Developing a Deep Neural Network model for COVID-19 diagnosis based on CT scan images

COVID-19 is most commonly diagnosed using a testing kit but chest X-rays and computed tomography (CT) scan images have a potential role in COVID-19 diagnosis. Currently, CT diagnosis systems based on Artificial intelligence (AI) models have been used in some countries. Previous research studies used complex neural networks, which led to difficulty in network training and high computation rates. Hence, in this study, we developed the 6-layer Deep Neural Network (DNN) model for COVID-19 diagnosis based on CT scan images. The proposed DNN model is generated to improve accurate diagnostics for classifying sick and healthy persons. Also, other classification models, such as decision trees, random forests and standard neural networks, have been investigated. One of the main contributions of this study is the use of the global feature extractor operator for feature extraction from the images. Furthermore, the 10-fold cross-validation technique is utilized for partitioning the data into training, testing and validation. During the DNN training, the model is generated without dropping out of neurons in the layers. The experimental results of the lightweight DNN model demonstrated that this model has the best accuracy of 96.71% compared to the previous classification models for COVID-19 diagnosis.

Body composition predicts hypertension using machine learning methods: a cohort study

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

Prognosis prediction in traumatic brain injury patients using machine learning algorithms

Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging worldwide. The present study aimed to achieve the most accurate machine learning (ML) algorithms to predict the outcomes of TBI treatment by evaluating demographic features, laboratory data, imaging indices, and clinical features. We used data from 3347 patients admitted to a tertiary trauma centre in Iran from 2016 to 2021. After the exclusion of incomplete data, 1653 patients remained. We used ML algorithms such as random forest (RF) and decision tree (DT) with ten-fold cross-validation to develop the best prediction model. Our findings reveal that among different variables included in this study, the motor component of the Glasgow coma scale, the condition of pupils, and the condition of cisterns were the most reliable features for predicting in-hospital mortality, while the patients' age takes the place of cisterns condition when considering the long-term survival of TBI patients. Also, we found that the RF algorithm is the best model to predict the short-term mortality of TBI patients. However, the generalized linear model (GLM) algorithm showed the best performance (with an accuracy rate of 82.03 ± 2.34) in predicting the long-term survival of patients. Our results showed that using appropriate markers and with further development, ML has the potential to predict TBI patients' survival in the short- and long-term.

CCTCOVID: COVID-19 detection from chest X-ray images using Compact Convolutional Transformers

COVID-19 is a novel virus that attacks the upper respiratory tract and the lungs. Its person-to-person transmissibility is considerably rapid and this has caused serious problems in approximately every facet of individuals' lives. While some infected individuals may remain completely asymptomatic, others have been frequently witnessed to have mild to severe symptoms. In addition to this, thousands of death cases around the globe indicated that detecting COVID-19 is an urgent demand in the communities. Practically, this is prominently done with the help of screening medical images such as Computed Tomography (CT) and X-ray images. However, the cumbersome clinical procedures and a large number of daily cases have imposed great challenges on medical practitioners. Deep Learning-based approaches have demonstrated a profound potential in a wide range of medical tasks. As a result, we introduce a transformer-based method for automatically detecting COVID-19 from X-ray images using Compact Convolutional Transformers (CCT). Our extensive experiments prove the efficacy of the proposed method with an accuracy of 99.22% which outperforms the previous works.

GSVMA: A Genetic Support Vector Machine ANOVA Method for CAD Diagnosis

Background

Coronary artery disease (CAD) is one of the crucial reasons for cardiovascular mortality in middle-aged people worldwide. The most typical tool is angiography for diagnosing CAD. The challenges of CAD diagnosis using angiography are costly and have side effects. One of the alternative solutions is the use of machine learning-based patterns for CAD diagnosis.

Methods

Hence, this paper provides a new hybrid machine learning model called genetic support vector machine and analysis of variance (GSVMA). The analysis of variance (ANOVA) is known as the kernel function for the SVM algorithm. The proposed model is performed based on the Z-Alizadeh Sani dataset so that a genetic optimization algorithm is used to select crucial features. In addition, SVM with ANOVA, linear SVM (LSVM), and library for support vector machine (LIBSVM) with radial basis function (RBF) methods were applied to classify the dataset.

