mass outbreak

  • 文章类型: Case Reports
    硫酸二甲酯(DMS)是一种广泛用作药物和合成原料的药物。另一方面,它具有剧毒性,需要作为有害物质进行管理和治疗。一家药厂发生了由DMS中毒引起的大规模化学烧伤。三个病人都被送到我们医院,三级紧急医疗设施,几个小时后暴露。他们的生命体征稳定,只有眼睛疼痛和喉咙痛。然而,入院后,两名患者因喉水肿需要紧急气管切开术或气管插管。通过服用类固醇来实现改善,但是一个严重受伤的病人需要延长治疗时间。DMS中毒是罕见的;然而,它可能是致命的,这取决于暴露浓度。此外,即使最初的症状很轻微,喉水肿可能会在以后发展,需要仔细监测和适当的气道干预。
    Dimethyl sulfate (DMS) is a drug widely used as a pharmaceutical and synthetic raw material. On the other hand, it is highly toxic and requires management and treatment as a hazardous substance. A mass outbreak of chemical burns resulting from DMS poisoning occurred at a drug factory. All three patients were brought to our hospital, a tertiary emergency medical facility, several hours after exposure. Their vital signs were stable, with only eye pain and a sore throat. However, after admission, two patients required emergency tracheostomy or endotracheal intubation due to laryngeal edema. Improvement was achieved through the administration of steroids, but a severely injured patient required an extended treatment period. DMS poisoning is rare; however, it can be fatal depending on the exposure concentration. Furthermore, even if the initial symptoms are mild, laryngeal edema may develop later, requiring careful monitoring and appropriate airway interventions.
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  • 文章类型: Journal Article
    气候变化通过增加干旱和热期直接挑战森林活力,间接挑战森林活力,例如,通过创造有利的条件,为群虫性昆虫的大规模爆发。过去,以苏格兰松树(PinussylvestrisL.)为主的大片森林覆盖了德国东北部的低地地区,过去已经经常受到脱叶昆虫物种的周期性大规模繁殖的影响,气候预测暗示了更具破坏性的爆发环境。未来。为了提高预测和响应能力,我们研究了广泛的生态参数,以确定与三个中心物种过去的爆发波最密切相关的参数。总的来说,我们分析了3748个变量,涵盖林分和邻域属性,现场质量,以及2002-2016年期间约75万公顷松林面积的气候条件。为了反映对不同气候的敏感性,我们计算了与相应昆虫的关键物候阶段相关的“浮动窗口”。具有最高解释力的参数来自随机森林(RF)方法的可变重要性度量,并已通过10倍交叉验证过程进行了评估。我们的发现紧密地反映了已知的特定等级模式,并表明相对变量重要性随物种而变化。虽然LymantriamonachaL.的喂养主要取决于各自林分的周围环境,DiprionpiniL.在其种群动态中几乎完全容易受到气候影响。松毛虫表现出涉及气候和森林结构参数的重要性可变的混合模式。在许多情况下,获得的统计结果支持众所周知的生态因果关系和长期人口变化动态。RF在开发的分类中提供了非常高水平的灵敏度和特异性,并且被证明是处理用于本研究的大量数据的出色工具。虽然提出的分类方法可能已经支持在爆发期间更好地预测振幅,所获得的(最重要的)变量被提出作为用于模拟所研究昆虫物种的种群动态的优选协变量。
    Climate change challenges forest vitality both directly by increasing drought and heat periods and indirectly, e.g., by creating favorable conditions for mass outbreaks of phyllophagous insects. The large forests dominated by Scots pine (Pinus sylvestris L.) that cover the lowland regions in northeast Germany have already been affected regularly by cyclic mass propagations of defoliating insect species in the past with climate projections implying an even more advantageous environment for devastating outbreaks in the future. To improve predictive and responsive capacities we have investigated a wide range of ecological parameters to identify those most strongly related to past outbreak waves of three central species. In total, we analyzed 3,748 variables covering stand and neighborhood properties, site quality, and climatic conditions for an area of roughly 750,000 ha of pine forests in the period 2002-2016. To reflect sensitivity against varying climate, we computed \"floating windows\" in relation to critical phenological phases of the respective insects. The parameters with the highest explanatory power resulted from the variable importance measures of the Random Forest (RF) methodology and have been evaluated by a 10-fold cross-validation process. Our findings closely reflect the known specific gradation patterns and show that relative variable importance varies with species. While Lymantria monacha L. feeding was mainly dependent on the surroundings of the respective stand, Diprion pini L. proved to be almost exclusively susceptible to climatic effects in its population dynamics. Dendrolimus pini L. exhibited a mixed pattern of variable importance involving both climatic and forest structure parameters. In many cases the obtained statistical results support well-known ecological cause-effect relations and long-term population change dynamics. The RF delivered very high levels of sensitivity and specificity in the developed classifications and proved to be an excellent tool to handle the large amounts of data utilized for this study. While the presented classification approach may already support a better prognosis of the amplitude during the outbreak culmination, the obtained (most important) variables are proposed as preferable covariates for modeling population dynamics of the investigated insect species.
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