Common Threats Research Articles

The relationship between nurses’ professional commitment and missed nursing care: a cross-sectional study in Iran

Background & aimsMissed nursing care is a global challenge that can have many consequences and it’s known as a common threat to the patient safety and quality of nursing care. The nurses’ professional commitment plays the final role in the occurrence of this issue. This study aimed to investigate the relationship between nurses’ professional commitment and missed nursing care in Iran.Materials & methodsThis cross-sectional descriptive-analytical study was conducted on 270 nurses working in two hospitals affiliated to Tehran University of Medical Sciences (Sina & Shariati) from September to December 2023. The research community included all nurses working in medical-surgical wards in the designated hospitals. The research samples were included in a targeted and quota method after obtaining organizational permits, ethical approval and informed consent. Data collection was done using three questionnaires including demographic information form, Nursing Professional Commitment Scale, and MISSCARE Questionnaire. The collected data was analyzed in SPSS software, version 25.ResultsThe results of Pearson’s correlation test showed that there is a significant negative relationship between nurses’ professional commitment and missed nursing care scores (r=-0.23) (p < 0.001). The mean score of nurses’ professional commitment was reported at a moderate to high level (83.72 ± 16.02) and the mean score of missed nursing care was reported at a low level (47.84 ± 16.48). Nurses over 40 years old, morning shift and employed nurses showed higher professional commitment. Also, nurses under 29 years old and male nurses had more missed nursing care other than their participants. No relationship was observed between other demographic variables with nurses’ professional commitment and missed nursing care.ConclusionThe results of this study showed that higher nurses’ professional commitment leads to higher quality of care and less missed nursing care. Based on findings of this research, it is recommended for health care providers and nursing managers to adopt programs to increase nurses’ professional commitment and consequently reduce missed nursing care.

Dissemination of Urinary Escherichia coli Phylogroup B2 in Provincial and Community Hospitals in Uthai Thani, Central Thailand.

Escherichia coli is a Gram-negative bacterium that causes a variety of clinical infections in humans, including diarrhea, sepsis, and urinary tract infection. This bacterium is a common multidrug-resistant threat in community and hospital settings worldwide. This study examined the antimicrobial susceptibility and genetic relationship based on Clermont phylotyping and enterobacterial repetitive intergenic consensus (ERIC)-PCR of 84 E. coli urinary isolates from provincial and community hospitals in Thailand. All isolates were susceptible to nitrofurantoin, and almost all isolates were susceptible to carbapenem, fosfomycin, and amikacin. High resistance rates to fluoroquinolone, ampicillin, and trimethoprim/sulfamethoxazole were observed. Clermont phylogroup B2 was predominant (n = 58). Subtyping of the B2 phylogroup revealed diverse subgroups, of which subgroup V (n = 11), VII (n = 9), III (n = 6), and II (n = 6) were most prevalent. ERIC-PCR showed that the strains of the B2 subgroups III and V were spread between provincial and community hospitals and between hospital wards. This evidence suggests the need for comprehensive infection control monitoring, with strong active surveillance at all hospital levels.

The effects of physical activity on adolescents' depression: evidence from China.

Depression is becoming a common threat to the mental health of Chinese adolescents. As an intermediate stage between being healthy and having depression, identifying factors influencing depressive may contribute to providing more options for the prevention and treatment of depression. The study aims to explore the effects of physical activity on adolescent depression, focusing on the times and hours of activity per week. The study used a cross-sectional dataset collected in Ruyang County, Henan Province in September 2022, including a sample of 5,629 adolescents in 31 compulsory public schools in the county. We utilized Ordinary Least Squares (OLS) to analyze the impact of physical activity on adolescents' depression scores, and probit model to analyze the influence of physical activity on adolescents' depression. To examine whether there is a U-shaped relationship between physical activity and depression, we included the squared terms of times and hours of activity in models. The results showed that: (1) The times of physical activity significantly reduces Chinese adolescent depression. An increase in physical activity by one time per week is associated with a mean decrease of 0.354 points in depression scores (p < 0.01). However, an increase of one time of physical activity per week is associated with an average 1% increase in the likelihood of experiencing depression(p < 0.05), while the hours of physical activity was statistically insignificant. (2) Physical activity has a U-shaped (not linear) relationship with adolescent depression, with 7-8 times per week or 7-9 h of physical activity per week being the optimal range. The study found that increasing the frequency of physical activity positively impacts adolescent depression, while increasing the hours does not show a significant association. Furthermore, a U-shaped relationship exists between times of activity, hours of activity, and adolescent depression, suggesting that moderate activity is optimal.

