University Of Kufa

Background and purpose Diabetes mellitus (DM) is a leading cause of death worldwide. Stigma is a sign of social disgrace occurring within public relations, and it is linked with many health conditions including diabetes. Stigma could worsen the disease course, reduce treatment adherence, and affect the quality of life of diabetic patients. The objective of this study was to assess the magnitude of diabetic stigma among patients with type 2 DM. Methods In this analytic cross-sectional study, data collection was performed from June 1, 2022, until November 1, 2022, et al.-Najaf City, Iraq. A consecutive sample of 429 patients with type 2 DM was interviewed using the Arabic version of the type 2 Diabetes Stigma Assessment Scale (DSAS-2), which is a validated tool. The total diabetic stigma score, treated differently score, self-stigma score, and blame and judgment score were estimated. Results The mean age of the sample was 56.6 years, and males represented 61.8% of them. The total diabetic stigma score mean was 51.72. The question regarding people's judgment of food choices showed the highest rate (53%) among patients. Problematic stigma appeared in 24.71% of DM patients. Lower educational level, being divorced or widow, age above 50 years, being unemployed or housewife, and lower income showed significantly higher diabetic stigma scores. Conclusion One-quarter of type 2 DM patients showed problematic stigma. The mean diabetic stigma score was significantly higher among patients with lower education, divorced or widow status, older age, unemployment or housewife category, and low-income status.

There has been a lack of both educational focus on computational thinking (CT) and research into effective methods of assessing CT competence. This research takes a comprehensive look at the methods used to grade CT in higher education. This study examines the use of educational robotics (ER) as a teaching strategy in higher education, with particular attention to how undergraduate students might respond differently to this kind of learning. Students collaborate using artificial intelligence to find out how to program robots (start installing, interact, sharing information, feedback, and evaluate). Of 181 undergraduates’ students from Indonesia, Saudi Arabia, Riyadh, Pakistan, the Philippines, Egypt, Algeria, Lesoto, Cameron, Bangladesh, Sudan, Uganda, Portugal, Ukraine, Pakistan, and England make up the study groups. These students are enrolled in the first semester of the 2022 academic year. In this work, researchers employed a quantitative method technique. During the exercise, the participants were closely monitored to assess their performance in relation to the core CT constructs in the robotics class. These constructs include confidence in dealing with complexity, persistence in problem-solving, tolerance for ambiguity, ability to handle open-ended problems, effective communication skills, and teamwork abilities. In order to enhance the implementation of strategic initiatives. To facilitate more strategic learning, this study found that the use of visual robotics of artificial intelligence helped to developing CT and the respondents strong believe it to increase students’ confidence in dealing with complexity, persistence in working through difficult questions, tolerance for ambiguity, ability to handle open problems, communication skills, and teamwork. It is thought that this study would be valuable to academics, curriculum designers, and teachers because students who play artificial intelligence games exhibit considerably greater cognitive flexibility than before in higher education.

Background The COVID-19 pandemic has presented unprecedented challenges to healthcare systems worldwide. Among its many impacts, the effect of the virus on vascular health, particularly endothelial function, has become a focal point of research. This study aims to evaluate the impact of COVID-19 on endothelial function in a diverse Iraqi patient population. Methods In a cross-sectional study design, we assessed 284 patients from various regions in Iraq, including 100 females and 184 males, aged between 35 and 83 years. The evaluation of endothelial function was conducted using non-invasive methods such as flow-mediated dilation and biomarker analysis to measure endothelial integrity and inflammatory response. Results Our findings indicate that COVID-19 significantly impacts endothelial function, suggesting potential long-term risks to blood vessel integrity and increased cardiovascular risk. The effects were particularly pronounced in older age groups, highlighting the need for targeted vascular health monitoring in these patients. Conclusions The study reveals critical insights into the vascular implications of COVID-19. It underscores the importance of including assessments of endothelial function in the post-COVID-19 healthcare management plan, especially for older patients. These findings prompt the need for comprehensive strategies to mitigate the long-term cardiovascular effects of COVID-19 and improve patient care during and after the pandemic.

In this paper, an asymmetrical novel 4D system with a bounded function of exponential form, which can exhibit chaotic and hyperchoatic behaviors has been proposed. By calculating Lyapunov exponents and bifurcation diagram, the dynamical behaviors of such system are discovered. The proposed system has involved in bounded function and we show the behavior changes according to the corresponding function. An application to image encryption has been obtained.

