Bioconjugates: A New Class of Therapeutics for Cancer Treatment

مثل المرافقات الحيوية فئة جديدة من العلاجات التي تبشر بالخير في علاج السرطان. تتشكل هذه المركبات من خلال الجمع بين جزيء استهداف ، مثل الجسم المضاد أو الببتيد ، مع عامل علاجي ، مثل عقار العلاج الكيميائي أو السم. يسمح هذا النهج بالتسليم المستهدف للعامل العلاجي للخلايا السرطانية ، وتقليل الأضرار التي تلحق بالأنسجة السليمة وتقليل الآثار الجانبية. أظهرت المقارنات الحيوية إمكانات كبيرة في الدراسات قبل السريرية والسريرية ، مع العديد من الأدوية المعتمدة من إدارة الغذاء والدواء والمتاحة حاليًا لعلاج السرطان. هناك عدة أنواع من المركبات الحيوية التي يتم تطويرها حاليًا لعلاج السرطان ، بما في ذلك اتحادات الأدوية والأجسام المضادة ADCs، وتقارنات العقاقير الببتيدية PDCs، واتحادات الجسيمات النانوية (NDCs). ADCs هي أكثر أنواع المركبات الحيوية ترسخًا وقد تمت الموافقة عليها لعلاج عدة أنواع من السرطان ، بما في ذلك سرطان الثدي وسرطان الغدد الليمفاوية وسرطان الدم. PDCs و NDCs هي فئات جديدة من المركبات الحيوية التي لا تزال في مراحل التطور السريرية قبل السريرية والمبكرة. تهدف الأبحاث الجارية في هذا المجال إلى تحسين فعالية وسلامة المركبات الحيوية وتوسيع استخدامها لتشمل مجموعة واسعة من أنواع السرطان. مع استمرار تقدم البحث في هذا المجال ، يمكننا أن نتوقع رؤية المزيد من العقاقير الموصلة بيولوجيًا المبتكرة والفعالة التي يتم تطويرها في المستقبل. تم تصميم هذه الأدوية لاستهداف خلايا سرطانية معينة ، مع ترك الخلايا السليمة دون أن تصاب بأذى ، ولديها القدرة على إحداث ثورة في علاج السرطان. علاوة على ذلك ، يمكن تصميم المقارنات الحيوية لتناسب المرضى الفرديين ، مما يسمح بعلاج السرطان المخصص والموجه. مثل المرافقات الحيوية فئة جديدة من العلاجات التي تبشر بالخير في علاج السرطان. تتشكل هذه المركبات من خلال الجمع بين جزيء استهداف ، مثل الجسم المضاد أو الببتيد ، مع عامل علاجي ، مثل عقار العلاج الكيميائي أو السم. يسمح هذا النهج بالتسليم المستهدف للعامل العلاجي للخلايا السرطانية ، وتقليل الأضرار التي تلحق بالأنسجة السليمة وتقليل الآثار الجانبية. أظهرت المقارنات الحيوية إمكانات كبيرة في الدراسات قبل السريرية والسريرية ، مع العديد من الأدوية المعتمدة من إدارة الغذاء والدواء والمتاحة حاليًا لعلاج السرطان. هناك عدة أنواع من المركبات الحيوية التي يتم تطويرها حاليًا لعلاج السرطان ، بما في ذلك اتحادات الأدوية والأجسام المضادة ADCs، وتقارنات العقاقير الببتيدية PDCs، واتحادات الجسيمات النانوية (NDCs). ADCs هي أكثر أنواع المركبات الحيوية ترسخًا وقد تمت الموافقة عليها لعلاج عدة أنواع من السرطان ، بما في ذلك سرطان الثدي وسرطان الغدد الليمفاوية وسرطان الدم. PDCs و NDCs هي فئات جديدة من المركبات الحيوية التي لا تزال في مراحل التطور السريرية قبل السريرية والمبكرة. تهدف الأبحاث الجارية في هذا المجال إلى تحسين فعالية وسلامة المركبات الحيوية وتوسيع استخدامها لتشمل مجموعة واسعة من أنواع السرطان. مع استمرار تقدم البحث في هذا المجال ، يمكننا أن نتوقع رؤية المزيد من العقاقير الموصلة بيولوجيًا المبتكرة والفعالة التي يتم تطويرها في المستقبل. تم تصميم هذه الأدوية لاستهداف خلايا سرطانية معينة ، مع ترك الخلايا السليمة دون أن تصاب بأذى ، ولديها القدرة على إحداث ثورة في علاج السرطان. علاوة على ذلك ، يمكن تصميم المقارنات الحيوية لتناسب المرضى الفرديين ، مما يسمح بعلاج السرطان المخصص والموجه.Bioconjugates represent a novel class of therapeutics that offer promise in the treatment of cancer. These compounds are formed by combining a targeting molecule, such as an antibody or peptide, with a therapeutic agent, such as a chemotherapy drug or toxin. This approach allows for targeted delivery of the therapeutic agent to cancer cells, minimizing damage to healthy tissues and reducing side effects. Bioconjugates have shown significant potential in preclinical and clinical studies, with several FDA-approved drugs currently available for the treatment of cancer. There are several types of bioconjugates currently being developed for cancer treatment, including antibody-drug conjugates (ADCs), peptide-drug conjugates (PDCs), and nanoparticle-drug conjugates (NDCs). ADCs are the most well-established type of bioconjugate and have been approved for the treatment of several types of cancer, including breast cancer, lymphoma, and leukemia. PDCs and NDCs are newer classes of bioconjugates that are still in the preclinical and early clinical stages of development. Ongoing research in this field aims to improve the efficacy and safety of bioconjugates and expand their use to a wider range of cancer types. As research in this field continues to advance, we can expect to see even more innovative and effective bioconjugate drugs being developed in the future. These drugs are designed to target specific cancer cells, while leaving healthy cells unharmed, and have the potential to revolutionize cancer treatment. Furthermore, bioconjugates can be tailored to individual patients, allowing for personalized and targeted cancer therapy. &nbsp

