Biosafety and Health最新文献_第2页

Metagenomics research on the gut microbiota of the Marmota himalayana of the Sanjiangyuan National Nature Reserve in Qinghai Province, China 青海省三江源国家级自然保护区喜马拉雅旱獭肠道微生物群的宏基因组学研究

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.09.003

Ying Ma , Ziyan Li , Pengbo Liu , Youwen Wei , Ke Jiang , Yujuan Yue , Aiping Zhang , Wenlong Wang , Lingwen Li , Penghui Zhang , Xingyue Gu , Qiyong Liu , Liang Lu

With the improvement of transportation and the rise of tourism on the Qinghai-Xizang Plateau, the scope of human activities has continuously expanded, increasing opportunities for contact with wildlife, also exacerbating the outbreak rate of zoonotic emerging infectious diseases. Currently, research on the gut microbiota of wildlife, especially Marmota himalayana (M. himalayana), which are reservoir hosts for plague, is scarce. In this study, we investigated the composition, function, and regional variations of the gut microbiota in M. himalayana based on the metagenomic sequencing of 45 fecal samples from the Sanjiangyuan National Nature Reserve in Qinghai Province. The results indicated that at the phylum level, the dominant bacterial phyla in the gut microbiota of the M. himalayana were Firmicutes, Bacteroidota, and Proteobacteria, collectively accounting for 74.16 % of the community. At the genus level, the top three most abundant genera were Alistipes (11.86 % ± 1.56 %), Bacteroides (6.68 % ± 0.95 %), and Clostridium (4.92 % ± 1.04 %). Kyoto encyclopedia of genes and genomes (KEGG) database annotation results showed that the most enriched functional categories of the marmot gut microbiota were metabolism, genetic information processing (GIP), and environmental information processing (EIP). These active functions played a crucial role in food digestion, nutrient absorption, metabolic balance maintenance, and pathogen defense, aiding the marmot in better adapting to the extreme environment of the Qinghai-Xizang Plateau. The study provided critical insights into host-microbe interactions, highlighting the role of microbiota in the survival and conservation of endangered species in unique habitats.

随着青藏高原交通运输的完善和旅游业的兴起，人类活动范围不断扩大，增加了与野生动物接触的机会，也加剧了人畜共患新发传染病的爆发。目前，对野生动物肠道菌群的研究较少，特别是对鼠疫宿主喜马拉雅旱獭（M.喜马拉雅山）的研究较少。本研究通过对青海省三江源国家级自然保护区45份粪便样本进行宏基因组测序，研究了喜马拉雅高原肠道微生物群的组成、功能和区域差异。结果表明，在门水平上，喜马拉雅山地山地肠道菌群优势菌门为厚壁菌门、拟杆菌门和变形菌门，共占群落总数的74.16%；在属水平上，丰度最高的前3个属分别为Alistipes（11.86%±1.56%）、Bacteroides（6.68%±0.95%）和Clostridium（4.92%±1.04%）。京都基因与基因组百科（KEGG）数据库注释结果显示，旱獭肠道微生物群最丰富的功能类别是代谢、遗传信息处理（GIP）和环境信息处理（EIP）。这些活性功能在食物消化、营养吸收、代谢平衡维持和病原体防御等方面发挥着至关重要的作用，帮助旱獭更好地适应青藏高原的极端环境。该研究提供了宿主-微生物相互作用的重要见解，突出了微生物群在独特栖息地濒危物种生存和保护中的作用。

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引用次数: 0

Global trends, age-period-cohort analysis, and future projections of diarrhea burden: Findings from the Global Burden of Disease Study 2021 腹泻负担的全球趋势、年龄期队列分析和未来预测：来自2021年全球疾病负担研究的结果

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.09.005

Mengjiao Xie , Yang Song , Jing Tao , Mengnan Jiang , Yang Liu , Io Hong Cheong , Zisis Kozlakidis , Zhaorui Chang , Qiang Wei