High-performance real-time fire detection and forecasting framework for industrial cables

In industrial scenarios, cable fires have always been the most common threat, and traditional fire detection systems often rely on a large number of sensors, and the detection range is very limited, and it is impossible to effectively predict the fire situation in time. In this paper, we propose a detection and prediction scheme for industrial cable fire, which breaks the limitations of the previous research on multi-sensor signal input, and highly couples the detection and prediction modules to realize fire prediction based on video image input only. In fire detection, we design an object detection model using HSV for flame feature enhancement based on YOLOv8, and in fire prediction aspect, we use iTransformer as a time series prediction model to mine the correlation between various parameters to predict the spread of fire. In the experiments, the average absolute percentage error of the flame detection model for the detection of flame height, width and longitudinal position was 3.49%–10.64 %, 2.45%–8.89 % and 1.61%–9.31 %, respectively, and the MAPE of the time series prediction model for the above three parameters was 11.18%–15.06 % and 4.35%–8.18 %, 3.37%–6.62 %.The results of the above experiments verify that the proposed model has the ability to quantitatively analyze the fire spread trend in the actual fire and help firefighters make decisions.

Laying train tracks en route: How institutional education leaders navigate complexity during mandated curriculum change.

Institutional education leaders serve key roles in leading major curricular change within residency education, yet little is known about how they accomplish these goals on the ground. Change management principles have predominantly been developed and described in the hierarchical context of management science and corporate settings. However, the non-hierarchical, complex and adaptive features of health professions education may render these traditional change management models inadequate. We explored how institutional educational leaders navigate the complex residency education system in implementing a major curricular change. Using constructivist grounded theory, we conducted and iteratively analysed semi-structured interviews with 11 institutional education leaders from across Canada who were responsible for leading the nationally mandated curricular change to competency-based residency education. Thematic analysis was performed iteratively using constant comparison. Leaders managing the change process focused on two priorities: steering the direction of the change process as it evolved and maintaining the momentum amongst stakeholders to move forward steadily. Four common threats and opportunities impacted the focus on direction and momentum: multiplicity of contexts, innovation, resistance and distractions. In response, leaders utilised various tactics and harnessed diverse leadership styles to manage these challenges accordingly. We identified a change framework that offers a more contextually nuanced understanding of curricular change in residency education that has not been described in the change management literature generated by the management sector. Institutional education leaders focused on maintaining the direction and momentum, while constantly assessing and adapting to evolving, uncertain and complex conditions. Our findings provide a simple and practical foundation to support leadership education in curricular change as well as researchers in developing further change theories in complex adaptive health professions education systems.

