CDMO: Chaotic Dwarf Mongoose Optimization Algorithm for feature selection.

In this paper, a modified version of Dwarf Mongoose Optimization Algorithm (DMO) for feature selection is proposed. DMO is a novel technique of the swarm intelligence algorithms which mimic the foraging behavior of the Dwarf Mongoose. The developed method, named Chaotic DMO (CDMO), is considered a wrapper-based model which selects optimal features that give higher classification accuracy. To speed up the convergence and increase the effectiveness of DMO, ten chaotic maps were used to modify the key elements of Dwarf Mongoose movement during the optimization process. To evaluate the efficiency of the CDMO, ten different UCI datasets are used and compared against the original DMO and other well-known Meta-heuristic techniques, namely Ant Colony optimization (ACO), Whale optimization algorithm (WOA), Artificial rabbit optimization (ARO), Harris hawk optimization (HHO), Equilibrium optimizer (EO), Ring theory based harmony search (RTHS), Random switching serial gray-whale optimizer (RSGW), Salp swarm algorithm based on particle swarm optimization (SSAPSO), Binary genetic algorithm (BGA), Adaptive switching gray-whale optimizer (ASGW) and Particle Swarm optimization (PSO). The experimental results show that the CDMO gives higher performance than the other methods used in feature selection. High value of accuracy (91.9-100%), sensitivity (77.6-100%), precision (91.8-96.08%), specificity (91.6-100%) and F-Score (90-100%) for all ten UCI datasets are obtained. In addition, the proposed method is further assessed against CEC'2022 benchmarks functions.

A Clinically Explainable AI-Based Grading System for Age-Related Macular Degeneration Using Optical Coherence Tomography.

We propose an automated, explainable artificial intelligence (xAI) system for age-related macular degeneration (AMD) diagnosis. Mimicking the physician's perceptions, the proposed xAI system is capable of deriving clinically meaningful features from optical coherence tomography (OCT) B-scan images to differentiate between a normal retina, different grades of AMD (early, intermediate, geographic atrophy (GA), inactive wet or active neovascular disease [exudative or wet AMD]), and non-AMD diseases. Particularly, we extract retinal OCT-based clinical imaging markers that are correlated with the progression of AMD, which include: (i) subretinal tissue, sub-retinal pigment epithelial tissue, intraretinal fluid, subretinal fluid, and choroidal hypertransmission detection using a DeepLabV3+ network; (ii) detection of merged retina layers using a novel convolutional neural network model; (iii) drusen detection based on 2D curvature analysis; (iv) estimation of retinal layers' thickness, and first-order and higher-order reflectivity features. Those clinical features are used to grade a retinal OCT in a hierarchical decision tree process. The first step looks for severe disruption of retinal layers' indicative of advanced AMD. These cases are analyzed further to diagnose GA, inactive wet AMD, active wet AMD, and non-AMD diseases. Less severe cases are analyzed using a different pipeline to identify OCT with AMD-specific pathology, which is graded as intermediate-stage or early-stage AMD. The remainder is classified as either being a normal retina or having other non-AMD pathology. The proposed system in the multi-way classification task, evaluated on 1285 OCT images, achieved 90.82% accuracy. These promising results demonstrated the capability to automatically distinguish between normal eyes and all AMD grades in addition to non-AMD diseases.

A THOROUGH STUDY AND META-ANALYSIS OF THE PROGNOSTIC RELEVANCE OF THE C-REACTIVE-ALBUMIN RATIO IN ACUTE PANCREATITIS.

