Knowledge and Perception of Paediatric Drug Dosing: Impact of Paediatric Drug Dosing Workshop.

BACKGROUND: Paediatric patients frequently encounter medication errors caused by the requirement for individualised drug dose estimates based on weight, age variance, and drug pharmacokinetics. One thing contributing to drug dosing errors is the lack of healthcare personnel's knowledge of paediatric drug dosing. The present study aimed to evaluate the knowledge and perception regarding the workshop on paediatric drug dosing among undergraduate pharmacy students. METHOD: A prospective pre-post study was conducted. A virtual workshop on paediatric drug dosing was designed and developed by the clinical pharmacy lecturer from Universiti Sultan Zainal Abidin (UniSZA) for pharmacy students. An online questionnaire with 15 questions regarding knowledge of paediatric drug dosing and perception of the virtual workshop on paediatric drug dosing was used to evaluate pharmacy students' knowledge pre- and post-workshop. RESULT: Twenty-six students took part in the study (100%). In the pre-workshop on paediatric drug dosing calculation, most students had poor knowledge of the paediatric drug dosing calculation, scored 8 out of 15, 26.92% between 9 to 11 and only 11.54% scored ≥ 12. There was a statistically significant difference in median knowledge score between pre- and post-workshop (p< 0.05). Among the students, 73.08% stated that they strongly agreed that the online workshop attracted their attention and 76.92% of students strongly agreed that they were able to calculate paediatric drug dosing after joining the online workshop. CONCLUSION: Results demonstrate that pharmacy students have insufficient knowledge of paediatric drug dosing calculations. Virtual workshop is one strategy that could improve the pharmacy students' knowledge.

Phosphate Restriction Prevents Metabolic Acidosis and Curbs Rise in FGF23 and Mortality in Murine Folic Acid-Induced AKI.

SIGNIFICANCE STATEMENT: Patients with AKI suffer a staggering mortality rate of approximately 30%. Fibroblast growth factor 23 (FGF23) and phosphate (P i ) rise rapidly after the onset of AKI and have both been independently associated with ensuing morbidity and mortality. This study demonstrates that dietary P i restriction markedly diminished the early rise in plasma FGF23 and prevented the rise in plasma P i , parathyroid hormone, and calcitriol in mice with folic acid-induced AKI (FA-AKI). Furthermore, the study provides evidence for P i -sensitive osseous Fgf23 mRNA expression and reveals that P i restriction mitigated calciprotein particles (CPPs) formation, inflammation, acidosis, cardiac electrical disturbances, and mortality in mice with FA-AKI. These findings suggest that P i restriction may have a prophylactic potential in patients at risk for AKI. BACKGROUND: In AKI, plasma FGF23 and P i rise rapidly and are independently associated with disease severity and outcome. METHODS: The effects of normal (NP) and low (LP) dietary P i were investigated in mice with FA-AKI after 3, 24, and 48 hours and 14 days. RESULTS: After 24 hours of AKI, the LP diet curbed the rise in plasma FGF23 and prevented that of parathyroid hormone and calcitriol as well as of osseous but not splenic or thymic Fgf23 mRNA expression. The absence of Pth prevented the rise in calcitriol and reduced the elevation of FGF23 in FA-AKI with the NP diet. Furthermore, the LP diet attenuated the rise in renal and plasma IL-6 and mitigated the decline in renal α -Klotho. After 48 hours, the LP diet further dampened renal IL-6 expression and resulted in lower urinary neutrophil gelatinase-associated lipocalin. In addition, the LP diet prevented the increased formation of CPPs. Fourteen days after AKI induction, the LP diet group maintained less elevated plasma FGF23 levels and had greater survival than the NP diet group. This was associated with prevention of metabolic acidosis, hypocalcemia, hyperkalemia, and cardiac electrical disturbances. CONCLUSIONS: This study reveals P i -sensitive FGF23 expression in the bone but not in the thymus or spleen in FA-AKI and demonstrates that P i restriction mitigates CPP formation, inflammation, acidosis, and mortality in this model. These results suggest that dietary P i restriction could have prophylactic potential in patients at risk for AKI.

A novel method for automated crystal visualization and quantification in murine folic acid-induced acute kidney injury.

