Grasp Posture Variability Leads to Greater Ipsilateral Sensorimotor Beta Activation During Simulated Prosthesis Use.

Motor behaviour using upper-extremity prostheses of different levels is greatly variable, leading to challenges interpreting ideal rehabilitation strategies. Elucidating the underlying neural control mechanisms driving variability benefits our understanding of adaptation after limb loss. In this follow-up study, non-amputated participants completed simple and complex reach-to-grasp motor tasks using a body-powered transradial or partial-hand prosthesis simulator.

Effect of Weight Distribution and Active Safety Systems on Electric Vehicle Performance.

This paper describes control methods to improve electric vehicle performance in terms of handling, stability and cornering by adjusting the weight distribution and implementing control systems (e.g., wheel slip control, and yaw rate control).

Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs.

Objectives: To develop and validate an artificial intelligence (AI) system for measuring and detecting signs of carpal instability on conventional radiographs.

Materials And Methods: Two case-control datasets of hand and wrist radiographs were retrospectively acquired at three hospitals (hospitals A, B, and C). Dataset 1 (2178 radiographs from 1993 patients, hospitals A and B, 2018-2019) was used for developing an AI system for measuring scapholunate (SL) joint distances, SL and capitolunate (CL) angles, and carpal arc interruptions.

Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.

Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep learning methods can yield high-performance levels in the detection of lung nodules in chest X-rays. However, the lack of gold-standard public datasets slows down the progression of the research and prevents benchmarking of methods for this task.

Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans.

Background: Outside a screening program, early-stage lung cancer is generally diagnosed after the detection of incidental nodules in clinically ordered chest CT scans. Despite the advances in artificial intelligence (AI) systems for lung cancer detection, clinical validation of these systems is lacking in a non-screening setting.

Method: We developed a deep learning-based AI system and assessed its performance for the detection of actionable benign nodules (requiring follow-up), small lung cancers, and pulmonary metastases in CT scans acquired in two Dutch hospitals (internal and external validation).

Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals.

Objective: To study trends in the incidence of reported pulmonary nodules and stage I lung cancer in chest CT.

Methods: We analyzed the trends in the incidence of detected pulmonary nodules and stage I lung cancer in chest CT scans in the period between 2008 and 2019. Imaging metadata and radiology reports from all chest CT studies were collected from two large Dutch hospitals.

Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

Objectives: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaphoid fractures and whether it aids their diagnosis on conventional multi-view radiographs.

Methods: Four datasets of conventional hand, wrist, and scaphoid radiographs were retrospectively acquired at two hospitals (hospitals A and B). Dataset 1 (12,990 radiographs from 3353 patients, hospital A) and dataset 2 (1117 radiographs from 394 patients, hospital B) were used for training and testing a scaphoid localization and laterality classification component.

Remote labs in higher engineering education: engaging students with active learning pedagogy.

In engineering education laboratories serve as experiential learning aimed at engaging students. The past decades saw an increased use of online laboratories, including virtual and remote labs. Remote labs, providing online interfaces to physical labs, allow students to conduct experiments with real-world equipment anywhere and at any time.

Partial-Hand Prosthesis Users Show Improved Reach-to-Grasp Behaviour Compared to Transradial Prosthesis Users with Increased Task Complexity.

Approaches to improve outcomes after upper-extremity amputation remain poorly understood. Examining prosthesis-use at different levels of loss elucidates motor control challenges. Non-amputated participants completed simple and complex reach-to-grasp actions using a body-powered transradial or partial-hand prosthesis simulator.

Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.

Purpose: To compare the performance of a convolutional neural network (CNN) to that of 11 radiologists in detecting scaphoid bone fractures on conventional radiographs of the hand, wrist, and scaphoid.

Materials And Methods: At two hospitals (hospitals A and B), three datasets consisting of conventional hand, wrist, and scaphoid radiographs were retrospectively retrieved: a dataset of 1039 radiographs (775 patients [mean age, 48 years ± 23 {standard deviation}; 505 female patients], period: 2017-2019, hospitals A and B) for developing a scaphoid segmentation CNN, a dataset of 3000 radiographs (1846 patients [mean age, 42 years ± 22; 937 female patients], period: 2003-2019, hospital B) for developing a scaphoid fracture detection CNN, and a dataset of 190 radiographs (190 patients [mean age, 43 years ± 20; 77 female patients], period: 2011-2020, hospital A) for testing the complete fracture detection system. Both CNNs were applied consecutively: The segmentation CNN localized the scaphoid and then passed the relevant region to the detection CNN for fracture detection.

Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.

Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the COVID-19 Reporting and Data System (CO-RADS) and CT severity scoring systems.

Whole blood thrombin generation profiles of patients with cirrhosis explored with a near patient assay.

Background And Aims: Patients with cirrhosis have a rebalanced hemostasis, often with normal or elevated thrombin-generating (TG) capacity in plasma. Whole blood (WB) TG allows faster determination and, importantly, includes the influence of all circulating blood cells. We aimed to study the TG profile of patients with cirrhosis in WB and in platelet poor plasma.

Weekly Survivorship Curves of Soybean Aphid Biotypes 1 and 4 on Insecticidal Seed-Treated Soybean.