According to reports, 60–70% of the estimated 50 million dementia patients globally have Alzheimer's disease. Forgetting earlier encounters or occurrences is one of the illness’ early warning signals. People with Alzheimer's frequently repeat words and inquiries, forget discussions, appointments, or activities, and then fail to recall them later, as well as routinely misplace their items and become lost in places they are acquainted with. There is no proven medication for Alzheimer's disease that can stop the brain's disease process in its tracks. The goal of this study is to develop a personal assistant that can remind a person with Alzheimer's or Parkinson's disease of important chores. The suggested remedy is a convolutional neural network-based voice-based smart controller. It makes it easier for the user to remember where they put the thing. The suggested solution also contains various extra characteristics that will be beneficial to both the Alzheimer's patient and regular people. The controller also often sends an alert at predetermined intervals so that individuals can pick up their phones, remind themselves of tasks, and see their own to-do list. The controller sends a notification before the meeting if the user has a meeting booked. This smart controller will serve as an assistant to the individual with Alzheimer’s and might also be helpful to ordinary human beings.

In a detailed study of 420 pregnant women in the last trimester from southern and central Iraq, aged 15 to 36 years, the impact of COVID-19 vaccinations on cardiovascular risk factors was assessed. The study's cohort displayed diverse vaccination statuses, with 50% receiving two vaccine doses and 10% receiving one dose, involving brands like Pfizer and Sinopharm. The findings indicated a notable distinction in cardiovascular responses between vaccinated and unvaccinated pregnant women. Vaccination seemed to reduce certain cardiovascular risks during pregnancy in the COVID-19 era. However, the extent of risk mitigation varied based on the number of vaccine doses and the vaccine type. In summary, the research suggests a potential protective effect of full COVID-19 vaccination against cardiovascular risks in pregnancy. These results highlight the need for further investigations into the specific effects of different COVID-19 vaccines on cardiovascular health in pregnancy.

Background: The COVID-19 pandemic's long-term effects on cardiovascular health, particularly regarding atherosclerotic diseases, are of increasing concern. Methods: In this retrospective cohort study, 450 patients from various Iraqi provinces who had recovered from COVID-19 were assessed over 12 months to evaluate the prevalence and severity of atherosclerotic cardiovascular diseases (CVD). Results: There was a significant increase in atherosclerotic changes among patients with a history of long-term COVID-19 compared to those without. A notable correlation was observed between the severity of post-COVID symptoms and the extent of atherosclerotic manifestation, across different demographic groups and geographical locations within Iraq. Conclusions: The study concludes that long-term COVID-19 may contribute to the accelerated development of atherosclerotic CVD. These findings underscore the need for enhanced cardiovascular monitoring and intervention strategies in patients recovering from COVID-19, particularly those with severe or prolonged symptoms.

Long-COVID, characterized by prolonged symptoms following an acute COVID-19 infection, has emerged as a significant public health concern. Cardiac arrhythmias are among the critical sequelae associated with long-COVID. This study aims to assess the incidence and nature of cardiac arrhythmias in long-term patients. This retrospective cohort study involved 340 patients diagnosed with long-term COVID-19, recruited from various hospitals in the Middle Euphrates region throughout 2022. The majority of the cohort were male, with ages ranging from 25 to 89 years. Data on cardiac arrhythmias were collated and analyzed. The study found a notable incidence of cardiac arrhythmias in long-COVID-19 patients, with variations across different age groups and a predominance in male patients. The types of arrhythmias and their severity differed significantly, indicating the diverse impact of long-term on cardiac health. The findings suggest a significant association between long-COVID-19 and the development of cardiac arrhythmias. The study highlights the need for vigilant cardiac monitoring in long-COVID-19 patients and underscores the importance of further research to understand the underlying mechanisms and to develop effective management strategies.

Three-dimensional almond shaped CuO nanostructures were prepared on the surface of Cu foil via hot water treatment (HWT) for the purpose of developing a high surface area supercapacitor electrode. The morphology and composition of CuO nanostructures were investigated by scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis, respectively. The electrochemical properties of CuO nanostructures were examined by cyclic voltammetry (CV) over various scan rates. Electrochemical measurements indicated that the maximum specific capacitance of 38.7 F/g was achieved at the scan rate of 5 mV/s in Na 2 SO 4 electrolyte. In addition, the capacitance retention rate was around 72% after 3000 consecutive cycles. All experimental results suggest that CuO nanostructures grown by HWT can create promising applications of CuO towards pseudosupercapacitor applications.

