Single ventricle patients undergoing comprehensive stage II palliation have higher incidence of severe acute kidney injury compared to the bidirectional Glenn palliation; however, the optimal method for early detection remains unknown. Several urinary biomarkers are increased in other patient populations with postoperative kidney injury. We explored the kinetics of these biomarkers in this high-risk population.

We conducted prospective, observational study of 20 patients with single ventricle physiology who underwent second stage palliation (July 2019–December 2021). Acute kidney injury was defined by Kidney Diseases Improving Global Guidelines, based on peak serum creatinine value and urine output. Urine samples were collected pre-operatively and at 1-, 6-, and 24-hours post-surgery. Urinary biomarkers neutrophil gelatinase-associated lipocalin, interleukin-18, liver fatty acid-binding protein, kidney injury molecule-1, and cystatin C were quantified by enzyme linked immunosorbent assay, normalised to urinary creatinine, and shown as median [interquartile range].

Four patients (50%) undergoing comprehensive stage II and 1 patient (8%) undergoing bidirectional Glenn palliation developed stage ≥ 2 acute kidney injury. Comprehensive stage II compared to bidirectional Glenn group had higher median neutrophil gelatinase-associated lipocalin (1769 [1309–1961] versus 91[18–1120] ng/mg) and liver fatty acid-binding protein (12,836 [5016–19798] versus 1272 [220–5172] ng/mg) that peaked 1-hour post-surgery. Kidney injury molecule-1 was significantly greater at 1-, 6-, and 24-hours (greatest) post-surgery in comprehensive stage II than bidirectional Glenn (24h: 11[9–23]) versus 2 [1–6] ng/mg).

Elevated urinary neutrophil gelatinase-associated lipocalin, liver fatty acid-binding protein, and kidney injury molecule-1 may be useful biomarkers for early detection of acute kidney injury in children following comprehensive stage II palliation.

Objectives/Goals: One in 14 individuals have a substance use disorder (SUD). We suggest that a trait of poor impulse control, or high impulsivity, may predict relapse risk. We explore how changes in brain structure linked to decision-making and reward might drive high impulsivity, helping create a “biosignature” to identify those most at risk and guide treatment choices. Methods/Study Population: Male rats were phenotyped as high impulsive (HI) or low impulsive (LI) based on premature responses on the one-choice serial reaction time (1-CSRT) task. Rats then received an intracranial infusion of a retrograde virus (AAVr2) in the nucleus accumbens (NAc) to trace corticoaccumbens neurons back to the medial prefrontal cortex (mPFC). After impulsivity phenotyping (ITI8), another cohort of animals performed cocaine self-administration followed by 30 days of abstinence. Cue reactivity, a measure of relapse-like behaviors, was performed on abstinence day 30. Analyses of microtubule-associated protein 2 (MAP2), a cytoskeletal marker of dendrites, spines, and somas was performed with western blotting and fluorescent images of brain slices after phenotyping and cocaine abstinence. Results/Anticipated Results: HI rats made greater premature responses, a marker of impulsive action vs. LI rats at baseline (p Discussion/Significance of Impact: Poor inherent impulse control and drug cues heighten relapse risk. We found high impulsivity linked to brain structure differences and lower protein markers of synaptic (units supporting signaling) strengthening. Future investigations into brain-behavior links with impulsivity may further identify a SUD relapse vulnerability biosignature.

Few studies have examined the genetic population structure of vector-borne microparasites in wildlife, making it unclear how much these systems can reveal about the movement of their associated hosts. This study examined the complex host–vector–microbe interactions in a system of bats, wingless ectoparasitic bat flies (Nycteribiidae), vector-borne microparasitic bacteria (Bartonella) and bacterial endosymbionts of flies (Enterobacterales) across an island chain in the Gulf of Guinea, West Africa. Limited population structure was found in bat flies and Enterobacterales symbionts compared to that of their hosts. Significant isolation by distance was observed in the dissimilarity of Bartonella communities detected in flies from sampled populations of Eidolon helvum bats. These patterns indicate that, while genetic dispersal of bats between islands is limited, some non-reproductive movements may lead to the dispersal of ectoparasites and associated microbes. This study deepens our knowledge of the phylogeography of African fruit bats, their ectoparasites and associated bacteria. The results presented could inform models of pathogen transmission in these bat populations and increase our theoretical understanding of community ecology in host–microbe systems.

Background: A subset of patients experience poor outcomes following anterior cervical discectomy and fusion (ACDF). Our study aimed to identify postoperative trajectories of disability, neck/arm pain and determine baseline measures that predict subgroup membership. Methods: Patients with cervical spondylotic radiculopathy undergoing ACDF are presented. Prognostic factors comprised demographic, health and surgery-related variables. Study outcomes were trajectories of neck disability index scores, numeric rating scales for neck/arm pain modeled with latent-class growth analysis. Associations were explored using robust Poisson models and reported with risk ratios and 95% confidence intervals. Results: Patients (N = 352; mean (SD) age = 50.9(9.5) years, 43.8% female) identified trajectories for disability (excellent=45.3%,fair=39.2%,poor=15.5%),arm pain (excellent=24.5%,good=52.0%,poor=23.5%),and neck pain (excellent=13.7%,good=63.1%,poor=23.2%). Greater physical and mental health-related quality of life were associated with a reduced risk of poor outcome(per SD,0.40[0.30,0.53]-0.80[0.65,0.99]), while higher risk for depression (per SD, 1.36[1.12,1.65]-2.26[1.84,2.78]), longer wait time(per 90 days, 1.31[1.05,1.63]-1.64[1.20,2.24]), and longer procedure time (per 30 min,1.07[1.03,1.10]-1.08[1.05,1.12]) were associated with an increased risk of poor outcome for all outcomes. Poor disability was increased with self-reported depression(3.03[1.76,5.21]), greater neck-to-arm pain ratio (2.63 [1.28 to 5.40]), ASA score > 2(2.26[1.33,3.83]), and preoperative opiates (2.05[1.18,3.56]), while preoperative physiotherapy (0.51[0.30, 0.88]), spinal injections (0.48[0.23 to 0.98]), and regular exercise (0.44 [0.24, 0.79]) decreased risk. Receiving compensation and smoking were associated with poor outcome for neck pain. Remaining candidate prognostic factors were not associated with clinical outcome. Conclusions: Perioperative factors were shown to decrease risk of poor outcomes for pain and disability two years following ACDF.

