An evidence for lack of pseudoneglect in patients with schizophrenia:An ERP study

Studies have reported an altered expression of pseudoneglect in patients with schizophrenia, but no study has examined pseudoneglect in schizophrenia at the neural level. We investigated pseudoneglect using the visual P3 event-related potential and the mental number bisection (MNB) task in 21 patients and 25 controls. Using an oddball task, participants were asked to discriminate an infrequent (‘one’ or ‘nine’) from a frequent written number (‘five’). The P3 ERP components were delayed to the targets on the right of the MNL (‘nine’) compared to the targets on the left (‘one’) in controls. The effect of number magnitude on the P3 latency was not observed in the patients. In MNB task, the patients did not show the normal leftward bias observed in healthy individuals. Our findings indicate a lack of pseudoneglect and the presence of an anomalous brain asymmetry in schizophreni

Numerical distance effect in patients with schizophrenia

There is growing evidence showing that mental representation of numbers is impaired in patients with schizophrenia. Yet, no study has examined the distance effect in the patients. We assessed the distance effect using two number size comparison tasks, with different number references (5 and 7) in 23 patients and 28 healthy individuals. Response times and error rates significantly increased when the distances between the centered references and the targets decreased in both groups. However, patients responded significantly slower and had more error rates compared to controls. Our finding indicates distance effect in patients is similar to the controls, indicating an automatic numerical processing is preserved in patients with schizophrenia

Associations Between Components of Metabolic Syndrome and Cognition in Patients With Schizophrenia

The metabolic syndrome and cognitive dysfunctions are common in patients with schizophrenia, yet there is no general consensus concerning the effects of the components of the metabolic syndrome on various cognitive domains. The goal of this study was to investigate the relationship between components of the metabolic syndrome and cognition in patients with schizophrenia. Components of the metabolic syndrome and neurocognitive functioning were assessed in 68 patients with schizophrenia. The Brief Assessment of Cognition in Schizophrenia (BACS) was used to assess neurocognition. Hyperglycemia and hypertension were the only components of the metabolic syndrome found to be associated with cognitive functioning. Patients with schizophrenia who were hypertensive showed cognitive impairments in 2 domains, with a negative association found between hypertension and verbal memory (P=0.047) and verbal fluency (P=0.007). Hyperglycemia was associated with higher scores on verbal memory (P=0.01) and verbal fluency (P<0.001). It appears that medical treatment of certain components of the metabolic syndrome could affect cognitive performance in patients with schizophrenia

Classroom management for instruction of unmotivated students

Introduction: Motivation is essential for increasing the quality of nursing education. This study aims to review published evidence on management of classrooms for unmotivated students. Methods: An integrative review of evidence based on Broom protocol was conducted in three stages; literature search, data evaluation and data analysis. Databases of SID, Magiran, IranMedex, Irandoc, MEDLINE, EMBASE, EBSCO and CINAHL were all searched. &nbsp;The searched key words were classroom management, unmotivated, students, management style in classroom and instructional skill. Of 1464 full texts and abstracts identified 43 articles were chosen based on inclusion criteria. For data analysis, data extracted from primary sources, after comparing one by one, data were integrated, ordered, categorized and summarized. Results: there are variety of challenges and solutions for classroom management to boost students' motivation, which categorized in three themes: use of modern teaching methods, improve the learning environment and improve interaction and communication. Conclusion: A new instructional strategy should be used for the improvement of classroom management to motivate unmotivated students

Alpha-pinene preserves human dopaminergic SH-SY5Y cells against 6-hydroxydopamine-induced toxicity through its antioxidant and antiapoptotic properties and gamma-aminobutyric acid type A signaling

Background: Parkinson's disease (PD) is one of the most common neurodegenerative disorders which is characterized by progressive loss of dopaminergic neurons in substantia nigra. Therefore, drugs or natural agents that have suppressive effects on dopaminergic cell death may reduce the progression of such disorder. Here, the effect of natural product alpha-pinene was evaluated on 6-hydroxydopamine (6-OHDA)-induced damage in SH-SY5Y human dopaminergic cell line as an in vitro model of PD. Methods: The cells were incubated by 150 μM 6-OHDA alone or accompanied with different concentration of alpha-pinene (10–180 μM). Cell viability was determined by MTT assay. The amount of intracellular reactive oxygen species (ROS) and mitochondrial membrane potential were measured by fluorescence spectrophotometry. In addition, the components of molecular apoptotic pathway such as cytochrome c release, Bax, Bcl-2, and caspase-3 levels were measured by immunoblotting. Gamma-aminobutyric acid (GABA) antagonist, bicuculline, was used to find the role of GABA Type A (GABAA) receptors in the signaling of alpha-pinene. Results: The data showed that 6-OHDA produced cell damage, decreased mitochondrial membrane potential, increased intracellular ROS and cytochrome c release, as well as increased Bax/Bcl-2 ratio and caspase-3 activity. Moreover, alpha-pinene (70 μM) significantly inhibited cellular and molecular abnormalities. Blockage of GABAA receptor significantly suppressed the protective effect of alpha-pinene. Conclusion: The results suggest that alpha-pinene has a protective effect against dopaminergic toxicity, and at least in part, its antioxidant and antiapoptotic properties are probably involved in such protection

Proactive and reactive inhibitory control are differently affected by video game addiction: An event‐related potential study

