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The Current Status of Drug Repositioning and Vaccine Developments for the COVID-19 Pandemic
Since the outbreak of coronavirus disease 2019 (COVID-19) was first identified, the world has vehemently worked to develop treatments and vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at an unprecedented speed. Few of the repositioned drugs for COVID-19 have shown that they were efficacious and safe. In contrast, a couple of vaccines against SARS-CoV-2 will be ready for mass rollout early next year. Despite successful vaccine development for COVID-19, the world will face a whole new set of challenges including scale-up manufacturing, cold-chain logistics, long-term safety, and low vaccine acceptance. We highlighted the importance of knowledge sharing and collaboration to find innovative answers to these challenges and to prepare for newly emerging viruses.
Journal Article
Adherence and persistence rates of major antidiabetic medications: a review
The objective of this paper was to review the adherence and persistence rates of major antidiabetic medication classes (i.e., metformin, sulfonylureas, sodium glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, insulin, glucagon-like peptide-1 receptor agonists, and thiazolidinediones) by summarizing the major findings of the studies published since 2017. In addition, we reported the potential causes for low adherence and persistence of antidiabetic medications. Based on the literature, the highest rate of adherence and persistence was consistently observed in metformin users. Second to metformin were sodium glucose cotransporter-2 inhibitors. Injectable therapies such as insulin and glucagon-like peptide-1 receptor agonists trailed low on the adherence and persistence rates. To the best of our knowledge, no studies published since the year 2017 analyzed the adherence and persistence of thiazolidinediones independently. The most frequently cited cause for low adherence and persistence was the severity of adverse events. Baseline characteristics (e.g., baseline HbA1c level), demographic information (e.g., age, gender, or ethnicity), and comorbidity profiles also had significant impacts on adherence and persistence in patients with type 2 diabetes mellitus.
Journal Article
جنون النساء وغباء الرجال : الحقيقة البسيطة لعلاقة معقدة
منذ فجر التاريخ وعندما حاول أول رجل بدائي سحرته امرأة أن يعبر عن عاطفته لتلك المرأة بطرحها في الوحل، أثبت الرجال أنه عندما يتعلق الأمر بالمرأة، فإنهم يتسمون بالغباء الشديد. أما على الجانب الآخر، فإنه عندما يتعلق الأمر بالرجال، تصبح النساء -بغض النظر عن مستوى الذكاء أو النضج- مجنونات واستنادا إلى هذه الرؤية البسيطة والعميقة في آن واحد وضع الزوجان كاتبا الكوميديا ومسلسلات الواقع \"هاوارد جيه. موريس\"و\"جيني لي\" دليلا للعلاقة بين الرجل والمرأة يتسم بالأمانة الشديدة والمرح التام والعملية المذهلة. وباستخدام قصة حبهما الغبية المجنونة كنموذج لهذه العوامل وقد وضعت موضع التطبيق، بدآ يشرحان السر وراء إلقاء النساء أسئلة لا يردن الأجابة عنها والسر وراء إصرار الرجال على إجابة هذه الأسئلة. فيم يفكر الرجال حق، أو بشكل أدق، لم لا يفكرون؟ ولماذا ترى النساء حتى أبسط الأشياء من خلال منظور عاطفي ؟ لماذا يمل الرجال من الأمور العاطفية ؟ ولماذا يقود أي حوار بينهم وبين أية امرأة إلى ما إذا كانت بدينة أم لا. وباستخدام حكم ذكية تم التوصل إليها بصعوبة وفي إطار مرح، اكتشف المؤلفان الطريق المدهش الذي قاد إلى غبائه والأسباب الحقيقية وراء جنونها، مع تقديم حلول واقعية للمشكلات المزمنة في العلاقات الإنسانية ومن خلال تعريف الرجال بكيفية وسبب غبائهم في تعاملهم مع النساء وتعريف النساء بالكيفية التي \"يسيطرن بها على جنونهن وذلك لمصلحة الجميع. إن هذا الكتاب يساعد الأزواج على الوصول إلى وضع لا يفهم فيه العطاء على أنه استسلام ولا الحاجة على أنها احتياج؛ وإلى وضع
Book
Associations of frailty with survival, hospitalization, functional decline, and toxicity among older adults with advanced non-small cell lung cancer
Abstract
Introduction
Among older adults with cancer receiving chemotherapy, frailty indices predict OS and toxicity. Given the increased use of immunotherapy and targeted therapy for advanced non-small cell lung cancer (aNSCLC), we evaluated frailty and Karnofsky Performance Status (KPS) among older adults with aNSCLC receiving chemotherapy, immunotherapy, and/or targeted therapy.
