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Recent advances in preoperative 3D templating software allow surgeons to plan implant size and position for stemless total shoulder arthroplasty (TSA). Whether these preoperative plans accurately reflect intraoperative decisions is yet unknown, and the purpose of this study was to evaluate concordance between planned and actual implant sizes in a series of patients undergoing stemless TSA.A retrospective cohort of consecutive, anatomic, stemless TSA cases performed by two surgeons between September 2019 and February 2021 was examined. Preoperative templated plans were collected using 3D planning software, and the sizes of planned glenoid, humeral head, and nucleus "stem" implants and other procedural data were recorded, along with sociodemographic information. These predicted parameters were compared with the implant sizes, and the concordance of these templated plans was quantified by direct comparison and bootstrapped simulations.Fifty cases met inclusion criteria, among which perfect concordance across all three implants was observed in 11 cases (22%). The glenoid implant had the highest concordance (80%) relative to the humeral head and nucleus implants (38% and 60%, respectively), which was statistically significant ( P0.001). Planned humeral head implants were more often oversized relative to their actual implanted size. However, 84% of the planned humeral heads were within 1 diameter size; in addition, 98% of the planned glenoid implants were within one size and all were within 10 mm of the implanted glenoid backside radius. All nucleus implants were within one size.Final implant sizes demonstrated variable concordance relative to preoperative plans, with glenoid implants having the highest accuracy and humeral heads having the highest variability. Multiple factors contributed to the varying concordances for the different implants, suggesting possible areas of improvement in this technology. These results may have implications for logistics, intraoperative efficiency, and overall cost and underscore the potential value of this technology.Level III.

Industrial hemp (Cannabis sativa L.) has recently been reintroduced as an agricultural commodity in the United States, and, through state-led pilot programs, growers and researchers have been investigating production strategies. Diseases and disorders of industrial hemp in the United States are largely unknowns because record-keeping and taxonomy have improved dramatically in the last several decades. In 2016, North Carolina launched a pilot program to investigate industrial hemp, and diseases and abiotic disorders were surveyed in 2017 and 2018. Producers, consultants, and agricultural extension agents submitted samples to the North Carolina Department of Agriculture and Consumer Services Agronomic Services Division (n = 572) and the North Carolina Plant Disease and Insect Clinic (n = 117). Common field diseases found included Fusarium foliar and flower blights (Fusarium graminearum), Fusarium wilt (Fusarium oxysporum), and Helminthosporium leaf spot (Exserohilum rostratum). Greenhouse diseases were primarily caused by Pythium spp. and Botrytis cinerea. Common environmental disorders were attributed to excessive rainfall flooding roots and poor root development of transplanted clones.

ImportanceSystem and center-level interventions to improve health equity in organ transplantation benefit from robust characterization of the referral population served by each transplant center. Transplant referral regions (TRRs) define geographic catchment areas for transplant centers in the US, but accurately characterizing the demographics of populations within TRRs using US Census data poses a challenge.ObjectiveTo compare 2 methods of linking US Census data with TRRs—a geospatial intersection method and a zip code cross-reference method.Design, Setting, and ParticipantsThis cohort study compared spatial congruence of spatial intersection and zip code cross-reference methods of characterizing TRRs at the census block level. Data included adults aged 18 years and older on the waiting list for kidney transplant from 2008 through 2018.ExposuresEnd-stage kidney disease.Main Outcomes and MeasuresMultiple assignments, where a census tract or block group crossed the boundary between 2 hospital referral regions and was assigned to multiple different TRRs; misassigned area, the portion of census tracts or block groups assigned to a TRR using either method but fall outside of the TRR boundary.ResultsIn total, 102 TRRs were defined for 238 transplant centers. The zip code cross-reference method resulted in 4627 multiple-assigned census block groups (representing 18% of US land area assigned to TRRs), while the spatial intersection method eliminated this problem. Furthermore, the spatial method resulted in a mean and median reduction in misassigned area of 65% and 83% across all TRRs, respectively, compared with the zip code cross-reference method.Conclusions and RelevanceIn this study, characterizing populations within TRRs with census block groups provided high spatial resolution, complete coverage of the country, and balanced population counts. A spatial intersection approach avoided errors due to duplicative and incorrect assignments, and allowed more detailed and accurate characterization of the sociodemographics of populations within TRRs; this approach can enrich transplant center knowledge of local referral populations, assist researchers in understanding how social determinants of health may factor into access to transplant, and inform interventions to improve heath equity.

Abiotic and biotic drivers of co-occurring fungal functional guilds across regional-scale environmental gradients remain poorly understood. We characterized fungal communities using Illumina sequencing from soil cores collected across three Neotropical rainforests in Panama that vary in soil properties and plant community composition. We classified each fungal OTU into different functional guilds, namely plant pathogens, saprotrophs, arbuscular mycorrhizal (AM), or ectomycorrhizal (ECM). We measured soil properties and nutrients within each core and determined the tree community composition and richness around each sampling core. Canonical correspondence analyses showed that soil pH and moisture were shared potential drivers of fungal communities for all guilds. However, partial the Mantel tests showed different strength of responses of fungal guilds to composition of trees and soils. Plant pathogens and saprotrophs were more strongly correlated with soil properties than with tree composition; ECM fungi showed a stronger correlation with tree composition than with soil properties; and AM fungi were correlated with soil properties, but not with trees. In conclusion, we show that co-occurring fungal guilds respond differently to abiotic and biotic environmental factors, depending on their ecological function. This highlights the joint role that abiotic and biotic factors play in determining composition of fungal communities, including those associated with plant hosts.

Summary Fungi play critical roles in ecosystem processes and interact with plant communities in mutualistic, pathogenic, and commensal ways. Fungal communities are thought to depend on both associated tree communities and soil properties. However, the relative importance of the biotic and abiotic drivers of soil fungal community structure and diversity in lowland tropical forests remains poorly understood. We examined the community structure of trees and fungi at different levels of phosphorus (0·17–16·3 mg kg−1) in moist tropical forests in Panama. We predicted that arbuscular mycorrhizal (AM) fungal composition would be more strongly associated with soil properties than with local tree communities while the composition of other fungal clades would be more strongly correlated with local tree communities than soil properties. We also predicted that fungal operational taxonomic unit (OTU) richness would be negatively correlated with soil fertility and positively correlated with tree species diversity within and among forests. We characterized soil chemistry, fine root biomass, and sequenced the ITS1 barcode region to describe fungal community composition from 70 soil cores across three 1-ha tropical rainforest sites in Panama. The sites vary in soil chemistry, including P, and in tree species community composition, but experience similar annual rainfall. AM fungal community composition was partially correlated with soil chemistry (r = 0·32, P ≤ 0·001), but not with local tree communities, while non-AM fungal communities were nearly equally correlated with soil chemistry (Partial Mantel test, r = 0·38, P ≤ 0·001) as with tree communities (r = 0·36, P ≤ 0·001). Linear models showed that AM OTU richness was not explained by any independent variable. For non-AM fungi, phosphorus, pH, and soil moisture better predicted OTU richness across all cores than other biotic and abiotic factors. Synthesis. Our results show that AM fungal structure is driven primarily by soil chemistry. For non-AM fungi, soil properties and the local tree community can play a joint role in structuring communities. Furthermore, we found that more diverse local tree communities did not harbour more fungal species. Our results suggest that soil properties act as an environmental filter for both trees and fungi, setting the stage for interactions between the two.