Predicting dental caries outcomes in young adults using machine learning approach.

OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques. METHODS: This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques. RESULTS: The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23. CONCLUSION: Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Identifying predictors of COVID-related delays in cancer-specific medical care.

PURPOSE: Evidence of the impact of the COVID-19 pandemic on cancer prevention and control is growing, but little is known about patient-level factors associated with delayed care. We analyzed data from a survey focused on Iowan cancer patients' COVID-19 experiences in the early part of the pandemic. METHODS: Participants were recruited from the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden (PERCH) program. We surveyed respondents on demographic characteristics, COVID-19 experiences and reactions, and delays in any cancer-related health care appointment, or cancer-related treatment appointments. Two-sided significance tests assessed differences in COVID-19 experiences and reactions between those who experienced delays and those who did not. RESULTS: There were 780 respondents (26% response), with breast, prostate, kidney, skin, and colorectal cancers representing the majority of respondents. Delays in cancer care were reported by 29% of respondents. In multivariable-adjusted models, rural residents (OR 1.47; 95% CI 1.03, 2.11) and those experiencing feelings of isolation (OR 2.18; 95% CI 1.37, 3.47) were more likely to report any delay, where experiencing financial difficulties predicted delays in treatment appointments (OR 5.72; 95% CI 1.96, 16.67). Health insurance coverage and concern about the pandemic were not statistically significantly associated with delays. CONCLUSION: These findings may inform cancer care delivery during periods of instability when treatment may be disrupted by informing clinicians about concerns that patients have during the treatment process. Future research should assess whether delays in cancer care impact long-term cancer outcomes and whether delays exacerbate existing disparities in cancer outcomes.

Citizen science initiatives document biodiversity baselines at an urban lake.

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment.

With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.

Causes of Death in the Presence of Law Enforcement in Johnson County, Iowa, 2011-2020.

Objectives. To examine sudden and unexpected or trauma-related deaths that occurred in the presence of law enforcement in Johnson County, Iowa, between 2011 and 2020. Methods. We identified deaths in the presence of law enforcement using definitions from the National Association of Medical Examiners. We obtained data, including demographics, cause and manner of death, toxicology results, and circumstances and location of event leading to death, from comprehensive medical examiner investigative reports. Results. There were 165 deaths that occurred in the presence of law enforcement: 114 were from a known disease, and 51 were either trauma related or the sudden, unexpected initial presentation of a previously unrecognized disease. Three deaths occurred in the context of physical restraint by law enforcement. Suicide was the leading manner of death among trauma-related deaths; the means of suicide was predictable based on in-custody (hanging) or precustody (firearm) circumstances. Conclusions. Our findings highlight the potential role of medical examiners and coroners in improving completeness of data on reporting death in the presence of law enforcement to public health agencies. (Am J Public Health. 2024;114(6):642-650. https://doi.org/10.2105/AJPH.2024.307616).

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells.

Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018-2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018-19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57-99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO3-N), median intake from water was 44 % (IQR: 26-72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R2 = 0.52) as diet (R2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.

Pesticide use and inflammatory bowel disease in licensed pesticide applicators and spouses in the Agricultural Health Study.