LINEARNO PROGRAMIRANJE KAO ALAT ZA PROJEKTIRANJE SIROVINSKE SMJESE U TVORNICI CEMENTA

This study uses linear programming to develop a methodology for selecting the best raw material mix in an ASCOM cement plant in Egypt. In cement factories, this type adheres to Egyptian chemical composition criteria for raw feed (e.g. 82.5% calcium carbonate, 14.08% silica, 2.5% alumina and 0.92% iron oxide). Furthermore, the model is bound by industry-specific characteristics (e.g. lime saturation factor, silica modulus, alumina modulus and loss of ignition). The results reveal that the model is able to accurately reproduce the mixing of high-quality feed with varying constituent percentages. It is also capable of determining the combining limitations of each ingredient. Furthermore, it demonstrates optimality for additive sourcing short-term planning and capping limestone quality to meet changeable component combinations. Additionally, improving the raw mix reduces limestone feed quality from 51 to 50.6%, resulting in the inclusion of extra limestone reserves.Studija prikazuje metodu linearnoga programiranja uporabljenu sa svrhom odabira najbolje sirovinske smjese u tvornici cementa ASCOM (Egipat). Takva smjesa poštuje egipatske standarde kemijskoga sastava sirovine (npr. 82,5 % kalcijeva karbonata, 14,08 % silikata, 2,5 % aluminijeva oksida, 0,92 % željeznoga oksida). Također, model je uvjetovan industrijskim standardima (npr. faktorom zasićenja vapnom, silikatnim i aluminatnim modulom te gubitkom (oksida) žarenjem). Modelom se mogla točno izračunati visokokvalitetna mješavina različitih (postotnih) komponenti te je dokazan kao optimalan za brz izračun raznih aditiva i postizanje najveće kvalitete vapnenačke sirovine uz doziranje ostalih komponenti. Time je udjel vapnenca bilo moguće smanjiti na 50,6 – 51 %, što je otvorilo put eksploataciji dodatnih rezervi te sirovine