The Tightrope of Individual Liberties amid Pakistan’s Counter-Terrorism Agenda

This doctrinal research article explores the nuances, pitfalls, and opportunities within this intricate landscape. This doctrinal research delves into the intricate balance between individual liberties and Pakistan's counter-terrorism agenda, navigating the complex terrain where security imperatives intersect with fundamental rights. As Pakistan grapples with persistent security threats from terrorism, its response has often entailed the implementation of stringent measures aimed at thwarting terrorist activities and ensuring public safety. However, these measures have raised concerns about their impact on civil liberties, including freedoms of expression, association, and privacy. Drawing upon legal frameworks, policy documents, and judicial precedents, this research critically examines the evolving landscape of counter-terrorism laws and practices in Pakistan and their implications for individual liberties. It scrutinizes the compatibility of counter-terrorism measures with constitutional guarantees and international human rights standards, assessing the extent to which security imperatives have encroached upon fundamental rights and freedoms. Furthermore, this research explores the role of judicial oversight, executive discretion, and legislative reforms in reconciling the tension between security concerns and individual liberties within Pakistan's legal framework. It analyses landmark court decisions, legislative enactments, and government policies to elucidate the legal and institutional mechanisms aimed at safeguarding individual liberties while countering terrorism effectively. Moreover, this research situates Pakistan's counter-terrorism efforts within the broader context of regional security dynamics, highlighting the interconnectedness of domestic security challenges with regional conflicts, geopolitical rivalries, and transnational terrorist networks. It underscores the importance of regional cooperation, information sharing, and diplomatic engagement in addressing common security threats while respecting individual liberties across borders. By critically examining the tightrope walk between individual liberties and Pakistan's counter-terrorism agenda, this research contributes to a nuanced understanding of the challenges and trade-offs inherent in balancing security imperatives with respect for fundamental rights.

Using anthropomorphism, transparency, and feedback to improve phishing detection aids

Phishing is a common cybersecurity threat to email users. An automated phishing decision-support aid can help users identify suspicious emails. The aid’s success depends on both the aid’s capability and the user’s trust in and usage of the aid. In this study, 465 participants were asked to judge phishing emails with an automated decision aid. We measured how users’ trust and decision making were affected by the type of aid (human, AI, text, no aid), gender (male, female), decision transparency (reasoning for aid’s decision present, absent), as well as feedback (present, absent). We found that an aid was helpful regardless of its anthropomorphic appearance (human vs. AI) and gender. Transparency was helpful with the human aid, but not the AI aid. Feedback effectively improved trust in all the aids, although it helped aid retention only for the text aid. Participants had overall positive comments about the aid and found it helpful. The findings can be applied to automated aid design to understand potential avenues for improving users’ trust, performance, and aid use.

Risk Assessment for Malware Attacks in Small Businesses

The presence of severe malware attacks in business systems compromises devices, data, information, and network hygiene. The increased usage of cyberspace as a convenient tool exposed all organisations to various malware attacks. The malware attacks have become one of the most common threats in all sectors. These attacks often find their way into systems where poor or inadequate security measures are implemented, leaving the institution’s resources vulnerable and compromised. This work collected data using purposive sampling from the selected small businesses that used cyberspace for business transactions. A questionnaire distributed to the participants was mounted on Google Forms. To analyse the collected data, this work assessed the malware attacks and used the risk management processes to determine the risk impact and probability. Risk management processes were used to analyse and interpret different risks associated with malware attacks and also ranked them from low, medium, and high. The work also revealed the different forms of common malware attacks, the business assets affected, the main causes of malware attacks, risk value, risk likelihood, and the risk impact. The extent of security measures implemented on different levels contributes to the overall state of the organisational resources. The study also shared the recommendations and accounted for the conclusion.

Silver bismuth sulphide (AgBiS2)-MXene composite as high-performance electrochemical sensing platform for sensitive detection of pollutant 4-nitrophenol