Results

As a result, the GSVMA hybrid method performs better than other methods. This proposed method has the highest accuracy of 89.45% through a 10-fold crossvalidation technique with 31 selected features on the Z-Alizadeh Sani dataset.

Conclusion

We demonstrated that SVM combined with genetic optimization algorithm could be lead to more accuracy. Therefore, our study confirms that the GSVMA method outperforms other methods so that it can facilitate CAD diagnosis.

Effect of oral administration of GnRHa+nanoparticles of chitosan in oogenesis acceleration of goldfish Carassius auratus

Several methods have been used to accelerate previtellogenesis and vitellogenesis stages in fish, including hormonal induction, sustained-release delivery systems, and oral delivery of gonadotropin-releasing hormone (GnRH). In this study, we proposed the oral administration of GnRH analog + nanoparticles of chitosan to accelerate oogenesis in goldfish as a model fish in reproductive biology and aquaculture. In this regard, adult female goldfish were fed with six experimental groups: chitosan, 50 μg GnRHa/kg b.w., 100 μg GnRHa/kg b.w., chitosan + 50 μg GnRHa/kg b.w., and chitosan + 100 μg GnRHa/kg b.w., and diet without any additive as the control for 40 days in triplicate. Every 10 days, ovarian samples were collected, and gonadosomatic index (GSI), oocyte diameter (OD), zona radiata thickness (Zr), and diameter of the follicular layer (Fl) were measured to assess ovarian developmental stage for each treatment. Additionally, blood sampling was done to measure serum 17β-estradiol concentration at the end of the experiment. All parameters remained unchanged during the experiment in the chitosan-fed group. In the group fed with 100 μg GnRH or chitosan nanoparticle + 100 μg GnRHa, these parameters in general were increased. However, the effects in 50 μg GnRHa or chitosan nanoparticle + 50 μg GnRHa treatments were uncertain; they affected serum E2 levels as a trend toward a significant increase was observed in goldfish treated with chitosan nanoparticle + 100 μg GnRHa. Finally, the results indicated the oral administration of chitosan + 100 μg GnRHa/kg b.w. significantly accelerated the oocyte development and growth of ovary.

Transgenerational disrupting impacts of atrazine in zebrafish: Beneficial effects of dietary spirulina

In a range of fish species, offspring sustainability is much dependent to their mother's investment into the egg yolk. A healthy environment helps broodfish to produce normal quality offspring. However, deviation from optimal conditions can disturb body functions that effect the next generation. Here, zebrafish (Danio rerio) was employed to investigate the transgenerational impacts of an immunotoxic and endocrine disruptor, atrazine (AZ). In addition, the possible ameliorated effects of a nutraceutical, Arthrospira platensis (spirulina- SP), was considered. Adult females were either exposed to 0 (Cn), 5 (AZ5), and 50 (AZ50) μg/L AZ or fed SP-supplemented diet (10 g/kg; SP). In combination treatments, fish were also exposed to AZ and fed SP (SP-AZ5 and SP-AZ50). Embryos were obtained after 28 d of exposure. Exposure to AZ50 caused females to produce eggs with significantly lower fertilization and hatching. No changes were observed in the concentrations of thyroid hormones. AZ significantly increased cortisol response and reduced levels of immunoglobulin, lysozyme and complement activities in females and their offspring. SP-AZ5 and SP-AZ50 females, however, resisted to the toxic effects of AZ, produced embryos with lower cortisol content and higher immunity competence. Bactericidal activity of the embryos also showed the transgenerational antimicrobial effects of SP along with the AZ immunotoxicity. Overall, these results indicate that AZ could have long lasting toxic effects on fish, and that dietary SP-supplementation could ameliorate AZ induced transgenerational toxic effects.