BACKGROUND: Pesticide exposure has been linked to some autoimmune diseases and colorectal cancer, possibly via alteration of gut microbiota or other mechanisms. While pesticides have been linked to gut dysbiosis and inflammation in animal models, few epidemiologic studies have examined pesticides in relation to inflammatory bowel disease (IBD). OBJECTIVES: We evaluated use of pesticides and incident IBD in 68,480 eligible pesticide applicators and spouses enrolled in the Agricultural Health Study. METHODS: Self-reported IBD cases were identified from follow-up questionnaires between enrollment (1993-1997) and 2022. We evaluated IBD incidence in relation to self-reported ever use of 50 pesticides among applicators and spouses. We also explored associations with intensity-weighted lifetime days (IWLD) of pesticide use among male applicators. Covariate-adjusted hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression. RESULTS: We identified 454 IBD cases, including 227 among male applicators. In analyses with applicators and spouses combined, associations were positive (HR > 1.2) for ever vs. never use of five organochlorine insecticides, three organophosphate insecticides, one fungicide, and five herbicides. HRs were highest for dieldrin (HR = 1.59, 95%CI: 1.03, 2.44), toxaphene (HR = 1.61, 95%CI: 1.17, 2.21), parathion (HR = 1.42, 95%CI: 1.03, 1.95), and terbufos (HR = 1.53, 95%CI: 1.19, 1.96). We had limited power in many IWLD of pesticide use analyses and did not find clear evidence of exposure-response trends; however, we observed elevated HRs in all tertiles of IWLD use of terbufos compared to never use (T1 vs. never use HR = 1.52, 95%CI: 1.03, 2.24; T2 vs. never use HR = 1.53, 95%CI: 1.04, 2.26; T3 vs. never use HR = 1.51, 95%CI: 1.03, 2.23). CONCLUSIONS: Exposure to specific pesticides was associated with elevated hazards of IBD. These findings may have public health importance given the widespread use of pesticides and the limited number of known modifiable environmental risk factors for IBD.

Detection of lymphoproliferative disease virus in Iowa Wild Turkeys (Meleagris gallopavo): Comparison of two sections of the proviral genome.

An accurate diagnostic test is an essential aspect of successfully monitoring and managing wildlife diseases. Lymphoproliferative Disease Virus (LPDV) is an avian retrovirus that was first identified in domestic turkeys in Europe and was first reported in a Wild Turkey (Meleagris gallopavo) in the United States in 2009. It has since been found to be widely distributed throughout North America. The majority of studies have utilized bone marrow and PCR primers targeting a 413-nucleotide sequence of the gag gene of the provirus to detect infection. While prior studies have evaluated the viability of other tissues for LPDV detection (whole blood, spleen, liver, cloacal swabs) none to date have studied differences in detection rates when utilizing different genomic regions of the provirus. This study examined the effectiveness of another section of the provirus, a 335-nucleotide sequence starting in the U3 region of the LTR (Long Terminal Repeat) and extending into the Matrix of the gag region (henceforth LTR), for detecting LPDV. Bone marrow samples from hunter-harvested Wild Turkeys (n = 925) were tested for LPDV with the gag gene and a subset (n = 417) including both those testing positive and those where LPDV was not detected was re-tested with LTR. The positive percent agreement (PPA) was 97.1% (68 of 70 gag positive samples tested positive with LTR) while the negative percent agreement (NPA) was only 68.0% (236 of 347 gag negative samples tested negative with LTR). Cohen's Kappa (κ = 0.402, Z = 10.26, p<0.0001) and the McNemar test (OR = 55.5, p<0.0001) indicated weak agreement between the two gene regions. We found that in Iowa Wild Turkeys use of the LTR region identified LPDV in many samples in which we failed to detect LPDV using the gag region and that LTR may be more appropriate for LPDV surveillance and monitoring. However, neither region of the provirus resulted in perfect detection and additional work is necessary to determine if LTR is more reliable in other geographic regions where LPDV occurs.

Potential for managing pool levels in a flood-control reservoir to increase nitrate-nitrogen load reductions.

Few strategies are available to reduce nitrate-nitrogen (NO3 -N) loads at larger landscape scales, but flood control reservoirs are known to reduce riverine loads. In this study, we evaluated the potential to increase nitrogen (N) loss at Lake Red Rock, a large reservoir located in central Iowa, by evaluating the inundation of sediments deposited at the reservoir inflow. Sediment samples were collected at 51 locations in the lower delta region and analyzed for particle size and nutrient content. Nitrogen loss rates in delta sediments were determined from laboratory assays, and satellite imagery was used to develop a rating curve to quantify land area inundated within the delta. The daily mass of NO3 -N reduced with delta inundation was estimated by applying the mean N 24-h loss rate (0.66 g N m2 day-1 ) by the area of inundation (m2 ). Results indicated that raising pool elevations to inundate more of the delta would result in greater N losses, ranging from 2 to 377 Mg per year. Potential N loss of 102 Mg achieved by increasing pool stage by 0.5 m would be equivalent to installing nearly 650 edge-of-field practices in the watershed. Although more work is needed to integrate with an existing environmental pool management plan, study results indicate that reservoir management could achieve N reductions at a novel landscape scale.

