Common Exposures Research Articles

Age- and sex-specific associations between risk scores for schizophrenia and self-reported health in the general population

PurposeThe health correlates of polygenic risk (PRS-SCZ) and exposome (ES-SCZ) scores for schizophrenia may vary depending on age and sex. We aimed to examine age- and sex-specific associations of PRS-SCZ and ES-SCZ with self-reported health in the general population.MethodsParticipants were from the population-based Netherlands Mental Health Survey and Incidence Study–2 (NEMESIS-2). Mental and physical health were measured with the 36-item Short Form Survey 4 times between 2007 and 2018. The PRS-SCZ and ES-SCZ were respectively calculated from common genetic variants and exposures (cannabis use, winter birth, hearing impairment, and five childhood adversity categories). Moderation by age and sex was examined in linear mixed models.ResultsFor PRS-SCZ and ES-SCZ analyses, we included 3099 and 6264 participants, respectively (age range 18–65 years; 55.7–56.1% female). Age and sex did not interact with PRS-SCZ. Age moderated the association between ES-SCZ and mental (interaction: p = 0.02) and physical health (p = 0.0007): at age 18, + 1.00 of ES-SCZ was associated with − 0.10 of mental health and − 0.08 of physical health, whereas at age 65, it was associated with − 0.21 and − 0.23, respectively (all units in standard deviations). Sex moderated the association between ES-SCZ and physical health (p < .0001): + 1.00 of ES-SCZ was associated with − 0.19 of physical health among female and − 0.11 among male individuals.ConclusionThere were larger associations between higher ES-SCZ and poorer health among female and older individuals. Accounting for these interactions may increase ES-SCZ precision and help uncover populational determinants of environmental influences on health.

Competitive Metabolism of Polycyclic Aromatic Hydrocarbons (PAHs): An Assessment Using In Vitro Metabolism and Physiologically Based Pharmacokinetic (PBPK) Modeling.

Humans are routinely exposed to complex mixtures such as polycyclic aromatic hydrocarbons (PAHs) rather than to single compounds, as are often assessed for hazards. Cytochrome P450 enzymes (CYPs) metabolize PAHs, and multiple PAHs found in mixtures can compete as substrates for individual CYPs (e.g., CYP1A1, CYP1B1, etc.). The objective of this study was to assess competitive inhibition of metabolism of PAH mixtures in humans and evaluate a key assumption of the Relative Potency Factor approach that common human exposures will not cause interactions among mixture components. To test this objective, we co-incubated binary mixtures of benzo[a]pyrene (BaP) and dibenzo[def,p]chrysene (DBC) in human hepatic microsomes and measured rates of enzymatic BaP and DBC disappearance. We observed competitive inhibition of BaP and DBC metabolism and measured inhibition coefficients (Ki), observing that BaP inhibited DBC metabolism more potently than DBC inhibited BaP metabolism (0.061 vs. 0.44 µM Ki, respectively). We developed a physiologically based pharmacokinetic (PBPK) interaction model by integrating PBPK models of DBC and BaP and incorporating measured metabolism inhibition coefficients. The PBPK model predicts significant increases in BaP and DBC concentrations in blood AUCs following high oral doses of PAHs (≥100 mg), five orders of magnitude higher than typical human exposures. We also measured inhibition coefficients of Supermix-10, a mixture of the most abundant PAHs measured at the Portland Harbor Superfund Site, on BaP and DBC metabolism. We observed similar potencies of inhibition coefficients of Supermix-10 compared to BaP and DBC. Overall, results of this study demonstrate that these PAHs compete for the same enzymes and, at high doses, inhibit metabolism and alter internal dosimetry of exposed PAHs. This approach predicts that BaP and DBC exposures required to observe metabolic interaction are much higher than typical human exposures, consistent with assumptions used when applying the Relative Potency Factor approach for PAH mixture risk assessment.

