multifaceted needs of patients, families, and healthcare providers.

Hydrogen peroxide (H2O2) is widely used in bleaching treatments in the pulp and paper industry, in wastewater treatment, and as a food additive. However, H2O2 solutions are unstable and decompose slowly when subjected to external factors such as light, high temperatures, or metal compounds. Therefore, a simple and reliable method to measure the concentration of H2O2 is required for its proper use in various applications. We determined the concentration of an H2O2 solution by measurement at a single wavelength (249 nm) without any reagents or complex analytical procedures. In the present work, the measurable concentration of H2O2 was as low as 0.015 wt% (4.41 mM) and as high as 0.300 wt% (88.2 mM), with high linearity (99.99% at 249 nm) between the concentration of H2O2 and the optical density (OD) values. In addition, the method could be used to measure the concentration of H2O2 in a peracetic acid solution without interference from acetic acid and peracetate ion.

Mesocrystals are macroscopic structures formed by the assembly of nanoparticles that possess distinct surface structures and collective properties when compared to traditional crystalline materials. Various growth mechanisms and their unique features have promise as material design tools for diverse potential applications. This paper presents a straightforward method for metal–organic coordination-based mesocrystals using nickel ions and terephthalic acid. The coordinative compound between Ni2+ and terephthalic acid drives the particle-mediated growth mechanism, resulting in the mesocrystal formation through a mesoscale assembly. Subsequent carbonization converts mesocrystals to multidirectional interconnected graphite nanospheres along the macroscopic framework while preserving the original structure of the Ni-terephthalic acid mesocrystal. Comprehensive investigations demonstrate that multi-oriented edge sites and high crystallinity with larger interlayer spacing facilitate lithium ion transport and continuous intercalation. The resulting graphitic superparticle electrodes show superior rate capability (128.6 mAh g− 1 at 5 A g− 1) and stable cycle stability (0.052% of capacity decay per cycle), certifying it as an advanced anode material for lithium-ion batteries.

국립원예특작과학원에서는 밝은 화색과 안정적인 화형의 생 육이 우수한 빨간색 스탠다드 장미 품종을 육성하기 위해 진한 적색 스탠다드 장미 품종 ‘엔드리스러브(Endless Love)’를 모 본으로, 꽃잎수가 많고 안정적으로 가시가 적은 밝은 노란색 ‘페니레인(Penny Lane)’ 품종을 부본으로 인공교배하였다. 37 개의 교배실생을 양성해 1, 2, 3차에 걸친 특성검정 및 현장실증 을 통해 꽃이 크고 화형이 안정적이며, 재배안정성 및 생산성, 절화특성이 우수한 ‘원교 D1-390’을 최종 선발하였다. 2023년 ‘루비레드(Ruby Red)’로 명명하여 국립종자원에 품종보호출원·등록되었다. ‘루비레드’ 품종은 밝은 적색(R53C)을 가졌으 며, 꽃잎수가 32.8매, 화폭과 화고는 각각 10.9, 5.9cm로 대조 품종보다 크다. 절화장은 평균 71.7cm, 절화수명은 약 16.7일, 수량은 연간 168대/m2로 대조품종인 ‘레드스퀘어(Red Square)’ 대비 절화장이 길고 절화수명도 2배 이상 길며, 수확량도 1.4배 우수하다. 2023년 국내 육성 장미 품종 서울식물원 관람객 대상 공동평가회에서 스탠다드 장미 중 우수한 평가를 받았으며, 현 장 실증 결과 농가별로 균일하고 우수한 수량과 절화품질을 보 였다. 절화용 장미 ‘루비레드’ 품종은 밝은 적색과 우수한 화형 을 가지는 품종으로 해외 대체 품종으로 국내에서 많이 재배될 것으로 기대된다.