Tendencies for Comparing Up and Down: An Examination of the Directional Subscales of the Iowa-Netherlands Comparison Orientation Measure.

People vary in their individual tendencies to compare to others-referred to as social comparison orientation (SCO). Researchers have heretofore developed and validated a scale to assess SCO-the Iowa-Netherlands Comparison Orientation Measure (INCOM). The standard INCOM assesses non-directional comparisons, but not directional comparisons to better- and worse-off others. The goal of the present research was to examine the factor structure and validity of directional (and non-directional) comparison tendencies using the expanded INCOM. Across four archival studies and one pre-registered study using student and non-student samples, we provide evidence for 1) a 3-factor structure for the INCOM with non-directional, directional-upward, and directional-downward SCO dimensions, 2) inter-correlations among the SCO dimensions suggesting convergent validity of the directional scales, 3) greater endorsement of non-directional, then directional-upward, and directional-downward SCO, 4) lower SCO among older individuals and members of racial/ethnic minority groups, and 5) strong and consistent associations of directional-upward SCO with well-being and affect, appearance beliefs (e.g., body satisfaction), social emotions (e.g., envy), and agency-related motivations and consequences in interpersonal contexts, but smaller and less consistent associations of non-directional and directional-downward SCO with outcomes (with notable exceptions). Taken together, this research indicates that SCO is a multi-faceted individual difference variable.

A review of extended coronavirus disease 2019 (COVID-19) isolation duration among inpatients in a tertiary-care hospital-Iowa, 2020-2022.

Of the 2,668 patients admitted with coronavirus disease 2019 (COVID-19), 4% underwent prolonged isolation for >20 days. Reasons for extended isolation were inconsistent with Centers for Disease Control and Prevention (CDC) guidelines in 25% of these patients and were questionable in 54% due to an ongoing critically ill condition at day 20 without CDC-defined immunocompromised status.

Impact of Foliar Fungicide Application on the Culturable Fungal Endophyte Community of Soybean Seed in the Midwest United States.

The purpose of our study was to determine whether the application of quinone outside inhibitor (QoI) and pyrazole-carboxamide fungicides as a tank mix would impact the endophyte community of soybean seed. Field trials during 2018 in Iowa, South Dakota, and Wisconsin, U.S.A., investigated the impact of a single combination fungicide spray at early pod set in soybeans. The composition of culturable endophytic fungi in mature soybean seed was assessed on three cultivars per state, with maturity groups (MGs) ranging from 1.1 to 4.7. An unusually wet 2018 season delayed harvest, which led to a high level of fungal growth in grain. The survey included 1,080 asymptomatic seeds that were disinfested and individually placed on 5-cm-diameter Petri plates of acidified water agar. The survey yielded 721 fungal isolates belonging to 24 putative species in seven genera; taxa were grouped into genera based on a combination of morphological and molecular evidence. The dominant genera encountered in the survey were Alternaria, Diaporthe, and Fusarium. The study showed that the fungicide treatment reduced the incidence of Fusarium in Wisconsin seed, increased the incidence of Diaporthe in seed from all states, and had no impact on the incidence of Alternaria. This is one of the first attempts to characterize the diversity of seed endophytes in soybean and the first to characterize the impacts of fungicide spraying on these endophyte communities across three states. Our study provides evidence that the impact of a fungicide spray on soybean seed endophyte communities may be influenced by site, weather, and cultivar maturity group.

In-depth assessment of critical access hospital stewardship program adherence to the CDC Core Elements in Iowa and Nebraska.