Diarrhea is currently a prominent global public health issue. This study evaluated recent trends in the global burden of diarrhea and projected future changes over the next decade. Using the diarrhea data from the global burden of disease (GBD) 2021, this study assessed the temporal trends using Joinpoint regression and explored the impact of different factors using age-period-cohort modeling. Decomposition analysis identified drivers of disease burden changes, and the Bayesian age-period-cohort (BAPC) model predicted future trends. Additionally, health inequalities were measured by the inequality slope index and the concentration index. Results show a downward trend in the global burden of diarrhea since 1990. Age-period-cohort analysis suggests that the risk of incidence decreases with age until the age of 20, but increases with age after the age of 60. Risk of death from diarrhea was highest in children aged 0–4 and also increasesd after the age of 60. Decomposition identified population growth as the primary driver of burden changes, and BAPC projections indicated that the burden of diarrhea will continue declining. However, significant inequalities persist, with lower sociodemographic index (SDI) countries bearing a disproportionately high burden, although these gaps have decreased over time. The conclusion highlights that children under 5 and adults over 60 face the highest risks of diarrhea incidence and death. More attention should be paid to these populations, and effective public health policies should be implemented.

腹泻是当前一个突出的全球公共卫生问题。这项研究评估了全球腹泻负担的最新趋势，并预测了未来十年的变化。利用全球疾病负担（GBD） 2021的腹泻数据，本研究使用Joinpoint回归评估了时间趋势，并使用年龄-时期-队列模型探讨了不同因素的影响。分解分析确定了疾病负担变化的驱动因素，贝叶斯年龄-时期-队列（BAPC）模型预测了未来趋势。此外，通过不平等斜率指数和浓度指数来衡量健康不平等。结果显示，自1990年以来，全球腹泻负担呈下降趋势。年龄-时期-队列分析表明，20岁前发病率随年龄增长而降低，60岁后发病率随年龄增长而增加。0-4岁儿童死于腹泻的风险最高，60岁以后也增加。分解确定人口增长是负担变化的主要驱动因素，BAPC预测表明腹泻负担将继续下降。然而，显著的不平等仍然存在，社会人口指数（SDI）较低的国家承受着不成比例的高负担，尽管这些差距随着时间的推移而缩小。结论强调，5岁以下儿童和60岁以上成年人腹泻发病率和死亡风险最高。应更多地关注这些人群，并实施有效的公共卫生政策。

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引用次数: 0

Interactions between zoonotic pathogens and infectious disease spread: Why understanding mechanisms and modelling matters more than ever 人畜共患病原体和传染病传播之间的相互作用：为什么理解机制和建模比以往任何时候都重要

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.07.008

Naizhe Li , Sunxiao Ruan , Huaiyu Tian

Interactions among zoonotic pathogens play a critical role in shaping disease transmission, severity, and public health responses. However, the mechanisms and population-level consequences of these interactions remain underexplored in current modelling frameworks. This review aims to synthesize emerging evidence and address key scientific challenges in understanding how pathogen interactions influence transmission dynamics and mathematical modelling, with a focus on zoonotic and other cocirculating pathogens. In this review, we synthesize current evidence on synergistic, antagonistic, and neutral interactions between zoonotic and other cocirculating pathogens. We explore the underlying mechanisms of these interactions, such as transmission enhancement, immune modulation, and resource competition, at both the individual and population levels. We further review mathematical models to illustrate how these interaction features, such as transmission pathways, coinfection histories, cross-immunity, and superspreading potential, could be incorporated into epidemiological frameworks to increase our understanding of the community transmission of infections. Particular attention is given to the challenges of parameter estimation, incomplete surveillance data, and the difficulty of modelling interactions across scales and pathogen types. Understanding and modelling these interactions is essential for predicting outbreak trajectories, designing effective vaccination strategies, and improving early-warning systems. We conclude by calling for enhanced integration of empirical data and mechanistic modelling, especially in the context of emerging zoonoses and postpandemic preparedness. This review provides a structured perspective to support future interdisciplinary efforts aimed at managing cocirculating pathogens and mitigating their public health impact.

