Malaysian Journal of Medical and Biological Research
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Using Secondary Health Data in Research
Full text linkThe use of data in medical research that was originally collected for different purposes, known as secondary data, is an effective way to conduct reliable and cost-effective studies so as to progress knowledge in medicine. A number of serious practical, ethical and legal issues and concerns about this process exist, however. Ensuring a high level of data quality is imperative to produce reliable results, and researchers may face accessibility problems. Projects designed to alleviate these issues are underway, however, lowering the cost and increasing the access to secondary data even further. Although secondary data is de-identified to protect the confidentiality, ethical problems of individual rights versus the benefit of society persist, leading some to call for a new ‘macroethics’ surrounding data use. Legislation to this end has been introduced in many countries, but issues relating to the exemptions it offers and its interpretability remain. To ensure that the use of secondary data in medical research can continue to accelerate the pace of development in medicine, a global effort involving technological and ethical standardization needs to be developed.
 
Molecular Generators and Optimizers Failure Modes
Full text linkIn recent years, there has been an uptick in interest in generative models for molecules in drug development. In the field of de novo molecular design, these models are used to make molecules with desired properties from scratch. This is occasionally used instead of virtual screening, which is limited by the size of the libraries that can be searched in practice. Rather than screening existing libraries, generative models can be used to build custom libraries from scratch. Using generative models, which may optimize molecules straight towards the desired profile, this time-consuming approach can be sped up. The purpose of this work is to show how current shortcomings in evaluating generative models for molecules can be avoided. We cover both distribution-learning and goal-directed generation with a focus on the latter. Three well-known targets were downloaded from ChEMBL: Janus kinase 2 (JAK2), epidermal growth factor receptor (EGFR), and dopamine receptor D2 (DRD2) (Bento et al. 2014). We preprocessed the data to get binary classification jobs. Before calculating a scoring function, the data is split into two halves, which we shall refer to as split 1/2. The ratio of active to inactive users. Our goal is to train three bioactivity models with equal prediction performance, one to be used as a scoring function for chemical optimization and the other two to be used as performance evaluation models. Our findings suggest that distribution-learning can attain near-perfect scores on many existing criteria even with the most basic and completely useless models. According to benchmark studies, likelihood-based models account for many of the best technologies, and we propose that test set likelihoods be included in future comparisons
Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach
Full text linkBiomarkers that are validated and robust are required for the enhancement of diagnosis, the observation of drug-related activity, therapeutic reactions, and as the blueprint for developing safer and more direct therapeutic efforts for a variety of chronic ailments. Various kinds of biomarkers have proven impactful when it comes to the discovery and development of drugs, but the procedure that involves identifying and verifying ailment-specific biomarkers has proven to be hassling. In recent times, there have been some advancements in multiple omics (also known as multi-omics) methods like transcriptomic, cytometry, genomics, proteomics, metabolomics and imaging. These advancements have made it possible for the discovery and development of distinct biomarkers for complicated chronic ailments to be accelerated expeditiously. In spite of the fact that numerous drawbacks still need to be looked into, ongoing efforts for the discovery and improvement of illness-associated biomarkers will go a long way in optimizing decision-making across the entire process of drug development and expand our comprehension of the infection processes. In addition, when the preclinical biomarkers are effectively translated into the clinic, the way will pave well to an equally effective implementation of personalized therapies throughout complicated illness environments to become beneficial to patients, healthcare service providers and the industry of bio-pharma.
 
Antioxidant and Subchronic Toxicity Study of Myrmecodia Platytyrae (MyP) Water Extract
Full text linkIn this study, Myrmecodia platytyrae (MyP) water extract was investigated to explain the antioxidant property and its safety. Water extract of MyP was prepared and tested for ORAC for each batch of preparations. The MyP water extract was administered daily onto three groups of experimental animals which were Low Dose (LD), Medium Dose (MD) and High Dose (HD) groups for a period of consecutive 28 days according to the OECD GLP guideline (OECD TG 407). The ORAC results showed that MyP water extract has an antioxidant activity for each batch. The subchronic toxicity test showed that MyP water extract product has no observable sub-chronic toxic effect on Sprague Dawley rats. The body weight of rats increased along with proportional food and water intake. In the same way, all hematological, biochemical parameters as well as histopathological observation do not show any abnormal finding. Gross observations, feed and water consumption, urine strip test and animals’ weight during necropsy did not show any difference compared to the control group. In conclusion, MyP water extract is suggested to have a broad safety margin in experimental animals.
 