Folic acid (FA)-induced acute kidney injury (FA-AKI) is an increasingly prevalent rodent disease model involving the injection of a high dose of FA that culminates in renal FA crystal deposition and injury. However, the literature characterizing the FA-AKI model is sparse and dated in part due to the absence of a well-described methodology for the visualization and quantification of renal FA crystals. Using widely available materials and tools, we developed a straightforward and crystal-preserving histological protocol that can be coupled with automated imaging for renal FA crystal visualization and generated an automated macro for downstream crystal content quantification. The applicability of the method was demonstrated by characterizing the model in male and female C57BL6/JRj mice after 3 and 30 h of FA treatment. Kidneys from both sexes and timepoints showed a bimodal distribution of FA crystal deposition in the cortical and medullary regions while, compared with males, females exhibited higher renal FA crystal content at the 30-h timepoint accompanied by greater kidney weight and higher plasma urea. Despite comparable plasma phosphate concentrations, FA-AKI resulted in a substantially more elevated plasma intact fibroblast growth factor 23 (FGF23) in females, reflected by a similar pattern in osseous Fgf23 mRNA expression. Therefore, the presented method constitutes a valuable tool for the quantification of renal FA crystals, which can aid the mechanistic characterization of the FA-AKI model and serves as a means to control for confounding changes in FA crystallization when using the model for investigating early and prophylactic AKI therapeutic interventions.NEW & NOTEWORTHY Here, we describe a novel method for the visualization and quantification of renal folic acid (FA) crystals in the rodent FA-induced acute kidney injury (FA-AKI) model. The protocol involves a straightforward histological approach followed by fully automated imaging and quantification steps. Applicability was confirmed by showing that the FA-AKI model is sex-dependent. The method can serve as a tool to aid in characterizing FA-AKI and to control for studies investigating prophylactic therapeutic avenues using FA-AKI.

Intact FGF23 predicts serum phosphate improvement after combined nicotinamide and phosphate binder treatment in hemodialysis patients.

Background: Hyperphosphatemia is associated with increased mortality and cardiovascular morbidity of end-stage kidney failure (ESKF) patients. Managing serum phosphate in ESKF patients is challenging and mostly based on limiting intestinal phosphate absorption with low phosphate diets and phosphate binders (PB). In a multi-centric, double-blinded, placebo-controlled study cohort of maintenance hemodialysis patients with hyperphosphatemia, we demonstrated the efficacy of nicotinamide modified release (NAMR) formulation treatment in addition to standard PB therapy in decreasing serum phosphate. Here we aimed to assess the relationship between phosphate, FGF23, inflammation and iron metabolism in this cohort. Methods: We measured the plasma concentrations of intact fibroblast growth factor 23 (iFGF23) and selected proinflammatory cytokines at baseline and Week 12 after initiating treatment. Results: We observed a strong correlation between iFGF23 and cFGF23 (C-terminal fragment plus iFGF23). We identified iFGF23 as a better predictor of changes in serum phosphate induced by NAMR and PB treatment compared with cFGF23. Recursive partitioning revealed at baseline and Week 12, that iFGF23 and cFGF23 together with T50 propensity were the most important predictors of serum phosphate, whereas intact parathyroid hormone (iPTH) played a minor role in this model. Furthermore, we found serum phosphate and iPTH as the best predictors of iFGF23 and cFGF23. Sex, age, body mass index, and markers of inflammation and iron metabolism had only a minor impact in predicting FGF23. Conclusion: Lowering serum phosphate in ESKF patients may depend highly on iFGF23 which is correlated to cFGF23 levels. Serum phosphate was the most important predictor of plasma FGF23 in this ESKF cohort.

Blocking FGF23 signaling improves the growth plate of mice with X-linked hypophosphatemia.

Fibroblast growth factor 23 (FGF23) is a phosphaturic hormone. X-linked hypophosphatemia (XLH) is the most prevalent inherited phosphate wasting disorder due to mutations in the PHEX gene, which cause elevated circulating FGF23 levels. Clinically, it is characterized by growth impairment and defective mineralization of bones and teeth. Treatment of XLH is challenging. Since 2018, neutralizing antibodies against FGF23 have dramatically improved the therapy of XLH patients, although not all patients fully respond to the treatment, and it is very costly. C-terminal fragments of FGF23 have recently emerged as blockers of intact FGF23 signaling. Here, we analyzed the effect on growth and bone of a short 26 residues long C-terminal FGF23 (cFGF23) fragment and two N-acetylated and C-amidated cFGF23 peptides using young XLH mice (Phex C733RMhda mice). Although no major changes in blood parameters were observed after 7 days of treatment with these peptides, bone length and growth plate structure improved. The modified peptides accelerated the growth rate probably by improving growth plate structure and dynamics. The processes of chondrocyte proliferation, death, hypertrophy, and the cartilaginous composition in the growth plate were partially improved in young treated XLH mice. In conclusion, these findings contribute to understand the role of FGF23 signaling in growth plate metabolism and show that this may occur despite continuous hypophosphatemia.

