Improving high throughput manufacture of laser-inscribed graphene electrodes via hierarchical clustering.

Laser-inscribed graphene (LIG), initially developed for graphene supercapacitors, has found widespread use in sensor research and development, particularly as a platform for low-cost electrochemical sensing. However, batch-to-batch variation in LIG fabrication introduces uncertainty that cannot be adequately tracked during manufacturing process, limiting scalability. Therefore, there is an urgent need for robust quality control (QC) methodologies to identify and select similar and functional LIG electrodes for sensor fabrication. For the first time, we have developed a statistical workflow and an open-source hierarchical clustering tool for QC analysis in LIG electrode fabrication. The QC process was challenged with multi-operator cyclic voltammetry (CV) data for bare and metalized LIG. As a proof of concept, we employed the developed QC process for laboratory-scale manufacturing of LIG-based biosensors. The study demonstrates that our QC process can rapidly identify similar LIG electrodes from large batches (n ≥ 36) of electrodes, leading to a reduction in biosensor measurement variation by approximately 13% compared to the control group without QC. The statistical workflow and open-source code presented here provide a versatile toolkit for clustering analysis, opening a pathway toward scalable manufacturing of LIG electrodes in sensing. In addition, we establish a data repository for further study of LIG variation.

Impact of Nutritional Status on Total Brain Tissue Volumes in Preterm Infants.

Preterm infants bypass the crucial in utero period of brain development and are at increased risk of malnutrition. We aimed to determine if their nutritional status is associated with brain tissue volumes at term equivalent age (TEA), applying recently published malnutrition guidelines for preterm infants. We performed a single center retrospective chart review of 198 infants < 30 weeks' gestation between 2018 and 2021. We primarily analyzed the relationship between the manually obtained neonatal MR-based brain tissue volumes with the maximum weight and length z-score. Significant positive linear associations between brain tissue volumes at TEA and weight and length z-scores were found (p < 0.05). Recommended nutrient intake for preterm infants is not routinely achieved despite efforts to optimize nutrition. Neonatal MR-based brain tissue volumes of preterm infants could serve as objective, quantitative and reproducible surrogate parameters of early brain development. Nutrition is a modifiable factor affecting neurodevelopment and these results could perhaps be used as reference data for future timely nutritional interventions to promote optimal brain volume.

NRBC concentrations over time in neonates with moderate to severe neonatal encephalopathy with and without sentinel events.

OBJECTIVE: To study the serum concentrations of nucleated red blood cells (NRBC) over time in neonates with moderate to severe neonatal encephalopathy (NE). STUDY DESIGN: A retrospective cohort study with subjects subdivided into three groups: definite sentinel events (n = 52), probable sentinel events (n = 20) and no history of sentinel events (n = 63). Peak absolute NRBC and NRBC/100 WBC were compared between groups and with MRI Injury score, cord and admission pH/base deficit. RESULTS: Absolute NRBC peaked at 24.05 h after birth (CI: 15.30-32.79), 17.56 h after birth (CI: 7.35-27.77), and 39.81 h after birth (CI: 28.73-50.89) in each respective group. The peak in absolute NRBC correlated with the severity of injury in the grey matter in group 2 and white matter in groups 1 and 2. Higher peak absolute NRBC value correlated to a lower admission ABG pH. CONCLUSION: NRBC peak at 24 h after birth in neonates with sentinel events.

Exploratory Analysis of Farm Vehicle and Farm Labor Transportation-Related Crashes.

OBJECTIVE: The purpose of this study was to investigate characteristics associated with farm vehicle and farm labor transportation-related roadway crashes in the state of Florida. Agricultural roadway crashes related to these vehicles have not been explored in Florida. METHODS: The data for this study comes from the Florida Department of Highway Safety and Motor Vehicles (FLHSMV) for the years 2013-2021. The data is recorded by the Florida Highway Patrol when a vehicular crash has occurred. The data is then coded to allow the selection of farm and agricultural-related vehicles. Specifically, this study focuses on farm labor transport vehicles and farm vehicles (e.g. farm tractors). RESULTS: There were 744 farm vehicle- and 209 farm labor transportation-related crashes during the 9-year study period. The farm labor transport vehicle crashes involved a total of 420 vehicles and 1,329 individuals, and the farm vehicle crashes involved 1,458 vehicles and 1,652 individuals. Injury risk for non-farm labor transportation vehicle occupants was significantly higher than injury risk for farm labor transportation vehicle occupants. CONCLUSIONS: The average fatality rate for farm vehicle-involved (2.1 fatalities per 100 crashes) and farm labor transportation vehicle-involved crashes (2.9 fatalities per 100 crashes) were much higher than the overall FL roadway crash fatality rate (0.45 fatalities per 100 crashes).

