Neural Correlates of Gain Control in Drosophila and Humans

Previous research has shown that visual sensitivity in human epilepsy patients is abnormal – characterized by increased responses at high contrast levels. These abnormalities have been linked to changes in neuronal gain control. Using animal models to study these changes is a useful approach. In this thesis, we used a steady-state visually evoked potential (SSVEP) technique similar to that used in humans to study photoreceptor-level and neuronal gain control in wild type (w-) Drosophila across a range of ages. We then compared these responses to those obtained from Drosophila carrying the kcc potassium channel mutation that renders young flies susceptible to light and shock-induced seizures. By taking into account the age and temperature dependence of the mutant (kccDHS1) flies, we were able to identify increased neural activity that recovers to the normal profile as they get older. We also found that these kccDHS1 flies are hypersensitive to light, particularly when young. These two findings are consistent with the fact that the level of the KCC protein increases with age. In addition, we found that kccDHS1 flies generate high frequency oscillations in their ERGs in response (50 – 100 Hz) to abrupt light onsets and offsets – a phenomenon that might be linked to abnormal changes in the gain control of neuronal feedback circuits. Studying visual abnormalities in Drosophila can reveal important information but eventually we need to link any visual abnormalities observed in animal models to humans. We therefore, attempted to measure subtle changes in gain control in humans due to adaptation, and at the same time make use of the human mental ability to measure another measure of gain control, attention, using an fMRI technique. Although our data did not show any interaction between adaptation and attention, it suggests that attention in early visual pathways largely affects the level of suppression in non-stimulated regions around the adaptor rather than responses to the probe itself. This is a manipulation that links to our work on adaptation in Drosophila in Chapter 6. Overall, the results presented in this thesis showed that fly models of epilepsy can be useful for studying changes in visual gain control, and showed that this work might be extended to humans

Thyroid disorders, epidemiology and outcome among patients in South Western region: Southern Saudi Arabia

Background: Thyroid gland may have a group of a medical condition that affects its main function. The thyroid gland is located at the front of the neck and produces thyroid hormones. The released hormones go through the blood to many body organs for regulating their function, meaning that it is an endocrine organ. These hormones normally act in the body to regulate energy use, infant development, and childhood development. The study aimed to assess the epidemiology of thyroid disorders among cases in the south-western region, Saudi Arabia, and to assess the reporting quality for these cases data.Methods: A retrospective record based descriptive approach was used through reviewing medical records of all cases that were admitted and diagnosed as thyroid related disorders for different indications in the main hospital (king Khalid Hospital) during the period from January 2018 to January 2020. Data extracted throng pre-structured questionnaire including patient's bio-clinical data, preoperative radiological and laboratory investigations. Also, laryngoscope pre and post operatively was reviewed to record findings.Results: The study included 405 cases with thyroid disorders whose ages ranged from 15 to 71 years old with a mean age of 30.5±10.6 years. Females were 82.7% of the included cases, and 83.8% were Saudi. Thyroid related symptoms were recorded for 1-2 years among 58.1% of the cases and for more than 5 years among 15.8%. Thyroid enlargement was recorded for 73.1% of the cases. The multinodular enlargement was recorded for 53.5% of the cases followed with diffuse thyroid enlargement (27.3%). Regarding the type of surgery undergone, total thyroidectomy was the most recorded followed with lobectomy.Conclusions: The study revealed that the majority of the cases were females at middle age presented with benign lesions with Euthyroid status. The most important conclusion was the significant remarkable underreporting of the different clinical data for the cases with many missing items

Oral semaglutide adequate glycaemia control with safe cardiovascular ‎profile

BackgroundType 2 diabetes is a chronic and progressive disease that ‎associated with series complication such as major adverse ‎cardiovascular events. Adequate glycaemic control proven ‎to reduce this risk. Orally administered semaglutide ‎promising medication in managing patient with type 2 ‎diabetes.‎AimsTo assess the cardiovascular safety and efficacy of semaglutide, a recently approved glucagon-like peptide 1 receptor agonist (GLP-1 RA) for type 2 diabetes.Methods Pub Med, ‎Google Scholar, and EBSCO ‎ databases were ‎systematically search for relevant articles. The terms‎ diabetes‎, Glucagon-like peptide, semaglutide‎ were used. Out of hundred twenty-two records, only ‎four fulfilled ‎the inclusion criteria.Results Four placebo-controlled studies with oral semaglutide ‎were included. Single study concern about the cardiovascular safety of oral semaglutide ‎and showed that, ‎compared with placebo, semaglutide ‎ was not associated ‎with increased in the cardiovascular events. On the other ‎hand, the remaining trials shown that, semaglutide ‎ can ‎effectively control the blood glucose as evident by ‎reduction in HA1c.ConclusionOral semaglutide can effectively and safely lower blood glucose without increase in the major adverse ‎cardiovascular events‎‎ (MACE).

Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis.

OBJECTIVES: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores ≥10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 ≥10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. STUDY DESIGN AND SETTING: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. RESULTS: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 ≥10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 ≥10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 ≥14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 ≥14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). CONCLUSION: PHQ-9 ≥10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies

Knowledge of the residents at King Abdul-Aziz University Hospital (KAAUH) about palliative care

Background: Palliative care is a rapidly growing subspecialty that aims at improving the quality of life and relieving suffering associated with life threatening disease. Despite its rapid growth and huge demand, the knowledge of health care professionals on palliative care remains inadequate. Objective: This study aims to determine the knowledge of residents at King Abdul-Aziz University Hospital (KAAUH) on palliative care. Materials and Methods: Through a cross-sectional design, all residents in the hospital were invited to complete a two-part self-administered questionnaire in June 2010. The first part of the questionnaire included variables describing the socio-demographic characteristics and educational background, and the second part developed by palliative care education initiative at Dalhousie University in Canada in 2000 had 25 items on the knowledge of palliative care. Results : Of the 80 residents 65 (81%) responded, the overwhelming majority of whom were Saudis (92.3%) with an equal representation of males and females. The mean age of the participants was 29.1 ± 2.4 years. Less than one-third (29.2%) indicated that they had previous didactic education on palliative care. The percentage of right answers on items reflecting knowledge on palliative care accounted for 29.9% ± 9.9%. No statistically significant difference was found in the level of knowledge among the residents according to their demographics or graduation and training characteristics. Conclusion: Resident physicians enrolled in postgraduate programs have suboptimal knowledge of basic palliative care. Substantial efforts should be made to incorporate a palliative care module into the theoretical and practical training of medical students and resident physicians

Prevalence of malnutrition and associated factors among hospitalized elderly patients in King Abdulaziz University Hospital, Jeddah, Saudi Arabia

Abstract Background Malnutrition is a nutritional disorder that adversely affects the body from a functional or clinical perspective. It is very often observed in the elderly population. This study aimed to estimate the prevalence of malnutrition among hospitalized elderly patients and its associated factors and outcomes in terms of length of stay and mortality in King Abdulaziz University Hospital, Jeddah, Saudi Arabia. Methods In a cross-sectional study, we evaluated the nutritional status of hospitalized elderly patients using the most recent version of the short form of Mini Nutritional Assessment (MNA-SF). Results A total of 248 hospitalized patients were included (70.0 ± 7.7 years; 60% female). According to the MNA-SF, a total of 76.6% patients were either malnourished or at risk of malnutrition. Malnourished patients had significantly lower levels of serum albumin (28.2 ± 7.7), hemoglobin (10.5 ± 1.8), and lymphocyte (1.7 ± 0.91). They had increased tendency to stay in the hospital for longer durations (IQR, 5-11 days; median = 7 days) and had a mortality rate of 6.9%. Conclusion Malnutrition was highly prevalent among hospitalized elderly and was associated with increased length of stay and mortality

Older Adults Get Lost in Virtual Reality: Visuospatial Disorder Detection in Dementia Using a Voting Approach Based on Machine Learning Algorithms

As the age of an individual progresses, they are prone to more diseases; dementia is one of these age-related diseases. Regarding the detection of dementia, traditional cognitive testing is currently one of the most accurate tests. Nevertheless, it has many disadvantages, e.g., it does not measure the extent of the brain damage and does not take the patient’s intelligence into consideration. In addition, traditional assessment does not measure dementia under real-world conditions and in daily tasks. It is therefore advisable to investigate the newest, more powerful applications that combine cognitive techniques with computerized techniques. Virtual reality worlds are one example, and allow patients to immerse themselves in a controlled environment. This study created the Medical Visuospatial Dementia Test (referred to as the “MVD Test”) as a non-invasive, semi-immersive, and cognitive computerized test. It uses a 3D virtual environment platform based on medical tasks combined with AI algorithms. The objective is to evaluate two cognitive domains: visuospatial assessment and memory assessment. Using multiple machine learning algorithms (MLAs), based on different voting approaches, a 3D system classifies patients into three classes: patients with normal cognition, patients with mild cognitive impairment (MCI), and patients with severe cognitive impairment (dementia). The model with the highest performance was derived from voting approach named Ensemble Vote, where accuracy was 97.22%. Cross-validation accuracy of Extra Tree and Random Forest classifiers, which was greater than 99%, indicated a greater discriminate capacity than that of other classes