Although most cases of acute pancreatitis (AP) are minor, severe cases are associated with a substantial risk of death. Acute pancreatitis (AP) is a common illness. Therefore, it is critical to assess AP severity as soon as possible. This review aimed to ascertain the predictive significance of the CRP to albumin ratio in individuals with AP. We searched PubMed, Science Direct, and Cochrane Library electronic databases Until January 2023. Studies that reported the CRP/alb ratio at admission and its relationship to the severity or death of patients with AP were included. Using a random-effects model, we computed the pooled mean difference (MD) and 95% confidence interval (CI). The quality of the included studies was evaluated using the Newcastle-Ottawa scale. This meta-analysis combined data from six trials with a total of 2244 patients. Upon admission, the CRP/alb ratio was higher in patients with severe AP than in those with mild to moderate AP (pooled MD:3.59; 95% CI:2.51-4.68; p<0.00001). Additionally, non-survivor AP patients had a substantially higher CRP/alb ratio than survivor AP patients (pooled MD:2.12; 95% CI:0.43-3.8; p<0.01). Individuals with AP may benefit from a high CRP/ALB ratio as a preliminary indicator of poor prognosis.

Social Media Big Data Analysis: Towards Enhancing Competitiveness of Firms in a Post-Pandemic World.

In this paper, we proposed an advanced business intelligence framework for firms in a post-pandemic phase to increase their performance and productivity. The proposed framework utilizes some of the most significant tools in this era, such as social media and big data analysis for business intelligence systems. In addition, we survey the most outstanding related papers to this study. Open challenges based on this framework are described as well, and a proposed methodology to minimize these challenges is given. Finally, the conclusion and further research points that are worth studying are discussed.

Age-at-death assessed with Lamendin's original and population-specific models in a modern Brazilian osteological collection.

BACKGROUND: Estimating the age at death is a common procedure in the fields of forensic human identification and anthropological/archaeological investigations. Root translucency and periodontosis are regressive parameters used to estimate the age of adults, more specifically in Lamendin's method - established in 1992 in a French population. This study aimed to test the applicability and validity of Lamendin's method in a Brazilian osteological collection. METHODS: The sample consisted of 74 single-rooted teeth obtained from 50 skeletal remains (mean age: 53.20 ± 16.17 years) from Southeast Brazil. Lamendin's method was applied to enable a comparison between chronological (CA) and estimated ages (EA). A new population-specific equation was designed for the studied sample and the outcomes were compared with those obtained with Lamendin's original equation. RESULTS: The original methods led to a general underestimation of 11.32 years (8.83 years in males and 15.91 years in females). The method had a better performance among individuals between 40 and 59 years (mean differences between CA and EA: 4.8 years). The population-specific equation led to a mean overestimation of -2.04 years in males, and a mean underestimation of 3.77 years in females. Underestimations were considerably higher in other age groups. CONCLUSION: Despite the apparent improvements, both the original and the population-specific equations revealed coefficients of concordance that were constantly low between CA and EA. These outcomes suggest restrictions to the application of Lamendin's method in the forensic field, especially for human identification. The method, however, seems to be applicable for anthropological/archaeological applications.

Evaluation of tuberculosis diagnostic tools, with extending MODS assay use to second line susceptibility testing.

Tuberculosis diagnosis and drug susceptibility testing (DST) are considered a priority for prompt initiation of effective therapy, increasing the chance of cure, decreasing the development of resistance, and reducing transmission. AIM: Our objective was to evaluate currently applied diagnostic tools for tuberculosis including microscopic examination, GeneXpert, culture, and microscopic observation drug susceptibility (MODS) assay, investigating MODS assay usage for second line DST against culture based methods. MATERIAL AND METHODS: In this study the 120 sputum samples collected from suspected cases were over one year duration from December 2018 to January 2020. The samples were subjected to ZN microscopic examination, GeneXpert, MODS assay, and culture for detection of mycobacteria. Moreover, resistance to 5 drugs: isoniazid, rifampicin, ofloxacin, levofloxacin, and amikacin were tested using MODS against the proportion method. RESULTS: The sensitivity and specificity of the MODS assay were similar culture method with the advantage of obtaining the results in a median time of 10.7 days. Whereas the specificity of ZN and GeneXpert was high among untreated cases and decreased in subjects with a history of treatment. Monoresistance was the most common form of resistance detected among new cases followed by multidrug resistance, with a categorical agreement between the two methods above 90% for all tested drugs. CONCLUSIONS: MODS assay is an attractive option once standardized for second line susceptibility testing and GeneXpert assay is of high sensitivity for rapid detection of MTB and RIF resistance especially in treatment naive cases.

