AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform.

The widespread proliferation of artificial intelligence (AI) and machine learning (ML) methods has a profound effect on the drug discovery process. However, many scientists are reluctant to utilize these powerful tools due to the steep learning curve typically associated with them. AIDDISON offers a convenient, secure, web-based platform for drug discovery, addressing the reluctance of scientists to adopt AI and ML methods due to the steep learning curve. By seamlessly integrating generative models, ADMET property predictions, searches in vast chemical spaces, and molecular docking, AIDDISON provides a sophisticated platform for modern drug discovery. It enables less computer-savvy scientists to utilize these powerful tools in their daily activities, as demonstrated by an example of identifying a valuable set of molecules for lead optimization. With AIDDISON, the benefits of AI/ML in drug discovery are accessible to all.

Revolutionizing medicine: Molecularly imprinted polymers as precision tools in cancer diagnosis and antibiotic detection.

Molecularly imprinted polymers (MIPs) are pivotal in medicine, mimicking biological receptors with enhanced specificity and affinity. Comprising templates, functional monomers, and cross-linkers, MIPs form stable three-dimensional polymer networks. Synthetic templates like glycan and aptamers improve efficiency, guiding the molecular imprinting process. Cross-linking determines MIPs' morphology and mechanical stability, with printable hydrogels offering biocompatibility and customizable properties, mimicking native extracellular matrix (ECM) microenvironments. Their versatility finds applications in tissue engineering, soft robotics, regenerative medicine, and wastewater treatment. In cancer research, MIPs excel in both detection and therapy. MIP-based detection systems exhibit superior sensitivity and selectivity for cancer biomarkers. They target nucleic acids, proteins, and exosomes, providing stability, sensitivity, and adaptability. In therapy, MIPs offer solutions to challenges like multidrug resistance, excelling in drug delivery, photodynamic therapy, photothermal therapy, and biological activity regulation. In microbiology, MIPs serve as adsorbents in solid-phase extraction (SPE), efficiently separating and enriching antibiotics during sample preparation. They contribute to bacterial identification, selectively capturing specific strains or species. MIPs aid in detecting antibiotic residues using fluorescent nanostructures and developing sensors for sulfadiazine detection in food samples. In summary, MIPs play a pivotal role in advancing medical technologies with enhanced sensitivity, selectivity, and versatility. Applications range from biomarker detection to innovative cancer therapies, making MIPs indispensable for the accurate determination and monitoring of diverse biological and environmental samples.

Low-dose ketamine improves animals' locomotor activity and decreases brain oxidative stress and inflammation in ammonia-induced neurotoxicity.

Ammonium ion (NH4 + ) is the major suspected molecule responsible for neurological complications of hepatic encephalopathy (HE). No specific pharmacological action for NH4 + -induced brain injury exists so far. Excitotoxicity is a well-known phenomenon in the brain of hyperammonemic cases. The hyperactivation of the N-Methyl- d-aspartate (NMDA) receptors by agents such as glutamate, an NH4 + metabolite, could cause excitotoxicity. Excitotoxicity is connected with events such as oxidative stress and neuroinflammation. Hence, utilizing NMDA receptor antagonists could prevent neurological complications of NH4 + neurotoxicity. In the current study, C57BL6/J mice received acetaminophen (APAP; 800 mg/kg, i.p) to induce HE. Hyperammonemic animals were treated with ketamine (0.25, 0.5, and 1 mg/kg, s.c) as an NMDA receptor antagonist. Animals' brain and plasma levels of NH4 + were dramatically high, and animals' locomotor activities were disturbed. Moreover, several markers of oxidative stress were significantly increased in the brain. A significant increase in brain tissue levels of TNF-α, IL-6, and IL-1ß was also detected in hyperammonemic animals. It was found that ketamine significantly normalized animals' locomotor activity, improved biomarkers of oxidative stress, and decreased proinflammatory cytokines. The effects of ketamine on oxidative stress biomarkers and inflammation seem to play a key role in its neuroprotective mechanisms in the current study.

The effect of maternal diabetes on the expression of gamma-aminobutyric acid and metabotropic glutamate receptors in male newborn rats' inferior colliculi.