Utilization of Agricultural Drones in Farming by Harnessing the Power of Aerial Intelligence
Full text linkAgricultural drones, sometimes called uncrewed aerial vehicles (UAVs) or unmanned aerial systems (UAS), have become a game-changing innovation in today\u27s farming practices. These airborne gadgets equipped with sophisticated sensors and imaging capabilities have made agricultural techniques of the past obsolete. This article explores the concept of airborne intelligence and serves as a lens through the many facets of farm drones and their impact on farming. We delve into how drones transform the farm scene, from crop monitoring and precision agriculture to data-driven decision-making, and we look at how drones enable these approaches
Homology Modelling and in Silico Substrate Binding Analysis of a Rhizobium sp. RC1 Haloalkanoic Acid Permease
Full text linkRhizobium sp. RC1 grows on haloalkanoic acid (haloacid) pollutants and expresses a haloacid permease (DehrP) which mediates the uptake of haloacids into the cells. For the first time, we report the homology model and docking analysis of DehrP and proposed its putative binding residues. The Protein Data Bank for protein of similar sequence. Ligand structures were retrieved from the ChemSpider database. The 3-dimensional (3-D) structure of DehrP was modelled based on the structure of Staphylococcus epidermidis glucose: H+ symporter (GlcPse) by Phyre2, refined by 3Drefine and evaluated by ProSA z-score, ERRAT and RAMPAGE. Docking of monobromoacetate, monochloroacetate, dibromoacetate, dichloroacetate, trichloroacetate, and 2,2-dichloropropionate ligands was done with AutoDock vina1.1.2. The 3-D structure of DehrP protein has twelve transmembrane helices. The overall quality factor of the model is ∼91%, with 93.6% of the residues in the favored region and the z-score is within the ≤ 10 limit. The putative H+ binding site residues are Gln133, Asp36, and Arg130. Docking analysis showed that Glu33, Trp34, Phe37, Phe38, Gln165, and Glu370 are potential haloacid interacting residues. DehrP-haloacid complexes had a binding affinity between -2.9 to -4.0 kcal/mol. DehrP has both putative H+ and haloacid binding sites that are most likely involved in the co-transport of H+ and haloacids. DehrP interacts with haloacids majorly through van der Waals and halogen bond interactions and has greater affinity for 2,2-dichloropropionate and could be a specialized chloropropionate uptake system. Site-directed mutagenasis of DehrP binding residues could improve its haloacid binding affinity.
 
Deep Learning-Enhanced Image Segmentation for Medical Diagnostics
Full text linkDeep learning-enhanced picture segmentation has transformed medical diagnostics by accurately and efficiently delineating anatomical features and clinical anomalies. This article examines how deep learning affects medical image segmentation, identifies the main methods, and evaluates the results and obstacles. This study covers recent field research and innovations using secondary data. CNNs, attention mechanisms, and generative models like GANs have increased segmentation performance in neuroimaging, oncology, cardiology, pathology, and radiology. However, issues must still be solved with model interpretability, dependency on massive annotated datasets, and imaging technique variability. Policy implications emphasize the need for consistent imaging methods, data-sharing agreements, and explainable AI to build clinical trust and acceptance. Federated learning requires reformed data privacy laws to protect patient privacy and enable collaborative model development. Innovative research and deliberate policy actions can improve deep learning in medical diagnostics, increasing patient care and clinical outcomes
Automatic Diagnosis of Diabetes Using Machine Learning: A Review
Full text linkThe health sector, like the other sectors, contains a large amount of data that should be used to better understand and treat the various ailments that are prevalent. For example, diabetes is a condition that is becoming more prevalent but that may be managed if discovered at an early stage. The algorithms of machine learning (ML) can be utilized for this purpose. We have examined the various machine learning methods and the attributes that can be utilized to train these algorithms for the purpose of detecting diabetic complications
Effect of Integrated Farmyard Manure and NP Fertilizers Use on Hybrid Maize Yield and Soil Properties in Western Ethiopia
Full text linkA study was carried out to assess the effect of integrated Farmyard Manure (FYM) and inorganic NP fertilizers use on yield and soil properties in Bako-Tibe district of Oromia, western Ethiopia. Five treatments (i.e., 110 kg N ha-1 + 46 kg P2O5 ha-1 (T1), 12 ton FYM ha-1 (T2) , 55 kg N ha-1 + 23 kg P2O5 ha-1 + 6 ton FYM ha-1(T3), 27.5kg N ha-1 + 11.5 kg P2O5 ha-1 + 6 ton FYM ha-1(T4) and the control (T5)) were used in a Randomized Complete Block Design (RCBD) with five replications using five farmers’ fields. Yield and yield related parameters were analyzed using SAS statistical software version 9.0. Economic analysis was performed to compare treatments advantages. The treatment with half the recommended NP (55 kg N ha-1 + 23 kg P2O5 ha-1 + 6 ton FYM ha-1) showed superior plant growth performance as compared to other treatments. Pure use of inorganic NP resulted in high Na, K, Ca and P composition of grain while pure FYM use resulted in high content of Mg and Ca composition. The level of P in grain decreased with the increasing of FYM. Soil fertility parameters considered showed no significance difference (P: 0.05) among the treatments. The mean difference values indicated that use of pure inorganic fertilizer increased soil PH, exchangeable Na, and available S. Use of pure farmyard manure resulted in an increase in the soil exchangeable Na, K, Mg, total Nitrogen, and available K and S. The use of half of the recommended inorganic fertilizer and FYM can enhance soil fertility in addition to yield improvement.
 
Structural Analysis of NaYF4 Solution Processed Nanoparticles for Hela Cell Studies
Full text linkThe NaYF4 nanoparticles were prepared and analyzed. Its structural analysis confirmed the formation of nanocrystals of desired sizes and spectral properties that can be incorporated into Hela cell studies. The internalization of NaYF4 nanoparticles in HeLa cells was determined at different nanoparticles concentrations and for incubation periods from 3 to 24 hours using various techniques. The images revealed a redistribution of nanoparticles inside the cell that increased with incubation time, concentration levels, and depended on the presence of the transfection factor. The study identified factors responsible for effective endocytosis of the NaYF4 nanoparticles to HeLa cells. Thus this procedure or method could be applied to investigate a wide range of future “smart” theranostic agents that may result in be very promising fluorescent probes for imaging real-time cellular dynamics