Detection of Ultraweak Photon Emission (UPE) from Cells as a Tool for Pathological Studies

OBJECTIVE

It is well-known that all living cells emit ultra-weak photon emission (UPE), which is due to byproducts of chemical reactions in cell metabolisms. It has been shown that Reactive Oxygen Species (ROS) in the cells enhances the UPE intensity. The magnitude of such UPE is extremely weak (i.e. a few to 10³ photons/ (sec.cm2²)), and the detection of such ultra-weak signals is hardly possible via sensitive instruments like photomultiplier tube (PMT) that can detect single photons.

MATERIALS AND METHODS

H₂O₂ factor with various concentrations was applied on the HT-29 cells to generate ROS. H₂O₂ concentrations were so low to be nondestructive to the cells. Then, the effect of ROS generation on UPE intensity was investigated. PMT was used to detect UPE from HT-29 cells.

RESULTS

The topical application of H₂O₂ was significantly different (P < 0.05) in comparison with HT-29 cells without H₂O₂ at a concentration of 1mM in 5 min detection time. The integrated UPE in the presence of H₂O₂ at concentration of 3mM was significantly higher (P < 0.05) than the integrated UPE in other groups at the same detection time. The difference between the concentrations of 3mM and 4mM was not significant (P > 0.01) for integrated UPE in the cell groups in the presence of H₂O₂.

CONCLUSION

The results show that the recorded UPE from HT-29 cells increased with the topical application of exogenous ROS inducer. As a result, UPE can be used as a non-invasive technique for monitoring ROS in cells.

Effects of the prebiotic mannan-oligosaccharide on the stress response of feed deprived zebrafish (Danio rerio)

Feed deprivation has deleterious effects on fish behavior and stress physiology which may susceptible them to disease outbreak. Functional ingredients in diets may substantially impact the physiology and stress responses of host organisms. Here, we hypothesized that the administration of a dietary prebiotic might attenuate the negative influences of feed deprivation on the behavioral profile of anxiety and physiological responses to stress in zebrafish (Danio rerio). Fish were fed with either basal or mannan-oligosaccharide supplemented (0.4% MOS/kg diet) diets, once per day (normal-control: CN, and normal-prebiotic: PN) or once every other day (starved-control: CS, and starved-prebiotic: PS) for 8weeks. Afterwards, fish were subjected to a novel tank test to measure anxiety. Fish from the CS treatment exhibited more pronounced bottom-dwelling behavior than the other treatments. The number of transitions from the bottom to the top third of the novel tank was significantly higher in PN fish than the CS specimens. No significant differences were found between the CN and PS treatments in all of the anxiety behaviors. CS fish showed higher baseline cortisol levels than the other treatments, which was in line with higher expression of CRH gene in fish subjected to this treatment. Cortisol levels and CRH gene expression of the subjects were also measured after induction of two routine aquaculture stressors. CN and PS fish exhibited similar patterns of cortisol responses at most of the sampling times after stress, and PN specimens showed a significantly lower concentration of cortisol than the other treatments in most cases. Expression of the CRH gene was higher in feed deprived fish immediately after stress induction. Overall, the results show that feed deprivation in some cases influenced anxiety-like behaviors and elevated stress response in zebrafish juveniles; however, the addition of MOS to the diet helped deprived fish exhibit behaviors more typical of normally fed animals.

Prozac impacts lateralization of aggression in male Siamese fighting fish

Previous studies have shown that Siamese fighting fish, Betta splendens, preferentially use right-eye during the aggressive displays. However, administration of antidepressant drugs may disrupt eye-use preference in association with a reduction in aggression; a phenomena that has not been explored in fish. The objective of the current study was to examine the effects of exposure to the antidepressant drug, fluoxetine, on lateralization in eye-use during aggressive displays in male Siamese fighting fish. Baseline aggression and lateralization in eye use of thirty fish were assessed toward live conspecifics, following which experimental subjects (n=15) were then exposed to fluoxetine (540ng/L) in a static renewal water system. Behavior was quantified again after 9 days of exposure. All of the subjects preferentially used the right-eye during aggressive responses before the exposure experiments. Fluoxetine exposed subjects showed a reduction in the time spent gill flaring as has previously been reported, indicative of a reduction in the level of aggression. Fluoxetine also had a significant effect on the lateralization in preferred eye-use while looking at their opponent. Fish exposed to fluoxetine switched from a preferential use of the right-eye during aggressive encounters prior to exposure to using their left-eye after exposure to fluoxetine. The results are discussed with regard to asymmetrical distribution of serotonin between the two brain hemispheres.