OBJECTIVES: Few studies have examined the molecular alterations in the auditory pathway of infants of diabetic mothers, notwithstanding the fact that maternal diabetes may have an impact on the development of the neonatal peripheral and central nervous systems. Male newborn rats were studied to determine how maternal diabetes affected the expression of gamma-aminobutyric acid (GABAAα1 and GABAB1) and metabotropic glutamate (mGlu2) receptors in the inferior colliculus (IC) in this research. METHODS: Female rats were given a single intraperitoneal injection of streptozotocin (STZ) at a 65 mg/kg dose to develop a model of diabetic mothers. The study population was split into sham, diabetes without treatment, and diabetes with insulin groups. Their male neonatal rats were anesthetized on P0, P7, and P14 after mating and delivery. The receptors' distribution pattern was studied using immunohistochemistry (IHC). RESULTS: Pairwise comparison in the groups revealed that the GABA receptors (Aα1 and B1) were significantly downregulated in the diabetes without treatment group (p<0.001). Furthermore, pairwise comparison in the groups indicated significant mGlu2 upregulation in the diabetes without treatment group (p<0.001). Regarding the concentration of all receptors, there was no discernible distinction between the diabetes with insulin and sham groups. CONCLUSIONS: This investigation showed that the concentration of GABAAα1 and GABAB1 receptors decreased significantly over time, whereas the concentration of mGlu2 receptors increased significantly over time in male neonatal rats born to streptozotocin-induced diabetic mothers.

Effects of cigarette smoke condensate on reproduction in mice in vivo.

Smoking has dangerous and sometimes irreversible effects on various body tissues, including the reproductive system. We conducted this research to determine the in vivo effects of cigarette smoke condensate (CSC) on reproduction in mice. In this experimental in vivo study, 32 male and female NMRI mice were divided into four groups. The mice were injected with CSC (CSC-1R3F) for 28 days. The mice were mated 1 day after the last injection and observed daily for 1 week for the presence of a vaginal plug to track mating. We evaluated mating success rate, and sperm and oocyte quality, pregnancy outcome, childbearing status, and in vitro fertilization (IVF). The results showed a decrease in successful mating in female mice that received the CSC injections. CSC significantly influenced the number of offspring born to males. When the CSC was injected into male mice, there was a significant increase in the number of offspring compared with the group in which only the females received CSC injections. According to the results, there was a negative effect of CSC on morphological parameters in male and female mice. Also, successful IVF after exposure to CSC was significantly decreased in the female mice treated group. The results indicated that CSC significantly affected the number of offspring and fecundity success in females.

Synchrony-Division Neural Multiplexing: An Encoding Model.

Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensity itself can be respectively represented by the synchronous and asynchronous spikes of S1 neurons in rats. This evidence capitalized on the ability of an ensemble of homogeneous neurons to multiplex, a coding strategy that was referred to as synchrony-division multiplexing (SDM). Although neural multiplexing can be conceived by distinct functions of individual neurons in a heterogeneous neural ensemble, the extent to which nearly identical neurons in a homogeneous neural ensemble encode multiple features of a mixed stimulus remains unknown. Here, we present a computational framework to provide a system-level understanding on how an ensemble of homogeneous neurons enable SDM. First, we simulate SDM with an ensemble of homogeneous conductance-based model neurons receiving a mixed stimulus comprising slow and fast features. Using feature-estimation techniques, we show that both features of the stimulus can be inferred from the generated spikes. Second, we utilize linear nonlinear (LNL) cascade models and calculate temporal filters and static nonlinearities of differentially synchronized spikes. We demonstrate that these filters and nonlinearities are distinct for synchronous and asynchronous spikes. Finally, we develop an augmented LNL cascade model as an encoding model for the SDM by combining individual LNLs calculated for each type of spike. The augmented LNL model reveals that a homogeneous neural ensemble model can perform two different functions, namely, temporal- and rate-coding, simultaneously.

Direct Discriminative Decoder Models for Analysis of High-Dimensional Dynamical Neural Data.

