Ecological studies of Bisheh-palan Wetland (Broojerd)

Bisheh-Dalan wetland is located in southern of Broojerd city near the Tireh River with 914 hectares area.This survey was done in 2002-2003.Water temperature variation between 8 at 23/5 °C, the quantity pH between 6.5-7.4, Ec between 362-443 μm/cm, minimum-dissolved oxygen 5/5 mg/l in Bisheh-Dalan area. The phytoplankton comprised 4 families and 15 genus include (Microcystis Gloeotrehia Gloeocapsa, Merismopedia Ceratium, Glenodinium, Gymnodinium, Peridinium Closterium, Stauratrum, Treubaria, Cymbella, Cyclotella, Nitzchia, Navieula), the zooplanktons had 3 families and 10 genus, consist (Stmocephalus, Shnucephalus, Diaphanasoma, Simocephalus, Daphnia, Eueyclops, Attheylla, Cyclops, Trinema, Aeanthoeyclops) and the benthos have been had 10 orders and 15 families with names (Ecdyonuridae, Caenidae, Baetidae, Chiranomidae, Calicidae, Dytiscidae, Limmaeidae, Planorbiidae, Glossosomatidae , Tubificidae, Erpobdellidae, Planariidae, Gammaridae) in Bisheh-Dalan area. The fishes of Bisheh-Dalan wetland composed 2 family with names Cyprinidae and poeciliidae with 7 genus and 8 species. Maximum number of fishes located to Capoeta with 2 Species

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration

Motor deficits are observed in Alzheimer’s disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans

Comparison of Two Methods for In Vivo Estimation of the Glenohumeral Joint Rotation Center (GH-JRC) of the Patients with Shoulder Hemiarthroplasty

Determination of an accurate glenohumeral-joint rotation center (GH-JRC) from marker data is essential for kinematic and dynamic analysis of shoulder motions. Previous studies have focused on the evaluation of the different functional methods for the estimation of the GH-JRC for healthy subjects. The goal of this paper is to compare two widely used functional methods, namely the instantaneous helical axis (IHA) and symmetrical center of rotation (SCoRE) methods, for estimating the GH-JRC in vivo for patients with implanted shoulder hemiarthroplasty. The motion data of five patients were recorded while performing three different dynamic motions (circumduction, abduction, and forward flexion). The GH-JRC was determined using the CT-images of the subjects (geometric GH-JRC) and was also estimated using the two IHA and SCoRE methods. The rotation centers determined using the IHA and SCoRE methods were on average 1.47±0.62 cm and 2.07±0.55 cm away from geometric GH-JRC, respectively. The two methods differed significantly (two-tailed p-value from paired t-Test ∼0.02, post-hoc power ∼0.30). The SCoRE method showed a significant lower (two-tailed p-value from paired t-Test ∼0.03, post-hoc power ∼0.68) repeatability error calculated between the different trials of each motion and each subject and averaged across all measured subjects (0.62±0.10 cm for IHA vs. 0.43±0.12 cm for SCoRE). It is concluded that the SCoRE appeared to be a more repeatable method whereas the IHA method resulted in a more accurate estimation of the GH-JRC for patients with endoprostheses

A Patient-Specific Foot Model for the Estimate of Ankle Joint Forces in Patients with Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the leading cause of childhood disability from a musculoskeletal disorder. It generally affects large joints such as the knee and the ankle, often causing structural damage. Different factors contribute to the damage onset, including altered joint loading and other mechanical factors, associated with pain and inflammation. The prediction of patients' joint loading can hence be a valuable tool in understanding the disease mechanisms involved in structural damage progression. A number of lower-limb musculoskeletal models have been proposed to analyse the hip and knee joints, but juvenile models of the foot are still lacking. This paper presents a modelling pipeline that allows the creation of juvenile patient-specific models starting from lower limb kinematics and foot and ankle MRI data. This pipeline has been applied to data from three children with JIA and the importance of patient-specific parameters and modelling assumptions has been tested in a sensitivity analysis focused on the variation of the joint reaction forces. This analysis highlighted the criticality of patient-specific definition of the ankle joint axes and location of the Achilles tendon insertions. Patient-specific detection of the Tibialis Anterior, Tibialis Posterior, and Peroneus Longus origins and insertions were also shown to be important

Forces in the Shoulder Joint: On validation of musculoskeletal shoulder models

Detailed information about muscle forces in the human musculoskeletal system are highly demanded for several applications. Unfortunately, the measurement of muscle forces in-vivo is hardly possible. To date, musculoskeletal models are best alternative for the direct measurement of these forces. A major concern in musculoskeletal modeling is, however, model validity. To validate a model we need to compare its predictions to real measured muscle forces which, as mentioned, are difficult to measure. The main objective of this thesis is the validation of a comprehensive musculoskeletal shoulder model, the Delft Shoulder and Elbow Model, at the level of kinematic and dynamic models. Recently, an implantable instrumented shoulder endoprosthesis has been developed that is capable of measuring contact loads in the glenohumeral joint in-vivo. Although direct measurement of muscle forces is still not possible by this implant, it does allow for a general validation at the level of the summed muscle forces in the glenohumeral joint. In the first part of this thesis, the in-vivo measured forces in the instrumented shoulder implant are used, as a ‘golden standard’, to quantitatively validate the model. A general conclusion of this part is that the model is moderately accurate for estimation of glenohumeral joint reaction forces. The second part of this thesis explores the reasons for the differences between model predictions and experimental data that were observed and described in the first part and focuses on model adjustments to find a closer match between model and experiment. A selection of potential causes (e.g. muscle co-contraction, articular friction) is identified and investigated. An important conclusion of this part would be that antagonist muscle co-contraction should be considered in the modeling procedure. It is also concluded that friction moments in the shoulder endoprosthesis are considerable and should be included in the biomechanical analysis of artificial shoulder joints.BioMechanical EngineeringMechanical, Maritime and Materials Engineerin

How well does a musculoskeletal model predict GH-joint contact forces? Comparison with in-vivo data

The Delft Shoulder and Elbow Model (DSEM), a large-scale musculoskeletal model, allows for estimation of individual muscle and joint reaction forces in the shoulder and elbow complex. Although the model has been qualitatively verified previously using EMG signals, quantitative validation has not yet been feasible. In this paper we report on the validation of the DSEM by comparing the GH-joint contact forces estimated by the DSEM with the in-vivo forces measured by a recently developed instrumented shoulder endoprosthesis, capable of measuring the glenohumeral (GH) joint contact forces in-vivo [1]. To validate the model, two patients with instrumented shoulder hemi-arthroplasty were measured. The measurement process included the collection of motion data as well as in-vivo joint reaction forces. Segment and joint angles were used as the model inputs to estimate the GH-joint contact forces. The estimated and recorded GH-joint contact forces for Range of Motion (RoM) and force tasks were compared based on the magnitude of the resultant forces. The results show that the estimated force follows the measured force for abduction and anteflexion motions up to 80 and 50 degrees arm elevations, respectively, while they show different behaviors for angles above 90 degrees (decrease is estimated but increase is measured). The DSEM underestimates the peak force for RoM (up to 38% for abduction motion and 64% for anteflexion motion), while overestimates the peak forces (up to 90%) for most directions of performing the force tasks