Molecular characterization of Pakistani wheat cultivars using random markers

The genetic diversity among fifteen varieties of wheat was studied by random amplified polymorphic DNA  (RAPD) analysis. By applying 20 RAPD primers, 182 fragments were amplified, out of which 118 were  polymorphic (64.84%). The number of fragments amplified per primer ranged from 10 to 24 with an average of  17 fragments per primer. Primer K-17 produced the maximum number of fragments (24) and all the fragments  were polymorphic. Range of polymorphism percentage was from as low as 0% (I to 15) to as high as 100%  (K-11). The number of fragments produced per wheat genotype varied from 36 to 56 with an average of 47.2  fragments per genotype. The variety Shahkar-95 produced maximum number of fragments (56). Cluster  analysis classified fifteen varieties of wheat into two main groups; three varieties were placed in group I and  the rest of the varieties were placed in group II. Second group (group II) was further divided into three  subgroups; IIA, IIB and IIC. The pair wise similarity values ranged from 54.88 to 82.93% and showed that  genotypes Kohinoor-83 and Pak-81 were the closest with highest similarity value (82.93%), while genotypes Kohinoor-83 and Kohistan-97 were most distinct with minimum similarity value (54.88%).Key words: Cultivar, polymorphism, random amplification of polymorphic deoxyribonucleic acid (RAPD), cluster analysis, genotype

Blockchain enabled data security in vehicular networks

Recently, researchers have applied blockchain technology in vehicular networks to take benefit of its security features, such as confidentiality, authenticity, immutability, integrity, and non-repudiation. The resource-intensive nature of the blockchain consensus algorithm makes it a challenge to integrate it with vehicular networks due to the time-sensitive message dissemination requirements. Moreover, most of the researchers have used the Proof-of-Work consensus algorithm, or its variant to add a block to a blockchain, which is a highly resource-intensive process with greater latency. In this paper, we propose a consensus algorithm for vehicular networks named as Vehicular network Based Consensus Algorithm (VBCA) to ensure data security across the network using blockchain that maintains a secured pool of confirmed messages exchanged in the network. The proposed scheme, based on a consortium blockchain, reduces average transaction latency, and increases the number of confirmed transactions in a decentralized manner, without compromising the integrity and security of data. The simulation results show improved performance in terms of confirmed transactions, transaction latency, number of blocks, and block creation time

Making prescriptions “talk” to stroke and heart attack survivors to improve adherence: Results of a randomized clinical trial (The Talking Rx Study)

Background: We developed and tested the effectiveness of a tailored health information technology driven intervention: TalkingPrescriptions (Talking Rx) to improve medication adherence in a resource challenged environment.Methods: We conducted a parallel, randomized, controlled, assessor-blinded trial at the Aga Khan University (AKU), Karachi, Pakistan. Adults with diagnosis of cerebrovascular accident (CVA) or coronary artery disease (CAD) diagnosed least one month before enrollment, on anti-platelets and statins, with access to a mobile phone were enrolled. The intervention group received a) Daily Interactive Voice Response (IVR) call services regarding specific statin and antiplatelet b) Daily tailored medication reminders for statin and antiplatelet and c) Weekly lifestyle modification messages for a period of 3 months. We assessed Medication adherence to statin and antiplatelets by a validated version of the 8-item Morisky Medication Adherence scale 8 (MMAS-8) at 3 months by a blinded assessment officer. Analysis was conducted by intention-to-treat principle (ITT).Results: Between April 2015 and December 2015, 197 participants (99 in intervention and 98 in the usual care group) enrolled in the Talking Rx Study. The dropout rate was 9.6%. Baseline group characteristics were similar. At baseline, the mean MMAS-8 was 6.68 (SD = 1.28) in the intervention group and 6.77 (SD = 1.36) in usual care group. At end of follow-up, the mean MMAS-8 increased to 7.41(0.78) in the intervention group compared with 7.38 (0.99) in usual care group with mean difference of 0.03 (S.D 0.13) (95% C.I [-0.23, 0.29]), which was not statistically significant. (P-Value = 0.40) CVA patients showed a relatively greater magnitude of adherence via the MMAS-8 at the end of follow up where the mean MMAS-8 increased to 7.29 (S.D 0.82) in the intervention group as compared to 7.07(S.D 1.24) in usual care group with mean difference of 0.22 (SD = 0.22) 95% C.I (-0.20, 0.65) with (P-value = 0.15). Around 84% of those on intervention arm used the service, calling at least 3 times and listening to their prescriptions for an average of 8 minutes. No user was excluded due to technologic reasons.Conclusion: The use of a phone based medication adherence program was feasible in LMIC settings with high volume clinics and low patient literacy. In this early study, with limited follow up, the program did not achieve any statistically significant differences in adherencebehavior as self-reported by the MMAS-8 Scale