IGF-I and IGF-II effects on local IGF system and signaling pathways in gilthead sea bream (Sparus aurata) cultured myocytes

The insulin-like growth factors (IGFs) have a fundamental role in a vast range of functions acting through a tyrosine-kinase receptor (IGF-IR). IGFs in muscle can affect the expression of components of the local IGF system, myogenic regulatory factors (MRFs), proliferating (proliferating cell nuclear antigen, PCNA) or differentiating molecules (myosin heavy chain, MHC) and, lead to the activation of different signaling pathways. The response of all these genes to IGFs incubation at two different times in day 4 cultured myocytes of gilthead sea bream was analyzed. Both IGFs increased the expression of IGF-I and IGFBP-5, but showed different effects on the receptors, with IGF-I suppressing the expression of both isoforms (IGF-IRa and IGF-IRb) and IGF-II up-regulating only IGF-IRb. Moreover, the protein levels of PCNA and target of rapamycin (TOR) increased after IGF-II incubation, although a decline in Myf5 and a rise in MHC gene expression was caused by IGF-I. Taken together, these results provide evidence for the importance of IGFs on controlling muscle development and growth in gilthead sea bream and suggest that each IGF may be preferentially acting through a specific IGF-IR. Moreover, the data support the hypothesis that IGF-II has a more important role during proliferation, whereas IGF-I seems to be relevant for the differentiation phase of myogenesis.

Quantity discrimination in parental fish: female convict cichlid discriminate fry shoals of different sizes

Numerical abilities have been found to be adaptive in different contexts, including mating, foraging, fighting assessment and antipredator strategies. In species with parental care, another potential advantage is the possibility to adjust parental behavior in relation to the numerosity of the progeny. The finding that many fish vary their parental investment in relation to brood size advocates the existence of a mechanism for appraising offspring number, an aspect that has never been directly investigated. Here we tested the ability of parental female convict cichlid (Amatitlania nigrofasciata) to discriminate between two fry groups differing in number by measuring time spent attempting to recover groups of fry experimentally displaced from the next. Females spent more time trying to recover the fry from larger groups when tested with contrasts 6 versus 12 (1:2) and 6 versus 9 fry (2:3); however, they showed no preference in the 6 versus 8 (3:4) contrast, suggesting that this task exceeds their discrimination capacity.

Distant Speaker Recognition: An Overview

Distant speaker recognition (DSR) system assumes the microphones are far away from the speaker’s mouth. Also, the position of microphones can vary. Furthermore, various challenges and limitation in terms of coloration, ambient noise and reverberation can bring some difficulties for recognition of the speaker. Although, applying speech enhancement techniques can attenuate speech distortion components, it may remove speaker-specific information and increase the processing time in real-time application. Currently, many efforts have been investigated to develop DSR for commercial viable systems. In this paper, state-of-the-art techniques in DSR such as robust feature extraction, feature normalization, robust speaker modeling, model compensation, dereverberation and score normalization are discussed to overcome the speech degradation components i.e., reverberation and ambient noise. Performance results on DSR show that whenever speaker to microphone distant increases, recognition rates decreases and equal error rate (EER) increases. Finally, the paper concludes that applying robust feature and robust speaker model varying lesser with distant, can improve the DSR performance.

