Severe combined immune deficiency syndrome

Objective: To determine the clinico-demographic features and laboratory parameters of children with severe combined immunodeficiency (SCID). Study Design: Case series. Place and Duration of Study: Department of Paediatrics and Child Health, the Aga Khan University, Karachi, from July 2006 to July 2011. Methodology: Thirteen infants who were discharged with a diagnosis of SCID were inducted in the study. Their clinicodemographic features and laboratory parameters were determined. Descriptive statistics has been used for computing frequency and percentage. Results: The median age at diagnosis was five months; 5 infants presented within 3 months of life. Three-fourth (77%) were males. Most of the infants were severely malnourished (85%) at the time of presentation. More than two-thirds (69%) were products of consanguineous marriages. All subjects had severe lymphopenia {absolute lymphocyte count (ALC) ranging between 170 – 2280} and low T and B lymphocyte counts. Conclusion: SCID should be considered in infants presenting with severe and recurrent infections. Low ALC (\u3c 2500/mm3), is a reliable diagnostic feature of SCID. These infants should be promptly referred to a facility where stem cell transplant can be done

The Relationship between Product Nature and Supply Chain Strategy; An empirical evidence

Abstract The purpose of the paper is to explore the relationship between the nature of product and respective supply chain strategy of the firms operation in manufacturing sector. The relationship is investigated by using the fishers model as conceptual framework. Data was collected through questionnaire-based self-administered survey. The results of the survey were analysed by testing the fishers model related to Supply Chain Strategy and product characteristics. The results of the study indicated that there is a significant relationship between nature of the product and supply chain strategy in manufacturing sector of Pakistan. The practical implication can be derived by the policy makers and practitioners of the supply chain strategy domain that characteristics of the product can have an impact of the decision to device supply chain strategy. Furthermore, this study is conducted in special context of underdeveloped country like Pakistan. Therefore, results of this study enhanced the existing literature on underdeveloped economies

Comparison of Caralluma tuberculata with Metformin for Anti-Diabetic Activity: An Animal Study

Background: Caralluma tuberculata, is a wild herb, which grows in the hills of Balochistan and has been known to have medicinal and nutritional properties since antiquity. This experimental research was designed to study the hypoglycemic properties of Caralluma tuberculata and to compare them with Metformin.Material and Methods: This was a laboratory-based animal experimental study. It was conducted in the Pharmacology laboratory of Khyber Medical University, Peshawar from February 2016 to August 2016. Two types of extracts of Caralluma tuberculata [crude extract and carbon tetrachloride (CCl4) extract] were prepared and administered to normal and alloxan treated diabetic rabbits. To study anti-diabetic activity, eighty-four rabbits were divided into two main groups. Group I (Normal/Non-Diabetic Rabbits; n= 21) and Group II (Diabetic/Alloxanized Rabbits; n=63). Each group was further divided into sub-groups (7 rabbits in each). Effect of Caralluma tuberculata, Metformin and 2% gum tragacanth on blood glucose levels were checked at 0, 2, 4, 6, 8, 12 and 24 hours of drug administration. The extracts were given in capsule form and in cooking oil. Data analysis was done using SPSS version 16. For calculation and comparison of the hypoglycemic effects at various doses and different time intervals, analysis of variance (ANOVA) and Tukey’s post hoc test were applied.Results: The crude extract, 200mg/kg body weight of Caralluma tuberculata showed significant decrease (p<0.001) in mean blood glucose levels from 2-hour till12 hours. Whereas, highly significant reduction of blood glucose was seen from 2 hours after treatment till 24 hours, when carbon tetrachloride (CCl4) fraction of Caralluma (100mg/kg body weight) in capsule form was administered. Metformin 500mg/kg body weight was given to compare its effects with plant crude extract and it was found that metformin appeared to be less effective in comparison with Caralluma tuberculata.Conclusion: Caralluma tuberculata lowered the blood glucose level and turned out to be more significant in developing hypoglycemia when taken with cooking oil. More work is essential to provide stronger evidence for the use of this natural agent in the management of Diabetes Mellites

Rice Seedling Characteristics of Various Genotypes Influenced by Different Sowing Dates in Swat-Pakistan