Exploring the relationship of cognitive function with and without COVID-19 recovered schizophrenic patients

BackgroundThe Coronavirus disease 2019 (COVID-19) is linked to the deterioration of cognitive function among individuals suffering from schizophrenia. The purpose of this study was to compare the cognitive performance of schizophrenic patients before and after COVID-19.MethodsA longitudinal cohort study involving a sample of 219 individuals diagnosed with schizophrenia was enrolled between June 2022 and May 2023. The participants were split into two groups infected with COVID-19 (n = 165) and not infected with COVID-19 (n = 54). The data were gathered via a questionnaire on demographic characteristics, the Brief Assessment of Cognition in Schizophrenia (BACS), the Positive and Negative Syndrome Scale (PANSS), the Calgary Depression Scale for Schizophrenia (CDSS), the Activities of Daily Living (ADL) scale, and the Insomnia Severity Index (ISI).ResultsThe repeated-measures ANOVA showed that Among patients diagnosed with COVID-19, there was a deterioration in global cognitive function (before COVID-19 = −2.45 vs. after COVID-19 = −3.02, p = 0.007), working memory (before COVID-19 = −2.76 vs. after COVID-19 = −3.34, p < 0.00 1), motor speed (before COVID-19 = −1.64 vs. after COVID-19 = −2.12, p < 0.001), attention and speed of information processing (before COVID-19 = −1.93 vs. after COVID-19 = −1.16, p = 0.008). multi-variable analysis showed that several factors as having a secondary grade of education (β = 0.434), experiencing insomnia (β = 0.411)and the interaction between COVID-19 diagnosis and cognition at baseline (β = 0.796) were significantly associated with cognitive deficits. At the same time, no significant associations were found between global cognition and clinical symptoms, autonomy, or depression (p > 0.05).ConclusionThe COVID-19 pandemic has significantly impacted various cognitive functions, such as verbal memory, working memory, and global cognition. Insomnia has been identified as the predominant determinant of cognitive impairment, alongside the confirmation of a COVID-19 diagnosis. Additional research is imperative to elucidate the diversification of cognitive functionality observed in individuals diagnosed with schizophrenia who have acquired COVID-19

Effectiveness of human mobility change in reducing the spread of COVID-19: ecological study of Kingdom of Saudi Arabia

Non-pharmacological interventions including mobility restriction have been developed to curb transmission of SARS-CoV-2. We provided precise estimates of disease burden and examined the impact of mobility restriction on reducing the COVID-19 effective reproduction number in the Kingdom of Saudi Arabia. This study involved secondary analysis of open-access COVID-19 data obtained from different sources between 2 March and 26 December 2020. The dependent and main independent variables of interest were the effective reproduction number and anonymized mobility indices, respectively. Multiple linear regression was used to investigate the relationship between the community mobility change and the effective reproduction number for COVID-19. By 26 December 2020, the total number of COVID-19 cases in Saudi Arabia reached 360,690, with a cumulative incidence rate of 105.41/10,000 population. Al Jouf, Northern Border, and Jazan regions were ≥2.5 times (OR = 2.93; 95% CI: 1.29–6.64), (OR = 2.50; 95% CI: 1.08–5.81), and (OR = 2.51; 95% CI: 1.09–5.79) more likely to have a higher case fatality rate than Riyadh, the capital. Mobility changes in public and residential areas were significant predictors of the COVID-19 effective reproduction number. This study demonstrated that community mobility restrictions effectively control transmission of the COVID-19 virus