Methods
Patients aged ≥ 65 with aNSCLC starting systemic therapy with non-curative intent underwent geriatric assessments over 6 months. We developed a deficit-accumulation frailty index to categorize patients as robust, pre-frail, or frail. To evaluate associations between frailty and KPS with OS, we used Cox proportional hazards models adjusted for race, insurance, and treatment. We used logistic regression to evaluate hospitalizations, functional decline, and severe toxicity.
Results
Among 155 patients (median age 73), 45.8% were robust, 36.1% pre-frail, and 18.2% frail; 34.8% had a KPS ≥ 90, 32.9% had a KPS of 80, and 32.3% had a KPS ≤ 70. The median OS was 17.9 months. Pre-frail/frail patients had worse OS compared to robust patients (adjusted hazard ratio [HR] 2.09, 95% CI, 1.31-3.34) and were more likely to be hospitalized (adjusted odds ratio [OR] 2.21, 95% CI, 1.09-4.48), functionally decline (adjusted OR 2.29, 95% CI, 1.09-4.78), and experience grade ≥ 3 hematologic toxicity (adjusted OR 5.18, 95% CI, 1.02-26.03). KPS was only associated with OS.
Conclusions
Our frailty index was associated with OS, hospitalization, functional decline, and hematologic AEs among older adults with aNSCLC receiving systemic therapies, while KPS was only associated with OS. Pretreatment frailty assessment may help identify older adults at risk for poor outcomes to optimize decision-making and supportive care.
Journal Article
A Comparison of AI and Population PK Models to Predict the Concentrations of Antiepileptic Drugs Using Therapeutic Drug Monitoring Records
Population pharmacokinetic (PK) models are commonly used to predict drug concentrations, but artificial intelligence (AI) models have gained interest due to their ability to identify complex patterns without requiring mathematical assumptions. This study compares the predictive performance of AI and population PK models using therapeutic drug monitoring (TDM) records of four antiepileptic drugs (AEDs): carbamazepine (CBZ), phenobarbital (PHB), phenytoin (PHE), and valproic acid (VPA). Additionally, we analyzed key covariates influencing drug concentration predicting using the most accurate model. We extracted concentration data for CBZ, PHB, PHE, and VPA from TDM reports at Seoul National University Hospital (2010–2021), along with patient diagnoses and lab results. The predictive performances of 10 AI models, including ensemble and deep learning models, were compared with published population PK models. The predictive performance of AI models generally exceeded that of population PK models. The best‐performing AI models, such as Adaboost, eXtreme Gradient Boosting, and Random Forest, had lower root mean squared error values for CBZ, PHB, PHE, and VPA (2.71, 27.45, 4.15, and 13.68 μg/mL, respectively) compared to population PK models (3.09, 26.04, 16.12, and 25.02 μg/mL). The most influential covariate was time after last drug administration. AI models, particularly ensemble methods, showed strong predictive performance and may support individualized AED dosing, improving therapeutic outcomes while minimizing adverse effects.
Journal Article
التسويق الفعال : كيف يمكن للتسويق التجاري إضافة قيمة دائمة لأي شركة ؟
يتناول الكتاب التسويق الفعال وكيف يمكن للتسويق التجاري إضافة قيمة دائمة لأي شركة حيث الهدف من هذا الكتاب عملي للغاية، إلا أنه لايحاول تقديم خلاصة وافية عن التسويق أو الشركات أو الفروع (الأقسام ضمن الشركات الكبيرة). إنما قام فقط بتغطية مفاهيم، وأساليب، وتكتيكات، واستراتيجيات التسويق التي تجدي نفعا أي التي يمكنها إضافة قيمة إلى مشاريع حقيقية فيما ننتقل إلى حقبة القرية العالمية الأكثر تواصلا.
BOOK
A programmable platform for photonic topological insulators
In the past decade, the field of topological photonics has gained prominence exhibiting consequential effects in quantum information science, lasing, and large-scale integrated photonics. Many of these topological systems exhibit protected states, enabling robust travel along their edges without being affected by defects or disorder. Nonetheless, conventional topological structures often lack the flexibility for implementing different topological models and for tunability postfabrication. Here, we present a method to implement magnetic-like Hamiltonians supporting topologically protected edge modes on a general-purpose programmable silicon photonic mesh of interferometers. By reconfiguring the lattice onto a two-dimensional mesh of ring resonators with carefully tuned couplings, we show robust edge state transport even in the presence of manufacturing tolerance defects. We showcase the system’s reconfigurability by demonstrating topological insulator lattices of different sizes and shapes and introduce edge and bulk defects to underscore the robustness of the photonic edge states. Our study paves the way for the implementation of photonic topological insulators on general-purpose programmable photonics platforms.
Journal Article