Bioprospecting autochthonous marine microalgae strain from the Arabian Gulf Seawater, Kuwait for biofuel feedstocks

Bioprospecting programs are the key to increasing the current portfolio of indigenous microalgal strains accessible for different applications in microalgal biotechnology. In this work, nine fast-growing microalgal strains isolated from Kuwait's Arabian/Persian Gulf coastal waters were evaluated for their potential as biofuel feedstocks. 18S rRNA gene sequencing showed that the strains belong to five different genera: Chlorella, Nannochloris, Scenedesmus, Tetraselmis, and Nannochloropsis. In terms of the total lipid content, in comparison to the other strains, Tetraselmis sp. KUBS13G and Tetraselmis sp. KUBS16G displayed higher lipid contents of 29.56% dry weight (DW) and 26.13% DW, respectively, dominated by palmitic and oleic acids. Fuel properties calculated from the fatty acid methyl esters (FAMES) by empirical equations were compared with EN14214 (European) and ASTM D6751--02 (American) biodiesel standards. Multicriteria decision analysis (MCDA) methods, such as the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GALA), were used to select suitable microalgae for biofuel feedstock based on their biodiesel fuel properties. Overall, the results suggested that the indigenous microalgal strain Tetraselmis, particularly Tetraselmis sp. KUBS37G, and Scenedesmus sp. KUB Sl7R are the most suitable strains for biofuel feedstock owing to their improved fuel properties, such as density (rho) (0.88 g cm-3), low kinematic viscosity (3.1 mm2 s-1), high cetane number (54 and 56, respectively), high oxidation stability (14.6 hr and 14.8 hr), and cold filter plugging point (1.0 degrees C and -6.1 degrees C).info:eu-repo/semantics/publishedVersio

The diabesity health economic crisis - the size of the crisis in a European island state following a cross-sectional study

Background: Diabetes type 2 and obesity are well-established global epidemics and contributors to clinical, social and economic health burdens. The prevalence rates of these diseases are still on the rise among countries resulting in a corresponding public health burden. The Mediterranean island of Malta, known for it’s high diabetes and obesity rates, provides a good fundamental basis to portray the economical health burden of these diseases. Method: A recent randomised stratified representative cross-sectional survey conducted in Malta tackling diabetes, obesity and other determinants, was used to work out the population prevalence of these diseases. The cost burden of diabetes and obesity, based on published data, was incorporated to the established population prevalence rates, in order to estimate the Maltese economical burden. Projections to the year 2050 by a bottom-up prevalence based design were performed. Results: One eight of the Maltese adults (25 to 64 years) suffered from diabetes out of which approximately 10,000 adults were unaware of the disease. Alarmingly, more than a third of the Maltese population suffer from obesity. The approximate health care costs (direct and indirect) for the diabetic adult population was of €29,159,217 (€21,994,676 - €38,919,121) annually, amounting to 3.64% (2.75–4.875%) of the total health expenditure in Malta. The obesity cost burden was of €23,732,781 (€21,514,972-€26,049,204) annually contributing for 2.97% (2.69–3.26%) of the total health expenditure. The projected prevalence and costs for 2050 exhibited an estimated cost burden increase of €33,751,487 (€25,458,606–€45,048,473) for the diabetes mellitus population and €46,532,294 (€42,183,889–€51,074,049) for the obese population. These projected cost burdens are expected to increase exponentially the total health care expenditure in Malta by 2050. Conclusion: Having an understanding of the prevalence and the economic cost burden of diabetes and obesity within a country, along with projections of the expected burden will enable policy and public health officials to clearly visualize this growing problem. It also helps in establishing effective preventive strategies and screening programs targeting these epidemics.peer-reviewe