4-Nitrophenol (4-NP) is one of the most common and extensive toxic threats to the environment; hence there is always a need to develop a robust analytical method. In this study, we present MXene-based AgBiS2 nanocomposite as an electrochemical sensing platform for detecting 4-NP. The synergistic combination of MXene and AgBiS2 within the composite structure enhances electrocatalytic performance, resulting in a highly sensitive and selective sensor. The electrochemical performance of the MXene-AgBiS2 modified GCE was evaluated through cyclic voltammetry (CV) and differential pulse voltammetry (DPV) analyses. The sensor exhibited excellent electrochemical properties, including a low detection limit (LOD) of 0.00254 µM (should consider the method how to get such low LOD – due to 10 times of the lowest conc tested S/N = 3, high sensitivity of 5.862 µA µM−1 cm−2, and a wide linear range (0.02–1869 µM). The sensor also demonstrated good selectivity against various interference compounds such as Di-Nitrophenol, Ortho-Nitrophenol, Copper, Cobalt, sodium, Manganese, Zinc, Glucose (GLU), Urea (Ur), Dopamine (DA), Ascorbic acid, and Uric Acid. Along with reproducibility, repeatability, and stability also performed shows, 2.21 %, and 2.71 % respectively. Our nanocomposite sensor, utilizing MXene-based AgBiS2, proves its practicality in real-time tap water analysis. This bridge between lab studies and environmental monitoring marks a significant advancement. The unique properties of our sensor enhance electrochemical sensing, providing a promising solution for swift on-site detection of 4-NP in water, potentially revolutionizing pollutant management.

РОЗВИТОК СУЧАСНИХ ТЕХНОЛОГІЙ: ВИКЛИКИ ДЛЯ НАЦІОНАЛЬНОЇ БЕЗПЕКИ ПОЛЬЩІ

The main purpose of the article is to analyze national security challenges related to the development of modern technologies. The impact of this phenomenon on many aspects of safety in cyberspace is presented. The relationship between modern technologies with the military security of the state is also presented. There is also a cross-discussion of the struggle of state entities with terrorist threats directly related to dynamic technological progress. The possibilities of cybersecurity education at universities, within the framework of postgraduate education, courses and trainings are analyzed. The study shows that modern technologies have a significant impact on Poland's national security. Rapid technological development poses a serious threat to national security for any country, including Poland. They directly influence national security aspects as the fight against terrorism, ensuring the security of state institutions in cyberspace and guaranteeing permanent military development necessary to counteract both common and hybrid threats. The functioning of state entities and their citizens requires constant adaptation to an environment that changes dynamically in the international arena. Poland, like any other country, should be in constant readiness to resist the above mentioned challenges to defend their own national interests. To do this, you need to use the opportunities and soften the threats associated with the constant inter -sectoral development of technology. Modern information technologies offer advanced means and capabilities of cybersecurity. However, it also increases the potential for cyberattacks, which requires constant improvement and adaptation of cybersecurity policy. The development of military technologies, including artificial intelligence, nanotechnology, or cybercribe, changes the face of national defense. Poland needs to be effectively investing in modern defense technologies in order to maintain their defense capability at a proper level. Modern technologies influence the protection of critical infrastructure from potential terrorist attacks. Integrated IT systems can increase efficiency, but at the same time increase the risk of cyberattacks that can have serious consequences for the country's functioning. It is also necessary to strengthen international cooperation to exchange advanced experiences and work together to protect against modern technological threats. Key words: technology, military safety, terrorism, cyberspace, cybersecurity, higher education, Poland.

Global Crisis Frame Matters for Unity: Resource Threat Hampers While Safety Threat Promotes Intergroup Cooperation

Realistic global crises trap humanity in common threats requiring intergroup unity to combat them. How do common threats shape intergroup cooperation? Previous studies have focused on the impact of threat severity on intergroup cooperation and yielded mixed results. We proposed that framing common threat based on two key aspects (resource vs. safety threats) has opposing effects on intergroup cooperation. We conducted three studies (N = 840) to test our assumptions. Across scenarios of combating wars (Study 1), reducing air pollutant emissions (Study 2), and mitigating climate change (Study 3), framing a crisis as resource threat hampered intergroup cooperation, whereas framing it as safety threat promoted intergroup cooperation. These effects were mediated by the pursuit of ingroup interests (Study 3). Our findings provide new insights into the complex effects of common threat on intergroup interactions and have practical implications for facilitating unity during global crises.

