Final, 10-Year Outcomes with Nivolumab plus Ipilimumab in Advanced Melanoma.

Background: Previous results from this trial showed longer overall survival after treatment with nivolumab plus ipilimumab or with nivolumab monotherapy than with ipilimumab monotherapy in patients with advanced melanoma. Given that patients with advanced melanoma are living longer than 7.5 years, longer-term data were needed to address new clinically relevant questions.

A Novel Risk Prediction Score for Clinically Significant Bleeding in Patients Anticoagulated for Venous Thromboembolism with Active Cancer.

Background:  Cancer-associated venous thromboembolism (Ca-VTE) treatment with anticoagulation is associated with bleeding complications and there are limited data on risk factors. Current models do not provide accurate bleeding risk prediction.

Methods:  UK Clinical Practice Research Datalink data (2008-2020) were used to generate a cohort of patients with anticoagulant initiation for first Ca-VTE.

Major variation in hepatocellular carcinoma treatment and outcomes in England: a retrospective cohort study.

Objective: Hepatocellular carcinoma (HCC) is increasingly incident in England, while survival remains poor with regional disparities. We aimed to explore the differences in HCC treatment across different geographical regions and to examine the impact on cancer survival.

Methods: Incident HCC cases and treatment were identified from the English Hospital Episode Statistics (2016-2017) and then a subset by National Health Service (NHS) regions.

Short-term side effects of COVID-19 vaccines: A cross-sectional study in Jordan.

The rapid manufacturing of vaccines has increased hesitancy toward receiving the COVID-19 vaccines. Clarifying what to expect after vaccination and revealing the possible side effects will lower hesitancy toward receiving the COVID-19 vaccine and increase public awareness. This descriptive cross-sectional survey-based study was conducted in Jordan (August 2021) to collect data on the short-term side effects following the COVID-19 vaccines.

Assessing Daily Evapotranspiration Methodologies from One-Time-of-Day sUAS and EC Information in the Project.

Daily evapotranspiration ( ) plays a key role in irrigation water management and is particularly important in drought-stricken areas, such as California and high-value crops. Remote sensing allows for the cost-effective estimation of spatial evapotranspiration (), and the advent of small unmanned aerial systems () technology has made it possible to estimate instantaneous high-resolution at the plant, row, and subfield scales. estimates using "instantaneous" remote sensing measurements with half-hourly/hourly forcing micrometeorological data, yielding hourly fluxes in W/m that are then translated to a daily scale (mm/day) under two assumptions: (a) relative rates, such as the ratios of -to-net radiation ( ) or -to-solar radiation ( ), are assumed to be constant rather than absolute, and (b) nighttime evaporation () and transpiration () contributions are negligible.

Development of High Performance Computing Tools for Estimation of High-Resolution Surface Energy Balance Products Using sUAS Information.

(small-Unmanned Aircraft System) and advanced surface energy balance models allow detailed assessment and monitoring (at plant scale) of different (agricultural, urban, and natural) environments. Significant progress has been made in the understanding and modeling of atmosphere-plant-soil interactions and numerical quantification of the internal processes at plant scale. Similarly, progress has been made in ground truth information comparison and validation models.

Evapotranspiration partitioning assessment using a machine-learning-based leaf area index and the two-source energy balance model with sUAV information.

Accurate quantification of the partitioning of evapotranspiration (ET) into transpiration and evaporation fluxes is necessary to understanding ecosystem interactions among carbon, water, and energy flux components. ET partitioning can also support the description of atmosphere and land interactions and provide unique insights into vegetation water status. Previous studies have identified leaf area index (LAI) estimation as a key descriptor of biomass conditions needed for the estimation of transpiration and evaporation.

The influence of low- intensity laser irradiation versus hyperbaric oxygen therapy on transcutaneous oxygen tension in chronic diabetic foot ulcers: a controlled randomized trial.

Background And Objective: Evaluation of the stage and severity of the chronic diabetic foot ulcer (CDFU) is vital to increase the healing rate and to select the suitable treatment. We aim to assess the influence of low-intensity laser irradiation (LILI) and hyperbaric oxygenation therapy (HBOT) to accelerate the CDFU healing thru the transcutaneous oxygen tension (TcPO2) measurements.