Interim Analysis of Acute Hepatitis of Unknown Etiology in Children Aged

On April 21, 2022, CDC issued a health advisory† encouraging U.S. clinicians to report all patients aged <10 years with hepatitis of unknown etiology to public health authorities, after identification of similar cases in both the United States (1) and Europe.§ A high proportion of initially reported patients had adenovirus detected in whole blood specimens, thus the health advisory encouraged clinicians to consider requesting adenovirus testing, preferentially on whole blood specimens. For patients meeting the criteria in the health advisory (patients under investigation [PUIs]), jurisdictional public health authorities abstracted medical charts and interviewed patient caregivers. As of June 15, 2022, a total of 296 PUIs with hepatitis onset on or after October 1, 2021, were reported from 42 U.S. jurisdictions. The median age of PUIs was 2 years, 2 months. Most PUIs were hospitalized (89.9%); 18 (6.1%) required a liver transplant, and 11 (3.7%) died. Adenovirus was detected in a respiratory, blood, or stool specimen of 100 (44.6%) of 224 patients.¶ Current or past infection with SARS-CoV-2 (the virus that causes COVID-19) was reported in 10 of 98 (10.2%) and 32 of 123 (26.0%) patients, respectively. No common exposures (e.g., travel, food, or toxicants) were identified. This nationwide investigation is ongoing. Further clinical data are needed to understand the cause of hepatitis in these patients and to assess the potential association with adenovirus.

Validated single urinary assay designed for exposomic multi-class biomarkers of common environmental exposures.

Epidemiological studies often call for analytical methods that use a small biospecimen volume to quantify trace level exposures to environmental chemical mixtures. Currently, as many as 150 polar metabolites of environmental chemicals have been found in urine. Therefore, we developed a multi-class method for quantitation of biomarkers in urine. A single sample preparation followed by three LC injections was optimized in a proof-of-approach for a multi-class method. The assay was validated to quantify 50 biomarkers of exposure in urine, belonging to 7 chemical classes and 16 sub-classes. The classes represent metabolites of 12 personal care and consumer product chemicals (PCPs), 5 polycyclic aromatic hydrocarbons (PAHs), 5 organophosphate flame retardants (OPFRs), 18 pesticides, 5 volatile organic compounds (VOCs), 4 tobacco alkaloids, and 1 drug of abuse. Human urine (0.2 mL) was spiked with isotope-labeled internal standards, enzymatically deconjugated, extracted by solid-phase extraction, and analyzed using high-performance liquid chromatography-tandem mass spectrometry. The methanol eluate from the cleanup was split in half and the first half analyzed for PCPs, PAH, and OPFR on a Betasil C18 column; and pesticides and VOC on a Hypersil Gold AQ column. The second half was analyzed for tobacco smoke metabolites and a drug of abuse on a Synergi Polar RP column. Limits of detection ranged from 0.01 to 1.0 ng/mL of urine, with the majority ≤0.5 ng/mL (42/50). Analytical precision, estimated as relative standard deviation of intra- and inter-batch uncertainty, variabilities, was <20%. Extraction recoveries ranged from 83 to 109%. Results from the optimized multi-class method were qualified in formal international proficiency testing programs. Further method customization options were explored and method expansion was demonstrated by inclusion of up to 101 analytes of endo- and exogenous chemicals. This exposome-scale assay is being used for population studies with savings of assay costs and biospecimens, providing both quantitative results and the discovery of unexpected exposures.

Identification of domestic reservoirs and common exposures in an emerging lineage of Shiga toxin-producing Escherichia coli O157:H7 in England: a genomic epidemiological analysis