人畜共患病原体之间的相互作用在形成疾病传播、严重程度和公共卫生反应方面起着关键作用。然而，在目前的建模框架中，这些相互作用的机制和人口水平的后果仍未得到充分探讨。本综述旨在综合新出现的证据，并解决理解病原体相互作用如何影响传播动力学和数学模型的关键科学挑战，重点关注人畜共患和其他共循环病原体。在这篇综述中，我们综合了目前关于人畜共患病和其他共循环病原体之间的增效、拮抗和中性相互作用的证据。我们在个体和种群水平上探讨了这些相互作用的潜在机制，如传播增强、免疫调节和资源竞争。我们进一步回顾了数学模型，以说明如何将这些相互作用的特征，如传播途径、共同感染史、交叉免疫和超传播潜力，纳入流行病学框架，以增加我们对社区感染传播的理解。特别注意参数估计的挑战，不完整的监测数据，以及跨尺度和病原体类型的相互作用建模的困难。了解这些相互作用并建立模型对于预测疫情发展轨迹、设计有效的疫苗接种策略和改进早期预警系统至关重要。最后，我们呼吁加强经验数据和机制建模的整合，特别是在新出现的人畜共患病和大流行后防范的背景下。本综述提供了一个结构化的视角，以支持未来旨在管理共循环病原体和减轻其公共卫生影响的跨学科努力。

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引用次数: 0

Predict SARS-CoV-2 genome interactions based on RNA language models 基于RNA语言模型预测SARS-CoV-2基因组相互作用

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.09.006

Weiwei Shen , Yixue Li , Liucun Zhu , Tao Huang

As a single-stranded ribonucleic acid (RNA) virus, the replication, transcription, and interactions with host cells of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on a complex network of RNA-RNA interactions. Investigating local RNA-RNA interactions is crucial for elucidating how viruses regulate their own functions and respond to host immune responses. This study aims to explore the application of machine learning techniques in analyzing and predicting RNA-RNA interactions within the coronavirus genome. Using virion RNA in situ conformation sequencing technology(vRIC-Seq) data and advanced computational models, we evaluated potential interactions between viral RNA fragments. By employing a variety of traditional machine learning algorithms, including traditional One-hot coding, Word2Vec models, a number of different neural network architectures, and the RNAErnie language modeling framework, we achieved significant predictive accuracy in determining the presence or absence of interactions. Furthermore, this approach provides a novel framework for investigating RNA-RNA interactions in other viral systems, thereby opening new avenues for the development of targeted therapeutic strategies against viral infections. The integration of computational models substantially enhances our comprehension of complex biological processes and represents a promising trajectory for future virology research. The source codes and models are freely available at https://github.com/VV1025/RNA-language-models.

作为一种单链核糖核酸（RNA）病毒，严重急性呼吸综合征冠状病毒2 （SARS-CoV-2）的复制、转录以及与宿主细胞的相互作用依赖于一个复杂的RNA-RNA相互作用网络。研究局部RNA-RNA相互作用对于阐明病毒如何调节自身功能和响应宿主免疫反应至关重要。本研究旨在探索机器学习技术在分析和预测冠状病毒基因组内RNA-RNA相互作用中的应用。利用病毒粒子RNA原位构象测序技术（vRIC-Seq）数据和先进的计算模型，我们评估了病毒RNA片段之间潜在的相互作用。通过采用各种传统的机器学习算法，包括传统的One-hot编码、Word2Vec模型、许多不同的神经网络架构和RNAErnie语言建模框架，我们在确定交互存在与否方面取得了显著的预测准确性。此外，该方法为研究其他病毒系统中的RNA-RNA相互作用提供了一个新的框架，从而为开发针对病毒感染的靶向治疗策略开辟了新的途径。计算模型的整合大大提高了我们对复杂生物过程的理解，并代表了未来病毒学研究的一个有希望的轨迹。源代码和模型可以在https://github.com/VV1025/RNA-language-models上免费获得。

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引用次数: 0

Beyond evolution: De novo designed protein toolkit rewriting the rules of synthetic biology 超越进化：从头设计的蛋白质工具箱重写了合成生物学的规则

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.09.004

Guohao Zhang , Chuanyang Liu , Wenying Li , Jiajie Lu, Ang Li, Lingyun Zhu

Artificial intelligence (AI)-driven de novo protein design is revolutionizing synthetic biology by facilitating the first-principle rational engineering of protein-based functional modules unbound by known structural templates and evolutionary constraints, enabling a diverse range of applications. Expressing these novel, structurally unprecedented proteins within cellular systems inherently adds complexity to their functional unpredictability. Robust biosafety and bioethics evaluations are therefore required to address potential risks such as immune reactions, cellular pathway disruptions, and environmental persistence. We systematically analyse the computational frameworks underpinning this revolution and highlight the capability of de novo proteins to act as a modular toolkit for synthetic biology. Looking forward, we envision integrating closed-loop validation with multi-omics profiling for comprehensive risk assessments along with a hierarchical design framework for advancing the future of synthetic biology – from the creation of tailored de novo functional protein modules and structure-guided rational genetic circuits design to the development of full-synthetic cellular systems, thereby establishing a scalable path from protein design to system-level implementation.