Smart Health System to Detect Dementia Disorders Using Virtual Reality

Smart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic surgery, diagnosis of some difficult diseases, and virtual reality pain distraction for severe burn patients. Smart VR health technology acts as a decision support system in the diseases diagnostic test of patients as they perform real world tasks in virtual reality (e.g., navigation). In this study, a non-invasive, cognitive computerized test based on 3D virtual environments for detecting the main symptoms of dementia (memory loss, visuospatial defects, and spatial navigation) is proposed. In a recent study, the system was tested on 115 real patients of which thirty had a dementia, sixty-five were cognitively healthy, and twenty had a mild cognitive impairment (MCI). The performance of the VR system was compared with Mini-Cog test, where the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. It was observed that visuospatial and memory recall scores in both clinical diagnosis and VR system of dementia patients were less than those of MCI patients, and the scores of MCI patients were less than those of the control group. Furthermore, there is a perfect agreement between the standard methods in functional evaluation and navigational ability in our system where P-value in weighted Kappa statistic= 100% and between Mini-Cog-clinical diagnosis vs. VR scores where P-value in weighted Kappa statistic= 93%

Older Adults Get Lost in Virtual Reality: Visuospatial Disorder Detection in Dementia Using a Voting Approach Based on Machine Learning Algorithms

As the age of an individual progresses, they are prone to more diseases; dementia is one of these age-related diseases. Regarding the detection of dementia, traditional cognitive testing is currently one of the most accurate tests. Nevertheless, it has many disadvantages, e.g., it does not measure the extent of the brain damage and does not take the patient’s intelligence into consideration. In addition, traditional assessment does not measure dementia under real-world conditions and in daily tasks. It is therefore advisable to investigate the newest, more powerful applications that combine cognitive techniques with computerized techniques. Virtual reality worlds are one example, and allow patients to immerse themselves in a controlled environment. This study created the Medical Visuospatial Dementia Test (referred to as the “MVD Test”) as a non-invasive, semi-immersive, and cognitive computerized test. It uses a 3D virtual environment platform based on medical tasks combined with AI algorithms. The objective is to evaluate two cognitive domains: visuospatial assessment and memory assessment. Using multiple machine learning algorithms (MLAs), based on different voting approaches, a 3D system classifies patients into three classes: patients with normal cognition, patients with mild cognitive impairment (MCI), and patients with severe cognitive impairment (dementia). The model with the highest performance was derived from voting approach named Ensemble Vote, where accuracy was 97.22%. Cross-validation accuracy of Extra Tree and Random Forest classifiers, which was greater than 99%, indicated a greater discriminate capacity than that of other classes

Effect of ethyl methanesulfonate mediated mutation for enhancing morpho-physio-biochemical and yield contributing traits of fragrant rice

Background Chemical mutagenesis has been successfully used for increasing genetic diversity in crop plants. More than 800 novel mutant types of rice (Oryza sativa L.) have been developed through the successful application of numerous mutagenic agents. Among a wide variety of chemical mutagens, ethyl-methane-sulfonate (EMS) is the alkylating agent that is most commonly employed in crop plants because it frequently induces nucleotide substitutions as detected in numerous genomes. Methods In this study, seeds of the widely consumed Basmati rice variety (Super Basmati, Oryza sativa L.) were treated with EMS at concentrations of 0.25%, 0.50%, 0.75%, 1.0%, and 1.25% to broaden its narrow genetic base. Results Sensitivity to a chemical mutagen such as ethyl methanesulfonate (EMS) was determined in the M1 generation. Results in M1 generation revealed that as the levels of applied EMS increased, there was a significant reduction in the germination percent, root length, shoot length, plant height, productive tillers, panicle length, sterile spikelet, total spikelet, and fertility percent as compared to the control under field conditions. All the aforementioned parameters decreased but there was an increase in EMS mutagens in an approximately linear fashion. Furthermore, there was no germination at 1.25% of EMS treatment for seed germination. A 50% germination was recorded between 0.50% and 0.75% EMS treatments. After germination, the subsequent parameters, viz. root length and shoot length had LD50 between 05.0% and 0.75% EMS dose levels. Significant variation was noticed in the photosynthetic and water related attributes of fragrant rice. The linear increase in the enzymatic attributes was noticed by the EMS mediated treatments. After the establishment of the plants in the M1 generation in the field, it was observed that LD50 for fertility percentage was at EMS 1.0% level, for the rice variety. Conclusion Hence, it is concluded that for creating genetic variability in the rice variety (Super Basmati), EMS doses from 0.5% to 0.75% are the most efficient, and effective