Future exposure of rainfall and temperature extremes to the most populous island of Indonesia: A projection based on CORDEX simulation

AbstractThe study focuses on understanding the future exposure to rainfall and temperature extremes in one of the world's most populous islands, Java, Indonesia. We use the high‐resolution climate projections from the Coordinated Regional Climate Downscaling Experiment (CORDEX) simulation for Southeast Asia by 2100 under RCP4.5 and RCP8.5 scenarios. Results show that the island will likely experience drying in the lowlands due to annual rainfall decline by approximately 13%–18%, potentially exposing around 27%–73% of the population (varying under different scenarios) during the end of the century (2060–2099). Additionally, the future drying condition may be exacerbated by extreme temperatures with a 1.7–3.1°C increase in maximum daily temperature, linked with more than half of the population (63%) likely to experience at least an unprecedented temperature of 3°C under RCP8.5. Our seasonal analysis also suggests that dry seasons get even drier, and wet seasons get wetter. In terms of landuse areas exposed, we show a higher fraction of crop and forest areas may face both drying and warming, which can potentially lead to crop failure and wildfire. Our study indicates that compound drought and heat may be a common threat in lowland Java in the future, while intensifying rainfall extremes in the uplands may lead to flash flooding downstream and landslides. These findings highlight the urgent need for adaptation and mitigation strategies to reduce the risks associated with climate change in Java as one of Indonesia's most critical regions in the future.

Fear in general populations: A cross-sectional study on perceived fear of common diseases, COVID-19, life events, and environmental threats in 30 countries

Fear in general populations: A cross-sectional study on perceived fear of common diseases, COVID-19, life events, and environmental threats in 30 countries

Social media threats and health among adolescents: evidence from the health behaviour in school-aged children study

BackgroundSocial media are immensely popular among adolescents. Thus, concerns have been raised about the threats adolescents encounter on social media and the possible negative health consequences, such as depressive symptoms and anxiety. This study investigated the prevalence of nine social media threats: (1) cyberbullying, (2) sexual harassment, (3) racism, (4) unauthorized distribution of sensitive material, (5) phishing attempts, (6) misinformation, (7) the sale or distribution of drugs, (8) harmful or dangerous social media challenges, (9) content causing appearance pressures. The study also investigated how individual and social factors, problematic social media use (PSMU), and online communication with strangers are associated with social media threat exposure, as well as the association between social media threats and self-rated health, depressive feelings, and anxiety symptoms.Methods and findingsNationally representative Health Behaviour in School-aged Children (HBSC) data from Finland were obtained from 2288 respondents aged 11, 13, and 15 years. Fixed effects regression models were applied. The most common threat, encountered daily and weekly, was misinformation. Regression models showed that individual and social factors, PSMU, and online communication with strangers explained adolescent exposure to social media threats in differing ways. Furthermore, certain factors (e.g., emotional intelligence, family support) were associated with encountering social media threats less frequently, whereas other factors (e.g., PSMU, online communication with strangers) were associated with more frequent encounters. Daily and weekly exposure to social media threats was systematically associated with poor self-rated health, frequent depressive feelings, and anxiety symptoms.ConclusionsOur study highlights the need for intervention and health promotion efforts to mitigate adolescent exposure to social media threats and ensuing negative health consequences.

Enhancing the Detection of Social Desirability Bias Using Machine Learning: A Novel Application of Person-Fit Indices.

Social desirability bias (SDB) is a common threat to the validity of conclusions from responses to a scale or survey. There is a wide range of person-fit statistics in the literature that can be employed to detect SDB. In addition, machine learning classifiers, such as logistic regression and random forest, have the potential to distinguish between biased and unbiased responses. This study proposes a new application of these classifiers to detect SDB by considering several person-fit indices as features or predictors in the machine learning methods. The results of a Monte Carlo simulation study showed that for a single feature, applying person-fit indices directly and logistic regression led to similar classification results. However, the random forest classifier improved the classification of biased and unbiased responses substantially. Classification was improved in both logistic regression and random forest by considering multiple features simultaneously. Moreover, cross-validation indicated stable area under the curves (AUCs) across machine learning classifiers. A didactical illustration of applying random forest to detect SDB is presented.