人工智能（AI）驱动的从头蛋白质设计正在彻底改变合成生物学，它促进了基于蛋白质的功能模块的第一性原理合理工程，不受已知结构模板和进化约束的约束，从而实现了各种应用。在细胞系统中表达这些新颖的、结构上前所未有的蛋白质，固有地增加了其功能不可预测性的复杂性。因此，需要进行强有力的生物安全和生物伦理评估，以应对免疫反应、细胞通路中断和环境持久性等潜在风险。我们系统地分析了支撑这场革命的计算框架，并强调了新生蛋白作为合成生物学模块化工具包的能力。展望未来，我们设想将闭环验证与多组学分析结合起来，进行全面的风险评估，以及推进合成生物学未来的分层设计框架——从量身定制的从头开始的功能蛋白质模块的创建和结构引导的合理遗传电路设计到全合成细胞系统的开发，从而建立一条从蛋白质设计到系统级实现的可扩展路径。

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引用次数: 0

Large language models for biological sequence analysis in infectious disease research 传染病研究中生物序列分析的大型语言模型

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-10-01 DOI: 10.1016/j.bsheal.2025.09.007

Junyu Luo , Xiyang Cai , Yixue Li

Large language models (LLMs) have emerged as transformative tools in infectious disease research, offering unprecedented capabilities in analyzing biological sequences. This review summarizes three primary types of biological LLMs, including protein language models, genomic language models, and multimodal models, highlighting their architectures and applications. These models are revolutionizing key areas such as pathogen identification, evolutionary surveillance, host-pathogen prediction, and therapeutic development by enabling the interpretation of complex genomic and proteomic data at an unparalleled scale. While recent advancements are remarkable, challenges persist in data quality, long-context processing, model interpretability, and biosafety considerations. Understanding the potential and limitations of LLMs is crucial for leveraging them effectively in infectious disease research while ensuring responsible development and deployment.

大型语言模型（llm）已经成为传染病研究的变革性工具，在分析生物序列方面提供了前所未有的能力。本文综述了蛋白质语言模型、基因组语言模型和多模态模型三种主要类型的生物法学硕士，重点介绍了它们的结构和应用。这些模型通过以无与伦比的规模解释复杂的基因组和蛋白质组学数据，正在彻底改变病原体鉴定、进化监测、宿主-病原体预测和治疗开发等关键领域。虽然最近的进展是显著的，但在数据质量、长期上下文处理、模型可解释性和生物安全考虑方面仍然存在挑战。了解法学硕士的潜力和局限性对于在传染病研究中有效利用它们，同时确保负责任的开发和部署至关重要。

引用次数: 0

Development of an identity test for COVID-19 mRNA vaccines using SARS-CoV-2 NAT standard 基于SARS-CoV-2 NAT标准的COVID-19 mRNA疫苗鉴定试验的建立

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-08-01 DOI: 10.1016/j.bsheal.2025.07.007

Miran Jo , Eunjo Lee , Ho Jung Oh , Jin Tae Hong , Kyung Hee Sohn

Despite the development of messenger ribonucleic acid (mRNA) vaccines for the infectious novel coronavirus 2 (SARS-CoV-2), further research on test methods is required to ensure their quality as well as rapid and effective approval for release to the market. During the current national lot release testing, identity tests cannot be conducted on other products using primers, probes, and in-house reference materials provided by the manufacturer and specific to one vaccine, because their sequences do not match. When key reagents and reference materials are dependent on the manufacturer in this way, difficulties in national lot release approval—which serves as an additional step for the government to verify product quality—arise if the manufacturer does not provide them. In this study, we aimed to develop a quantitative polymerase chain reaction (qPCR) assay by using commercially available nucleic acid amplification test (NAT) reference material and a dye instead of a probe along with primers that were newly designed in this study. It can be applied to both vaccines. This study suggests a test method that can be applied when the in-house reference standard for the identity test, a major step to confirm the quality of vaccines, is not secured.