Machine Learning for Improved Detection of Pathogenic E. coli in Hydroponic Irrigation Water Using Impedimetric Aptasensors: A Comparative Study.

Reuse of alternative water sources for irrigation (e.g., untreated surface water) is a sustainable approach that has the potential to reduce water gaps, while increasing food production. However, when growing fresh produce, this practice increases the risk of bacterial contamination. Thus, rapid and accurate identification of pathogenic organisms such as Shiga-toxin producing Escherichia coli (STEC) is crucial for resource management when using alternative water(s). Although many biosensors exist for monitoring pathogens in food systems, there is an urgent need for data analysis methodologies that can be applied to accurately predict bacteria concentrations in complex matrices such as untreated surface water. In this work, we applied an impedimetric electrochemical aptasensor based on gold interdigitated electrodes for measuring E. coliO157:H7 in surface water for hydroponic lettuce irrigation. We developed a statistical machine-learning (SML) framework for assessing different existing SML methods to predict the E. coliO157:H7 concentration. In this study, three classes of statistical models were evaluated for optimizing prediction accuracy. The SML framework developed here facilitates selection of the most appropriate analytical approach for a given application. In the case of E. coliO157:H7 prediction in untreated surface water, selection of the optimum SML technique led to a reduction of test set RMSE by at least 20% when compared with the classic analytical technique. The statistical framework and code (open source) include a portfolio of SML models, an approach which can be used by other researchers using electrochemical biosensors to measure pathogens in hydroponic irrigation water for rapid decision support.

A capacitive laser-induced graphene based aptasensor for SARS-CoV-2 detection in human saliva.

SARS-CoV-2 virus induced CoVID-19 pandemic has accelerated the development of diagnostic tools. Devices integrated with electrochemical biosensors may be an interesting alternative to respond to the high demand for testing, particularly in contexts where access to standard detection technologies is lacking. Aptamers as recognition elements are useful due to their stability, specificity, and sensitivity to binding target molecules. We have developed a non-invasive electrochemical aptamer-based biosensor targeting SARS-CoV-2 in human saliva. The aptamer is expected to detect the Spike protein of SARS-CoV-2 wildtype and its variants. Laser-induced graphene (LIG) electrodes coated with platinum nanoparticles were biofunctionalized with a biotin-tagged aptamer. Electrochemical Impedance Spectroscopy (EIS) for BA.1 sensing was conducted in sodium chloride/sodium bicarbonate solution supplemented with pooled saliva. To estimate sensing performance, the aptasensor was tested with contrived samples of UV-attenuated virions from 10 to 10,000 copies/ml. Selectivity was assessed by exposing the aptasensor to non-targeted viruses (hCoV-OC43, Influenza A, and RSV-A). EIS data outputs were further used to select a suitable response variable and cutoff frequency. Capacitance increases in response to the gradual loading of the attenuated BA.1. The aptasensor was sensitive and specific for BA.1 at a lower viral load (10-100 copies/ml) and was capable of discriminating between negative and positive contrived samples (with strain specificity against other viruses: OC43, Influenza A, and RSV-A). The aptasensor detected SARS-CoV-2 with an estimated LOD of 1790 copies/ml in contrived samples. In human clinical samples, the aptasensor presents an accuracy of 72%, with 75% of positive percent of agreement and 67% of negative percent of agreement. Our results show that the aptasensor is a promising candidate to detect SARS-CoV-2 during early stages of infection when virion concentrations are low, which may be useful for preventing the asymptomatic spread of CoVID-19.

Concentration of Serum Biomarkers of Brain Injury in Neonates With a Low Cord pH With or Without Mild Hypoxic-Ischemic Encephalopathy.