Experimental realization of an active non-reciprocal metamaterial using an eigen-structure assignment control strategy.

This paper presents a class of active non-reciprocal metamaterials (ANMMs) in an attempt to control the flow of acoustic waves along a one-dimensional acoustic duct. The proposed method distinguishes itself from the available approaches where the non-reciprocities are generated either actively or passively by various sources of nonlinearities, circulators and gyroscopic/gyrator components, and/or spatiotemporal modulation. The proposed method relies in its operation on a controller that is designed by simultaneous allocation of both the eigenvalues and eigenvectors. In other words, the entire eigen-structure of the closed-loop system is assigned as deemed necessary. Conventionally, the placement of the eigenvalues has been employed to enhance both the damping and response of the system. However, in this study, the focus is placed on adjusting the eigenvectors in a way that enables the spatial control and redistribution of the wave propagation along the acoustic duct in order to produce any desirable non-reciprocal behavior. During this entire process, the system continues to behave in a linear fashion. The theory governing the operation of this proposed approach is introduced, and a comprehensive experimental validation effort is presented to demonstrate the basic features, non-reciprocal behavior, and control characteristics. Generalization of the presented strategies to two-dimensional acoustic systems is a natural extension of the present work.

A multiparametric MRI-based CAD system for accurate diagnosis of bladder cancer staging.

Appropriate treatment of bladder cancer (BC) is widely based on accurate and early BC staging. In this paper, a multiparametric computer-aided diagnostic (MP-CAD) system is developed to differentiate between BC staging, especially T1 and T2 stages, using T2-weighted (T2W) magnetic resonance imaging (MRI) and diffusion-weighted (DW) MRI. Our framework starts with the segmentation of the bladder wall (BW) and localization of the whole BC volume (Vt) and its extent inside the wall (Vw). Our segmentation framework is based on a fully connected convolution neural network (CNN) and utilized an adaptive shape model followed by estimating a set of functional, texture, and morphological features. The functional features are derived from the cumulative distribution function (CDF) of the apparent diffusion coefficient. Texture features are radiomic features estimated from T2W-MRI, and morphological features are used to describe the tumors' geometric. Due to the significant texture difference between the wall and bladder lumen cells, Vt is parcelled into a set of nested equidistance surfaces (i.e., iso-surfaces). Finally, features are estimated for individual iso-surfaces, which are then augmented and used to train and test machine learning (ML) classifier based on neural networks. The system has been evaluated using 42 data sets, and a leave-one-subject-out approach is employed. The overall accuracy, sensitivity, specificity, and area under the receiver operating characteristics (ROC) curve (AUC) are 95.24%, 95.24%, 95.24%, and 0.9864, respectively. The advantage of fusion multiparametric iso-features is highlighted by comparing the diagnostic accuracy of individual MRI modality, which is confirmed by the ROC analysis. Moreover, the accuracy of our pipeline is compared against other statistical ML classifiers (i.e., random forest (RF) and support vector machine (SVM)). Our CAD system is also compared with other techniques (e.g., end-to-end convolution neural networks (i.e., ResNet50).

Precise higher-order reflectivity and morphology models for early diagnosis of diabetic retinopathy using OCT images.