With the accelerated development of neural recording technology over the past few decades, research in integrative neuroscience has become increasingly reliant on data analysis methods that are scalable to high-dimensional recordings and computationally tractable. Latent process models have shown promising results in estimating the dynamics of cognitive processes using individual models for each neuron's receptive field. However, scaling these models to work on high-dimensional neural recordings remains challenging. Not only is it impractical to build receptive field models for individual neurons of a large neural population, but most neural data analyses based on individual receptive field models discard the local history of neural activity, which has been shown to be critical in the accurate inference of the underlying cognitive processes. Here, we propose a novel, scalable latent process model that can directly estimate cognitive process dynamics without requiring precise receptive field models of individual neurons or brain nodes. We call this the direct discriminative decoder (DDD) model. The DDD model consists of (1) a discriminative process that characterizes the conditional distribution of the signal to be estimated, or state, as a function of both the current neural activity and its local history, and (2) a state transition model that characterizes the evolution of the state over a longer time period. While this modeling framework inherits advantages of existing latent process modeling methods, its computational cost is tractable. More important, the solution can incorporate any information from the history of neural activity at any timescale in computing the estimate of the state process. There are many choices in building the discriminative process, including deep neural networks or gaussian processes, which adds to the flexibility of the framework. We argue that these attributes of the proposed methodology, along with its applicability to different modalities of neural data, make it a powerful tool for high-dimensional neural data analysis. We also introduce an extension of these methods, called the discriminative-generative decoder (DGD). The DGD includes both discriminative and generative processes in characterizing observed data. As a result, we can combine physiological correlates like behavior with neural data to better estimate underlying cognitive processes. We illustrate the methods, including steps for inference and model identification, and demonstrate applications to multiple data analysis problems with high-dimensional neural recordings. The modeling results demonstrate the computational and modeling advantages of the DDD and DGD methods.

Effect of Helicobacter pylori eradication on metabolic profile: an international, multicenter, case-control study.

BACKGROUND: As a gram-negative and microaerophilic bacterium, Helicobacter pylori (HP) is the main cause of chronic gastritis. Therefore, considering the high prevalence of HP infection worldwide, as well as the increasing prevalence of metabolic disorders, the present study aimed to investigate the relationship between HP infection eradication and metabolic profile. METHODS: This prospective case-control study was performed on patients with HP infection whom referred to 7 medical centers in 3 countries (Iran, Egypt, and Vietnam) in 2020-2021. The metabolic profile of all of the participants evaluated before starting of treatment for HP eradication and 3 months after the treatment. Then changes of metabolic profile compared between those with successful HP eradication (group A) and subjects who failed to eradicate (group B). RESULTS: Overall, 199 patients, including 93 male (46.7%) with the mean age of 44.5 years (18-93 years) included. Based on response to treatment, the participants allocate into group A (those who respond to HP eradication): 164 cases (82.42%); or group B as those who failed to achieve eradication (35 cases, 17.58%). Racially 86.9% of participants were Caucasian and 89% diagnosed as non-ulcer dyspepsia (NUD). The most prevalent comorbidity include hypertension (11.5%) and hyperlipidemia (10%) which were more prevalent in group B (P = 0.002). Three months after therapy, average weight of participants among those who achieved eradication (group A) decreased from 73.1 to 71.4 kg (P = 0.01), but in comparison with group B, was non-significant (P = 0.171). The BMI of patients before and after treatment did not show any significant differences. The biochemical parameters of patients before and after treatment were not significantly different regardless of treatment success (P > 0.05). The levels of total cholesterol and VLDL cholesterol after treatment were not significantly different from baseline values in two groups. HDL and LDL cholesterol levels before and after treatment in the resistant group were significantly higher than the responding group. Average serum TG level decreased significantly after treatment in the group A (P < 0.0001), in contrast to the resistant group (P = 0.356). The liver transaminases (AST and ALT) before and after treatment were not significantly different between the two groups (P > 0.05). The results of logistic regression showed that the eradication of infection has no significant affect any of the metabolic profile parameters. CONCLUSION: HP infection treatment in individuals without significant metabolic disorders does not affect metabolic parameters up to 3 months after eradication. HP eradication among subjects with several comorbidities mandates eradication protocol intensification to avoid treatment failure.

Design and evaluation of novel analogs of 2-amino-4-boronobutanoic acid (ABBA) as inhibitors of human gamma-glutamyl transpeptidase.

