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Summary: Background: Methotrexate (MTX) is the gold-standard first-line disease-modifying anti-rheumatic drug for juvenile idiopathic arthritis (JIA), despite only being either effective or tolerated in half of children and young people (CYP). To facilitate stratified treatment of early JIA, novel methods in machine learning were used to i) identify clusters with distinct disease patterns following MTX initiation; ii) predict cluster membership; and iii) compare clusters to existing treatment response measures. Methods: Discovery and verification cohorts included CYP who first initiated MTX before January 2018 in one of four UK multicentre prospective cohorts of JIA within the CLUSTER consortium. JADAS components (active joint count, physician (PGA) and parental (PGE) global assessments, ESR) were recorded at MTX start and over the following year.Clusters of MTX ‘response’ were uncovered using multivariate group-based trajectory modelling separately in discovery and verification cohorts. Clusters were compared descriptively to ACR Pedi 30/90 scores, and multivariate logistic regression models predicted cluster-group assignment. Findings: The discovery cohorts included 657 CYP and verification cohorts 1241 CYP. Six clusters were identified: Fast improvers (11%), Slow Improvers (16%), Improve-Relapse (7%), Persistent Disease (44%), Persistent PGA (8%) and Persistent PGE (13%), the latter two characterised by improvement in all features except one. Factors associated with clusters included ethnicity, ILAR category, age, PGE, and ESR scores at MTX start, with predictive model area under the curve values of 0.65–0.71. Singular ACR Pedi 30/90 scores at 6 and 12 months could not capture speeds of improvement, relapsing courses or diverging disease patterns. Interpretation: Six distinct patterns following initiation of MTX have been identified using methods in artificial intelligence. These clusters demonstrate the limitations in traditional yes/no treatment response assessment (e.g., ACRPedi30) and can form the basis of a stratified medicine programme in early JIA. Funding: Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children's Charity, Olivia’s Vision, and the National Institute for Health Research.

ABSTRACT We present a case of a 69-year-old man who presented for routine check-up and was incidentally found to have kidney failure with an initially unrevealing history and bland urinary sediment. He was diagnosed with oxalate nephropathy in the setting of chronic turmeric supplementation and chronic antibiotic therapy with associated diarrhea. Our case provides several key insights into oxalate nephropathy. First, the diagnosis requires a high index of clinical suspicion. It is uncommonly suspected clinically unless there is an obvious clue in the history such as Roux-en-Y gastric bypass or ethylene glycol poisoning. Diagnosis can be confirmed by histopathologic findings and corroborated by serum levels of oxalate and 24-hour urinary excretion. Second, the diagnosis can often be missed by the pathologist because of the characteristics of the crystals unless the renal pathologist has made it a rule to examine routinely all H&E sections under polarized light. This must be done on H&E, as the other stains dissolve the crystals. Third, one oxalate crystal in a routine needle biopsy is considered pathologic and potentially contributing to the AKI or to the CKD in an important way. Fourth, secondary oxalosis can be largely mitigated or prevented in many cases, especially iatrogenic cases. This can come through the surgeon or the gastroenterologist providing proper instructions to patients on an oxalate-restricted diet or other specific dietary measures. Lastly, this case highlights the success that results from cooperation and communication between the pathologist and the treating physician.

Cover crops provide a habitat for pests and beneficial arthropods. Unexpected pest pressure in a cover-crop-to-corn system can occur and result in increased use of insecticides. Eight site-years of on-farm field studies were conducted in 2019, 2020, and 2021. The objective of the study was to evaluate the impact of insecticide timing relative to cover-crop termination on arthropod activity in a cover-crop-to-corn system. The treatments consisted of (i) glyphosate to terminate the cover crop, (ii) glyphosate and pyrethroid tank mix to terminate the cover crop, and (iii) glyphosate to terminate the cover crop and pyrethroid application 25 days after the termination. Arthropod activity was measured with pitfall traps before and at each treatment application. A total of 33,316 arthropods were collected. Total arthropods, Collembola, and Aphididae were the only taxa reduced with an insecticide application. The other arthropod taxa were mainly influenced by the sampling period. No significant pest pressure occurred at any site-year. Insecticide applications are not generally needed in a cover-crop-to-corn system. Scouting for pests and applying strategies only when necessary is crucial to conserve potentially beneficial arthropods in the system.