The toxicological effect of Ruta graveolens extract in Siamese fighting fish: a behavioral and histopathological approach

The effects of pharmacological waste on aquatic ecosystems are increasingly highlighted in ecotoxicology research. Many of these products are designed for human physiology but owing to the conservative nature of vertebrate evolution they also tend to have effects on aquatic organisms and fishes in particular when they find their way into aquatic systems via wastewater effluent. One area of research has focused on reproductive control and the associated hormone treatments. Many of these hormones affect the reproductive physiology of fishes and may cause feminization of male reproductive traits. Alternative medicines have also been widely used particularly in traditional cultures but few of these alternative treatments have been assessed with respect to their potential impact on aquatic ecosystems. Rue (Ruta graveolens) has been used as a male contraceptive in traditional medicines but its effects on fish behavior and reproductive anatomy have yet to be established. Here we show that treating Siamese fighting fish, Betta splendens, with extract of rue has a significant effect on key aggressive/reproductive behaviors and the propensity to explore novel objects (boldness). In all cases the respective behaviors were reduced relative to controls and sham injected fish. Histological analysis of the testes revealed that rue exposure reduced the number of spermatozoa but increased the number of spermatocytes relative to controls.

Characterization data of gilthead sea bream (Sparus aurata) IGF-I receptors (IGF-IRa/Rb)

In this data article we describe the coding sequence of two IGF-IR paralogues (IGF-IRa and IGF-IRb) obtained from gilthead sea bream embryos. The putative protein architecture (domains and other important motifs) was determined and, amino acid sequences alignment and phylogenetic analysis of both receptors together with IGF-IR orthologues from different vertebrates was performed. Additionally, a semi-quantitative conventional PCR was done to analyze the mRNA expression of both receptors in different tissues of gilthead sea bream. These data will assist in further physiological studies in this species. In this sense, the expression of both receptors during ontogeny in muscle as well as the differential effects of IGF-I and IGF-II on their regulation during in vitro myogenesis has been recently studied (doi: 10.1016/j.ygcen.2015.11.011; [1]).

Lysine and Leucine Deficiencies Affect Myocytes Development and IGF Signaling in Gilthead Sea Bream (Sparus aurata)

Optimizing aquaculture production requires better knowledge of growth regulation and improvement in diet formulation. A great effort has been made to replace fish meal for plant protein sources in aquafeeds, making necessary the supplementation of such diets with crystalline amino acids (AA) to cover the nutritional requirements of each species. Lysine and Leucine are limiting essential AA in fish, and it has been demonstrated that supplementation with them improves growth in different species. However, the specific effects of AA deficiencies in myogenesis are completely unknown and have only been studied at the level of hepatic metabolism. It is well-known that the TOR pathway integrates the nutritional and hormonal signals to regulate protein synthesis and cell proliferation, to finally control muscle growth, a process also coordinated by the expression of myogenic regulatory factors (MRFs). This study aimed to provide new information on the impact of Lysine and Leucine deficiencies in gilthead sea bream cultured myocytes examining their development and the response of insulin-like growth factors (IGFs), MRFs, as well as key molecules involved in muscle growth regulation like TOR. Leucine deficiency did not cause significant differences in most of the molecules analyzed, whereas Lysine deficiency appeared crucial in IGFs regulation, decreasing significantly IGF-I, IGF-II and IGF-IRb mRNA levels. This treatment also down-regulated the gene expression of different MRFs, including Myf5, Myogenin and MyoD2. These changes were also corroborated by a significant decrease in proliferation and differentiation markers in the Lysine-deficient treatment. Moreover, both Lysine and Leucine limitation induced a significant down-regulation in FOXO3 gene expression, which deserves further investigation. We believe that these results will be relevant for the production of a species as appreciated for human consumption as it is gilthead sea bream and demonstrates the importance of an adequate level of Lysine in fishmeal diet formulation for optimum growth.

Fluoxetine inhibits aggressive behaviour during parental care in male fighting fish (Betta splendens, Regan)