Objective: To determine the concentrations of four neuroprotein biomarkers and 68 miRNAs in neonates with low cord pH and/or mild hypoxic-ischemic encephalopathy (HIE). Study Design: A prospective cohort study enrolled neonates with low cord pH (n = 18), moderate-severe HIE (n = 40), and healthy controls (n = 38). Groups provided serum samples at 0-6 h of life. The concentrations of biomarkers and miRNAs were compared between cohorts. Result: The low cord pH and moderate-severe HIE groups had increased concentrations of GFAP, NFL and Tau compared to controls (P < 0.05, P < 0.001, respectively). NFL concentrations in mild HIE was higher than controls (P < 0.05) but less than moderate-severe HIE (P < 0.001). Of 68 miRNAs, 36 in low cord pH group and 40 in moderate-severe HIE were upregulated compared to controls (P < 0.05). Five miRNAs in low cord pH group (P < 0.05) and 3 in moderate-severe HIE were downregulated compared to controls (P < 0.05). Conclusion: A biomarker panel in neonates with low cord pH may help clinicians make real-time decisions.

Examining Older Adults' Home Functioning Using the American Housing Survey.

Identifying individuals at risk of experiencing functional difficulty at home would support timely home safety assessment and modification services, which could lead to reducing home incidents such as falls. The objective of this study was to calculate older adults' functional difficulty at home scores using the 12 physical function items in the American Housing Survey National and Metropolitan Data (AHS). Among the 28,474 older adults selected for this study, we used 19,932 for measurement model development and 8542 for model testing. Confirmatory factor analysis confirmed an adequate fit of the one-dimensional model with all AHS 12 items loading on one latent construct (functional difficulty at home) (RMSEA: 0.034, CFI: 0.990, and TLI: 0.988). Based on our model selection process, we determined that the Graded Response Model was an optimal model for our analysis and separated two detected differential functioning items for each sex. Using the testing dataset, we validated that the estimated functional difficulty scores showed an expected item hierarchy and statistically significant differences in their association with housing and demographic conditions (p < 0.001). Our results demonstrated the process of using the 12 AHS physical function at home items to produce validated scores of older adults' functional difficulty at home.

Metabolomic selection for enhanced fruit flavor.

Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties.

Improving national level spatial mapping of malaria through alternative spatial and spatio-temporal models.

The most common approach to create spatial prediction of malaria in the literature is to approximate a Gaussian process model using stochastic partial differential equation (SPDE). We compared SPDE to computationally faster alternatives, generalized additive model (GAM) and state-of-the-art machine learning method gradient boosted trees (GBM), with respect to their predictive skill for country-level malaria prevalence mapping. We also evaluated the intuition that incorporation of past data and the use of spatio-temporal models may improve predictive accuracy of present spatial distribution of malaria. Model performances varied among the countries and setting with SPDE and GAM performed well generally. The inclusion of past data is beneficial for GAM and GBM, but not for SPDE. We further investigated the weaknesses of SPDE at spatio-temporal setting and GAM at the edges of the countries. Taken together, we believe that spatial/spatio-temporal SPDE models should be evaluated alongside with the alternatives or at least GAM.

Comparing head ultrasounds and susceptibility-weighted imaging for the detection of low-grade hemorrhages in preterm infants.

OBJECTIVE: Intraventricular hemorrhage (IVH) is a complication of prematurity. Grades III and IV IVH lead to significant morbidity, but mounting evidence shows low-grade IVH (grades I-II) may be associated with adverse sequelae. Head ultrasounds (HUS) are used to screen infants for IVH but may miss low-grade IVH. Our study compared the results of HUS around 7 days of age to susceptibility-weighted imaging (SWI) obtained at term-corrected age in infants born at <30 wGA. STUDY DESIGN: Infants <30 weeks gestational age (GA) with an HUS and MRI at admission to UF Health were identified by a retrospective chart review. Images were re-read by a pediatric neuroradiologist. RESULTS: Ninety-four infants with a mean GA of 25.8 weeks were identified. Of those with normal HUS, 50% had low-grade IVH on the term-corrected MRI. CONCLUSIONS: HUS are effective for screening for high-grade IVH. SWI is more sensitive in identifying low-grade IVH.

Early exposure to a methyl donor supplemented diet and the development of repetitive motor behavior in a mouse model.