Because of its modest properties, the slot antenna has become an unsuitable contender in many applications. To achieve high gain, small size, and a wide frequency range in the proposed antenna, two layers of flower-shaped cells are positioned at various heights according to Al-Fabry–Perot theory. The improvements in antenna performance extended to the feed line and the slot drilled by the ground plate, allowing the amount of current flowing to be controlled. The number of cells in each of the metasurface layers above the typical antenna is 4 × 4. The antenna has a peak gain of 9.8 dB and a bandwidth of 2.6 GHz between 4.33 and 6.93 GHz. The CST software was used to carry out the simulation procedure. The antenna’s characteristics have made it an excellent contender for wireless applications.

The system of Brusselator-type reaction-diffusion equations (RDs) on open bounded convex domains 𝒟 ⊂ ℝ d {\mathcal{D}\subset\mathbb{R}^{d}} ( d ≤ 3 ) {(d\leq 3)} with Robin boundary conditions (Rbcs) has been mathematically analyzed. The Faedo–Galerkin approach is used to demonstrate the global existence and uniqueness of a weak solution to the system. The weak solution’s higher regularity findings are constructed under more regular conditions on the initial data. In addition, continuous dependence on the initial conditions has been proved.

Immune thrombocytopenic purpura (ITP) is a challenging disease in its presentation and management as it may cause life-threatening hemorrhaging in vital organs and may resist several lines of treatment. This systematic review and meta-analysis aimed to evaluate the safety and efficacy of mycophenolate mofetil (MMF) in treating patients with ITP. We systematically searched four electronic databases (PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials) from inception until 10 October 2022. We included all clinical trials, either controlled or single arm, and prospective and retrospective observational studies that evaluate the efficacy and safety of MMF in patients with ITP. We assessed the risk of bias using three tools (ROBINS-I, Cochrane ROB-2, and NIH), each for eligible study design. Nine studies were included in this meta-analysis, with a total of 411 patients with ITP. We found that MMF demonstrated an overall response rate of (62.09%; 95% CI = [43.29 to 77.84]) and the complete response rate was (46.75%; 95% CI = [24.84 to 69.99]). The overall proportion of adverse events was (12%; 95% CI = [6 to 24]). After the sensitivity analysis, the overall response rate became 50%; 95% CI = [38 to 63]) and the complete response rate became (32%; 95% CI = [24 to 42]). However, MMF did not appear to affect white blood cell counts or hemoglobin levels significantly. This systematic review and meta-analysis demonstrate that MMF appears to be an effective and relatively safe treatment option for patients with ITP when combined with steroids and even in those who have not responded to standard therapies (steroid-resistant cases). Further research with well-designed studies is warranted to better understand the factors influencing treatment response and to refine the use of MMF in the management of ITP. An interactive version of our analysis can be accessed from here: https://databoard.shinyapps.io/mycophenolate_meta/

This research paper delves into the interplay between viral load dynamics and the formulation of public health strategies for enhanced pandemic preparedness. By harnessing the capabilities of global epidemiological platforms such as the World Health Organization's Global Influenza Surveillance and Response System (GISRS) and Johns Hopkins University's COVID-19 Dashboard, our study constructed sophisticated computational models to predict and analyze viral transmission patterns. The study revealed that monitoring fluctuations in community viral loads could act as an early-warning system, prompting pre-emptive public health interventions. Our findings emphasize that interventions tailored to viral load assessments can markedly curb transmission, alleviate healthcare system strains, and reduce pandemic-induced mortality. Key insights from our research advocate for the integration of real-time data from global surveillance platforms into national health strategies to bolster pandemic response initiatives. We highlight the vital role of global data transparency and the swift exchange of viral load information in crafting agile and targeted public health policies. The research underscores the importance of international collaboration in pandemic preparedness, advocating for the establishment of an interconnected global network that leverages viral load dynamics for forecasting outbreaks. By doing so, public health authorities can better anticipate pandemic phases, optimize resource allocation, and implement timely interventions. The predictive models presented here offer a blueprint for decision-makers to strengthen pandemic readiness and protect global health.