We review 1982–1984 articles identifying Superfund sites in three nationalnewspapers. Articles almost never identify the race of nearby residents. Basedon sites receiving disproportionate coverage, readers might conclude thatSuperfund generally affected white, working-class families, but results do notsupport this narrative. In a pooled sample, neither race nor income predicts thenumber of times a site gets mentioned. When the sample is partitioned bynewspaper or by each newspaper's coverage of nearby sites, a positiverelationship emerges between the proportion of Hispanic or nonwhite residentsand the number of articles about a site. We discuss this apparentcontradiction.

Microscopic examination of blood smears remains the gold standard for laboratory inspection and diagnosis of malaria. Smear inspection is, however, time-consuming and dependent on trained microscopists with results varying in accuracy. We sought to develop an automated image analysis method to improve accuracy and standardization of smear inspection that retains capacity for expert confirmation and image archiving. Here, we present a machine learning method that achieves red blood cell (RBC) detection, differentiation between infected/uninfected cells, and parasite life stage categorization from unprocessed, heterogeneous smear images. Based on a pretrained Faster Region-Based Convolutional Neural Networks (R-CNN) model for RBC detection, our model performs accurately, with an average precision of 0.99 at an intersection-over-union threshold of 0.5. Application of a residual neural network-50 model to infected cells also performs accurately, with an area under the receiver operating characteristic curve of 0.98. Finally, combining our method with a regression model successfully recapitulates intraerythrocytic developmental cycle with accurate lifecycle stage categorization. Combined with a mobile-friendly web-based interface, called PlasmoCount, our method permits rapid navigation through and review of results for quality assurance. By standardizing assessment of Giemsa smears, our method markedly improves inspection reproducibility and presents a realistic route to both routine lab and future field-based automated malaria diagnosis.

A survey of Veterans’ Affairs Medical Centers on control of carbapenem-resistant Enterobacteriaceae (CRE) and carbapenem-producing CRE (CP-CRE) demonstrated that most facilities use VA guidelines but few screen for CRE/CP-CRE colonization regularly or regularly communicate CRE/CP-CRE status at patient transfer. Most respondents were knowledgeable about CRE guidelines but cited lack of adequate resources.

Generative neural networks (GNNs) have successfully used human-created designs to generate novel 3D models that combine concepts from disparate known solutions, which is an important aspect of design exploration. GNNs automatically learn a parameterization (or latent space) of a design space, as opposed to alternative methods that manually define a parameterization. However, GNNs are typically not evaluated using an explicit notion of physical performance, which is a critical capability needed for design. This work bridges this gap by proposing a method to extract a set of functional designs from the latent space of a point cloud generating GNN, without sacrificing the aforementioned aspects of a GNN that are appealing for design exploration. We introduce a sparsity preserving cost function and initialization strategy for a genetic algorithm (GA) to optimize over the latent space of a point cloud generating autoencoder GNN. We examine two test cases, an example of generating ellipsoid point clouds subject to a simple performance criterion and a more complex example of extracting 3D designs with a low coefficient of drag. Our experiments show that the modified GA results in a diverse set of functionally superior designs while maintaining similarity to human-generated designs in the training data set.

Disease surveillance in wildlife populations presents a logistical challenge, yet is critical in gaining a deeper understanding of the presence and impact of wildlife pathogens. Erinaceus coronavirus (EriCoV), a clade C Betacoronavirus, was first described in Western European hedgehogs (Erinaceus europaeus) in Germany. Here, our objective was to determine whether EriCoV is present, and if it is associated with disease, in Great Britain (GB). An EriCoV-specific BRYT-Green® real-time reverse transcription PCR assay was used to test 351 samples of faeces or distal large intestinal tract contents collected from casualty or dead hedgehogs from a wide area across GB. Viral RNA was detected in 10.8% (38) samples; however, the virus was not detected in any of the 61 samples tested from Scotland. The full genome sequence of the British EriCoV strain was determined using next generation sequencing; it shared 94% identity with a German EriCoV sequence. Multivariate statistical models using hedgehog case history data, faecal specimen descriptions and post-mortem examination findings found no significant associations indicative of disease associated with EriCoV in hedgehogs. These findings indicate that the Western European hedgehog is a reservoir host of EriCoV in the absence of apparent disease.

In Cameroon, there is a national programme engaged in the control of schistosomiasis and soil-transmitted helminthiasis. In certain locations, the programme is transitioning from morbidity control towards local interruption of parasite transmission. The volcanic crater lake villages of Barombi Mbo and Barombi Kotto are well-known transmission foci and are excellent context-specific locations to assess appropriate disease control interventions. Most recently they have served as exemplars of expanded access to deworming medications and increased environmental surveillance. In this paper, we review infection dynamics through time, beginning with data from 1953, and comment on the short- and long-term success of disease control. We show how intensification of local control is needed to push towards elimination and that further environmental surveillance, with targeted snail control, is needed to consolidate gains in preventive chemotherapy as well as empower local communities to take ownership of interventions.