Inhibitors of gamma-glutamyl transpeptidase (GGT1, aka gamma-glutamyl transferase) are needed for the treatment of cancer, cardiovascular illness and other diseases. Compounds that inhibit GGT1 have been evaluated in the clinic, but no inhibitor has successfully demonstrated specific and systemic GGT1 inhibition. All have severe side effects. L-2-amino-4­boronobutanoic acid (l-ABBA), a glutamate analog, is the most potent GGT1 inhibitor in vitro. In this study, we have solved the crystal structure of human GGT1 (hGGT1) with ABBA bound in the active site. The structure was interrogated to identify interactions between the enzyme and the inhibitor. Based on these data, a series of novel ABBA analogs were designed and synthesized. Their inhibitory activity against the hydrolysis and transpeptidation activities of hGGT1 were determined. The lead compounds were crystalized with hGGT1 and the structures solved. The kinetic data and structures of the complexes provide new insights into the critical role of protein structure dynamics in developing compounds for inhibition of hGGT1.

CROW-based Fano structures for all optical switching devices.

In this paper, an improved optical Fano switch based on coupled resonator optical waveguides (CROWs) is presented. The new topological design is employed to achieve steeper and highly asymmetric Fano resonances (FRs). Physically, in the proposed structures, due to the increase in the effective refractive index at the center of the CROW, a confined mode arises in the continuum background according to the variational theorem and leads to FR. The results show that in CROW-based Fano switches, the Fano spectrum is improved by tuning the number of nanocavities. The ratio between the slope ratio and linewidth shows an improvement of 55.25% from single to CROW5. As an important application of FR, an ultra-compact device with a CROW-based Fano structure is demonstrated. The results of the numerical finite difference time domain simulation agree well with the theoretical coupled mode theory.

Effect of cigarette smoke condensate on mouse embryo development and expression of pluripotency and apoptotic genes in vitro.

The aim of the present study was to investigate the effect of cigarette smoke condensate (CSC) on in vitro development of mouse embryos. In total 3000 NMRI mice 2PN embryos were divided into six groups (n = 500). The test group was exposed to 20, 40, 80, 160 or 320 µg/ml of CSC. In the control group, CSC was not added to the culture medium during the development of 2PN embryos. The effects of 20 and 80 µg/ml of CSC on genes involved in pluripotency and apoptosis, and also, the aryl hydrocarbon receptor gene was assessed in the blastocysts. Our results showed that CSC had an adverse effect on the viability of mouse embryos at the concentrations of 80, 160 and 320 µg/ml compared with the control group (P < 0.05). In contrast, it had positive effects on the viability of mouse embryos at the concentrations of 20 and 40 µg/ml compared with the control group (P < 0.05). The 20 and 80 µg/ml concentrations of CSC increased the expression of pluripotency, apoptotic, and aryl hydrocarbon receptor genes in the blastocyst embryo stage compared with the control group (P < 0.05). It can be concluded that concentrations higher than 40 µg/ml of CSC have an adverse effect on mouse embryo development in the preimplantation stages. Also, 20 and 80 µg/ml concentrations of CSC have a significant effect on the expression of pluripotency, apoptotic, and the aryl hydrocarbon receptor genes in the blastocyst embryo stage compared with the control group.

Glycine protects the male reproductive system against lead toxicity via alleviating oxidative stress, preventing sperm mitochondrial impairment, improving kinematics of sperm, and blunting the downregulation of enzymes involved in the steroidogenesis.

Lead (Pb) is a highly toxic heavy metal widely dispersed in the environment because of human industrial activities. Many studies revealed that Pb could adversely affect several organs, including the male reproductive system. Pb-induced reproductive toxicity could lead to infertility. Thus, finding safe and clinically applicable protective agents against this complication is important. It has been found that oxidative stress plays a fundamental role in the pathogenesis of Pb-induced reprotoxicity. Glycine is the simplest amino acid with a wide range of pharmacological activities. It has been found that glycine could attenuate oxidative stress and mitochondrial impairment in various experimental models. The current study was designed to evaluate the role of glycine in Pb-induced reproductive toxicity in male mice. Male BALB/c mice received Pb (20 mg/kg/day; gavage; 35 consecutive days) and treated with glycine (250 and 500 mg/kg/day; gavage; 35 consecutive days). Then, reproductive system weight indices, biomarkers of oxidative stress in the testis and isolated sperm, sperm kinetic, sperm mitochondrial indices, and testis histopathological alterations were monitored. A significant change in testis, epididymis, and Vas deferens weight was evident in Pb-treated animals. Markers of oxidative stress were also significantly increased in the testis and isolated sperm of the Pb-treated group. A significant disruption in sperm kinetic was also evident when mice received Pb. Moreover, Pb exposure caused significant deterioration in sperm mitochondrial indices. Tubular injury, tubular desquamation, and decreased spermatogenic index were histopathological alterations detected in Pb-treated mice. It was found that glycine significantly blunted oxidative stress markers in testis and sperm, improved sperm mitochondrial parameters, causing considerable higher velocity-related indices (VSL, VCL, and VAP) and percentages of progressively motile sperm, and decreased testis histopathological changes in Pb-exposed animals. These data suggest glycine as a potential protective agent against Pb-induced reproductive toxicity. The effects of glycine on oxidative stress markers and mitochondrial function play a key role in its protective mechanism.