Motor behaviors that are repetitive and exhibit little variability in form are common in neurodevelopmental disorders (e.g., autism spectrum disorder). C58 mice exhibit persistent, high levels of repetitive motor behavior when reared in restricted, but not enriched, environments implicating epigenetic mechanisms (e.g., DNA methylation). We sought to determine if alteration of DNA methylation played a role in the development of repetitive behavior in C58 mice. Thus, we tested the hypothesis that early exposure (in utero and preweaning) to a methyl donor supplemented diet would alter the developmental trajectory of repetitive behavior. Such dietary exposure resulted in significant attenuation of repetitive motor behavior development, persisting through early adulthood. This was despite mice being housed in standard cages and maintained on a standard diet, postweaning. Early exposure to methyl donor supplementation not only affected the frequency of repetitive behavior but also its temporal structure, resulting in more variable patterns of repetitive behavior. Early exposure to the diet was also shown to induce long-lasting increases in DNA methylation in brain tissue of female mice. The role for alterations in DNA methylation in this model may be one mechanism accounting for the robust effects of the environment on the development of repetitive behavior.

A Spatio-Temporal Modeling Framework for Surveillance Data of Multiple Infectious Pathogens with Small Laboratory Validation Sets.

Many surveillance systems of infectious diseases are syndrome-based, capturing patients by clinical manifestation. Only a fraction of patients, mostly severe cases, undergo laboratory validation to identify the underlying pathogen. Motivated by the need to understand transmission dynamics and associate risk factors of enteroviruses causing the hand, foot and mouth disease (HFMD) in China, we developed a Bayesian spatio-temporal modeling framework for surveillance data of infectious diseases with small validation sets. A novel approach was proposed to sample unobserved pathogen-specific patient counts over space and time and was compared to an existing sampling approach. The practical utility of this framework in identifying key parameters was assessed in simulations for a range of realistic sizes of the validation set. Several designs of sampling patients for laboratory validation were compared with and without aggregation of sparse validation data. The methodology was applied to the 2009 HFMD epidemic in southern China to evaluate transmissibility and the effects of climatic conditions for the leading pathogens of the disease, enterovirus 71 and Coxsackie A16.

A Pilot Study of Inhaled CO Therapy in Neonatal Hypoxia-Ischemia: Carboxyhemoglobin Concentrations and Brain Volumes.

Objective: The objective of this pilot study was to start evaluating the efficacy and the safety (i.e., carboxyhemoglobin concentration of carbon monoxide (CO)) as a putative neuroprotective therapy in neonates. Study Design: Neonatal C57BL/6 mice were exposed to CO at a concentration of either 200 or 250 ppm for a period of 1 h. The pups were then sacrificed at 0, 10, 20, 60, 120, 180, and 240 min after exposure to either concentration of CO, and blood was collected for analysis of carboxyhemoglobin. Following the safety study, 7-day-old pups underwent a unilateral carotid ligation. After recovery, the pups were exposed to a humidified gas mixture of 8% oxygen and 92% nitrogen for 20 min in a hypoxia chamber. One hour after the hypoxia exposure, the pups were randomized to one of two groups: air (HI+A) or carbon monoxide (HI+CO). An inhaled dose of 250 ppm of CO was administered to the pups for 1 h per day for a period of 3 days. At 7 days post-injury, the pups were sacrificed and the brains analyzed for cortical and hippocampal volumes. Results: CO exposure at 200 and 250 ppm produced a peak carboxyhemoglobin concentration of 21.52 ± 1.18% and 27.55 ± 3.58%, respectively. The carboxyhemoglobin concentrations decreased rapidly, reaching control concentrations by 60 min post exposure. At 14 days of age (7 days post injury), the HI+CO (treated with 1 h per day of 250 ppm of CO for 3 days post injury) had significant preservation of the ratio of ipsilateral to contralateral cortex (median 1.07, 25% 0.97, 75% 1.23, n = 10) compared the HI+A group (p < 0.05). Conclusion: CO exposure of 250 ppm did not reach carboxyhemoglobin concentrations which would induce acute neurologic abnormalities and was effective in preserving cortical volumes following hypoxic-ischemic injury.

Enteral Feeding as an Adjunct to Hypothermia in Neonates with Hypoxic-Ischemic Encephalopathy.