This study proposes a novel computer assisted diagnostic (CAD) system for early diagnosis of diabetic retinopathy (DR) using optical coherence tomography (OCT) B-scans. The CAD system is based on fusing novel OCT markers that describe both the morphology/anatomy and the reflectivity of retinal layers to improve DR diagnosis. This system separates retinal layers automatically using a segmentation approach based on an adaptive appearance and their prior shape information. High-order morphological and novel reflectivity markers are extracted from individual segmented layers. Namely, the morphological markers are layer thickness and tortuosity while the reflectivity markers are the 1st-order reflectivity of the layer in addition to local and global high-order reflectivity based on Markov-Gibbs random field (MGRF) and gray-level co-occurrence matrix (GLCM), respectively. The extracted image-derived markers are represented using cumulative distribution function (CDF) descriptors. The constructed CDFs are then described using their statistical measures, i.e., the 10th through 90th percentiles with a 10% increment. For individual layer classification, each extracted descriptor of a given layer is fed to a support vector machine (SVM) classifier with a linear kernel. The results of the four classifiers are then fused using a backpropagation neural network (BNN) to diagnose each retinal layer. For global subject diagnosis, classification outputs (probabilities) of the twelve layers are fused using another BNN to make the final diagnosis of the B-scan. This system is validated and tested on 130 patients, with two scans for both eyes (i.e. 260 OCT images), with a balanced number of normal and DR subjects using different validation metrics: 2-folds, 4-folds, 10-folds, and leave-one-subject-out (LOSO) cross-validation approaches. The performance of the proposed system was evaluated using sensitivity, specificity, F1-score, and accuracy metrics. The system's performance after the fusion of these different markers showed better performance compared with individual markers and other machine learning fusion methods. Namely, it achieved [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], respectively, using the LOSO cross-validation technique. The reported results, based on the integration of morphology and reflectivity markers and by using state-of-the-art machine learning classifications, demonstrate the ability of the proposed system to diagnose the DR early.

Tacrolimus and Sirolimus Once Daily Monotherapy Regimen as a Safe and Effective Long-Term Maintenance Immunosuppressive Therapy in Pediatric Liver Transplantation.

BACKGROUND: Long-term efficiency of attenuated immunosuppressive therapies is not well characterized in pediatric liver transplantation (LT). OBJECTIVE: To assess the efficiency of tacrolimus once daily (TAC-OD) and sirolimus once daily (SLR-OD) immunosuppression in pediatric LT. METHODS: We retrospectively evaluated 59 children who underwent LT in our center during 2002 to 2016. Those including children who underwent planned decrease in immunosuppressant dose (stable clinical conditions after 2 years of LT), and those who underwent unplanned decrease in immunosuppressant dose (because of complications such as post-transplant lymphoproliferative disorder [PTLD] and renal failure). RESULTS: 25 of 59 children underwent planned decrease in immunosuppressant dosage (mean±SD duration of 4.5±1.8, range: 3-11 years); 34 had unplanned decrease (mean±SD of 1.3±0.6, range: 0.5-2.6 years). 19 of 25 children with planned conversion received TAC-OD; 6 received SLR-OD (22 with 1 mg/day dose, and 3 with 1 mg every two days). Of 34 children with unplanned conversion, 27 received TAC-OD, 7 SLR-OD (25 children with 1 mg/day, 7 with 1 mg every two days, 1 with 0.5 mg/day TAC, and 1 with 0.5 mg TAC every two days). We found no adverse events including acute or chronic graft rejection, renal insufficiency, infections, PTLDs, or cardiovascular thrombotic events after initiation of the modified immunosuppression in none of the groups. CONCLUSION: TAC-OD or SLR-OD monotherapies are safe and effective for long-term management of LT children with either stable clinical conditions or those with LT complications.

Active synthesis of a gyroscopic-nonreciprocal acoustic metamaterial.

A class of active nonreciprocal metamaterials is developed to control the flow and distribution of energy along periodic dynamical systems. Such a development constitutes a radical departure from the currently available approaches where the non-reciprocities are generated either by utilizing various physical sources of passive nonlinearities, gyroscopic circulators, spatiotemporal modulation, or active control of nonlinear systems. The proposed active Nonreciprocal Gyroscopic Meta-Material (NGMM) cell consists of a one-dimensional acoustic duct provided with linear dynamic control capabilities that virtually synthesize a gyroscopic control action that generates non-reciprocal characteristics of tunable magnitude and direction. The controller is designed in order to enable the spatial control and redistribution of the wave propagation energy flow along the acoustic duct. During this entire process, the system behaves in a linear fashion. Numerical examples are presented to demonstrate the basic features, non-reciprocal behavior, as well as the energy flow characteristics. The presented concept and controller design of the NGMM can be extended to various critical structures to achieve realistic acoustic diode configurations in a simple and programmable manner.