The relationship between mindfulness, personality factors and perfectionism with anger in hypertensive patients

Background and Objectives: High blood pressure is one of the most common and important threats to human health and is the main cause of premature death all over the world. High blood pressure is caused by psycho-physiological factors. The present study was conducted with the aim of determining the relationship between mindfulness, personality factors and perfectionism with anger in high blood pressure patients. Material and Methods: This research was a descriptive-cross-sectional and correlational study. The statistical population was the patients with high blood pressure who referred to the medical centers of Tabriz city in 1401. The sample size of the research using Cochran's formula was 184 people who were selected by available method. Research tools were Multidimensional Perfectionism Questionnaire, Spielberger State-Trait Anger Questionnaire, Revised NEO Questionnaire (short form), Brown and Ryan Mindfulness Assessment Scale. Data were analyzed by correlation and regression tests with SPSS-25 software. Results: The results showed that there is a negative and significant relationship between mindfulness and anger in high blood pressure patients (P&lt;0/05). Among the personality factors, narcissism and conscientiousness have a positive and significant relationship with anger. There is a negative and significant relationship between extroversion, flexibility and agreeableness with anger in high blood pressure patients (P &lt; 0/05). There is a positive and significant relationship between self-oriented, other-oriented and community-oriented perfectionism with anger in high blood pressure patients (P&lt; 0/05). Also, mindfulness, personality factors and perfectionism can predict anger (P&lt;0/05). Conclusion: The results showed that there is a relationship between mindfulness, personality factors and perfectionism with anger. Therefore, by identifying psychological variables such as mindfulness, personality factors and perfectionism and its relationship with anger, blood pressure reduction in patients can be helped.

A threat to the natural World Heritage site rarely happens alone

This study contributes an empirical investigation of the likelihood that different external threats to a UNESCO Natural World Heritage Site occur in combination with each other when site characteristics and location are controlled for. For the purpose of the analysis, the World Heritage database and the UNESCO State of Conservation Reports are used and the nine most frequently appearing external threats are identified. These databases include 6852 site-year observations and 3316 threats over the period 1979–2023. The most commonly identified external threats are illegal activities, with eleven percent of all observations and mining with six percent. Transport infrastructure, tourism and visitor pressure are also common threats. Estimation results based on the multivariate Probit (equation system) model demonstrate that there are strong positive correlations between many pairs of the nine external threats. Most apparent are the links between illegal activities and loss of identity, social cohesion, changes in local population and community, water infrastructure (dams) and farming, as well as illegal activities and land conversion. There are also clear links between tourism and infrastructure. This emphasises that the various threats seldom appear in isolation from each other. Results also highlight that the threats have different drivers. Among the determinants, site characteristics and location are the most important ones. The likelihood of threats is highest for Natural Heritage Sites covered by forests or those in marine and coastal areas, Africa as well as the Arab region. It is also possible to identify a general increase in threats over time, although with a diminishing rate of growth towards the period 2015–2019. Contrary to this development and the general downturn in threats during the Covid-19 pandemic period of 2020–2023, pressure from tourism continues to grow. Methodologically, the results emphasize the need for multivariate Probit models when research goes beyond analyses of descriptive statistics and single equation approaches.