The zoonotic pathogen Shiga toxin-producing Escherichia coli (STEC) O157:H7 emerged during the 1980s as a causative agent of foodborne outbreaks associated with haemorrhagic colitis and haemolytic uraemic syndrome, which can be fatal. We investigated the emerging lineage IIc that was causing outbreaks of STEC O157:H7, identified and quantified the domestic and non-domestic reservoirs, and quantified patient exposures across the population of England. In this genomic epidemiological analysis study, all human STEC O157:H7 lineage IIc (n=925) isolates cultured from faecal specimens submitted to the UK Health Security Agency between June 1, 2015, and Dec 31, 2020, from patients in England in the community or in hospital, were whole-genome sequenced and the genomic population structure was described. Explanatory variables were obtained from microbiological surveillance data and STEC Enhanced Surveillance Questionnaire responses. Ancestral-state reconstruction using patient travel information was used to define domestic and non-domestic clades and transmission dynamics. Exposures for patients infected with isolates from domestic clades were assessed using mixed-effects multinomial univariable and multivariable regression. Lineage IIc emerged 50 years ago, and subsequent clonal expansions have resolved into six major extant clades. We defined two English domestic clades that emerged during the past 30 years, and four non-domestic clades comprising isolates that infected or were transmitted to patients in England via international travel or the consumption or handling of imported food. Throughout the study period, non-domestic clades contributed approximately twice the number of infections as domestic clades did. Patients infected with domestic IIc clade strains reported more frequent exposure to fresh produce (raw vegetables p=0·012; prepackaged salad p=0·0009), contact with animals (cattle p=0·021), and visits to farms (p=0·0053) than patients infected with strains from other STEC O157:H7 lineages. A multivariable mixed-effects multinomial model confirmed that within the domestic clades, the major risk factors for infection were prepackaged salad (clade 2.3.3, relative risk ratio [RRR] 1·72, 95% CI 1·09-2·72; p=0·019) and visits to farms (clade 2.5.2, RRR 1·98, 1·12-3·52; p=0·020) as fixed effects. Local authority district as a random variable had a strong but variable effect for clades 2.3.3 and 2.5.2. Lineage IIc has emerged as the most prevalent lineage of STEC O157:H7 in England, with a sizeable domestic reservoir. Human infection is associated with the consumption of contaminated fresh produce and contact with domestic livestock. The collection of routine, detailed exposure data on patients who are infected, integrated with high-resolution microbiological typing, enables powerful reframing of our understanding of foodborne disease risk within a One Health context. National Institute for Health and Care Research Health and UK Health Security Agency.

BofAEG: Automated Stack Buffer Overflow Vulnerability Detection and Exploit Generation Based on Symbolic Execution and Dynamic Analysis

Stack buffer overflow vulnerability is a common software vulnerability that can overwrite function return addresses and hijack program control flow, causing serious system problems. Existing automated exploit generation (AEG) solutions cannot bypass position-independent executable (PIE) exploit mitigation and cannot cope with the situation where the standard output function is not introduced into the program. In this paper, we propose a solution to alleviate the above difficulties: BofAEG, which is based on symbolic execution and dynamic analysis to automatically detect stack buffer overflow vulnerability and generate exploit. We used to capture the flag (CTF) and common vulnerabilities and exposures (CVE) programs for experiments. Results show that BofAEG can not only detect and generate exploits effectively but also implement more exploit techniques and is faster than existing AEG solutions.

Associations between autoimmune dysfunction and pollutants in Akwesasne Mohawk women: Dichlorodiphenyltrichloroethane and polychlorinated biphenyl exposure.

Pollutant exposures, including polychlorinated biphenyls (PCBs) and dichlorodiphenyltrichloroethane (DDT), have been found to disrupt normal immune function. Native American communities are disproportionately affected by autoimmune dysfunction and are more likely to be exposed to harmful pollutants than the general population. To determine the association between autoimmune dysfunction and pollutant exposure levels, this study evaluates the statistical relationship between the presence of autoimmune dysfunction and pollutant exposure. Information was collected from Akwesasne Mohawk women (n=182), 21-39 years of age, between 2009 and 2013. Data collection included anthropometric measurements, medical diagnoses of autoimmune disease and symptoms of autoimmune dysfunction in the medical record, and blood draws for measurement of pollutants. Multivariate analyses determined the association between toxicant exposure and autoimmune dysfunction. Toxicant p,p'-DDE was positively associated with an almost two-fold risk of autoimmune dysfunction. p,p'-DDE and PCB congeners 32, 136, and 138 were positively associated in a multivariate analysis with an autoimmune diagnosis. Pollutant exposures, specifically to p,p'-DDE and some PCB congeners, are common exposures that are associated with autoimmune dysfunction and autoimmune disease, although there are other factors and causes related to autoimmune dysfunction incidence.