To study the effect of different sowing dates on rice nursery rising and to evaluate their effect on yield and yield components of rice genotypes, an experiment was conducted at Agriculture Research Institute (N) Mingora Swat, Pakistan, during summer 2011. The experiment was laid out in randomized complete block design with four replications. Seven genotypes (PARC 403, OM5627,IR64,IR8225-9-3-2-3, CIBOGO,GA-5015, and FakhreMalakand) and 5 sowing dates (D1= 25th April, D2= 10th May, D3= 25th May, D4= 9th June, and D5= 24th June) were used. Each genotype was sown in six rows in dry bed nursery. The germination percentage was above 90%. The nursery reached its optimum size up to 30 days and was ready for transplantation.Sowing on either D5 (24th June) or D4(9th June)gave maximum leaf area(9.6 and 9.1 cm2) followed by D3 (7.2 cm2), maximum leaves seedling-1 produced by D3 (5.3) followed by D2 (5.0). Maximum seedling height was gave by sowing on D5 (23.5 cm) followed by D4 (19.9 cm), maximum biomass gave by sowing on D4 (15.3 gm) and D5 (13.8 gm) followed by D2 and D3 (12.8 and 12.2 gm), highest root number gave by D4 (13.0) followed by D2 and D3 (11.3 and 11.5) and highest root length gave by D1 and D2 (10.7 and 10.7 cm) followed by D3 (9.6 cm). Among the rice genotypes FakhreMalakand produced highest seedling height (21.9 cm), highest biomass (14.0 gm), highest root length (12.9 cm) followed by GA-5015 while maximum leaf area gave by genotype PARC 403 (9.8 cm2) and number of leaves (4.9) followed by FakhreMalakand (8.3 cm2 and 4.6) respectively. Later data showed that highest paddy yield (6.49 t ha-1) was produced by FakhreMalakand sown on either D2 or D3 while the other genotypes were at par valued in this order. On the basis of the above results, it is recommended that rice nursery rising should be either D2 or D3May10th or 25th in the agro-ecological conditions of swat valley. Keywords: Rice (Oryza sativa L.), genotypes, sowing dates, biomass, seedlin

The Diversity of Arbuscular Mycorrhizal Fungi in the Black Cumin Rhizosphere (Nigella sativa L.) in Cianjur, West Java, Indonesia

Arbuscular Mycorrhizal Fungi (AMF) is a type of fungus that can form a symbiotic mutualism with most plants. Some AMF can only be symbiotic with a certain plant species. This research aims to determine and obtain the genus AMF from black cumin (Nigella sativa L.) accessions from America, Turkey, Hong Kong, Slovenia, India, and Kuwait accessions which had been grown in West Java, Indonesia. Three samples from each accession, four replications each, were collected for examination. The results showed that six generas of AMF were found in the rhizosphere of black cumin: Glomus, Gigaspora, Acaulospora, Scutellospora, Dentiscutata, and Entrophospora. The genus Glomus was predominantly found in the Indian accession, i.e. 96.42 spores.Keywords: black cumin, diversity, fungi, exploration, AM

Testing Technical Trading Rules: Evidence from SAARC Countries

Technical analysis is widely accepted tool in professional place which is frequently used for investment decisions. Technical analysis beliefs that there exist patterns and trends and by capturing trends and patterns one can bless with above average profits. We test two technical strategies: Moving averages and Trading Range to question, either these techniques can yield profitable returns with the help of historical data. Representative daily indices of Four countries namely Pakistan, India, Srilanka, Bangladesh ranging from 1997 to 2011 have been examined. In case of Moving Average Rule, both simple and exponential averages have been examined to test eleven different short term and long term rules with and without band condition. Our results delivered that buy signals generate consistent above average returns for the all sub periods and sell signals generate lower returns than the normal returns.  Intriguing observation is that Exponential average generates higher returns than the Simple Average. The results of Trading Range Break strategy are parallel with Moving average Method. However, Trading Range Strategy found not to give higher average higher return when compared with Moving Averages Rules and degree of volatility in returns is higher when compared with moving Average rule. In attempt to conclude, there exist patterns and trends that yield above average and below average returns which justify the validity of technical analysis

Thrombolytic therapy in acute myocardial infarction in Pakistan.

To characterize features of acute myocardial infarction (AMI) in a Pakistani population, and assess the role of thrombolysis in our country, we studied 194 consecutive admitted patients with enzyme positive AMI. Males were affected three times more frequently; women, although affected less, had a higher incidence of complications than men. Premature coronary artery disease (CAD) was present in 50% patients presenting with AMI. An unusually high incidence of anterior wall myocardial infarction (39%) was seen. Complications were frequent with a predominance of LV failure symptoms. Cardiogenic shock was associated with a very high mortality, in excess of 93%. Streptokinase (SK) was administered in 60% patients with suspected transmural AMI. A statistically significant reduction in mortality was seen in the group that received SK (15.2%) compared to those who did not receive SK (24.7%), (p = \u3c 0.05)