Finite element modeling of one-dimensional nonreciprocal acoustic metamaterial with anti-parallel diodes.

A class of passive nonreciprocal acoustic metamaterials is developed to control the flow and distribution of acoustic energy in acoustic cavities and systems. Such development departs radically from present methods that favor the transmission direction by using hardwired arrangements of the hardware and hence, it cannot be reversed. The proposed nonreciprocal acoustic metamaterial (NAMM) cell consists of a cylindrical acoustic cavity with piezoelectric flexible boundaries that provide control in one-dimension. These boundaries are connected to an array of anti-parallel diodes to introduce simultaneous nonlinear damping and stiffness effects that break the reciprocity of energy flow through the NAMM cell. A finite element model of the NAMM cell is developed to investigate the nonreciprocal characteristics of the cell by optimizing the parameters that influence the nonlinear damping and stiffness effects introduced by the diodes. Numerical examples are presented to demonstrate the effectiveness of the proposed NAMM in tuning the directivity, flow, and distribution of acoustic energy propagating though the metamaterial.

Active nonreciprocal metamaterial using an eigen-structure assignment control strategy.

A class of active nonreciprocal metamaterials (ANMMs) is developed to control the flow and distribution of energy along periodic dynamical systems. Such a development constitutes a radical departure from the currently available approaches where the non-reciprocities are generated either by utilizing various sources of passive nonlinearities, gyroscopic circulators, spatiotemporal modulation, or active control of nonlinear systems. The proposed ANMM cell consists of a one-dimensional acoustic duct provided with linear active control capabilities. The controller is designed by simultaneous assignment of both the eigenvalues and eigenvectors, i.e., the entire eigen-structure, of the closed-loop system. Conventionally, the placement of the eigenvalues has been considered to improve the damping and system's response. However, in this study, the emphasis is placed also on tailoring the eigenvectors in order to enable the spatial control and redistribution of the wave propagation energy flow along the acoustic duct in such a manner that it can introduce non-reciprocity as well as control its direction and reversal. During this entire process, the system remains behaving in a linear fashion. Numerical examples are presented to demonstrate the basic features and non-reciprocal behavior, as well as the energy flow characteristics.

A New Framework for Performing Cardiac Strain Analysis from Cine MRI Imaging in Mice.

Cardiac magnetic resonance (MR) imaging is one of the most rigorous form of imaging to assess cardiac function in vivo. Strain analysis allows comprehensive assessment of diastolic myocardial function, which is not indicated by measuring systolic functional parameters using with a normal cine imaging module. Due to the small heart size in mice, it is not possible to perform proper tagged imaging to assess strain. Here, we developed a novel deep learning approach for automated quantification of strain from cardiac cine MR images. Our framework starts by an accurate localization of the LV blood pool center-point using a fully convolutional neural network (FCN) architecture. Then, a region of interest (ROI) that contains the LV is extracted from all heart sections. The extracted ROIs are used for the segmentation of the LV cavity and myocardium via a novel FCN architecture. For strain analysis, we developed a Laplace-based approach to track the LV wall points by solving the Laplace equation between the LV contours of each two successive image frames over the cardiac cycle. Following tracking, the strain estimation is performed using the Lagrangian-based approach. This new automated system for strain analysis was validated by comparing the outcome of these analysis with the tagged MR images from the same mice. There were no significant differences between the strain data obtained from our algorithm using cine compared to tagged MR imaging. Furthermore, we demonstrated that our new algorithm can determine the strain differences between normal and diseased hearts.

The effect of platelet-rich plasma as a scaffold in regeneration/revitalization endodontics of immature permanent teeth assessed using 2-dimensional radiographs and cone beam computed tomography: a randomized controlled trial.

