A comparison of three automated root-knot nematode egg counting approaches using machine learning, image analysis, and a hybrid model.

Meloidogyne spp. (root-knot nematodes, RKN) are a major threat to a wide range of agricultural crops worldwide. Breeding crops for RKN resistance is an effective management strategy, yet assaying large numbers of breeding lines requires laborious bioassays that are time-consuming and require experienced researchers. In these bioassays, quantifying nematode eggs through manual counting is considered the current standard for quantifying establishing resistance in plant genotypes. Counting RKN eggs is highly laborious, and even experienced researchers are subject to fatigue or misclassification, leading to potential errors in phenotyping. Here, we present three automated egg counting models that rely on machine learning and image analysis to quantify RKN eggs extracted from tobacco and sweetpotato plants. The first method relied on convolutional neural networks trained using annotated images to identify eggs (M. enterolobii R2 = 0.899, M. incognita R2 = 0.927, M. javanica R2 = 0.886), while a second contour-based approach used image analysis to identify eggs from their morphological characteristics and did not rely on neural networks (M. enterolobii R2 = 0.977, M. incognita R2 = 0.990, M. javanica R2 = 0.924). A third hybrid model combined these approaches and was able to detect and count eggs nearly as well as human raters (M. enterolobii R2 = 0.985, M. incognita R2 = 0.992, M. javanica R2 = 0.983). These automated counting protocols have the potential to provide significant time and resource savings annually for breeders and nematologists, and may be broadly applicable to other nematode species.

Disentangling morphology and genetics in two voles (Microtus pennsylvanicus and M. ochrogaster) in a region of sympatry.

Species in recent, rapid radiations can be difficult to distinguish from one another due to incomplete sorting of traits, insufficient time for novel morphologies to evolve, and elevated rates of hybridization and gene flow. The vole genus Microtus (58 spp.) is one such system where all three factors are likely at play. In the central United States, the prairie vole, Microtus ochrogaster, and the eastern meadow vole, M. pennsylvanicus, occur in sympatry and can be distinguished on the basis of molar cusp patterns but are known to be exceptionally difficult to distinguish using external morphological characters. Using a combination of morphometrics, pelage color analyses, and phylogenetics, we explored which traits are most effective for species identification and whether these same traits can be used to identify the subspecies M. o. ohionensis. While we were able to identify six traits that differed significantly between M. ochrogaster and M. pennsylvanicus, we also found substantial measurement overlap which limits the utility of these traits for species identification. The subspecies M. o. ohionensis was particularly difficult to distinguish from M. p. pennsylvanicus, and we did not find any evidence that this subspecies forms a distinct genetic clade. Furthermore, the full species M. ochrogaster and M. pennsylvanicus did not form reciprocal clades in phylogenetic analyses. We discuss several possible reasons for these patterns, including unrecognized variation in molar cusp patterns and/or localized hybridization. Overall, our results provide useful information that will aid in the identification of these species and subspecies in the future, and provides a case study of how genetics, morphometrics, and fur color analyses can be used to disentangle signatures of evolutionary history and hybridization.

Postdischarge opioid use and persistent use after general surgery: A retrospective study.

BACKGROUND: Opioid overprescribing after surgery is a significant public health issue in most developed countries, including New Zealand. However, there is a lack of literature on the patterns and risk factors for postoperative opioid use among general surgical patients in New Zealand. This study aimed to examine opioid use in patients undergoing general surgery at Auckland District Health Board between January and December 2019 and to identify factors associated with opioid use after surgery and persistent opioid use (defined as having filled ≥1 opioid prescription in the 91 to 180 days after surgery). METHODS AND MATERIALS: This is a retrospective cohort study. Data from patients' electronic clinical records and community pharmacy dispensing records were extracted to obtain data on sociodemographics, surgical characteristics, comorbidities, co-prescribed medications, and opioid use. RESULTS: A total of 1,110 patients were included in the study, with 42.4% dispensed an opioid following discharge after surgery. Of opioid-naïve patients who filled opioids after surgery (n = 401), 9.5% became persistent opioid users. Preoperative use of nonopioid analgesics, longer hospital stays, higher operation severity, procedure type, and higher pain scores were positively associated with opioid use, whereas older age was a negative predictor. Longer hospital stays, an initial discharge prescription with high opioid load, and female sex increased the risk of persistent opioid use. Conversely, a higher severity of surgery was associated with lower risk of persistent opioid use. CONCLUSION: The findings suggest that a considerable proportion of patients become persistent opioid users after surgery. The risk factors identified can guide clinicians to prescribe in a manner that reduces opioid-related adverse outcomes and help guide future interventions.

Kidney Disease-Associated APOL1 Variants Have Dose-Dependent, Dominant Toxic Gain-of-Function.

BACKGROUND: Two coding renal risk variants (RRVs) of the APOL1 gene (G1 and G2) are associated with large increases in CKD rates among populations of recent African descent, but the underlying molecular mechanisms are unknown. Mammalian cell culture models are widely used to study cytotoxicity of RRVs, but results have been contradictory. It remains unclear whether cytotoxicity is RRV-dependent or driven solely by variant-independent overexpression. It is also unknown whether expression of the reference APOL1 allele, the wild-type G0, could prevent cytotoxicity of RRVs. METHODS: We generated tetracycline-inducible APOL1 expression in human embryonic kidney HEK293 cells and examined the effects of increased expression of APOL1 (G0, G1, G2, G0G0, G0G1, or G0G2) on known cytotoxicity phenotypes, including reduced viability, increased swelling, potassium loss, aberrant protein phosphorylation, and dysregulated energy metabolism. Furthermore, whole-genome transcriptome analysis examined deregulated canonical pathways. RESULTS: At moderate expression, RRVs but not G0 caused cytotoxicity in a dose-dependent manner that coexpression of G0 did not reduce. RRVs also have dominant effects on canonical pathways relevant for the cellular stress response. CONCLUSIONS: In HEK293 cells, RRVs exhibit a dominant toxic gain-of-function phenotype that worsens with increasing expression. These observations suggest that high steady-state levels of RRVs may underlie cellular injury in APOL1 nephropathy, and that interventions that reduce RRV expression in kidney compartments may mitigate APOL1 nephropathy.