In 21 antimicrobial stewardship programs in critical-access hospitals in Nebraska and Iowa that self-reported nonadherence to a CDC Core Element or Elements, in-depth program assessment and feedback revealed that accountability and education most needed improvement. Recommendations included providing physician and pharmacist training, tracking interventions, and providing education. Program barriers included lack of time and/or personnel and antimicrobial stewardship and/or infectious diseases expertise.

Descriptive epidemiology of central line-associated bloodstream infections at an academic medical center in Iowa, 2019-2022.

BACKGROUND: Central line-associated bloodstream infections (CLABSIs) increased nationally during the COVID-19 pandemic. We described CLABSIs at our institution during 2019 to 2022. METHODS: This retrospective observational study examined CLABSIs among adult inpatients at an 866-bed teaching hospital in the Midwest. CLABSI incidence was trended over time and compared to monthly COVID-19 admissions. Manual chart review was performed to obtain patient demographics, catheter-associated variables, pathogens, and clinical outcomes. RESULTS: We identified 178 CLABSIs. The CLABSI incidence (cases per 1,000 line days) tripled in October 2020 as COVID-19 admissions increased. CLABSIs in 2020 were more frequently caused by coagulase-negative staphylococci and more frequently occurred in the intensive care units 7+ days after central line insertion. The CLABSI incidence normalized in early 2021 and did not increase during subsequent COVID-19 surges. Throughout 2019 to 2022, about half of the nontunneled central venous catheters involved in CLABSI were placed emergently. One-quarter of CLABSIs involved multiple central lines. Chlorhexidine skin treatment adherence was limited by patient refusal. CONCLUSIONS: The increase in CLABSIs in late 2020 during a surge in COVID-19 admissions was likely related to central line maintenance but has resolved. Characterizing CLABSI cases can provide insight into adherence to guideline-recommended prevention practices and identify areas for improvement at individual institutions.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

IMPORTANCE: This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. OBJECTIVES: The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. METHODS: A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. RESULTS: To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. CONCLUSION: The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

Benefits and Challenges of Sealing Deceased Individual Immunization Records in Immunization Information Systems (IIS): An Overview of Iowa's Process.

Data cleansing practices aimed to improve data quality in immunization information systems (IIS) continue to be identified and evaluated by immunization programs to generate accurate and reliable immunization coverage rates. The Iowa Immunization Program has implemented several automated, daily data cleansing practices to improve the quality of records in Iowa's Immunization Registry Information System (IRIS), including the process of sealing records of deceased individuals through vital records matching. This process removes deceased individual records from the active IIS population, which helps reduce denominator inflation and improve the accuracy of immunization rate calculations. Other benefits to this process include decreasing record fragmentation, increasing completeness and accuracy of IIS data, improving reminder/recall functionality, and supporting better clinical decision-making for providers. This process is one of multiple practices implemented in IIS to improve data quality and is limited by several factors, including the inability to capture deaths for out-of-state records.

Iowa family physician's reporting of elder abuse: 20-year follow-up.

The purpose of this project was to assess changes over 20 years, between family physicians perceived magnitude of elder mistreatment, physician knowledge of state laws, barriers to reporting suspected cases, and what is done in practice. Questionnaires were mailed to 1,080 physician members of the Iowa Academy of Family Physicians. Thirty-six percent of physicians returned the questionnaire. These respondents had a mean age of 51 years, were licensed for 19 years, and 51% were male. Twenty-nine percent of physicians ask their patients direct questions about elder abuse in 2022 compared to 14% in 2002. Identifying an elder abuse case was associated with asking direct questions about abuse and the belief that prompt action would be taken. Knowledge of elder abuse legislation was associated with reporting of all abuse cases, along with thinking there were clear definitions of abuse and that reporting benefits patients.

Detection and disease diagnosis trends (2017-2022) for Streptococcus suis, Glaesserella parasuis, Mycoplasma hyorhinis, Actinobacillus suis and Mycoplasma hyosynoviae at Iowa State University Veterinary Diagnostic Laboratory.