Preferences for Rent Control: Between Political Geography and Political Economy

Following geographically concentrated changes in housing markets, real estate prices have skyrocketed in many cities and metropolitan areas across Germany. These developments have not only shifted the macro-level distribution of asset wealth among homeowners but have also resulted in price spikes in rental markets, which in turn have intensified social and economic risks among renters. This preregistered study aims to provide a theoretical rationale for, and first-time insights into, the determinants of individual preferences for rent control. It argues that policy preferences are shaped by individuals’ economic and geographic positions in the housing market. It not only explores differences between homeowners and renters but also considers how heterogeneity in exposure to the burden of rental costs—structured by local rents and disposable income—explains differences within the group of renters. The results reveal the precedence of egotropic considerations over geotropic effects of common market exposures. Homeowners oppose rent control far more strongly than renters do, whose support for rent control is primarily a function of income. Market rents, in contrast, only heighten support for rent control among low-income renters. These findings deepen our understanding of the politicization of housing policy in Germany and advance important debates on political reactions to housing markets.

Lifestyle, demographic and Skindex measures associated with cutaneous T-cell lymphoma: a single institution cohort study.

Cutaneous T-cell lymphoma (CTCL) risk factors and associated quality of life are poorly understood. Previous studies of CTCL risk factors explored patient comorbidities and lifestyle exposures, but not in conjunction with disease stage, subtype, severity, or health-related quality of life (HRQoL). We investigated lifestyle exposures and demographic factors associated with advanced-stage disease, increased disease severity, and poorer HRQoL outcomes in this single-center cohort study. A cohort survey study was conducted at Northwestern's Multidisciplinary Cutaneous Lymphoma specialty clinic between April 2019 and June 2021. REDCap surveys were administered to 140 patients with CTCL, investigating patients' demographics, lifestyle and chemical exposures. QoL was evaluated using the Skindex survey; pain and itch with ten-point Likert scales. Modified Severity Weighted Assessment Tool (mSWAT), disease stage, and disease subtype were confirmed upon enrollment in the study by a single board-certified dermatologist specializing in CTCL. Factors were compared by t test or Fischer's exact test. Median age was 63years (range 14-92) with male-to-female ratio of 1.2:1. The most common diagnosis was CD4 + MF (n = 94, 67.1%). Common lifestyle exposures included smoking (past or current) (52.3%) and chemical exposure history (all sources [53.7%]; industrial only [33.0%]). History of chemical exposures were associated with advanced stage disease (p = 0.003) and worse QoL outcomes (p = 0.001). There were significant racial differences, respectively, in early (I-IIA) vs late (IIB-IV) stage disease (p = 0.003). Obesity, hygiene, smoking, recent sun exposure, education and atopy were not significantly associated with disease stage or severity. We provide an analysis of lifestyle and demographic factors in the context of CTCL disease severity, stage, and HRQoL. We identified race as a potential risk factor for advanced stage disease and both skin phototype and chemical exposures as a risk factor for increased disease severity as measured by mSWAT. QoL outcomes were multifactorial and significantly associated with history of chemical exposure, severe pain/itch, race, disease stage and subtype. An improved understanding of these associations may lead to better individualized care. As chemical exposure and race were found to be significant factors associated with advanced-stage disease, taking exposure histories and addressing racial disparities may improve care for CTCL patients.

Assessment of rabies immune globulin dose rounding at a university health system

PurposeDescribe a dose rounding strategy for rabies immune globulin (RIG) administration. MethodsMulticenter, retrospective, observational review of patients that received RIG following an exposure from an animal with potential to transmit rabies infection in one health-system from March 2011 through December 2021. The primary outcome was to describe the RIG dose rounding strategy and population of patients that received RIG rounded to the nearest vial size compared to those that did not. Secondary outcomes evaluated additional costs and RIG international units (IU) wasted that could have occurred (rounded group) or did occur (not rounded group), re-presentation to the ED or primary care provider (PCP) within 7 days due to RIG related complaint, and occurrence of rabies infection. Data collection included patient demographics, exposure information, and RIG dose administered. Descriptive data and univariate analyses are reported. Cost and RIG IU wasted were calculated for the dosing strategies. Results426 patients were included; 373 (88%) had RIG rounded to the nearest vial size and 53 (12%) did not (mean age 36.1 years ±20.5, 51.6% male, most common exposures were bats [50%], type was bite [58%], and category III exposures [92%]). Those that had RIG rounded were younger and had lower total RIG doses, but similar IU/kg doses to those not rounded. A cost savings of $144,815 and prevention of 40,572 RIG IU wasted was calculated from those patients that had RIG rounded. There was no difference in the rate of re-presentation within 7 days and no cases of human rabies infection in the region during the study period. ConclusionsRIG dose rounding to the nearest vial size is associated with cost savings and prevention of wasting RIG IU. There was no association with re-presentation to the ED or PCP with RIG related issues within 7 days from administration.