BACKGROUND: Withholding enteral feedings during hypothermia lacks supporting evidence. OBJECTIVES: We aimed to determine if minimal enteral nutrition (MEN) during hypothermia in patients with hypoxic-ischemic encephalopathy was associated with a reduced duration of parenteral nutrition, time to full oral feeds, and length of stay, but would not be associated with increased systemic inflammation or feeding complications. METHODS: We performed a pilot, retrospective, matched case-control study within the Florida Neonatal Neurologic Network from December 2012 to May 2016 of patients who received MEN during hypothermia (n = 17) versus those who were not fed (n = 17). Length of stay, feeding-related outcomes, and brain injury identified by MRI were compared. Serum inflammatory mediators were measured at 0-6, 24, and 96 h of life by multiplex assay. MRI were scored using the Barkovich system. RESULTS: MEN subjects had a reduced length of hospital stay (mean 15 ± 11 vs. 24 ± 19 days, p < 0.05), days receiving parenteral nutrition (7 ± 2 vs. 11 ± 6, p < 0.05), and time to full oral feeds (8 ± 5 vs. 18 ± 18, p < 0.05). MEN was associated with a significantly reduced serum IL-12p70 at 24 and 96 h (p < 0.05). Brain MRI scores were not significantly different between groups. CONCLUSION: MEN during hypothermia was associated with a reduced length of stay and time to full feeds, but did not increase feeding complications or systemic inflammation.

The development of repetitive motor behaviors in deer mice: Effects of environmental enrichment, repeated testing, and differential mediation by indirect basal ganglia pathway activation.

Little is known about the mechanisms mediating the development of repetitive behaviors in human or animals. Deer mice reared with environmental enrichment (EE) exhibit fewer repetitive behaviors and greater indirect basal ganglia pathway activation as adults than those reared in standard cages. The developmental progression of these behavioral and neural circuitry changes has not been characterized. We assessed the development of repetitive behavior in deer mice using both a longitudinal and cohort design. Repeated testing negated the expected effect of EE, but cohort analyses showed that progression of repetitive behavior was arrested after 1 week of EE and differed significantly from controls after 3 weeks. Moreover, EE reductions in repetitive behavior were associated with increasing activation of indirect pathway nuclei in males across adolescence, but not females. These findings provide the first assessment of developmental trajectories within EE and support indirect pathway mediation of repetitive behavior in male deer mice.

Bayesian Variable Selection on Model Spaces Constrained by Heredity Conditions.

This paper investigates Bayesian variable selection when there is a hierarchical dependence structure on the inclusion of predictors in the model. In particular, we study the type of dependence found in polynomial response surfaces of orders two and higher, whose model spaces are required to satisfy weak or strong heredity conditions. These conditions restrict the inclusion of higher-order terms depending upon the inclusion of lower-order parent terms. We develop classes of priors on the model space, investigate their theoretical and finite sample properties, and provide a Metropolis-Hastings algorithm for searching the space of models. The tools proposed allow fast and thorough exploration of model spaces that account for hierarchical polynomial structure in the predictors and provide control of the inclusion of false positives in high posterior probability models.

Repetitive motor behavior: further characterization of development and temporal dynamics.

Repetitive behaviors are diagnostic for autism spectrum disorders, common in related neurodevelopmental disorders, and normative in typical development. In order to identify factors that mediate repetitive behavior development, it is necessary to characterize the expression of these behaviors from an early age. Extending previous findings, we characterized further the ontogeny of stereotyped motor behavior both in terms of frequency and temporal organization in deer mice. A three group trajectory model provided a good fit to the frequencies of stereotyped behavior across eight developmental time points. Group based trajectory analysis using a measure of temporal organization of stereotyped behavior also resulted in a three group solution. Additionally, as the frequency of stereotyped behavior increased with age, the temporal distribution of stereotyped responses became increasingly regular or organized indicating a strong association between these measures. Classification tree and principal components analysis showed that accurate classification of trajectory group could be done with fewer observations. This ability to identify trajectory group membership earlier in development allows for examination of a wide range of variables, both experiential and biological, to determine their impact on altering the expected trajectory of repetitive behavior across development. Such studies would have important implications for treatment efforts in neurodevelopmental disorders such as autism.