A Mechanism-Based Targeted Screen To Identify Epstein-Barr Virus-Directed Antiviral Agents.

Epstein-Barr virus (EBV) is one of nine human herpesviruses that persist latently to establish permanent residence in their hosts. Periodic activation into the lytic/replicative phase allows such viruses to propagate and spread, but can also cause disease in the host. This lytic phase is also essential for EBV to cause infectious mononucleosis and cancers, including B lymphocyte-derived Burkitt lymphoma and immunocompromise-associated lymphoproliferative diseases/lymphomas as well as epithelial cell-derived nasopharyngeal cell carcinoma. In the absence of anti-EBV agents, however, therapeutic options for EBV-related diseases are limited. In earlier work, we discovered that through the activities of the viral protein kinase conserved across herpesviruses and two cellular proteins, ATM and KAP1, a lytic cycle amplification loop is established, and disruption of this loop disables the EBV lytic cascade. We therefore devised a high-throughput screening assay, screened a small-molecule-compound library, and identified 17 candidates that impair the release of lytically replicated EBV. The identified compounds will (i) serve as lead compounds or may be modified to inhibit EBV and potentially other herpesviruses, and (ii) be developed into anticancer agents, as functions of KAP1 and ATM are tightly linked to cancer. Importantly, our screening strategy may also be used to screen additional compound libraries for antiherpesviral and anticancer drugs.IMPORTANCE Epstein-Barr virus, which is nearly ubiquitous in humans, is causal to infectious mononucleosis, chronic active EBV infection, and lymphoid and epithelial cancers. However, EBV-specific antiviral agents are not yet available. To aid in the identification of compounds that may be developed as antivirals, we pursued a mechanism-based approach. Since many of these diseases rely on EBV's lytic phase, we developed a high-throughput assay that is able to measure a key step that is essential for successful completion of EBV's lytic cascade. We used this assay to screen a library of small-molecule compounds and identified inhibitors that may be pursued for their anti-EBV and possibly even antiherpesviral potential, as this key mechanism appears to be common to several human herpesviruses. Given the prominent role of this mechanism in both herpesvirus biology and cancer, our screening assay may be used as a platform to identify both antiherpesviral and anticancer drugs.

The risk factors associated with COVID-19-Related death among patients with end-stage renal disease.

BACKGROUND: The extent to which patients with End-stage renal disease (ESRD) are at a higher risk of COVID-19-related death is still unclear. Therefore, the aim of this study was to identify the ESRD patients at increased risk of COVID-19 -related death and its associated factors. METHODS: This retrospective cohort study was conducted on 74 patients with ESRD and 446 patients without ESRD hospitalized for COVID-19 in Alborz province, Iran, from Feb 20 2020 to Apr 26 2020. Data on demographic factors, medical history, Covid-19- related symptoms, and blood tests were obtained from the medical records of patients with confirmed COVID-19. We fitted univariable and multivariable Cox regression models to assess the association of underlying condition ESRD with the COVID-19 in-hospital mortality. Results were presented as crude and adjusted Hazard Ratios (HRs) and 95% confidence intervals (CIs). In the ESRD subgroup, demographic factors, medical history, symptoms, and blood parameters on the admission of survivors were compared with non-survivors to identify factors that might predict a high risk of mortality. RESULTS: COVID-19 patients with ESRD had in-hospital mortality of 37.8% compared to 11.9% for those without ESRD (P value < 0.001). After adjusting for confounding factors, age, sex, and comorbidities, ESRD patients were more likely to experience in-hospital mortality compared to non-ESRD patients (Adjusted HR (95% CI): 2.59 (1.55-4.32)). The Log-rank test revealed that there was a significant difference between the ESRD and non-ESRD groups in terms of the survival distribution (χ2 (1) = 21.18, P-value < 0.001). In the ESRD subgroup, compared to survivors, non-survivors were older, and more likely to present with lack of consciousness or O2 saturation less than 93%; they also had lower lymphocyte but higher neutrophil counts and AST concentration at the presentation (all p -values < 0.05). CONCLUSIONS: Our findings suggested that the presence of ESRD would be regarded as an important risk factor for mortality in COVID-19 patients, especially in those who are older than age 65 years and presented with a lack of consciousness or O2 saturation less than 93%.