Abstract Introduction Video game addiction (VGA) is associated with physical and mental disorders, one of which is problem in executive function, particularly inhibitory control. The present study aimed to investigate reactive and proactive inhibitory controls by event‐related potential (ERP). Methods Thirty video game (action video games)‐addicted subjects and 30 matched healthy controls participated in the study, who were tested by the selective stop‐signal task. Results The main results revealed that the VGA group had significantly more problems in preparatory processes and proactive stop trials, showing that VGA has a negative effect on proactive inhibition. Conclusion Finding the problem in proactive inhibitory control might be helpful in developing new treatments and rehabilitation methods in these fields

EEG‐biomarker theta/beta ratio and attentional quotients in adults who stutter: An electrophysiological and behavioral study

Abstract Introduction There is increasing evidence that connects developmental stuttering to attention. However, findings have represented contradiction. Therefore, this study was conducted to investigate the possible relationship between stuttering and attention in resting and undertask conditions. Methods In a cross‐sectional study, 26 right‐handed AWS (adults who stutter) and 25 matched fluent speakers were enrolled. Demographic data were collected, and the Beck anxiety inventory (BAI) was filled out for all participants. Then, QEEG was conducted, followed by IVA2. CPT test for all subjects. Finally, data were analyzed using SPSS software version 16. Results AWS indicated significantly weaker auditory focus attention in the task (p = .02) than the control group, while a similar resting‐state EEG marker of attention was found between groups (p > .05). Moreover, attention was not correlated between the two conditions (p > .05). Conclusion The EEG marker of attention did not necessarily designate the attentional performance of AWS under the task. Furthermore, attentional skills could be considered in the assessment and therapeutic programs of at least some groups of AWS

The role of basolateral amygdala orexin 1 receptors on the modulation of pain and psychosocial deficits in nitroglycerin-induced migraine model in adult male rats

Background: Migraine headaches have been associated with sensory hyperactivity and anomalies in social/emotional responses. The main objective of this study was to evaluate the potential involvement of orexin 1 receptors (Orx1R) within the basolateral amygdala (BLA) in the modulation of pain and psychosocial dysfunction in a nitroglycerin (NTG)-induced rat model of migraine. Methods: Adult male Wistar rats were injected with NTG (5 mg/kg, intraperitoneal) every second day over nine days to induce migraine. The experiments were done in the following six groups (6 rats per group): untreated control, NTG, NTG plus vehicle, and NTG groups that were post-treated with intra-BLA microinjection of Orx1R antagonist SB-334867 (10, 20, and 40 nM). Thermal hyperalgesia was assessed using the hot plate and tail-flick tests. Moreover, the elevated plus maze (EPM) and open field (OF) tests were used to assess anxiety-like behaviors. The animals' sociability was evaluated using the three-chamber social task. The NTG-induced photophobia was assessed using a light-dark box. Results: We observed no change in NTG-induced thermal hyperalgesia following administration of SB-334867 (10, 20, and 40 nM). However, SB-334867 (20 and 40 nM) aggravated the NTG-induced anxiogenic responses in both the EPM and OF tasks. The NTG-induced social impairment was overpowered by SB-334867 at all doses. Time spent in the dark chamber of light-dark box was significantly increased in rats treated with SB-334867 (20 and 40 nM/rat). Conclusions: The findings suggest a role for Orx1R within the BLA in control comorbid affective complaints with migraine in rats

Artificial Intelligence in Cancer Care: From Diagnosis to Prevention and Beyond

&lt;p&gt;Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care, encompassing various aspects from diagnosis to prevention and beyond. With its ability to analyze vast amounts of data, recognize patterns, and make accurate predictions, AI has emerged as a powerful tool in the fight against cancer. This article explores the applications of AI in cancer care, highlighting its role in diagnosis, treatment decision-making, prevention, and ongoing management. In the realm of cancer diagnosis, AI has demonstrated remarkable potential. By processing patient data, including medical imaging, pathology reports, and genetic profiles, AI algorithms can assist in early detection and accurate diagnosis. Image recognition algorithms can analyze radiological images, such as mammograms or CT scans, to detect subtle abnormalities and assist radiologists in identifying potential tumors. AI can also aid pathologists in analyzing tissue samples, leading to more precise and efficient cancer diagnoses. AI's impact extends beyond diagnosis into treatment decision-making. The integration of AI algorithms with clinical data allows for personalized treatment approaches. By analyzing patient characteristics, disease stage, genetic markers, and treatment outcomes, AI can provide valuable insights to oncologists, aiding in treatment planning and predicting response to specific therapies. This can lead to more targeted and effective treatment strategies, improving patient outcomes and reducing unnecessary treatments and side effects. Furthermore, AI plays a crucial role in cancer prevention. By analyzing genetic and environmental risk factors, AI algorithms can identify individuals at higher risk of developing certain cancers. This enables targeted screening programs and early interventions, allowing for timely detection and prevention of cancer. Additionally, AI can analyze population-level data to identify trends and patterns, contributing to the development of public health strategies for cancer prevention and control. AI's involvement in cancer care goes beyond diagnosis and treatment, encompassing ongoing management and survivorship. AI-powered systems can monitor treatment response, track disease progression, and detect recurrence at an early stage. By continuously analyzing patient data, including imaging, laboratory results, and clinical assessments, AI algorithms can provide real-time insights, facilitating timely interventions and adjustments to treatment plans. This proactive approach to disease management improves patient outcomes and enhances quality of life.&lt;/p&gt