AIM: To assess the outcomes of platelet-rich plasma as a scaffold in regenerative/revitalization endodontics (RET) using cone beam computed tomography (CBCT) and 2-dimensional radiographs. METHODOLOGY: Twenty-six healthy patients with mean age of 12.66 ± 4.47, and immature permanent anterior teeth with necrotic pulps, were randomly allocated to two groups, whereby RET was performed using platelet-rich plasma (PRP, test group) and blood clot (BLC, control group). Changes in root length (RL), root dentinal thickness (RDT), apical foramen width (AFW) and radiographic root area (RRA), were assessed using both radiographic methods, whilst changes in periapical area diameter (PAD) were assessed using CBCT, over a period of 12 months. T-test and chi-square/Fisher's exact tests were used to compare continuous and categorical data between BLC and PRP groups, respectively. Changes in RL, RDT, AFW, RRA and PAD were examined by comparing the two groups (PRP versus BLC) using multilevel modelling, considering the clustering effect of repeated measures of several teeth originating from the same participant. RESULTS: Changes in RL, RDT, AFW, RRA and PAD, over time, were found to be significant for both groups. There was, however, no difference between the RET techniques (PRP versus BLC), using both radiographic and CBCT methods. The results of both assessment techniques (CBCT and 2-dimensional radiographic methods) were highly consistent (overall ICC ranged between 0.80 and 0.94). In addition, a significant effect of baseline PAD was found on RL, RRA and AD at 12 months (RL effect = -0.68, P < 0.001; RRA effect = -1.91, P = 0.025; AD effect = 0.08, P = 0.024). CONCLUSION: The current study highlights successful and comparable clinical and radiographic outcomes of RET techniques using PRP and BLC. Standardized and calibrated 2-dimensional radiographic assessment was as effective as CBCT in assessing RET outcomes; therefore, the routine use of CBCT in RET is not recommended. Although an effect of baseline periapical lesion diameter on root development outcomes, at 12 months, were observed, more studies are recommended in order to assess such an effect.

EARLY ASSESSMENT OF RENAL TRANSPLANTS USING BOLD-MRI: PROMISING RESULTS.

Non-invasive evaluation of renal transplant function is essential to minimize and manage renal rejection. A computer-assisted diagnostic (CAD) system was developed to evaluate kidney function post-transplantation. The developed CAD system utilizes the amount of blood-oxygenation extracted from 3D (2D + time) blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) to estimate renal function. BOLD-MRI scans were acquired at five different echo-times (2, 7, 12, 17, and 22) ms from 15 transplant patients. The developed CAD system first segments kidneys using the level-sets method followed by estimation of the amount of deoxyhemoglobin, also known as apparent relaxation rate (R2*). These R2* estimates were used as discriminatory features (global features (mean R2*) and local features (pixel-wise R2*)) to train and test state-of-the-art machine learning classifiers to differentiate between non-rejection (NR) and acute renal rejection. Using a leave-one-out cross-validation approach along with an artificial neural network (ANN) classifier, the CAD system demonstrated 93.3% accuracy, 100% sensitivity, and 90% specificity in distinguishing AR from non-rejection . These preliminary results demonstrate the efficacy of the CAD system to detect renal allograft status non-invasively.

Hydatidosis: Preparation and evaluation of radiolabeled antigens and antibodies.