Fabrication and characterisation of novel chitosan-based polymer inclusion membranes and their application in environmental remediation.

Several water and wastewater technologies have been implored for the removal of dyes during wastewater treatments; however; different types have been reportedly found in surface and groundwater systems. Hence, there is a need to investigate other water treatment technologies for the complete remediation of dyes in aquatic environments. In this study, novel chitosan-based polymer inclusion membranes (PIMs) were synthesized for the removal of malachite green dye (MG) which is a recalcitrant of great concern in water. Two types of PIMs were synthesized in this study, the first PIM (PIMs-A) was composed of chitosan, bis-(2-ethylhexyl) phosphate (B2EHP), and dioctyl phthalate (DOP). While, the second PIMs (PIMs-B) were composed of chitosan, Aliquat 336, and DOP. The physico-thermal stability of the PIMs was investigated using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA), both PIMs demonstrated good stability with a weak intermolecular force of attraction amongst the various components of the membranes. The effects of the initial concentration of MG, pH of the MG solution, stripping solution, and time were investigated. At optimum conditions, both membranes (PIM-A and B) recorded the highest efficiencies of 96 % and 98 % at pH 4 and initial contaminants concentration of 50 mg/L, respectively. Finally, both PIMs were used for the removal of MG in different environmental samples (river water, seawater, and tap water) with an average removal efficiency of 90 %. Thus, the investigated PIMs can be considered a potential suitable technique for the removal of dyes and other contaminants from aquatic matrices.

Are probiotics, prebiotics, and synbiotics beneficial in primary thyroid diseases? A systematic review with meta-analysis.

INTRODUCTION AND OBJECTIVE: A number of studies indicate the presence of a thyroid-gut axis and the important influence of the gut microbiota on thyroid function. As prebiotics, probiotics and synbiotics show therapeutic potential in the treatment of intestinal dysbiosis, the aim of this review is to evaluate the efficacy of their supplementation in primary thyroid diseases. REVIEW METHODS: Electronic databases (Ovid MEDLINE, Embase, CENTRAL), registers of clinical trials, and grey literature up to 6 October 2022 were searched for randomised controlled trials (RCTs) meeting pre-specified inclusion criteria. The protocol was registered in PROSPERO (CRD42021235054). BRIEF DESCRIPTION OF THE STATE OF KNOWLEDGE: After screening 1,721 references, two RCTs were identified, which included 136 hypothyroid participants in total. Meta-analysis of the results after eight weeks of supplementation with predominantly Lactobacillus and Bifidobacterium strains indicated a clinically and statistically nonsignificant decrease in TSH (MD -0.19 mIU/L; 95% CI -0.43 to 0.06; I2= 0%), and no effect on fT3 levels (MD 0.01 pg/mL; 95% CI-0.16 to 0.18; I2= 0%). Data from single studies indicated no significant change in the levels of fT4, thyroid auto-antibodies, BMI, levothyroxine doses, and severity of symptoms measured with validated scales. Only constipation scores showed significant improvement (MD -8.71 points in the Faecal Incontinence Questionnaire; 95% CI -15.85 to -1.57; I2= 0%). SUMMARY: Low-certainty evidence from two randomised trials, suggests that routine administration of probiotics, prebiotics or synbiotics may result in little to no benefit in patients with primary hypothyroidism.

Fabrication of chitosan@activated carbon composites in EmimAc for Cd(II) adsorption from aqueous solution: Experimental, optimization and DFT study.