This study investigates the efficacy of online social support networks in reducing post-pandemic psychological distress among women in Iraq. Conducted on a diverse group of 260 women from various provinces, the research aimed to understand the role these networks play in mental health during the challenging post-pandemic period. The study utilized a mixed-methods approach, combining quantitative data from surveys with qualitative insights from interviews and discussions. The survey focused on assessing levels of psychological distress and the usage of online social support networks. The qualitative aspect delved into personal experiences, exploring how these networks provided emotional support, information, and a sense of community. Findings revealed that online social support networks significantly contributed to mitigating psychological distress among the participants. Women who actively engaged in these networks reported lower levels of stress, anxiety, and loneliness. These platforms provided a crucial outlet for sharing experiences, receiving advice, and maintaining social connections during times of physical distancing. The study also highlighted some challenges, such as the digital divide and privacy concerns, which could hinder the effectiveness of these networks. However, the overall positive impact was evident, especially for women in remote or socially conservative areas, who otherwise have limited access to traditional support systems. In conclusion, the research underscores the importance of online social support networks as valuable tools for mental health support among women in post-pandemic Iraq. It suggests that further investment in digital infrastructure and awareness programs could enhance their accessibility and effectiveness, offering a sustainable approach to mental health care in similar contexts.

This study, conducted between 2022 and 2023, investigates the adoption and impact of telehealth services among women in Iraq post-COVID-19, focusing on the barriers, benefits, and long-term feasibility. Employing a mixed-methods approach, the research combined quantitative data from surveys with qualitative insights from interviews and focus groups, involving 500 women from diverse regions of Iraq. Throughout 2022 and 2023, the study assessed the extent of telehealth adoption among Iraqi women, considering a range of demographic factors, including age, socioeconomic status, and healthcare needs. Quantitative data analysis was used to identify trends in telehealth usage and influencing factors, while qualitative analysis offered an in-depth understanding of women's experiences and perceptions. The findings reveal a marked increase in telehealth adoption among Iraqi women since the COVID-19 pandemic. However, significant barriers were identified, including technological limitations, gaps in digital literacy, cultural reservations, and concerns about privacy and care quality. Despite these challenges, many participants reported notable benefits of telehealth, such as improved access to healthcare services, especially for women in remote or underserved areas, and convenience in receiving medical consultations. The research also delved into the long-term feasibility of telehealth within the Iraqi healthcare context, considering aspects such as infrastructure development, policy frameworks, and educational initiatives for users. The study concludes that while there are substantial hurdles to surmount, the advantages of telehealth, particularly in enhancing healthcare accessibility for women, are significant. To maximize the effectiveness and adoption of telehealth services in Iraq, strategic investments in technological infrastructure, coupled with targeted educational programs and policy reform, are essential.

Background: Immune-inflammatory pathways in major depressive disorder are confined to the major dysmood disorder (MDMD) phenotype (Maes et al., 2022). No studies have addressed the immune profile of first episode MDMD (FE-MDMD). Methods: This study investigated the immune profiles of 71 patients with the acute phase of first-episode major depressive disorder (FE-MDMD) and 40 healthy controls. We measured 48 cytokines/chemokines/growth factors, classical M1, alternative M2, T helper (Th)-1, Th-2, and Th-17 phenotypes, immune-inflammatory response system (IRS), compensatory immunoregulatory system (CIRS), and neuro-immunotoxicity profiles. Results: FE-MDMD patients show significantly activated M1, M2, Th-1, IRS, CIRS, and neurotoxicity, but not Th-2 or Th-17, profiles compared to controls. FE-MDMD is accompanied by Th-1 polarization, while there are no changes in M1/M2 or IRS/CIRS ratios. The top single indicator of FE-MDMD was by far interleukin (IL)-16, followed at a distance by TRAIL, IL-2R, tumor necrosis factor (TNF)-β. The severity of depression and anxiety was strongly associated with IRS (positively) and Th-2 (inversely) profiles, whereas suicidal behavior was associated with M1 activation. Around 56-60% of the variance in depression, anxiety, and suicidal behavior scores was explained by IL-16, platelet-derived growth factor (PDGF) (both positively), and IL-1 receptor antagonist (inversely). Increased neurotoxicity is mainly driven by IL-16, TNF-α, TRAIL, IL-6, and chemokine (CCL2, CCL11, CXCL1, CXCL10) signaling. Antidepressant-treated patients show an increased IRS/CIRS ratio as compared with drug-naïve FE-MDMD patients. Conclusions: FE-MDMD is accompanied by positive regulation of the IRS mainly driven by Th-1 polarization and T cell activation (via binding of IL-16 to CD4), and TNF, chemokine, and growth factor signaling.