An innovative state-of-the-art health storytelling technique for better management of type 2 diabetes

Background: Type 2 diabetes (T2D) is a chronic lifelong disease that requires long-term prevention and management strategies in a community setting. A health story is a novel technique that may be used as an effective tool for better prevention and management of T2D. Objective: The main objective of this study is to develop a story to be used as a social health technique based on contemporary scientific knowledge that may be used at a community level for better communication and management of T2D. Methods: A community–academic partnership was formed with a not-for-profit Nutrition Education, Awareness, and Training (NEAT) organization in Khyber Pakhtunkhwa, Pakistan. We agreed to develop a story that may be used as a health and nutrition education communication tool for better management of patients with T2D. The following phases were followed during the story creation process: (1) the theory phase, (2) the modeling phase, and (3) the evaluation phase. Raters evaluated the story to determine its literary and scientific quality, comprehensiveness, and T2D specificity. Results: The title of the story translated into English is “The Story of Diabetes—The Story of Success.” It is text based and contains 86 pages in the local language, “Pashto,” with an English translation. The story is divided into five chapters and describes the initial diagnosis, fear associated with the disease, issues related to referral to certified practitioners, the importance of a balanced diet, and related lifestyle habits. After story evaluation, the raters suggested its literary and scientific quality, comprehensiveness, and T2D specificity (Pearson correlation scores of \u3e0.8). Conclusion: This unique story was created for T2D and found to be of significant quality in terms of its literary and scientific quality, as well as its comprehensiveness and diabetes specificity. As a result, it may be suggested that it can be used in subsequent studies to improve T2D management among adult patients

Multi-Modal Data Analysis Based Game Player Experience Modeling Using LSTM-DNN

Game player modeling is a paradigm of computational models to exploit players’ behavior and experience using game and player analytics. Player modeling refers to descriptions of players based on frameworks of data derived from the interaction of a player’s behavior within the game as well as the player’s experience with the game. Player behavior focuses on dynamic and static information gathered at the time of gameplay. Player experience concerns the association of the human player during gameplay, which is based on cognitive and affective physiological measurements collected from sensors mounted on the player’s body or in the player’s surroundings. In this paper, player experience modeling is studied based on the board puzzle game “Candy Crush Saga” using cognitive data of players accessed by physiological and peripheral devices. Long Short-Term Memory-based Deep Neural Network (LSTM-DNN) is used to predict players’ effective states in terms of valence, arousal, dominance, and liking by employing the concept of transfer learning. Transfer learning focuses on gaining knowledge while solving one problem and using the same knowledge to solve different but related problems. The homogeneous transfer learning approach has not been implemented in the game domain before, and this novel study opens a new research area for the game industry where the main challenge is predicting the significance of innovative games for entertainment and players’ engagement. Relevant not only from a player’s point of view, it is also a benchmark study for game developers who have been facing problems of “cold start” for innovative games that strengthen the game industrial economy

Methane decomposition for hydrogen production over biomass fly ash-based CeO2 nanowires promoted cobalt catalyst

In this work, the biomass fly ash (BFA) was investigated as a potential catalyst for the thermo-catalytic decomposition of methane and attractive approach for hydrogen (H-2) production. The BFA based CeO2 nanowires promoted cobalt catalyst was synthesized for catalytic methane (CH4) decomposition and was tested in a fixed bed reactor. The physicochemical properties of the catalyst were investigated using various techniques such as X-ray powder diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, thermal gravimetric analysis, and Fourier transformed infrared. The pure crystalline micro-flake BFA was modified using synthesized CeO2 nanowires and the resulted micro flakes cross-linked with nanowires shown thermal stability up to 900 degrees C. The high stability of the catalyst makes it suitable for the thermal catalytic decomposition of methane. The activity of the catalyst was tested at 850 degrees C to analyze the H-2 production and CH4 conversion. The obtained results revealed that support and promoter exhibit a strong impact on the CH4 conversion and H-2 yield in catalyst screening tests. A maximum conversion of 71% for CH4 with 44.9% H-2 yield was recorded for 34 h on stream activity while using 5% Co/CeO2-BFA as the catalyst. While BFA and Co-BFA as catalyst showed 36% and 47% conversion of CH4, respectively which indicates that the addition of promoter shows an increase in values of both conversion of CH4 and H-2 yield. Compared to traditional catalyst support, the use of waste-sourced catalyst support for CH4 decomposition provides a greener and more economical route for H-2 production

