Pulmonary hypertension in association with lung disease : quantitative CT and artificial intelligence to the rescue? State-of-the-art review

Accurate phenotyping of patients with pulmonary hypertension (PH) is an integral part of informing disease classification, treatment, and prognosis. The impact of lung disease on PH outcomes and response to treatment remains a challenging area with limited progress. Imaging with computed tomography (CT) plays an important role in patients with suspected PH when assessing for parenchymal lung disease, however, current assessments are limited by their semi-qualitative nature. Quantitative chest-CT (QCT) allows numerical quantification of lung parenchymal disease beyond subjective visual assessment. This has facilitated advances in radiological assessment and clinical correlation of a range of lung diseases including emphysema, interstitial lung disease, and coronavirus disease 2019 (COVID-19). Artificial Intelligence approaches have the potential to facilitate rapid quantitative assessments. Benefits of cross-sectional imaging include ease and speed of scan acquisition, repeatability and the potential for novel insights beyond visual assessment alone. Potential clinical benefits include improved phenotyping and prediction of treatment response and survival. Artificial intelligence approaches also have the potential to aid more focused study of pulmonary arterial hypertension (PAH) therapies by identifying more homogeneous subgroups of patients with lung disease. This state-of-the-art review summarizes recent QCT developments and potential applications in patients with PH with a focus on lung disease

Pesticide Fate and Transport throughout Unsaturated Zones in Five Agricultural Settings, USA

Pesticide transport through the unsaturated zone is a function of chemical and soil characteristics, application, and water recharge rate. The fate and transport of 82 pesticides and degradates were investigated at five different agricultural sites. Atrazine and metolachlor, as well as several of the degradates of atrazine, metolachlor, acetochlor, and alachlor, were frequently detected in soil water during the 2004 growing season, and degradates were generally more abundant than parent compounds. Metolachlor and atrazine were applied at a Nebraska site the same year as sampling, and focused recharge coupled with the short time since application resulted in their movement in the unsaturated zone 9 m below the surface. At other sites where the herbicides were applied 1 to 2 yr before sampling, only degradates were found in soil water. Transformations of herbicides were evident with depth and during the 4-mo sampling time and reflected the faster degradation of metolachlor oxanilic acid and persistence of metolachor ethanesulfonic acid. Th e fraction of metolachlor ethanesulfonic acid relative to metolachlor and metolachlor oxanilic acid increased from 0.3 to \u3e0.9 at a site in Maryland where the unsaturated zone was 5 m deep and from 0.3 to 0.5 at the shallowest depth. The flux of pesticide degradates from the deepest sites to the shallow ground water was greatest (3.0–4.9 μmol m−2 yr−1) where upland recharge or focused flow moved the most water through the unsaturated zone. Flux estimates based on estimated recharge rates and measured concentrations were in agreement with fluxes estimated using an unsaturated-zone computer model (LEACHM)