Background Out-of-hospital cardiac arrest (OHCA) is a significant healthcare burden, with an average global incidence of 55 per 100,000 person-years among adults. OHCA patients require blood pressure support to maintain effective mean arterial pressure (MAP) for cerebral reperfusion, which is usually achieved by intravascular fluids and vasopressors in the intensive care unit (ICU). Targeting a specific MAP has been evaluated as a treatment strategy after OHCA; however, the current evidence lacks clear guidelines regarding the optimal MAP target after OHCA. Purpose We aim to evaluate the efficacy of targeting a high MAP (>70 mmHg) versus a low MAP target (< 65 mmHg) after OHCA resuscitation. Methods We conducted a systematic review and meta-analysis synthesizing randomized controlled trials (RCTs), which were retrieved by systematically searching: PubMed, EMBASE, Web of Science, SCOPUS, and Cochrane through January 18th, 2023. Continuous and dichotomous outcomes were pooled using mean difference (MD) and risk ratio (RR) along with confidence interval (CI), using Revman V. 5.4 software. Our review protocol was prospectively published on PROSPERO with ID: CRD42023395333. Results Four RCTs with a total of 1070 patients (531 in the high MAP target group and 534 in the low MAP target group) were included in our analysis. High MAP target was significantly associated with decreased ICU length of stay (MD: -0.78 with a 95 CI [-1.54, -0.02], P= .04) and mechanical ventilation duration (MD: -0.91 with a 95 CI of [-1.51, -0.31], P= .003). However, There was no difference between targeting a high MAP versus low MAP regarding all-cause mortality (RR: 1.07 with a 95% CI [0.91, 1.27], P= 0.4), favorable neurological recovery (cerebral categories scale (CPC) ≤ 2) (RR: 1.02 with a 95% CI [0.93, 1.13], P= 0.68), and neuron-specific enolase (NSE) at 48 hours (MD: 0.54 with 95% CI [-1.67, 2.75], P = 0.63), the incidence of adverse events, including any bleeding (RR: 0.89 with a 95% CI [0.69, 1.36], P= 0.39); arrhythmia (RR: 0.91 with a 95% CI [0.46, 1.82], P= 0.79), or acute kidney injury (RR: 0.80 with a 95% CI [0.36, 1.76] and P = 0.58). Conclusion In patients with OHCA who have been resuscitated, targeting a higher MAP significantly reduced the ICU length of stay and mechanical ventilation, implying potential clinical benefit with an acceptable safety margin. However, there was no difference between targeting a high MAP versus a low MAP regarding all-cause mortality, favorable neurological recovery, and NSE. Therefore, further RCTs are still warranted to elucidate the potential clinical benefit of targeting a high MAP after OHCA before endorsement in clinical practice.

In this study, an all-optical multiplexer (Mux) based on elliptical insulator-metal-insulator (IMI) plasmonic waveguides is designed. The area of the proposed structure is very small (400 nm × 400 nm) which operates at a wavelength of 1,550 nm. The developed device utilizes constructive and destructive interferences between the input signals and the selector signal. This structure is less complex and has lower loss compared to the previous works. Transmission (T), contrast ratio (CR), modulation depth (MD), insertion loss (IL), and contrast loss (CL) are the five parameters that describe the performance of the plasmonic Mux. The transmission threshold between logic 0 and logic 1 is 0.5. Moreover, the maximum transmission efficiency of the device is 163%. Moreover, based on the MD value of 95.09%, the dimensions of the proposed structure are excellent and optimal. The proposed plasmonic Mux structure contributes substantially to developing an all-optical arithmetic logic unit (ALU) and all-optical signal processing nanocircuits. The finite element method (FEM) simulates the proposed plasmonic multiplexer with COMSOL Multiphysics 5.4 software.