DETECTION OF FRAUDULENT PHONE CALLS DETECTION IN MOBILE APPLICATIONS

The primary challenge faced over the course of this decade-long endeavour is the difficulty in devising effective features without direct access to telephony network infrastructure. we conducted an extensive three-month measurement study using these call logs, which encompassed a staggering 9 billion records. Based on the insights gleaned from this study, we identified and designed 29 features that could be used by machine learning algorithms to predict malicious calls. Fraudulent phone calls or scams and spam s via telephone or mobile phone have become a common threat to individuals and organizations. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful tools in detecting and analyzing fraud or malicious calls. This paper presents an overview of AI-based fraud or spam detection and analysis techniques, along with its challenges and potential solutions. The novel fraud call detection approach is proposed that achieved high accuracy and precision. The outcomes revealed that the most effective approach could reduce unblocked malicious calls by up to 90%, while maintaining a precision rate exceeding 93.79% for benign call traffic. Moreover, our analysis demonstrated that these models could be implemented efficiently without incurring significant latency overhead.

Leveraging the Cloud: A Security Renaissance for Modern Businesses

The modern business landscape thrives on cloud computing, offering scalability, agility, and cost- effectiveness. However, this reliance on remote storage introduces new security challenges. This paper explores how cloud security can usher in a renaissance of data protection and business resilience. We delve into the core concepts of cloud security, analyze common threats and best practices, and explore the numerous benefits it offers, including enhanced data protection, improved business continuity, and significant cost savings. The paper outlines the crucial steps for implementing cloud security measures, emphasizing the importance of assessing security needs, selecting a reliable provider, securing data, and enforcing multi-factor authentication. We delve into cloud security compliance, exploring regulatory considerations, auditing practices, and robust monitoring strategies. The paper acknowledges potential security risks like data breaches, insider threats, and cloud provider vulnerabilities, but proposes effective mitigation strategies. Finally, we explore the future of cloud security, highlighting the role of emerging technologies like artificial intelligence and machine learning in combating the evolving threat landscape.

Potential plasma biomarkers for the onset of heart and skeletal muscle inflammation from Piscine orthoreovirus-1 infection in Atlantic salmon (Salmo salar)

Biomarkers that give quantifiable information about disease development are valuable diagnostic indicators providing opportunities to thwart adverse outcomes through timely detection and initiation of countermeasures. Whereas human medicine already relies extensively on biomarker analysis, their application in the diagnostics of fish diseases is still at a tentative beginning. However, the increased utilisation of broad-range analytical approaches such as untargeted proteomics enhances the chances to discover changes in the levels of proteins, which are connected to fish health and could serve as novel biomarkers. In the present study, proteomic analysis accompanied by biostatistical data processing was employed with the aim of identifying plasma biomarker candidates for the onset of heart and skeletal muscle inflammation (HSMI) caused by Piscine orthoreovirus (PRV)-1 infection in Atlantic salmon. HSMI is a common viral disease and threat to fish welfare and productivity in Norwegian aquaculture, so that the early detection of HSMI development would allow a timely intervention to limit the damage. In the search for biomarker candidates, salmon plasma was sampled five and eight weeks after a PRV-1 cohabitation challenge experiment and from adequate control fish, and analysed by mass spectrometry-based proteomics. The proteome dataset contained 695 proteins with >90% probability of correct identification according to the set cut-off criteria for peptide quality. Time- and condition-related differences in protein abundance levels were revealed by multivariate analysis. Comparison of the proteins identified as significant using three different biostatistical models resulted in a short list of four potential biomarkers: galectin-3-binding protein (Gal-3BP), fucolectin-6, urokinase plasminogen activator surface receptor and ryanodine receptor 3. The physiological functions described for these proteins in mammals designate them as interesting indicators of inflammatory diseases also in other species, such as PRV-1 pathogenesis in salmon. In situ-hybridisation targeting Gal-3BP and PRV-1 mRNA in heart tissue sections from the same challenge trial showed a significant upregulation of Gal-3BP mRNA in infected salmon hearts as compared to controls, supporting the findings of the proteomic analysis and suggesting a role in the onset of heart- and skeletal muscle inflammation.