A Framework for Policy Inconsistency Detection in Software-Defined Networks

Software-Defined Networking (SDN) has aggressively grown in data center networks, telecommunication providers, and enterprises by virtue of its programmable and extensible control plane. Also, there have been many kinds of research on the security of SDN components along with the growth of SDN. Some of them have inspected network policy inconsistency problems that can severely cause network reliability and security issues in SDN. However, they do not consider whether a single network policy itself is corrupted during processing inside and between SDN components. In this paper, we thus focus on the question of how to automatically identify cases in which the SDN stack fails to prevent policy inconsistencies from arising among those components. We then present AudiSDN, an automated fuzz-testing framework designed to formulate test cases in which policy inconsistencies can arise in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OpenFlow</i> networks, the most prevalent SDN protocol. To prove its feasibility, we applied AudiSDN to two widely used SDN controllers, Floodlight and ONOS, and uncovered three separate CVEs (Common Vulnerabilities and Exposures) that cause the network policy inconsistencies among SDN components. Furthermore, we investigate the design flaws that cause the inconsistencies in modern SDN components, suggesting specific validations to address such a serious but understudied pragmatic concern.

Does Intrapartum Epidural Analgesia Increase the Risk of Autism Spectrum Disorder in Offspring? Most Likely Not

There is no doubt that epidural analgesia is one of the most effective methods of pain relief in labor,1 with up to 7 of every 10 women receiving such analgesia during delivery.2 Local anesthetic with or without adjunct opioid is therefore one of the most common prenatal drug exposures.

DATA SECURITY APPROACH ON CYBERCRIME USING WEB VULNERABILITY

Internet could be a major supply of spreading terrorist act through speeches and videos. Terrorist organizations use net particularly social networks to brain wash people and promote terrorist activities through provocative websites that inspire helpless individuals to affix terrorist organizations. Therefore, here we have a tendency to propose Associate in Nursing economical net data processing system to observe such net properties and flag them mechanically for human review. websites are created from hypertext mark-up language (Hypertext markup language). In numerous arrangements and have pictures, texts etc., intermixed on a single website. Here, we have a tendency to used data processing further as net mining to observe patterns and mine out matter info on websites. Here, we have a tendency to are victimization E-mail System to observe the unwanted messages that are additional prone to terrorist act and can send to the spam on to the recipient who is victimization the system. Despite the speedy increase of cyber threats, there has still been very little analysis into the foundations of the topic or methodologies that would serve to guide info systems researchers and practitioners UN agency touch upon cybersecurity. additionally, very little is thought regarding crime- as-a-service (CaaS), a criminal business model that underpins the crime underground. This analysis gap and also the sensible cybercrime issues we have a tendency to face have impelled North American nation to research the crime underground economy by taking an information analytics approach from a style science perspective. to realize this goal, we: (1) propose a data analysis framework for analyzing the crime underground; (2) propose CaaS and crimeware definitions; (3) propose Associate in Nursing associated classification model, Associate in Nursingd (4) develop an example application to demonstrate however the planned framework and classification model might be enforced in apply. We then use this application to research the crime underground economy by analyzing an oversized knowledge set obtained from the net hacking community. By taking a style science analysis approach, this paper contributes to the planning of the email phishing in the area of cybercrime and the area is to fulfill the data security to the email messages consisting the data and providing them the security using the naïve bayes to planning the International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 06 Issue: 05 | May - 2022 Impact Factor: 7.185 ISSN: 2582-3930 © 2022, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM12419 | Page 2 industries will harden attacks by the crime underground. Among these, one of the attack is the email phishing. Keywords: CAAS (Crimeware-as-a-Service), ICMP (Internet Control Message Protocol), IRC (Internet Relay Chat), MIB (Management Information Base), CVE (Common Vulnerabilities and Exposures).