尽管针对传染性新型冠状病毒2 （SARS-CoV-2）的信使核糖核酸（mRNA）疫苗已经开发出来，但仍需要进一步研究检测方法，以确保其质量，并快速有效地批准上市。在目前的国家批号放行检测期间，由于序列不匹配，不能使用制造商提供的特定于一种疫苗的引物、探针和内部参考材料对其他产品进行鉴定检测。当关键试剂和标准物质以这种方式依赖于制造商时，如果制造商不提供，国家批号批准（这是政府验证产品质量的额外步骤）就会出现困难。在本研究中，我们旨在利用市售的核酸扩增试验（NAT）参比物和染料代替探针，以及本研究新设计的引物，建立定量聚合酶链反应（qPCR）检测方法。它可以应用于两种疫苗。本研究提出了一种检测方法，可以在确认疫苗质量的主要步骤身份检测的内部参考标准没有得到保障时应用。

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引用次数: 0

A metagenomic approach for microbial risk assessment and source attribution in high-risk ports of entry environments 高风险入境口岸环境中微生物风险评估和来源归因的宏基因组方法

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-08-01 DOI: 10.1016/j.bsheal.2025.07.001

Xiaozhou He , Ran Zhang , Jie Dong , Wei Zhen , Li Zhu , Junkai Ren , Xuejun Ma , Feng Wang , Shuang Zhang , Ke Xu , Feng Qiu , Qiudong Su , Jian’an He , Weimin Zhou , Guizhen Wu

The epidemiological characteristics of emerging infectious disease outbreaks in recent years have underscored the critical importance of controlling imported infectious diseases. In this study, we implemented dynamic tracking of microbial invasions by monitoring environmental microbes at the customs and ports. From July to September 2024, a total of 126 environmental samples were collected from three ports of entry in Shenzhen, China. Metagenomic analysis detected 55 non-viral microbial communities and 12 viral taxa. Among these, 26.8 % of the bacteria, 100 % of the fungi, 71.4 % of the protists, and none of the archaea exhibited potential pathogenic properties. Viruses were the most prevalent, including bacteriophages (100 %), unclassified viruses (96.8 %), giant viruses (27.8 %), fungal viruses (4.8 %), and vertebrate viruses (1.6 %). No statistical differences were observed in viral distribution across areas (χ² = 18.70, P = 0.541), sites (χ² = 14.02, P = 0.597), or ports of entry (χ² = 10.27, P = 0.247). However, viral distribution varied significantly across three sampling months (χ² = 21.06, P = 0.002), with a higher proportion of giant viruses detected in July. Thirty-nine and forty microorganisms were identified across the six areas and five sites, respectively, with relatively few area/site-specific microorganisms. Four distinct disinfection level zones were categorized: relatively safe zone, less safe zone, general disinfection zone and key disinfection zone. Two strains of viruses with potential pathogenicity were identified: pigeon circovirus and Influenza A virus (H4N2). This study established a metagenomics-based surveillance framework for microbial risk assessment in high-risk port environments and proposed a four-tier disinfection strategy to prioritize high-contact zones. Our findings highlighted environmental metagenomics as a critical complement to traveler screening and provided early warning signals for the prevention and control of imported infectious diseases.

近年来新出现的传染病爆发的流行病学特点突出了控制输入性传染病的极端重要性。在本研究中，我们通过监测海关和港口的环境微生物，实现了微生物入侵的动态跟踪。2024年7月至9月，在中国深圳的三个入境口岸采集了126份环境样本。宏基因组分析检测到55个非病毒微生物群落和12个病毒分类群。其中，26.8%的细菌、100%的真菌、71.4%的原生生物和无一的古细菌表现出潜在的致病特性。病毒最常见，包括噬菌体（100%）、未分类病毒（96.8%）、巨型病毒（27.8%）、真菌病毒（4.8%）和脊椎动物病毒（1.6%）。病毒在地区（χ2 = 18.70, P = 0.541）、地点（χ2 = 14.02, P = 0.597）、入境口岸（χ2 = 10.27, P = 0.247）的分布差异均无统计学意义。但病毒分布在3个采样月份间差异显著（χ2 = 21.06, P = 0.002），其中7月份检测到的巨型病毒比例较高。在6个区域和5个站点中分别鉴定出39种和40种微生物，区域/站点特异性微生物相对较少。将消毒等级划分为相对安全区、较不安全区、一般消毒区和重点消毒区。鉴定出两株具有潜在致病性的病毒：鸽子圆环病毒和甲型流感病毒（H4N2）。本研究建立了基于宏基因组学的高风险港口环境微生物风险评估监测框架，并提出了优先考虑高接触区的四层消毒策略。我们的研究结果强调了环境宏基因组学作为旅行者筛查的重要补充，并为预防和控制输入性传染病提供了早期预警信号。