The effect of education based on PEN-3 cultural model on students' menstrual health behaviors: a mixed method study.

Menstruation is a natural process in girls, but sometimes it is accompanied by beliefs and behaviors with cultural roots that result in poor health consequences; this study aimed to consider perceptions of individual, families and community to current cultural beliefs, and to determine the effect of education based on the PEN-3 cultural model on students' menstrual health behaviors in Iran. Study had a mixed method design. In the qualitative phase, data were collected from students, their mothers and teachers through focused group discussion and in-depth interviews. In the quantitative phase, training was done in four 2-h sessions for intervention group. The data were collected immediately and 2 months after the training by a questionnaire and they were analyzed by Friedman and Wilcoxon non-parametric tests. Training was effective on all of the model structures and significantly increased mean score of the health behavior after training and 2 months later by 8.74 and 13.86, respectively, in intervention group (P<0.05). The perception and behavior of the others and access to sanitary services and products, especially cultural factors affect girls'' menstrual health behaviors, therefore, it is necessary to design the health plans regarding each of these factors, and the cultural context of each community.

Circuit level implementation of photonic crystal devices.

Different types of photonic crystal components have been modeled by approximate RLC circuits. The proposed lumped circuits exploit the analogy of photonic crystal elements and RLC circuits. They are either coupled to each other or inserted like lumped circuits to imitate wave propagation within the photonic devices. Different examples such as side-coupled waveguide-cavity systems, side-coupled cavity-cavity systems, and improved structures are investigated for evaluating the theory. It is shown that the proposed circuits are exact enough to be substituted into the complicated calculations of numerical methods. In addition, the presented practical and straightforward procedure can be employed for flexible and efficient design. The results are verified using the finite-difference time-domain numerical simulations and coupled-mode theory for various devices.

A Novel Method for Sleep-Stage Classification Based on Sonification of Sleep Electroencephalogram Signals Using Wavelet Transform and Recurrent Neural Network.

INTRODUCTION: Visual sleep-stage scoring is a time-consuming technique that cannot extract the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel method for sleep-stage differentiation based on sonification of sleep-EEG signals using wavelet transform and recurrent neural network (RNN). METHODS: Two RNNs were designed and trained separately based on a database of classical guitar pieces and Kurdish tanbur Makams using a long short-term memory model. Moreover, discrete wavelet transform and wavelet packet decomposition were used to determine the association between the EEG signals and musical pitches. Continuous wavelet transform was applied to extract musical beat-based features from the EEG. Then, the pretrained RNN was used to generate music. To test the proposed model, 11 sleep EEGs were mapped onto the guitar and tanbur frequency intervals and presented to the pretrained RNN. Next, the generated music was randomly presented to 2 neurologists. RESULTS: The proposed model classified the sleep stages with an accuracy of >81% for tanbur and more than 93% for guitar musical pieces. The inter-rater reliability measured by Cohen's kappa coefficient (κ) revealed good reliability for both tanbur (κ = 0.64, p < 0.001) and guitar musical pieces (κ = 0.85, p < 0.001). CONCLUSION: The present EEG sonification method leads to valid sleep staging by clinicians. The method could be used on various EEG databases for classification, differentiation, diagnosis, and treatment purposes. Real-time EEG sonification can be used as a feedback tool for replanning of neurophysiological functions for the management of many neurological and psychiatric disorders in the future.