Cyberattack Path Generation and Prioritisation for Securing Healthcare Systems

Cyberattacks in the healthcare sector are constantly increasing due to the increased usage of information technology in modern healthcare and the benefits of acquiring a patient healthcare record. Attack path discovery provides useful information to identify the possible paths that potential attackers might follow for a successful attack. By identifying the necessary paths, the mitigation of potential attacks becomes more effective in a proactive manner. Recently, there have been several works that focus on cyberattack path discovery in various sectors, mainly on critical infrastructure. However, there is a lack of focus on the vulnerability, exploitability and target user profile for the attack path generation. This is important for healthcare systems where users commonly have a lack of awareness and knowledge about the overall IT infrastructure. This paper presents a novel methodology for the cyberattack path discovery that is used to identify and analyse the possible attack paths and prioritise the ones that require immediate attention to ensure security within the healthcare ecosystem. The proposed methodology follows the existing published vulnerabilities from common vulnerabilities and exposures. It adopts the common vulnerability scoring system so that base metrics and exploitability features can be used to determine and prioritise the possible attack paths based on the threat actor capability, asset dependency and target user profile and evidence of indicator of compromise. The work includes a real example from the healthcare use case to demonstrate the methodology used for the attack path generation. The result from the studied context, which processes big data from healthcare applications, shows that the uses of various parameters such as CVSS metrics, threat actor profile, and Indicator of Compromise allow us to generate realistic attack paths. This certainly supports the healthcare practitioners in identifying the controls that are required to secure the overall healthcare ecosystem.

PDFuzzerGen: Policy-Driven Black-Box Fuzzer Generation for Smart Devices

Black-box fuzzing is a testing technique to find both known and unknown vulnerabilities in software. When applying black-box fuzzing to smart devices, the main idea is to take a smart device as a black box and provide random input through a network-based interface, such as a Web interface. Due to the diversity of Web interface implementations and complex data format, a blind mutation of the message makes the message unable to pass the verification of the device component. Therefore, each Web interface needs a unique fuzzer, which precisely defines a message format of the target interface, a state maintenance method, the field positions to be mutated, and a specific input mutation method. At the time of writing, a fuzzer is completely developed by a security engineer. To save human labor, we present PDFuzzerGen, a tool to automatically synthesize complex black-box fuzzers for smart devices. PDFuzzerGen generates multiple fuzzing policies by analyzing raw messages and then synthesizes fuzzers based on policies. PDFuzzerGen requires no human intervention and can be applied to a wide range of smart devices. Furthermore, the generated fuzzers can expose bugs and flaws that rest deep in smart devices. PDFuzzerGen was evaluated to generate fuzzers for 19 different smart devices from 6 vendors. It has found 14 previously unknown vulnerabilities, 5 of which were confirmed and disclosed by the China National Vulnerability Database (CNVD) and 2 of which were confirmed and disclosed by Common Vulnerabilities and Exposures (CVE). The generated fuzzers outperform some manually crafted fuzzers on a few metrics, including the vulnerability detection rate and time cost of a newly developed fuzzer, which demonstrates the effectiveness and efficiency of PDFuzzerGen.

Environmental Exposures and Extracellular Vesicles: Indicators of Systemic Effects and Human Disease.

Environmental pollutants contribute to the pathogenesis of numerous diseases including chronic cardiovascular, respiratory, and neurodegenerative diseases, among others. Emerging evidence suggests that extracellular vesicles (EVs) may mediate the association of environmental exposures with chronic diseases. The purpose of this review is to describe the impact of common environmental exposures on EVs and their role in linking environmental pollutants to the pathogenesis of chronic systemic diseases. Common environmental pollutants including particulate matter, tobacco smoke, and chemical pollutants trigger the release of EVs from multiple systems in the body. Existing research has focused primarily on air pollutants, which alter EV production and release in the lungs and systemic circulation. Air pollutants also impact the selective loading of EV cargo including microRNA and proteins, which modify the cellular function in recipient cells. As a result, pollutant-induced EVs often contribute to a pro-inflammatory and pro-thrombotic milieu, which increases the risk of pollutant-related diseases including obstructive lung diseases, cardiovascular disease, neurodegenerative diseases, and lung cancer. Common environmental exposures are associated with multifaceted changes in EVs that lead to functional alterations in recipient cells and contribute to the pathogenesis of chronic systemic diseases. EVs may represent emerging targets for the prevention and treatment of diseases that stem from environmental exposures. However, novel research is required to expand our knowledge of the biological action of EV cargo, elucidate determinants of EV release, and fully understand the impact of environmental pollutants on human health.