BACKGROUND: Accurate measurement of disease associated with endemic bacterial agents in pig populations is challenging due to their commensal ecology, the lack of disease-specific antemortem diagnostic tests, and the polymicrobial nature of swine diagnostic cases. The main objective of this retrospective study was to estimate temporal patterns of agent detection and disease diagnosis for five endemic bacteria that can cause systemic disease in porcine tissue specimens submitted to the Iowa State University Veterinary Diagnostic Laboratory (ISU VDL) from 2017 to 2022. The study also explored the diagnostic value of specific tissue specimens for disease diagnosis, estimated the frequency of polymicrobial diagnosis, and evaluated the association between phase of pig production and disease diagnosis. RESULTS: S. suis and G. parasuis bronchopneumonia increased on average 6 and 4.3%, while S. suis endocarditis increased by 23% per year, respectively. M. hyorhinis and A. suis associated serositis increased yearly by 4.2 and 12.8%, respectively. A significant upward trend in M. hyorhinis arthritis cases was also observed. In contrast, M. hyosynoviae arthritis cases decreased by 33% average/year. Investigation into the diagnostic value of tissues showed that lungs were the most frequently submitted sample, However, the use of lung for systemic disease diagnosis requires caution due to the commensal nature of these agents in the respiratory system, compared to systemic sites that diagnosticians typically target. This study also explored associations between phase of production and specific diseases caused by each agent, showcasing the role of S. suis arthritis in suckling pigs, meningitis in early nursery and endocarditis in growing pigs, and the role of G. parasuis, A. suis, M. hyorhinis and M. hyosynoviae disease mainly in post-weaning phases. Finally, this study highlighted the high frequency of co-detection and -disease diagnosis with other infectious etiologies, such as PRRSV and IAV, demonstrating that to minimize the health impact of these endemic bacterial agents it is imperative to establish effective viral control programs. CONCLUSIONS: Results from this retrospective study demonstrated significant increases in disease diagnosis for S. suis, G. parasuis, M. hyorhinis, and A. suis, and a significant decrease in detection and disease diagnosis of M. hyosynoviae. High frequencies of interactions between these endemic agents and with viral pathogens was also demonstrated. Consequently, improved control programs are needed to mitigate the adverse effect of these endemic bacterial agents on swine health and wellbeing. This includes improving diagnostic procedures, developing more effective vaccine products, fine-tuning antimicrobial approaches, and managing viral co-infections.

One-Week-Ahead Prediction of Cyanobacterial Harmful Algal Blooms in Iowa Lakes.

Cyanobacterial harmful algal blooms (CyanoHABs) pose serious risks to inland water resources. Despite advancements in our understanding of associated environmental factors and modeling efforts, predicting CyanoHABs remains challenging. Leveraging an integrated water quality data collection effort in Iowa lakes, this study aimed to identify factors associated with hazardous microcystin levels and develop one-week-ahead predictive classification models. Using water samples from 38 Iowa lakes collected between 2018 and 2021, feature selection was conducted considering both linear and nonlinear properties. Subsequently, we developed three model types (Neural Network, XGBoost, and Logistic Regression) with different sampling strategies using the nine selected variables (mcyA_M, TKN, % hay/pasture, pH, mcyA_M:16S, % developed, DOC, dewpoint temperature, and ortho-P). Evaluation metrics demonstrated the strong performance of the Neural Network with oversampling (ROC-AUC 0.940, accuracy 0.861, sensitivity 0.857, specificity 0.857, LR+ 5.993, and 1/LR- 5.993), as well as the XGBoost with downsampling (ROC-AUC 0.944, accuracy 0.831, sensitivity 0.928, specificity 0.833, LR+ 5.557, and 1/LR- 11.569). This study exhibited the intricacies of modeling with limited data and class imbalances, underscoring the importance of continuous monitoring and data collection to improve predictive accuracy. Also, the methodologies employed can serve as meaningful references for researchers tackling similar challenges in diverse environments.