The increasing presence of aquatic contaminants, such as the pharmaceutical fluoxetine, has raised concerns over potentially disrupting effects on several aspects of fish reproduction. However, the effects of fluoxetine on reproductive and paternal behavior in fish remain understudied, particularly at environmentally relevant concentrations. In the current study, we therefore tested the hypothesis that waterborne fluoxetine at an environmentally relevant concentration (540 ng/l), disrupts specific reproductive and paternal behaviors in male Siamese fighting fish at distinct reproductive phases. A pre-post test design was adopted to investigate specific behavioral responses at the individual fish level in response to male conspecific intruders at two different distances from the nest across four distinct reproductive phases (before bubblenest construction, following bubblenest construction, after spawning and after hatching of the larvae). In the control specimens, the measured behaviours were not different between the spawning times and among the interactions in either distance to nest at the different reproduction phases. Our results indicate that fluoxetine specifically disrupts characteristic paternal territorial aggression behaviour only after spawning and hatching of the larvae, while male behaviour in previous reproductive phases is unaffected by fluoxetine exposure. Results of comparison between males at 1st spawning and specimens exposed to fluoxetine at 2nd spawning showed that the first reaction of the nest-holding males to the intruders, duration of fin spreading, number of bites, and 90° turn, and the frequency of sweeps were different between the spawning times after spawning or hatching of embryos. However, interaction of spawning time and reproduction phase was significant on biting behaviour. These results demonstrate that fluoxetine exposure at environmental concentrations negatively affects territorial defense behaviour in fighting fish during parental care after larval hatching, which may have possible implications on reproductive success and population dynamics.

High levels of corticosterone, and gene expression of star, cyp17a2, hsd3b, cyp21, hsd11b2 during acute stress in common carp with interrenal hyperplasia

We investigated the acute stress response in a common carp strain (E5) with interrenal hyperplasia due to 17α-hydroxylase deficiency, and in an isogenic standard (STD) carp strain. Cortisol, corticosterone and the head kidney-somatic index were measured during and after a 3 h net confinement stress. Star, cyp17a2, hsd3b, cyp21, hsd11b2 mRNA levels were measured in head kidneys using real-time qPCR. The results show very high corticosterone levels and enlargement of the head kidney in E5 fish. This is the first report in a teleost fish showing a significant increase of corticosterone levels in response to stress due to interrenal hyperplasia. The high levels of corticosterone in E5 suggest that corticosterone is not converted to aldosterone in common carp. star and hsd3b mRNA levels were significantly higher in E5 compared to STD fish, while cyp17a2 levels were significantly lower in E5. In contrast to E5, star levels did not change during stress and recovery in STD, suggesting that the enzyme is regulated in a different manner in E5 and STD fish. In E5, the levels of cyp17a2 dropped below control values after 20 min stress. These findings strongly suggest that cyp17a2 is impaired at (post)-transcriptional level. As a consequence the accumulated precursor (pregnenolone) is not converted to cortisol, but to corticosterone. In contrast to STD, significant levels of cortisol could not be detected in E5. Finally, hsd11b2 mRNA levels were significantly lower in E5 compared to STD, and did not change during stress and recovery. These results support the idea that hsd11b2 is involved in the conversion of physiologically active cortisol to inactive cortisone, as reported earlier for STD carp. In conclusion our results show high levels of corticosterone in E5 and differences in star and mRNA levels of steroidogenic genes between E5 and STD carp during net confinement stress.

Transcript levels of five enzymes involved in cortisol synthesis and regulation during the stress response in common carp: relationship with cortisol

In this study the expression of five genes involved in cortisol synthesis and regulation in the head kidneys of common carp (Cyprinus carpio L.) has been investigated in response to 3h net confinement stress, followed by 22h recovery. Cortisol, glucose, lactate and free fatty acid levels were measured in blood plasma. StAR, P450c17a2, 3betaHSD, P450c21 and 11betaHSD2 transcript sequences were identified based on Cyprinidae homologs and quantified by real-time PCR. Results showed that the plasma cortisol level reached a peak at one hour post-stress (85-fold higher than in control) and quickly returned to normal after 4h recovery. 11betaHSD2 transcripts were for the first time identified in interrenals. Changes in cortisol levels during and after confinement were correlated in a time-delayed relationship with increase and decrease in mRNA levels of 11betaHSD2, respectively. These results suggest that cortisol may be involved in the control or activation of 11betaHSD2. StAR and P450c21 mRNA levels did not change during net confinement stress and recovery, but P450c17a2 levels were significantly increased 4 and 22h after recovery. Since plasma cortisol levels increased by 68-fold within 5min net confinement stress, it seems that transcriptional activation of this enzyme is not directly involved in acute cortisol production.