Cumulative burden of psychiatric disorders and self-harm across 26 adult cancers

Cancer is a life-altering event causing considerable psychological distress. However, information on the total burden of psychiatric disorders across all common adult cancers and therapy exposures has remained scarce. Here, we estimated the risk of self-harm after incident psychiatric disorder diagnosis in patients with cancer and the risk of unnatural deaths after self-harm in 459,542 individuals. Depression was the most common psychiatric disorder in patients with cancer. Patients who received chemotherapy, radiotherapy and surgery had the highest cumulative burden of psychiatric disorders. Patients treated with alkylating agent chemotherapeutics had the highest burden of psychiatric disorders, whereas those treated with kinase inhibitors had the lowest burden. All mental illnesses were associated with an increased risk of subsequent self-harm, where the highest risk was observed within 12 months of the mental illness diagnosis. Patients who harmed themselves were 6.8 times more likely to die of unnatural causes of death compared with controls within 12 months of self-harm (hazard ratio (HR), 6.8; 95% confidence interval (CI), 4.3–10.7). The risk of unnatural death after 12 months was markedly lower (HR, 2.0; 95% CI, 1.5–2.7). We provide an extensive knowledge base to help inform collaborative cancer-psychiatric care initiatives by prioritizing patients who are most at risk.

Comparative Evaluation of NLP-Based Approaches for Linking CAPEC Attack Patterns from CVE Vulnerability Information

Vulnerability and attack information must be collected to assess the severity of vulnerabilities and prioritize countermeasures against cyberattacks quickly and accurately. Common Vulnerabilities and Exposures is a dictionary that lists vulnerabilities and incidents, while Common Attack Pattern Enumeration and Classification is a dictionary of attack patterns. Direct identification of common attack pattern enumeration and classification from common vulnerabilities and exposures is difficult, as they are not always directly linked. Here, an approach to directly find common links between these dictionaries is proposed. Then, several patterns, which are combinations of similarity measures and popular algorithms such as term frequency–inverse document frequency, universal sentence encoder, and sentence BERT, are evaluated experimentally using the proposed approach. Specifically, two metrics, recall and mean reciprocal rank, are used to assess the traceability of the common attack pattern enumeration and classification identifiers associated with 61 identifiers for common vulnerabilities and exposures. The experiment confirms that the term frequency–inverse document frequency algorithm provides the best overall performance.

Introduction: Occupational Hazards to the Joint Replacement Surgeon

Introduction: Occupational Hazards to the Joint Replacement Surgeon

Risk factors, immune response and whole‐genome sequencing of SARS‐CoV‐2 in a cruise ship outbreak in Norway

ObjectiveTo improve understanding of SARS-CoV-2-transmission and prevention measures on cruise ships, we investigated a Norwegian cruise ship outbreak from July to August 2020 using a multidisciplinary approach after a rapid outbreak response launched by local and national health authorities. MethodsWe conducted a cross-sectional study among crew members using epidemiologic data and results from SARS-CoV-2 polymerase chain reaction (PCR) of nasopharynx-oropharynx samples, antibody analyses of blood samples, and whole-genome sequencing. ResultsWe included 114 multinational crew members (71% participation), median age 36 years, and 69% male. The attack rate was 33%; 32 of 37 outbreak cases were seropositive 5-10 days after PCR. One PCR-negative participant was seropositive, suggesting a previous infection. Network-analysis showed clusters based on common exposures, including embarkation date, nationality, sharing a cabin with an infected cabin-mate (adjusted odds ratio [AOR] 3.27; 95% confidence interval [CI] 0.97-11.07, p = 0.057), and specific workplaces (mechanical operations: 9.17 [1.82-45.78], catering: 6.11 [1.83-20.38]). Breaches in testing, quarantine, and isolation practices before/during expeditions were reported. Whole-genome sequencing revealed lineage B.1.36, previously identified in Asia. Despite extensive sequencing, the continued transmission of B.1.36 in Norway was not detected. ConclusionsOur findings confirm the high risk of SARS-CoV-2-transmission on cruise ships related to workplace and cabin type and show that continued community transmission after the outbreak could be stopped by implementing immediate infection control measures at the final destination.