Sweetpotato (Ipomoea batatas L.) is a globally important food crop that is susceptible to infestation with the root-knot nematode, Meloidogyne incognita, which causes substantial crop losses. Previous transcriptomic and proteomic analyses identified several genes that displayed differential expression patterns in susceptible and resistant cultivars in response to root-knot nematode (RKN) infection. As a result of previous study, RKN infection was confirmed in the RKN-susceptible sweetpotato cultivar Yulmi. Transcriptome analysis confirmed that among the genes that respond in this process, there are many genes related to ethylene biosynthesis. Therefore, in this study, we focused on the ACC oxidase (ACO) gene, the final enzyme of ethylene biosynthesis, and analyzed the expression patterns under various abiotic stress conditions. Using transcriptome data from our previous study, various expression changes in the four ACO genes used in this study were confirmed during RKN infection. The expression of G25011|TU41034 decreased during RKN infection compared to the untreated control, while the expression of G31097|TU51009, G28360|TU46486, and G15447|TU25395 genes increased in the early stages of RKN infection. Expressions of four ACO genes in leaves of sweetpoato were investigated under abiotic stress conditions such as wounding, high salinity, dehydration, and low temperature stress treatment. Expression of the G25011|TU41034 was significantly increased under abiotic stress conditions except low temperature. G31097|TU51009 was hardly expressed under abiotic stress conditions. Although the expression pattern of G28360|TU46486 and G15447|TU25395 was slightly different depending on the type of abiotic stress, an overall increase in expression was observed. It is expected that this study will be used as basic data on how ethylene biosynthesis responds not only to nematode infection but also to various abiotic stress conditions and will be helpful in functional studies of various crops.

국내 원예작물에서 화분매개곤충의 의존도는 해마다 증가하고 있다. 우리는 사과, 딸기 등 화분매개곤충의 의존도가 높은 주요 과수와 시설작물에 대하여 화분매개곤충의 사용기술을 개발하고 이를 현장에 적용하는 연구를 수행하고 있다. 2021년부터 2022년까지 딸기, 키위 등 5가지 주요 농작물에서 화분매개벌을 적용한 결과, 딸기에서 뒤영벌의 적용결과 기존 꿀벌과 통계적으로 같은 수준의 화분매개효과를 나타내었으며, 하우스에서 농약적용시 하우스 밖으로 벌통을 위치시키는 것이 방치보다 벌의 소실을 20% 더 감소시킬 수 있었다. 인공수분 에 의존하고 있는 씨없는 수박에서 수분수 식재와 꿀벌을 이용함으로 기존 벌 방사보다 16% 착과율을 향상시킬 수 있었다. 시설고추에서 꿀벌과 뒤영벌의 혼합사용시 기존 꿀벌 방사보다 고추 수량이 10% 향상되었고, 토마토 에서 660㎡당 뒤영벌의 봉군량을 1.5배 증가시 토마토 수량은 4.4% 향상되었다. 키위는 꿀벌로 기존의 인공수분 을 충분히 대체할 수 있었고, 인건비가 60%이상 절감되었다. 또한 현재 시판중인 30종의 살충제와 27종의 살균제 에 대하여 24시간내 반수치사를 보인 농약은 각각 살충제 6종와 살균제 4종 이었다. 이어서 2023년부터 참외, 멜론, 사과, 단감에 대한 현장적용연구가 진행되고 있다.

Bee traffic at the hive entrance can be used as an important indicator of foraging activity. We investigated patterns of honeybees and bumblebees near their hives as a basis for calculating bee traffic using the image deep learning. The flight pattern near the hive differed significantly according to bee at entering and leaving the hive. Honeybees mainly showed flight that changed flight direction more than once (69.5%), whereas bumblebees mainly performed straight flight (48.7%) or had a single turn (36.5%) in flight. When bees entered the hive, honeybees primarily showed one-turn or two-turn flight patterns(88.5%), and bumblebees showed a one-turn flight pattern (48.0%). In contrast, when leaving the hive, honeybees primarily showed a straight flight pattern (63.0%), and bumblebees primarily showed a straight or one-turn pattern (90.5%). There was a significant difference in flight speed according to the flight pattern. The speed of straight flight (0.89±0.47 m/s) was 1.5 to 2.1 times faster than flight where direction changed. Therefore, our results can help determine the capturing and recognizing the flying image of bees when calculating bee traffic by image deep learning.