Risperidone oral disintegrating mini-tablets: A robust-product for pediatrics

This study was aimed at developing risperidone oral disintegrating mini-tablets (OD-mini-tablets) as age-appropriate formulations and to assess their suitability for infants and pediatric use. An experimental Box-Behnken design was applied to assure high quality of the OD-mini-tablets and reduce product variability. The design was employed to understand the influence of the critical excipient combinations on the production of OD-mini-tablets and thus guarantee the feasibility of obtaining products with dosage form uniformity. The variables selected were mannitol percent in Avicel (X1), swelling pressure of the superdisintegrant (X2), and the surface area of Aerosil as a glidant (X3). Risperidone-excipient compatibilities were investigated using FTIR and the spectra did not display any interaction. Fifteen formulations were prepared and evaluated for pre- and post-compression characteristics. The prepared OD-mini-tablet batches were also assessed for disintegration in simulated salivary fluid (SSF, pH 6.2) and in reconstituted skimmed milk. The optimized formula fulfilled the requirements for crushing strength of 5 kN with minimal friability, disintegration times of 8.4 and 53.7 s in SSF and skimmed milk, respectively. This study therefore proposes risperidone OD-mini-tablet formula having robust mechanical properties, uniform and precise dosing of medication with short disintegration time suitable for pediatric use

Spectrum of Paediatric Lysosomal Storage Disorders in Oman

Objectives: The aim of this study was to look at the spectrum of paediatric lysosomal disorders in Oman. Lysosomal storage disorders (LSDs) are a heterogeneous group of inherited metabolic diseases. Few studies on the birth prevalence and prevalence of LSDs have been reported from the Arabian Peninsula. Methods: We studied 86 children with LSDs diagnosed over a period of nine years, from June 1998 to May 2007. Detailed clinical data, including age of onset, sex, age and mode of first presentation, and presence of consanguinity were collected. Results: Our data showed the combined birth prevalence for all LSDs in Oman to be around 1 in 4,700 live births. Sphingolipidoses was the most common group of disorder encountered (47.7%), followed by neuronal ceroid lipofuscinoses (NCL) (23.2%) and mucopolysaccharidoses (MPS) (23.2%). The proportion of consanguineous marriages in our series was found to be 87.5%. Conclusion: Our data represent the birth prevalence and clinicalspectrum of such disorders in Oman, one of the highly consanguineous societies in the Middle East.

Obsessive-Compulsive Disorder in Primary Care: Overview on Diagnosis and Management

Background: Obsessive-Compulsive Disorder (OCD) is a debilitating condition marked by the presence of intrusive obsessions and repetitive compulsions. The primary care setting often serves as the first line of contact for individuals grappling with mental health issues, making it a crucial frontier in the early detection and management of OCD. Therefore, the accurate diagnosis of OCD in such settings is essential for effective management. Objective: This review article aims to provide a comprehensive overview of the diagnostic process for OCD, emphasizing the clinical presentation, differential diagnosis, and various diagnostic tools available. Additionally, it explores current strategies for managing OCD, including pharmacological and psychotherapeutic interventions. Methodology: For this review, a comprehensive literature search was conducted using Google Scholar and PubMed databases. Keywords such as "Diagnosis," "obsessive compulsive disorder," and "management" were employed to narrow down relevant studies. Both qualitative and quantitative research papers were included, while non-English publications and those lacking peer-review were excluded. Results: Core symptoms of OCD include obsessions and compulsions, with the Y-BOCS being a standard measure for diagnosis. Differential diagnosis is essential to distinguish OCD from other conditions. SSRIs have been recognized as first-line pharmacological treatments. CBT, particularly Exposure and Response Prevention, remains a potent psychotherapeutic intervention. Emerging treatments like DBS and TMS offer hope for those unresponsive to conventional treatments. Combination therapies have shown enhanced efficacy in certain cases. Conclusion: The meticulous diagnosis of OCD requires recognizing its core symptoms, ruling out other conditions, and leveraging validated clinical tools. A multi-faceted management approach combining pharmacological and psychological treatments ensures optimal patient outcomes, with ongoing research introducing promising new interventions

Governing Divorce Practices of Somali Finnish Muslims : Does Religious Literacy Matter?

Peer reviewe

Development of nonlaboratory-based risk prediction models for cardiovascular diseases using conventional and machine learning approaches

Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low–middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case–control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities