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The proposal introduces a frugal device designed to optimize cardiopulmonary resuscitation (CPR) procedures, offering a promising solution to enhance emergency medical care. In CPR, maintaining adequate chest compressions is crucial for sustaining blood circulation and oxygen supply to vital organs until professional medical help arrives. The proposed device addresses this challenge by continuously monitoring the pressure of chest compressions. When the pressure exceeds a preset threshold, the device automatically triggers the deflation of an airbag, thereby damping excess pressure and ensuring compression levels remain within the optimal range. This innovative approach not only improves the effectiveness of CPR delivery but also mitigates the risk of injury to the patient, as excessive compression force can cause rib fractures or other complications. By providing real-time feedback and assistance during CPR, the device has the potential to enhance the quality of care delivered by both trained professionals and lay rescuers, ultimately improving patient outcomes in emergency situations. Overall, the development of this frugal device represents a significant advancement in emergency medical technology,offering a cost- effective and accessible solution to optimize CPR procedures and save lives.

BACKGROUND: Affirming spaces have been associated with improved mental health outcomes for lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) adolescents. METHODS: With data from adolescents currently enrolled in middle or high school across the United States, this study used topic modeling methods to examine students' reports of what they were looking for in LGBTQ-affirming schools and, separately, the association of LGBTQ-affirming schools with suicide risk reduction. RESULTS: Topic models demonstrated consistent themes in how students determined that their school was affirming, such as LGBTQ clubs, teachers requesting pronouns, pride flags, and accepting peers. Students of color uniquely looked for actionable responses in addressing LGBTQ issues. Transgender and nonbinary students required explicit mention of support for transgender issues. Quantitatively, LGBTQ students who reported that their school was LGBTQ-affirming had 20% lower odds of attempting suicide in the past year (adjusted odds ratio = 0.80). CONCLUSIONS: These findings suggest that schools must be safe for all youth and implementing policies that make LGBTQ students feel seen and supported in their identities is a protective factor for mental health. IMPLICATIONS: School policies must ensure that youth have access to supportive people, symbols of support, and LGBTQ clubs and that they are also salient to LGBTQ students of color and transgender and nonbinary students.

The novel acyl-CoA:cholesterol acyltransferase (ACAT) inhibitor CP-113,818 has been characterized in vitro against ACAT isolated from liver and intestine from a variety of species including human subjects, and in vivo in cholesterol-fed rats, hamsters, rabbits, and two species of nonhuman primates. CP-113,818 is a potent and specific inhibitor of liver and intestinal ACAT with IC50s ranging from 17 to 75 nM. This ACAT inhibitor also prevented the absorption of exogenous radiolabeled cholesterol in hamsters (ED50 = 6 micrograms/kg), rabbits (ED50 1/2 10 micrograms/kg), and cynomolgus and African green monkeys (40 and 26% inhibition at 10 mg/kg, respectively). CP-113,818 effectively prevented the increase in liver cholesterol levels in cholesterol-fed rats, hamsters, and rabbits. In lipoprotein characterization studies in rabbits, CP-113,818 selectively decreased apoB-containing lipoproteins (beta-VLDL, IDL, and LDL) and shifted the distribution of cholesterol from beta-VLDL, IDL, and LDL (96% before treatment to 81% after treatment) to HDL (4% before treatment to 19% after treatment). Finally, in monkeys, CP-113,818 significantly decreased LDL cholesterol by approximately 30% while either increasing HDL cholesterol (cynomolgus monkeys) or not affecting HDL cholesterol (African green monkeys), thereby improving the total plasma cholesterol/HDL ratios. In summary, CP-113,818 significantly inhibited cholesterol absorption, prevented the increase in liver cholesterol, and improved the lipoprotein profiles by selectively decreasing the cholesterol concentrations of the atherogenic lipoproteins (VLDL, IDL, and LDL) in a variety of cholesterol-fed animals. These data suggest that ACAT inhibition may be a useful therapeutic approach for lowering LDL cholesterol and thereby reducing the risk of developing coronary heart disease.

Abstract Background Identifying pregnancies at risk for preterm birth, one of the leading causes of worldwide infant mortality, has the potential to improve prenatal care. However, we lack broadly applicable methods to accurately predict preterm birth risk. The dense longitudinal information present in electronic health records (EHRs) is enabling scalable and cost-efficient risk modeling of many diseases, but EHR resources have been largely untapped in the study of pregnancy. Methods Here, we apply machine learning to diverse data from EHRs with 35,282 deliveries to predict singleton preterm birth. Results We find that machine learning models based on billing codes alone can predict preterm birth risk at various gestational ages (e.g., ROC-AUC = 0.75, PR-AUC = 0.40 at 28 weeks of gestation) and outperform comparable models trained using known risk factors (e.g., ROC-AUC = 0.65, PR-AUC = 0.25 at 28 weeks). Examining the patterns learned by the model reveals it stratifies deliveries into interpretable groups, including high-risk preterm birth subtypes enriched for distinct comorbidities. Our machine learning approach also predicts preterm birth subtypes (spontaneous vs. indicated), mode of delivery, and recurrent preterm birth. Finally, we demonstrate the portability of our approach by showing that the prediction models maintain their accuracy on a large, independent cohort (5978 deliveries) from a different healthcare system. Conclusions By leveraging rich phenotypic and genetic features derived from EHRs, we suggest that machine learning algorithms have great potential to improve medical care during pregnancy. However, further work is needed before these models can be applied in clinical settings.

This paper motivates and sketches a set of nuclear-use cases involving conflict on the Korean peninsula. The cases reflect a wide range of ways that nuclear weapons might be brandished or used in a Korean crisis. We identify possible cases by using two different lenses: a “logical” or taxonomic lens and a decisionmaking lens that asks how an actual national leader might decide to use nuclear weapons first. We then select cases from the space of possibilities to reflect that range usefully. The use cases consider mistakes, unintended escalation, coercive threats, limited nuclear use to reinforce threats, defensive operations, and offensive operations. They also consider the potential role of fear, desperation, responsibility, grandiosity, indomitability, and other human emotions. Some use cases are far more plausible than others at present, but estimating likelihoods is a dubious activity. The real challenge is to avoid circumstances where the use cases would become more likely.

Abstract The product encoded by the X-linked inhibitor of apoptosis (XIAP) gene is a multi-functional protein which not only controls caspase-dependent cell death, but also participates in inflammatory signalling, copper homeostasis, response to hypoxia and control of cell migration. Deregulation of XIAP, either by elevated expression or inherited genetic deletion, is associated with several human disease states. Reconciling XIAP-dependent signalling pathways with its role in disease progression is essential to understand how XIAP promotes the progression of human pathologies. In this study we have created a panel of genetically modified XIAP-null cell lines using TALENs and CRISPR/Cas9 to investigate the functional outcome of XIAP deletion. Surprisingly, in our genetically modified cells XIAP deletion had no effect on programmed cell death, but instead the primary phenotype we observed was a profound increase in cell migration rates. Furthermore, we found that XIAP-dependent suppression of cell migration was dependent on XIAPdependent control of C-RAF levels, a protein kinase which controls cell signalling pathways that regulate the cytoskeleton. These results suggest that XIAP is not necessary for control of the apoptotic signalling cascade, however it does have a critical role in controlling cell migration and motility that cannot be compensated for in XIAP-knockout cells.

Since the end of World War II, outer space has been an arena in which both high and low politics have played out, and both the US and Europe have been heavily invested. This article examines the case study of space exploration as a window into the evolving nature of the transatlantic relationship. With the US government regularly deprioritizing Europe in its foreign policy and at times taking the transatlantic relationship for granted, the author argues that transnational and non-state actors have played an important role in maintaining the stability of the alliance. In terms of space, this means that the space community—space agencies, private actors, space enthusiasts, engineers, and scientists, among others—often enable transatlantic cooperation despite initial conflictual rhetoric stemming from political leaders. Importantly, while these transnational or non-state actors tend to view space as a peaceful domain for all of humankind, governments and militaries often treat space as the next battlefield. To support this argument, the article considers two major transatlantic space developments: the US’s Space Force, which reflects a US desire to be dominant in space, and Europe’s Galileo satellite system, which reflects a European goal to have strategic autonomy from the US. The author argues that the idea that space should be a peaceful domain for all of humankind is more strongly reflected in outcomes, despite the presence of conflictual, militaristic rhetoric.

When light hits organic semiconductors, bound charge pairs, called excitons, are usually produced. Here, the authors show that in the best performing organic solar material to date, free charges, rather than excitons, are directly created by light.

Abstract Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Abstract Background There have been ongoing efforts to identify anti-tick vaccine targets to protect cattle from infestation with cattle fever ticks Rhipicephalus (Boophilus) microplus. Two commercial vaccines based on the tick gut protein Bm86 have had variable effectiveness, which has led to poor acceptance, and numerous studies have attempted to identify vaccine antigens that will provide more consistently effective protection. Transcriptomic analysis of R. microplus led to identification of three aquaporin genes annotated to code for transmembrane proteins involved in the transport of water across cell membranes. Previous work showed that vaccination with full-length recombinant aquaporin 1 (RmAQP1) reduced tick burdens on cattle. Targeted silencing of aquaporin 2 (RmAQP2) expression suggested it might also be a good anti-tick vaccination target. Methods Three synthetic peptides from the predicted extracellular domains of RmAQP2 were used to vaccinate cattle. Peptides were conjugated to keyhole limpet hemocyanin (KLH) as an antigenic carrier molecule. We monitored the antibody response with ELISA and challenged vaccinated cattle with R. microplus larvae. Results There was a 25% reduction overall in the numbers of ticks feeding to repletion on the vaccinated cattle. Immune sera from vaccinated cattle recognized native tick proteins on a western blot and reacted to the three individual synthetic peptides in an ELISA. The vaccinated calf with the highest total IgG titer was not the most effective at controlling ticks; ratios of IgG isotypes 1 and 2 differed greatly among the three vaccinated cattle; the calf with the highest IgG1/IgG2 ratio had the fewest ticks. Ticks on vaccinated cattle had significantly greater replete weights compared to ticks on controls, mirroring results seen with RNA silencing of RmAQP2. However, protein data could not confirm that vaccination had any impact on the ability of the tick to concentrate its blood meal by removing water. Conclusions A reduced number of ticks feed successfully on cattle vaccinated to produce antibodies against the extracellular domains of RmAQP2. However, our predicted mechanism, that antibody binding blocks the ability of RmAQP2 to move water out of the blood meal, could not be confirmed. Further study will be required to define the mechanism of action and to determine whether these vaccine targets will be useful components of an anti-tick vaccine cocktail. Graphical Abstract

Abstract Background Mental health is an integral part of overall health. Mental health disorders following childbirth are common and poor maternal mental health has consequences for both the mother and her infant. Preeclampsia is also relatively common in pregnancy but there is little known about the intersection between these two important conditions. Gaining a better understanding of the psychological consequences following preeclampsia is important, especially the link with depression, anxiety and posttraumatic stress disorder. If women who experience preeclampsia are recognised as being at increased risk of poor mental health, targeted screening in the postpartum period should be implemented. Aims To describe the prevalence and symptom severity of depression, anxiety and posttraumatic stress disorder at six months postpartum in women, who had a diagnosis of preeclampsia, compared to those who had normal blood pressure in pregnancy. Methods The mental health component of the prospective cohort study, the Postpartum, Physiology, Psychology and Paediatric follow-up study (P4 Study) was used. Women diagnosed with preeclampsia (n = 90) and those who were normotensive during pregnancy (n = 302) completed the Edinburgh Postnatal Depression Scale, General Anxiety Disorder Scale, and the Posttraumatic Stress Diagnostic Scale or Posttraumatic Stress Diagnostic Sclae-5 at six months postpartum. Results At six months postpartum, depressive scores were similar in both groups but a higher proportion of women from the preeclampsia group scored above the threshold for depression (2% v 7% p = 0.04). There were no differences between the groups in the prevalence or severity of anxiety or PTSD. However, more women in the preeclampsia group reported their birth experience as a traumatic event (1% vs 7%, p = 0.01). On correlation testing and modelling, booking Edinburgh Postnatal Depression Scale score, any mental health history, experiencing birth as traumatic and the General Anxiety Disorder Scale score were independent predictors of postpartum Edinburgh Postnatal Depression Scale scores. Conclusion The postpartum clinical care of women with preeclampsia often focusses on the immediate physical health issues, but these women may also benefit from mental health screening. Targeted screening of preeclamptic women in the postpartum period may lead to more timely referral and initiation of treatment. Trial registration Retrospectively registered on 18/11/2013 with the Australian and New Zealand Clinical Trials Registry. Registration Number: ACTRN12613001260718 .

Abstract Background Characteristics of both individuals and innovations are foundational determinants to the adoption of evidenced-based practices (EBPs). However, our understanding about what drives EBP adoption is limited by few studies examining relationships among implementation determinants and implementation outcomes through theory-driven hypothesis testing. Therefore, drawing on the Theory of Planned Behavior and Diffusion of Innovations Theory, this study will disentangle relationships between provider characteristics and innovation factors on the early adoption of the Ohio State University Traumatic Brain Injury Identification Method (OSU TBI-ID) in behavioral health settings. Methods This study will utilize an explanatory sequential mixed methods design. In Phase I (quantitative), Time 1, we will investigate behavioral health providers (N = 200) attitudes, perceived behavioral control, subjective norms, and intentions to screen for TBI upon completion of a video module introducing the OSU TBI-ID. At Time 2, we will examine the number of TBI screens conducted over the previous month, as well as the feasibility, appropriateness, and acceptability of using the OSU TBI-ID in practice. Structural equation modeling will be used to determine whether provider characteristics predict TBI screening intentions, and whether intentions mediate actual TBI screening behaviors. We will then test whether feasibility, appropriateness, and acceptability of the OSU TBI-ID moderates the relationship between intentions and TBI screening behaviors. In Phase II (qualitative), we will develop an interview guide using results from Phase I and will conduct semi-structured interviews with providers (N = 20) to assess contextual determinants of TBI screening adoption. Qualitative data will be thematically analyzed using sensitizing concepts from the Consolidated Framework for Implementation Research and integrated with the quantitative results using a joint display. Discussion This mixed methods study capitalizes on two theory-driven hypotheses bridging proximal (e.g., screening intent) to distal (actual behaviors) implementation outcomes and will contextualize these results qualitatively to advance our understanding about why TBI screening adoption has failed to translate to the behavioral healthcare context. Results of this study will offer insights into what is driving TBI screening adoption so that implementation strategies can be selected with greater precision to improve the adoption, sustainment, and scale-up of TBI screening in behavioral healthcare.

Abstract Background Unfair treatment such as discrimination and racism contribute to depression and perceived stress in African Americans. Although studies have examined how responding to such treatment is associated with ameliorating depressive symptoms and levels of perceived stress, most do not focus on African Americans. The purpose of this study is to assess how talking to others in response to unfair treatment is associated with self-reported depressive symptoms and perceived stress levels in African Americans. Methods A sample from the 2010–2013 Minority Health Genomics and Translational Research Bio-Repository Database was used and consisted of 376 African American adults aged 30–55 years old residing in the southern region of the United States. Linear regression models were used to assess the association between talking to others following unfair treatment, compared to keeping it to oneself, on self-reported depressive symptoms and perceived stress. The predictor variable was based on the question “If you have been treated unfairly, do you usually talk to people about it or keep it to yourself?”. Results Talking to someone after being treated unfairly was inversely associated with perceived stress ( $$\beta$$ β : -3.62, SE: 1.14, p ≤ 0.05) and depressive symptoms ( $$\beta$$ β : -3.62, SE: 1.14, p ≤ 0.05). Conclusions African Americans who talked to others in response to unfair treatment had lower depressive symptoms and perceived stress than those who kept it to themselves. More outreach to African Americans regarding the importance of talk in response to exposure to unfair treatment is needed as a potential coping mechanism.