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引用次数: 0

Inactivation of BSL-2 and BSL-3 human pathogens using FATHHOME’s Trinion Disinfector: A rapid and eco-friendly ozone-based dry disinfection approach 使用FATHHOME的Trinion消毒器灭活BSL-2和BSL-3人类病原体：一种快速和环保的臭氧干消毒方法

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-08-01 DOI: 10.1016/j.bsheal.2025.07.006

Kabita Adhikari , Elizabeth Zhou , Majid Khan , Shubhasish Goswami , Amir Khazaieli , Blake A. Simmons , Deepika Awasthi , Subhash C. Verma

The role of personal protective equipment (PPE) in protecting against exposure to infectious agents and toxic chemicals is well-established. However, the global surge in PPE demand during the pandemic exposed challenges, including shortages and environmental impacts from disposable waste. Developing effective, scalable, and sustainable decontamination methods for the reuse of PPE is essential. Ozone has emerged as a promising, eco-friendly disinfectant due to its strong oxidative properties, rapid action, and residue-free breakdown into oxygen. This study evaluates the effectiveness of the FATHHOME Trinion Disinfector, an innovative ozone-based dry sterilization device, for inactivating pathogens on PPE materials, such as not resistant to oil 95 (N95) masks and face shields. The device’s bactericidal performance was tested against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Salmonella typhimurium, Enterococcus durans, Enterococcus faecalis, and Saccharomyces cerevisiae, achieving a 1- to 2-log reduction in these bacterial and fungal pathogens. A 30-minute ozone exposure cycle was found to attain maximum sterilization efficiency. We also demonstrated the disinfector’s efficacy against viral pathogens, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), adeno-associated virus (AAV), herpes simplex virus type 1 (HSV-1), and hepatitis B virus (HBV) on PPE surfaces. SARS-CoV-2 contamination on face shields and N95 masks decreased by 99.9 %, and AAV infectivity was nearly eliminated. Similar reductions were observed for HSV-1 and HBV. Overall, the findings confirm that ozone-based disinfection offers a rapid, scalable, and sustainable method for decontaminating PPE. These results support the establishment of standardized ozone disinfection protocols to enhance infection control, address PPE shortages, and minimize environmental waste.

个人防护装备（PPE）在防止接触传染原和有毒化学品方面的作用是公认的。然而，大流行期间全球个人防护装备需求激增带来了挑战，包括短缺和一次性废物对环境的影响。制定有效、可扩展和可持续的个人防护装备净化方法至关重要。臭氧因其强大的氧化特性、快速的作用和无残留物分解成氧气而成为一种有前途的环保消毒剂。本研究评估了FATHHOME Trinion消菌器的有效性，该消菌器是一种创新的臭氧干式灭菌装置，用于灭活PPE材料上的病原体，如不耐油95 （N95）口罩和面罩。该装置对大肠杆菌、铜绿假单胞菌、金黄色葡萄球菌、鼠伤寒沙门氏菌、durans肠球菌、粪肠球菌和酿酒酵母的杀菌性能进行了测试，这些细菌和真菌病原体的杀灭率降低了1- 2倍。发现30分钟的臭氧暴露周期可达到最大的灭菌效率。我们还证明了消毒剂对PPE表面的病毒性病原体，严重急性呼吸综合征冠状病毒2 (SARS-CoV-2)，腺相关病毒（AAV），单纯疱疹病毒1型（HSV-1）和乙型肝炎病毒（HBV）的有效性。口罩和N95口罩上的SARS-CoV-2污染下降99.9%，基本消除了AAV感染。在HSV-1和HBV中观察到类似的减少。总体而言，研究结果证实，基于臭氧的消毒提供了一种快速、可扩展和可持续的个人防护装备去污方法。这些结果支持建立标准化的臭氧消毒方案，以加强感染控制，解决个人防护装备短缺问题，并尽量减少环境浪费。