Effect of Ajwa date pits powder (Phoenix dactylifera L.) on body composition, lipid profile and blood pressure in patients with hyperlipidemia: A randomized clinical trial

Objective: To evaluate the effect of Ajwa dates pit powder (ADP) on lipid profile, body composition and blood pressure in patients with hyperlipidemia.Materials and Methods: This randomized controlled clinical study was carried out on 40 patients with total cholesterol >200 mg/dl, triglycerides >150 mg/dl and BMI >25, of either sex, aged 30-50 years, who were recruited through written consent. The patients were divided into two groups (n=20 each): the ADP and the control group (CG). All patients received the doctor’s prescribed class A statin (Rosuvastatin/ Atorvastatin) 10 mg/day, while 2.7 g ADP was given on daily basis before breakfast with lukewarm water for 40 days and the control group received the same amount of wheat flour. Body composition, blood pressure and lipid profile were determined at baseline, and after 20 and 40 days. Data were analyzed by using SPSS and GraphPad Prism.Results: ADP significantly reduced body weight (p<0.001), BMI (p<0.001), fat mass, body fat percentage, visceral fat area and waist circumference compared to the control group. Similarly, ADP significantly (p=0.000) decreased the serum level of total cholesterol and low-density lipoprotein. Conclusion: ADP may have the potential to improve dyslipidemia and obesity

Using Spiritual Connections to Cope With Stress and Anxiety During the COVID-19 Pandemic

During the initial phases of the COVID-19 pandemic, stress and anxiety were pervasive among the masses due to high morbidity and mortality. Besides the fear of coronavirus was also particularly driven by social media. Many people started to look for faith and spiritual connections to gain comfort. The role of spiritual ties and religious beliefs in relation to coping with pandemic stress has acquired the attention of researchers in some parts of the world. This cross-sectional survey aimed at assessing the intensity of stress and anxiety symptoms experienced by people and how much they were alleviated by employing spiritual connections. The study sample comprises 795 respondents with 52% males and 48% females living in Saudi Arabia. The brief online study questionnaire collected data about background variables, anxiety and stress scale from DASS-21, and items from the WHOQOL (SRBP) instrument assessed the use of spiritual beliefs to cope. Multiple regression models were tested to determine the role of spiritual connections after adjusting demographic variables. Results illustrated that after adjusting for gender and age, participants’ anxiety symptoms decreased by (β = −0.27; p = 0.000) units with each unit increase in the use of spiritual connections, and participants’ stress symptoms reduce by (β = −0.36; p = 0.000) units with each unit increase in coping with spirituality. Additionally, females’ risk to experience anxiety and stress symptoms was more than males [(β = 0.88; p = 0.01) and (β = 0.92; p = 0.000)], respectively. An increase in age decreases the likelihood of experiencing anxiety symptoms and stress symptoms by (β = −0.75; p = 0.02) and (β = −0.11; p = 0.000) units, respectively. Findings support the protective role of spiritual connections despite small beta coefficients. The social and cultural context in Saudi Arabia favors deep-rooted connections with spirituality and faith. Our findings support the fact that the reliance on spiritual connections helped older people to deal with exaggerated fear during the initial phase of the COVID-19 pandemic and reduces the risk of experiencing anxiety and stress symptoms. Females and younger participants were relatively vulnerable to developing these symptoms. We discussed these findings considering some recent studies that reported similar relationships and made recommendations for future research