Thiamethoxam, an insecticide used in soybean seed treatments, effectively suppresses soybean aphids (Aphis glycines) Matsumura (Hemiptera: Aphididae) for a short time after planting. However, exactly when and how quickly soybean aphid populations could increase is unknown. Likewise, we lack data on virulent soybean aphid biotypes (that can overcome soybean resistance) when fed on seed-treated soybean.

The Application of the Weighted k-Partite Graph Problem to the Multiple Alignment for Metabolic Pathways.

The problem of aligning multiple metabolic pathways is one of very challenging problems in computational biology. A metabolic pathway consists of three types of entities: reactions, compounds, and enzymes. Based on similarities between enzymes, Tohsato et al.

Effects of Bt Corn and Egg Density on Western Corn Rootworm (Coleoptera: Chrysomelidae) Adult Emergence and Estimation of Effective Bt Dose.

Since 2003, rootworm-protected transgenic corn has been commercially deployed in the United States as a principal method of control of western corn rootworm, Diabrotica virgifera virgifera LeConte. Durability of this technology depends partly on larval mortality ("dose") exerted by the traits, but density-dependent mortality can confound calculations of dose. Research reported here examined the effects of density-dependent mortality on adult emergence and estimates of trait dose.

Efficacy of pyramided Bt proteins Cry1F, Cry1A.105, and cry2Ab2 expressed in Smartstax corn hybrids against lepidopteran insect pests in the northern United States.

Commercial field corn (Zea mays L.) hybrids transformed to express some or all of the lepidopteran insect-resistant traits present in SmartStax corn hybrids were evaluated for insecticidal efficacy against a wide range oflepidopteran corn pests common to the northern United States, during 2008 to 2011 at locations in 15 states. SmartStax hybrids contain a pyramid of two Bacillus thuringiensis (Bt) derived events for lepidopteran control: event TC1507 expressing Cry1F protein and MON 89034 expressing CrylA.

Evaluation of corn hybrids expressing Cry34Ab1/Cry35Ab1 and Cry3BbL against the western corn rootworm (Coleoptera: Chrysomelidae).

Studies were conducted across nine U.S. states, over 5 yr, to characterize the efficacy of transgenic corn (Zea mays L.

Evaluation of corn hybrids expressing Cry1F, cry1A.105, Cry2Ab2, Cry34Ab1/Cry35Ab1, and Cry3Bb1 against southern United States insect pests.

Studies were conducted across the southern United States to characterize the efficacy of multiple Bacillus thuringiensis (Bt) events in a field corn, Zea mays L., hybrid for control of common lepidopteran and coleopteran pests. Cry1F protein in event TC1507 and Cry1A.

DENSE: efficient and prior knowledge-driven discovery of phenotype-associated protein functional modules.

Background: Identifying cellular subsystems that are involved in the expression of a target phenotype has been a very active research area for the past several years. In this paper, cellular subsystem refers to a group of genes (or proteins) that interact and carry out a common function in the cell. Most studies identify genes associated with a phenotype on the basis of some statistical bias, others have extended these statistical methods to analyze functional modules and biological pathways for phenotype-relatedness.

Analysis of hepatic glycogen-associated proteins.

Glycogen particles are associated with a population of proteins that mediate its biological functions, including: management of glucose flux into and out of the glycogen particle, maintenance of glycogen structure and regulation of particle size, number, and cellular location. A survey of the glycogen-associated proteome would be predicted to identify the relative representation of known members of this population, and associations with unexpected proteins that have the potential to mediate other functions of the glycogen particle. We therefore purified glycogen particles from both mouse and rat liver, using different techniques, and analyzed the resulting tryptic peptides by MS.

Pesticides and nitrate in groundwater and rainwater in the Province of Limburg in The Netherlands.

The purpose of this study was to investigate the occurrence of high levels of pesticides in groundwater and rainwater in The Province of Limburg in The Netherlands. In groundwater samples in particular the presence of triazines--atrazine, simazine and propazine--was observed; besides these pesticides, dieldrin has also been observed. Atrazine and simazine were found to exceed the groundwater standard of 100 ng L(-1).

Board certification in optometry.

Background: In keeping with current expectations in the health care community, the purpose of the American Board of Optometric Practice (ABOP) is to enhance the quality of optometric care available to the public by fostering continued competence for practitioners through administering education and examinations for certification and re-certification. The formation of ABOP makes possible for the first time a board certification process for optometrists.

Methods: The optometry model for board certification and recertification emphasizes the breadth of the profession.

Relationship of trait, Type A behavior, and physical fitness variables to cardiovascular reactivity and coronary heart disease risk potential.

Purpose: This research investigated the effects of individual characteristics on cardiovascular reactivity, and in turn on the potential for developing coronary heart disease.

Design: Path analysis was performed using LISREL, a structural equation modeling program providing maximum likelihood estimators and goodness-of-fit measures.

Setting: Data were collected during a health assessment program, from participants attending a Department of Defense senior service school.

Epoetin alfa--focus on optimal hematocrit. Case study of the anemic patient.

Epoetin alfa therapy has dramatically improved therapeutic responses and outcomes for anemic patients with end-stage renal disease. This article examines clinical evidence supporting the correlation between patient outcomes and a higher hematocrit and addresses some of the barriers that may hinder optimal patient outcomes.