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引用次数: 0

Random forest-based predictor selection and pneumonia risk probability assessment in acute respiratory infections: A cross-sectional study in Chongqing, China, 2023–2024 基于随机森林的急性呼吸道感染预测因子选择和肺炎风险概率评估：中国重庆2023-2024年的横断面研究

IF 3 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Biosafety and Health

Pub Date : 2025-08-01 DOI: 10.1016/j.bsheal.2025.07.004

Yunshao Xu , Yuping Duan , Jule Yang , Mingyue Jiang , Yanxia Sun , Yanlin Cao , Li Qi , Zeni Wu , Luzhao Feng

Progression of acute respiratory infection (ARI) to pneumonia increases severity and healthcare burden. Limited evidence exists on using machine learning to identify predictors from demographics, clinical, and pathogen detection data. This study aimed to identify pneumonia predictors in ARI patients using machine learning methods. This observational study was conducted in Chongqing, China, from September 2023 to April 2024. Outpatients and inpatients with ARI were recruited weekly. A random forest algorithm was used for predictor selection, followed by a logistic regression-based nomogram to analyze the probability of pneumonia. Among the 1,638 patients with ARI, those with pneumonia had higher rates of influenza A virus (IFV-A) (49.2 % vs. 39.6 %), influenza B virus (26.3 % vs. 18.6 %), and respiratory syncytial virus (6.1 % vs. 1.9 %) infection than those without pneumonia. In the subgroup of 79 patients with comprehensive blood tests, pneumonia was positively associated with hemoglobin (130.00 g/L vs. 124.00 g/L), blood urea nitrogen (5.73 mmol/L vs. 4.85 mmol/L), C-reactive protein (36.10 mg/L vs. 25.25 mg/L), procalcitonin (0.11 μg/L vs. 0.07 μg/L), and D-dimer (0.95 μg/L vs. 0.80 μg/L) levels, whereas pneumonia was inversely associated with neutrophils (4.20 × 10⁹/L vs. 4.76 × 10⁹/L), aspartate aminotransferase (22.50 U/L vs. 24.00 U/L), and uric acid (280.90 μmol/L vs. 330.00 μmol/L) levels. Elevated D-dimer levels (adjusted odds ratio [aOR] = 1.002, 95 % confidence interval [CI]: 1.001–1.004) and IFV-A infection (aOR = 9.308, 95 % CI: 2.433–35.606) were significantly associated with increased pneumonia probability. In future clinical practice, particular attention should be given to ARI patients with elevated D-dimer levels and IFV-A infections.

急性呼吸道感染（ARI）发展为肺炎会增加严重程度和医疗负担。使用机器学习从人口统计、临床和病原体检测数据中识别预测因子的证据有限。本研究旨在使用机器学习方法确定ARI患者的肺炎预测因素。该观察性研究于2023年9月至2024年4月在中国重庆进行。每周招募ARI门诊和住院患者。使用随机森林算法选择预测因子，然后使用基于逻辑回归的nomogram来分析肺炎的概率。在1,638例ARI患者中，肺炎患者感染甲型流感病毒（IFV-A）（49.2%对39.6%）、乙型流感病毒（26.3%对18.6%）和呼吸道合胞病毒（6.1%对1.9%）的比例高于无肺炎患者。在79例综合血液检查患者亚组中，肺炎与血红蛋白（130.00 g/L vs. 124.00 g/L）、血尿素氮（5.73 mmol/L vs. 4.85 mmol/L）、c反应蛋白（36.10 mg/L vs. 25.25 mg/L）、降钙素原（0.11 μg/L vs. 0.07 μg/L）、d -二聚体（0.95 μg/L vs. 0.80 μg/L）水平呈正相关，与中性粒细胞（4.20 × 109/L vs. 4.76 × 109/L）、天冬氨酸转氨酶（22.50 U/L vs. 24.00 U/L）水平呈负相关。尿酸水平（280.90 μmol/L vs. 330.00 μmol/L）。d -二聚体水平升高（调整优势比[aOR] = 1.002, 95%可信区间[CI]: 1.001 ~ 1.004）和IFV-A感染（aOR = 9.308, 95% CI: 2.433 ~ 35.606）与肺炎发生概率增加显著相关。在未来的临床实践中，应特别注意伴有d -二聚体水平升高和IFV-A感染的ARI患者。

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