Sensitivity of Epworth Sleepiness Scale in Detecting Obstructive Sleep Apnea in Pakistani Adults

Background: Self-reported measures of Excessive daytime Sleepiness, such as the Epworth Sleepiness Scale (ESS), have been widely used as a screening tool for OSA, but their accuracy in predicting OSA has been questioned. Objective: The main objective of this research is to re-evaluate the usage of ESS in predicting Obstructive Sleep Apnea (OSA) and to consider additional screening tools, such as polysomnography, to improve the accuracy of OSA diagnosis in the Pakistani population. Methods: It was a retrospective cross-sectional study design, conducted on 500 participants. Data was obtained from the hospital records at the Sleep Lab of Dow University Hospital from January 2021 to March 2023 who completed the Epworth Sleepiness Scale (ESS), received a clinical evaluation from a doctor, and underwent diagnostic polysomnography (PSG), polysomnography is a comprehensive sleep study that monitors various physiological parameters to diagnose sleep disorders. Results: Out of a total sample of 500 participants, 272 were males and 228 were females. The average age was 51 ± 12 years. The average body mass index (BMI) was 37.2 ± 8.1 Kg/m2 . The average Epworth Sleepiness Scale (ESS) score of the participants was 12.4 ± 4.2. The finding of our study shows Epworth sleepiness score is a good predictor of OSA (AUC: 0.84, 95% CI: 0.757-0.923). However, the optimal cutoff of ESS is 8.4 and above which shows sensitivity and specificity of 83.1% and 81.8% respectively. Conclusion: The results suggest that the Epworth Sleepiness Scale may be a useful tool for identifying individuals with OSA, although it also has a low false positive rate, there is a need for further research, and the importance of combining clinical assessment and diagnostic tests for accurate OSA diagnosis

Solutions for Insider Trading and Regulatory Challenges in Financial Governance

Insider trading and regulatory inconsistencies have important historical challenges to the integrity and stability of global financial markets. These issues challenge trust, transparency, and fairness are requiring solutions. In this study, we introduce a novel artificial intelligence (AI)-driven system that carefully addressing these challenges. The proposed system employs machine learning models for insider trading detection, natural language processing (NLP) for sentiment analysis, and graph neural networks (GNNs) to detect irregular patterns in blockchain transactions. Moreover, reinforcement learning techniques are utilized here to complement regulatory standards dynamically, enhancing policy flexibility and market agreement. Explainable AI (XAI) were used here as well to ensure the transparency and trust in decision-making processes, this helps stakeholders to take actions. Experimental evaluations prove the system efficiency, with promising precision and recall percentages, enhanced governance in decentralized systems, and robust cross-jurisdictional regulatory alignment. This research contributes to knowledge by proving the transformative prospective of AI in strengthening regulatory frameworks and improving governance mechanisms in financial systems. The achievements here provide a roadmap for policymakers, financial institutions, and technology developers to build reasonable, efficient, and resistant markets.El tráfico de información privilegiada y las inconsistencias regulatorias han sido desafíos históricos importantes para la integridad y estabilidad de los mercados financieros globales. Estos problemas desafían la confianza, la transparencia y la equidad y requieren soluciones. En este estudio, presentamos un nuevo sistema impulsado por inteligencia artificial (IA) que aborda cuidadosamente estos desafíos. El sistema propuesto emplea modelos de aprendizaje automático para la detección de tráfico de información privilegiada, procesamiento del lenguaje natural (NLP) para el análisis de sentimientos y redes neuronales gráficas (GNN) para detectar patrones irregulares en transacciones de blockchain. Además, aquí se utilizan técnicas de aprendizaje de refuerzo para complementar los estándares regulatorios de forma dinámica, mejorando la flexibilidad de las políticas y el acuerdo del mercado. Aquí también se utilizó IA explicable (XAI) para garantizar la transparencia y la confianza en los procesos de toma de decisiones, lo que ayuda a las partes interesadas a tomar medidas. Las evaluaciones experimentales prueban la eficiencia del sistema, con porcentajes prometedores de precisión y recuperación, una gobernanza mejorada en sistemas descentralizados y una sólida alineación regulatoria interjurisdiccional. Esta investigación contribuye al conocimiento al demostrar la perspectiva transformadora de la IA en el fortalecimiento de los marcos regulatorios y la mejora de los mecanismos de gobernanza en los sistemas financieros. Los logros aquí alcanzados proporcionan una hoja de ruta para que los responsables de las políticas, las instituciones financieras y los desarrolladores de tecnología construyan mercados razonables, eficientes y resistentes