Circulating levels of oxidized low-density lipoprotein in patients with obstructive sleep apnea: a systematic review and meta-analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is associated with an increased risk of developing atherosclerotic cardiovascular disease (ASCVD). Patients with OSA have increased levels of oxidative stress and several studies have shown higher levels of oxidative stress markers. Oxidized-LDL (Ox-LDL) is an important risk factor for ASCVD and a number of studies have measured its levels in patients with OSA, though results from these studies are conflicting. This meta-analysis aimed to reassess circulating levels of Ox-LDL in patients with OSA in comparison with controls. METHODS: Studies evaluating Ox-LDL levels in patients with OSA and controls were explored in databases of PubMed, EMBASE, Scopus, and Web of Science. Two authors independently performed the search from January 1990 to February 2019. Two authors independently screened the studies according to title, abstract, and full text. In addition, the Newcastle-Ottawa Quality Assessment Scale was utilized to evaluate the quality of the studies. The impact of OSA on Ox-LDL levels was determined using the random effects model. RESULTS: Of 195 articles retrieved, 98 were duplicates, 49 were excluded by title, 20 excluded by abstract, and 22 by full texts. Six eligible studies were included in the meta-analysis. Pooled analysis demonstrated that Ox-LDL increased in patients with OSA compared with controls. In addition, subgroup analysis revealed that studies matching age or BMI between OSA patients and controls showed no significant difference between patients with OSA and healthy controls, while unmatched studies had higher levels of Ox-LDL in patients with OSA in comparison with controls. CONCLUSION: This study demonstrated higher circulating concentrations of Ox-LDL in patients with OSA. However, no significant difference was found in studies in which patients and controls were matched for age and BMI, suggesting the involvement of these two confounding factors as a cause for elevated concentrations of circulating Ox-LDL in patients with OSA.

Serum testosterone/cortisol ratio in people with obstructive sleep apnea.

OBJECTIVES: Obstructive sleep apnea (OSA) is a major health problem that has been associated with endocrine dysfunction in the hypothalamic-pituitary-gonadal (HPG) and hypothalamic-pituitary-adrenal (HPA) axes. This study investigated cortisol, testosterone, and the testosterone/cortisol ratio in patients with OSA compared to normal sleepers. METHODS: Thirty-nine OSA patients diagnosed by overnight polysomnography (PSG) were divided into three groups, including ten mild OSA patients, 16 patients with moderate OSA, and 13 patients with severe OSA according to the apnea-hypopnea index (AHI). In addition, 13 normal sleepers with normal PSG findings were recruited as the control group. Serum levels of cortisol, testosterone, and sex hormone-binding globulin (SHBG) were measured using enzyme-linked immunosorbent assay (ELISA). RESULTS: There were no significant differences between the normal sleepers and the three subtypes of OSA in terms of total and free testosterone levels (P > .1). The results showed significantly higher levels of cortisol in the severe OSA group compared to the normal sleepers and the two other subtypes of OSA (P < .01). In addition, the testosterone/cortisol (T/C) ratio was significantly lower among the severe OSA compared to the moderate OSA patients (P = .01). A significant correlation was observed between minimal SpO2 and AHI (r=-0.69, P < .01), cortisol and AHI (r = .47, P < .01) and cortisol and minimal SpO2 (r = -.26, P = .06). CONCLUSION: According to the findings, OSA is linked to HPA axis activity in severe OSA patients but not among the mild and moderate subtypes of the disorder.

A Time-Varying Information Measure for Tracking Dynamics of Neural Codes in a Neural Ensemble.

The amount of information that differentially correlated spikes in a neural ensemble carry is not the same; the information of different types of spikes is associated with different features of the stimulus. By calculating a neural ensemble's information in response to a mixed stimulus comprising slow and fast signals, we show that the entropy of synchronous and asynchronous spikes are different, and their probability distributions are distinctively separable. We further show that these spikes carry a different amount of information. We propose a time-varying entropy (TVE) measure to track the dynamics of a neural code in an ensemble of neurons at each time bin. By applying the TVE to a multiplexed code, we show that synchronous and asynchronous spikes carry information in different time scales. Finally, a decoder based on the Kalman filtering approach is developed to reconstruct the stimulus from the spikes. We demonstrate that slow and fast features of the stimulus can be entirely reconstructed when this decoder is applied to asynchronous and synchronous spikes, respectively. The significance of this work is that the TVE can identify different types of information (for example, corresponding to synchronous and asynchronous spikes) that might simultaneously exist in a neural code.