The present preliminary study intends to evaluate the in vitro use of hydatid antigen and their antibodies once labeled with iodine 125(I125) and characterized from viewpoint of radiochemical purity and immunoreactivity. Radiolabelled molecules gave satisfactory purity of 94% and 96%-98%, for hydatid antigen and IgG respectively. As regards, the specific activity of these latter, varied between 4.79 and 5.97 µCi/µg. The specificity test of radiolabelled IgG against the hydatid membranes showed a significant recognition that increased proportionally according to the contact surface. Likewise this immunoreactivity test performed with a simple binding assay, using human hydatid fluid antigen (HHF-Ag), previously fixed on a solid phase, gave satisfactory fixation rate of the order of 356 ±â€¯48.08cpm, 2539 ±â€¯550.12cpm and 6558 ±â€¯712.76cpm for the concentrations of 0.1 µg/ml, 2 µg/ml and 25 µg/ml respectively. Statistical study of 88 sera, carried out with radiolabelled antigen (125I-HHF-Ag) in competitive radioimmunoassay test (CRIA) showed highly significant difference (p < 0.0001) in the binding capacity of antigens from patients sera with hydatid disease (65.63 ±â€¯9.12) compared to the negative sera (19.25 ±â€¯14.84). No cross reaction was observed using sera from patients with toxoplasmosis (33, 07 ±â€¯13, 07) and the difference was highly significant (p < 0.0001) compared to E granulosus infected patient sera. Furthermore, this test seemed to be sensitive since among the 43 sera tested, only 37 (86%) were found to be positive by passive hemagglutination (HAP), while the totality (100%) responded positively by CRIA. Our findings are encouraging, suggesting that these radiolabeled molecules could be useful for advancing toward new diagnostic and therapeutic modalities.

Detection of microspheres in vivo using multispectral optoacoustic tomography.

We introduce a new approach to detect individual microparticles that contain NIR fluorescent dye by multispectral optoacoustic tomography in the context of the hemoglobin-rich environment within murine liver. We encapsulated a near infrared (NIR) fluorescent dye within polystyrene microspheres, then injected them into the ileocolic vein, which drains to the liver. NIR absorption was determined using multispectral optoacoustic tomography. To quantitate the minimum diameter of microspheres, we used both colorimetric and spatial information to segment the regions in which the microspheres appear. Regional diameter was estimated by doubling the maximum regional distance. We found that the minimum microsphere size threshold for detection by multispectral optoacoustic tomography images is 78.9 µm.

A review of the status and development of Kuwait's fisheries.

The status of Kuwait's fisheries landings and relative abundance for major species was reviewed using research data from Kuwait Institute for Scientific Research and landing data from the Kuwait's Central Statistical Bureau. Landing data showed significant decreases for major commercial species such as zobaidy (Pampus argenteus), suboor (Tenualosa ilisha), hamoor (Epinephelus coioides), newaiby (Otolithes ruber) and hamra (Lutjanus malabaricus) while abundance data for the shrimp Penaeus semisulcatus showed significant reduction in the recent years mainly because of overfishing. The catch-rate data showed continuous decline for major species such as zobaidy, newaiby and hamoor, which indicate that stock abundances of these species are low. The reduction in stock abundance in context with changes in habitat quality, particularly the effects of reduced discharge of the Shatt Al-Arab, is discussed.

[Relation between structure and function, of the cerebral artery "carotid" in laboratory rat submitted to atherogenic diet]. / Relation entre structure et fonction de l'artère cérébrale « carotide ¼ chez le rat Wistar soumis à un régime athérogène.

OBJECTIVE OF THE STUDY: The aim of our investigation was the study of the pathophysiology of the carotid artery in cases of nutritional stress in male atheroresistant Wistar rats. MATERIALS AND METHODS: Were administered daily by gavage to experimental rats a high fat diet consisting of peanut oil, cholesterol (3%) and sodium cholate (1%). Throughout this experiment, we conducted monitoring of some biochemical parameters and the morpho-histopathology of the carotid cerebral artery. The results obtained are compared to those of control rats in the same experimental conditions. RESULTS: We found that this fat diet resulted in experimental rats disruption of biochemical tests and tissular and cellular alterations in carotid wall. Indeed, the biochemical examination shows a significant increase of the parameters studied. Morphological examination revealed thickening of the carotid wall and histopathological examination of this artery, highlights the installation of a vascular remodeling from thickening of the intima-media to the installation of a probable atherosclerosis accompanied by a possible hyalinization and a net fibrosis. CONCLUSION: At the end of this study, although notes that our fat diet could cause a metabolic disorder that can cause multiple tissue and cell damage observed in cerebral artery "carotid" of atheroresistant rats.