Materials And Methods: Seventy-five diabetic patients (type 2) of both genders, their ages ranged from 40-65 years with CDFUs (duration of ulcer < 6 weeks).

Nivolumab in gastric/gastroesophageal junction cancer: real-world data from UK Early Access to Medicines Scheme.

This study provides real-world insight into patient profile, clinical effectiveness and health-related quality of life among patients with advanced gastric/gastroesophageal junction (GEJ) adenocarcinoma treated with nivolumab. Data were collected from medical records of patients with advanced GEJ adenocarcinoma treated with nivolumab in a UK Early Access to Medicines Scheme and from the patient-reported EuroQoL five dimensions questionnaire. Evaluable patients (n = 113; median age 62 years) were predominantly male (76.

Application of a machine learning algorithm for detection of atrial fibrillation in secondary care.

Atrial fibrillation (AF) is the most common sustained heart arrhythmia and significantly increases risk of stroke. Opportunistic AF testing in high-risk patients typically requires frequent electrocardiogram tests to capture the arrhythmia. Risk-prediction algorithms may help to more accurately identify people with undiagnosed AF and machine learning (ML) may aid in the diagnosis of AF.

To What Extend Does the Eddy Covariance Footprint Cutoff Influence the Estimation of Surface Energy Fluxes Using Two Source Energy Balance Model and High-Resolution Imagery in Commercial Vineyards?

Validation of surface energy fluxes from remote sensing sources is performed using instantaneous field measurements obtained from eddy covariance (EC) instrumentation. An eddy covariance measurement is characterized by a footprint function / weighted area function that describes the mathematical relationship between the spatial distribution of surface flux sources and their corresponding magnitude. The orientation and size of each flux footprint / source area depends on the micro-meteorological conditions at the site as measured by the EC towers, including turbulence fluxes, friction velocity (u), and wind speed, all of which influence the dimensions and orientation of the footprint.

Implications of Soil and Canopy Temperature Uncertainty in the Estimation of Surface Energy Fluxes Using TSEB2T and High-resolution Imagery in Commercial Vineyards.

Estimation of surface energy fluxes using thermal remote sensing-based energy balance models (e.g., TSEB2T) involves the use of local micrometeorological input data of air temperature, wind speed, and incoming solar radiation, as well as vegetation cover and accurate land surface temperature (LST).

Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards.

Evapotranspiration () is a key variable for hydrology and irrigation water management, with significant importance in drought-stricken regions of the western US. This is particularly true for California, which grows much of the high-value perennial crops in the US. The advent of small Unmanned Aerial System () with sensor technology similar to satellite platforms allows for the estimation of high-resolution at plant spacing scale for individual fields.

Estimation of surface thermal emissivity in a vineyard for UAV microbolometer thermal cameras using NASA HyTES hyperspectral thermal, Landsat and AggieAir optical data.

Microbolometer thermal cameras in UAVs and manned aircraft allow for the acquisition of high-resolution temperature data, which, along with optical reflectance, contributes to monitoring and modeling of agricultural and natural environments. Furthermore, these temperature measurements have facilitated the development of advanced models of crop water stress and evapotranspiration in precision agriculture and heat fluxes exchanges in small river streams and corridors. Microbolometer cameras capture thermal information at blackbody or radiometric settings (narrowband emissivity equates to unity).

Implications of sensor inconsistencies and remote sensing error in the use of small unmanned aerial systems for generation of information products for agricultural management.

Small, unmanned aerial systems (sUAS) for remote sensing represent a relatively new and growing technology to support decisions for agricultural operations. The size and power limitations of these systems present challenges for the weight, size, and capability of the sensors that can be carried, as well as the geographical coverage that is possible. These factors, together with a lack of standards for sensor technology, its deployment, and data analysis, lead to uncertainties in data quality that can be difficult to detect or characterize.

Prevalence of minor musculoskeletal anomalies in children with congenital hypothyroidism.

In the last decade a high frequency of extrathyroidal congenital anomalies has been reported in infants with congenital hypothyroidism (CH) detected by neonatal screening. In the present study the occurrence of additional congenital malformations (CM) in a cohort of children with confirmed primary CH due to thyroid dysgenesis was investigated. A high prevalence of extrathyroidal major congenital anomalies (15.