Recognition systems in the remote sensing domain often operate in “open-world” environments, where they must be capable of accurately classifying data from the in-distribution categories while simultaneously detecting and rejecting anomalous/out-of-distribution (OOD) inputs. However, most modern designs use deep neural networks (DNNs) to perform this recognition function that are trained under “closed-world” assumptions in offline-only environments. As a result, by construction, these systems are ill-posed to handle anomalous inputs and have no mechanism for improving OOD detection abilities during deployment. In this work, we address these weaknesses from two aspects. First, we introduce advanced DNN training methods to codesign for accuracy and OOD detection in the offline training phase. We then propose a novel “learn-online” workflow for updating the DNNs during deployment using a small library of carefully collected samples from the operating environment. To show the efficacy of our methods, we consider experimenting with two popular recognition tasks in remote sensing: scene classification in electro-optical satellite images and automatic target recognition in synthetic aperture radar imagery. In both, we find that our two primary design contributions can individually improve detection performance, while also being complementary. Additionally, we find that detection performance on difficult and highly granular OOD samples can be drastically improved using only tens or hundreds of samples collected from the environment. Finally, through analysis, we determine that the logic for adding/removing samples from the collection library is of key importance and using a proper learning rate during the model update step is critical.

Abstract Psilocybin has shown promise for the treatment of mood disorders, which are often accompanied by cognitive dysfunction including cognitive rigidity. Recent studies have proposed neuropsychoplastogenic effects as mechanisms underlying the enduring therapeutic effects of psilocybin. In an open-label study of 24 patients with major depressive disorder, we tested the enduring effects of psilocybin therapy on cognitive flexibility (perseverative errors on a set-shifting task), neural flexibility (dynamics of functional connectivity or dFC via functional magnetic resonance imaging), and neurometabolite concentrations (via magnetic resonance spectroscopy) in brain regions supporting cognitive flexibility and implicated in acute psilocybin effects (e.g., the anterior cingulate cortex, or ACC). Psilocybin therapy increased cognitive flexibility for at least 4 weeks post-treatment, though these improvements were not correlated with the previously reported antidepressant effects. One week after psilocybin therapy, glutamate and N-acetylaspartate concentrations were decreased in the ACC, and dFC was increased between the ACC and the posterior cingulate cortex (PCC). Surprisingly, greater increases in dFC between the ACC and PCC were associated with less improvement in cognitive flexibility after psilocybin therapy. Connectome-based predictive modeling demonstrated that baseline dFC emanating from the ACC predicted improvements in cognitive flexibility. In these models, greater baseline dFC was associated with better baseline cognitive flexibility but less improvement in cognitive flexibility. These findings suggest a nuanced relationship between cognitive and neural flexibility. Whereas some enduring increases in neural dynamics may allow for shifting out of a maladaptively rigid state, larger persisting increases in neural dynamics may be of less benefit to psilocybin therapy.

Abstract Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk. We used genetic approaches to identify inflammatory mechanisms associated with kynurenine variability and their relationship to cardiometabolic disease. We identified single-nucleotide polymorphisms (SNPs) previously associated with plasma kynurenine, including a missense-variant (rs3184504) in the inflammatory gene SH2B3/LNK. We examined the association between rs3184504 and plasma kynurenine in independent human samples, and measured kynurenine levels in SH2B3-knock-out mice and during human LPS-evoked endotoxemia. We conducted phenome scanning to identify clinical phenotypes associated with each kynurenine-related SNP and with a kynurenine polygenic score using the UK-Biobank (n = 456,422), BioVU (n = 62,303), and Electronic Medical Records and Genetics (n = 32,324) databases. The SH2B3 missense variant associated with plasma kynurenine levels and SH2B3 −/− mice had significant tissue-specific differences in kynurenine levels.LPS, an acute inflammatory stimulus, increased plasma kynurenine in humans. Mendelian randomization showed increased waist-circumference, a marker of central obesity, associated with increased kynurenine, and increased kynurenine associated with C-reactive protein (CRP). We found 30 diagnoses associated (FDR q

Genome-wide association studies of COVID-19 have identified genetic loci affecting disease severity, but the mechanisms remain to be fully described. Here, the authors use genetically predicted transcriptome, splicing and proteome data to identify potential genes and pathways underlying COVID- 19 severity.

Genetic studies on complex traits have revealed a substantial role for common, small-effect polygenic burden and large-effect variants. Here, the authors investigate how these types of variation can inform disease risk stratification and prediction.

Summary: Understanding which biological pathways are specific versus general across diagnostic categories and levels of symptom severity is critical to improving nosology and treatment of psychopathology. Here, we combine transdiagnostic and dimensional approaches to genetic discovery for the first time, conducting a novel multivariate genome-wide association study of eight psychiatric symptoms and disorders broadly related to mood disturbance and psychosis. We identify two transdiagnostic genetic liabilities that distinguish between common forms of psychopathology versus rarer forms of serious mental illness. Biological annotation revealed divergent genetic architectures that differentially implicated prenatal neurodevelopment and neuronal function and regulation. These findings inform psychiatric nosology and biological models of psychopathology, as they suggest that the severity of mood and psychotic symptoms present in serious mental illness may reflect a difference in kind rather than merely in degree.

Antibody responses to SARS-CoV-2 are critical in the immune response to infection, but the potential cross-reactivity to other human corona viruses is poorly appreciated. Here the authors apply a systems based approach to characterise the antibody response in pre-pandemic cohorts and assess heterotypic reactivity to SARS-CoV-2.

Longitudinal analyses are needed to show how the immune response to Sars-Cov-2 infection changes over time. Here, the authors use multiple strategies to profile the change in immune cell responses from patients with convalescent COVID-19 over the course of ~5 months, showing that although neutralizing antibody responses drop off after ~4 months, B cell immune responses strengthen.

Worldwide, there are increasing concerns about postsecondary students’ mental health and how student success is implicated. Previous research has established psychological well-being and self-regulated learning are important components of student success, however, there is a paucity of research examining the interplay between these factors during a semester-long course. In this study, 118 students in a learning-to-learn elective university course completed nine weekly online planning and reflection tools. Students planned for a study session, completed an academic engagement and a psychological well-being measure, then reflected on a challenge faced and described the strategy chosen to overcome that challenge. Findings revealed (a) students who reported always attaining their goals also reported higher overall psychological well-being, and (b) within-person patterns of psychological well-being and academic engagement over time may affect regulatory responses to challenge or vice versa. Implications for theory, research, and practice are discussed.

The Pacific Northwest (PNW) is one of the largest commercial harvesting areas for Pacific oysters (Crassostrea gigas) in the United States. Vibrio parahaemolyticus, a bacterium naturally present in estuarine waters accumulates in shellfish and is a major cause of seafood-borne illness. Growers, consumers, and public-health officials have raised concerns about rising vibriosis cases in the region. Vibrio parahaemolyticus genetic markers (tlh, tdh, and trh) were estimated using an most-probable-number (MPN)-PCR technique in Washington State Pacific oysters regularly sampled between May and October from 2005 to 2019 (N = 2,836); environmental conditions were also measured at each sampling event. Multilevel mixed-effects regression models were used to assess relationships between environmental measures and genetic markers as well as genetic marker ratios (trh:tlh, tdh:tlh, and tdh:trh), accounting for variation across space and time. Spatial and temporal dependence were also accounted for in the model structure. Model fit improved when including environmental measures from previous weeks (1-week lag for air temperature, 3-week lag for salinity). Positive associations were found between tlh and surface water temp, specifically between 15 and 26°C, and between trh and surface water temperature up to 26°C. tlh and trh were negatively associated with 3-week lagged salinity in the most saline waters (> 27 ppt). There was also a positive relationship between tissue temperature and tdh, but only above 20°C. The tdh:tlh ratio displayed analogous inverted non-linear relationships as tlh. The non-linear associations found between the genetic targets and environmental measures demonstrate the complex habitat suitability of V. parahaemolyticus. Additional associations with both spatial and temporal variables also suggest there are influential unmeasured environmental conditions that could further explain bacterium variability. Overall, these findings confirm previous ecological risk factors for vibriosis in Washington State, while also identifying new associations between lagged temporal effects and pathogenic markers of V. parahaemolyticus.