Adsorption efficiency of a duo-material blend featuring the fabrication of modified chitosan adsorbents (powder (C-emimAc), bead (CB-emimAc) and sponge (CS-emimAc)) for the removal of Cd(II) from aqueous solution was investigated. The chitosan@activated carbon (Ch/AC) blend was developed in a green ionic solvent, 1-ethyl-3-methyl imidazolium acetate (EmimAc) and its characteristics was examined using FTIR, SEM, EDX, BET and TGA. The possible mechanism of interaction between the composites and Cd(II) was also predicted using the density functional theory (DFT) analysis. The interactions of various blend forms (C-emimAc, CB-emimAc and CS-emimAc) with Cd(II) gave better adsorption at pH 6. The composites also present excellent chemical stability in both acidic and basic conditions. The monolayer adsorption capacities obtained (under the condition 20 mg/L [Cd], adsorbent dosage 5 mg, contact time 1 h) for the CB-emimAc (84.75 mg/g) > C-emimAc (72.99 mg/g) > CS-emimAc (55.25 mg/g), as this was supported by their order of increasing BET surface area (CB-emimAc (120.1 m2/g) > C-emimAc (67.4 m2/g) > CS-emimAc (35.3 m2/g)). The feasible adsorption interactions between Cd(II) and Ch/AC occurs through the O-H and N-H groups of the composites, as supported by DFT analysis in which an electrostatic interactions was predicted as the dominant force. The interaction energy (-1309.35 eV) calculated via DFT shows that the Ch/AC with amino (-NH) and hydroxyl (-OH) groups are more effective with four significant electrostatic interactions with the Cd(II) ion. The various form of Ch/AC composites developed in EmimAc possess good adsorption capacity and stability for the adsorption Cd(II).

On finding natural antibiotics based on TCM formulae.

CONTEXT: Novel kinds of antibiotics are needed to combat the emergence of antibacterial resistance. Natural products (NPs) have shown potential as antibiotic candidates. Current experimental methods are not yet capable of exploring the massive, redundant, and noise-involved chemical space of NPs. In silico approaches are needed to select NPs as antibiotic candidates. OBJECTIVE: This study screens out NPs with antibacterial efficacy guided by both TCM and modern medicine and constructed a dataset aiming to serve the new antibiotic design. METHOD: A knowledge-based network is proposed in this study involving NPs, herbs, the concepts of TCM, and the treatment protocols (or etiologies) of infectious in modern medicine. Using this network, the NPs candidates are screened out and compose the dataset. Feature selection of machine learning approaches is conducted to evaluate the constructed dataset and statistically validate the im- portance of all NPs candidates for different antibiotics by a classification task. RESULTS: The extensive experiments prove the constructed dataset reaches a convincing classification performance with a 0.9421 weighted accuracy, 0.9324 recall, and 0.9409 precision. The further visu- alizations of sample importance prove the comprehensive evaluation for model interpretation based on medical value considerations.

Transcriptional landscape of Burkholderia pseudomallei cultured under environmental and clinical conditions.

Burkholderia pseudomallei, a Gram-negative pathogen, is the causative agent of melioidosis in humans. This bacterium can be isolated from the soil, stagnant and salt-water bodies, and human and animal clinical specimens. While extensive studies have contributed to our understanding of B. pseudomallei pathogenesis, little is known about how a harmless soil bacterium adapts when it shifts to a human host and exhibits its virulence. The bacterium's large genome encodes an array of factors that support the pathogen's ability to survive under stressful conditions, including the host's internal milieu. In this study, we performed comparative transcriptome analysis of B. pseudomallei cultured in human plasma versus soil extract media to provide insights into B. pseudomallei gene expression that governs bacterial adaptation and infectivity in the host. A total of 455 genes were differentially regulated; genes upregulated in B. pseudomallei grown in human plasma are involved in energy metabolism and cellular processes, whilst the downregulated genes mostly include fatty acid and phospholipid metabolism, amino acid biosynthesis and regulatory function proteins. Further analysis identified a significant upregulation of biofilm-related genes in plasma, which was validated using the biofilm-forming assay and scanning electron microscopy. In addition, genes encoding known virulence factors such as capsular polysaccharide and flagella were also overexpressed, suggesting an overall enhancement of B. pseudomallei virulence potential when present in human plasma. This ex vivo gene expression profile provides comprehensive information on B. pseudomallei's adaptation when shifted from the environment to the host. The induction of biofilm formation under host conditions may explain the difficulty in treating septic melioidosis.

A Case of Hypermotor Seizures in Posterior Insular Cortex Epilepsy.

Insular seizure is a rare entity. Insular spikes spread to the temporal, parietal, and frontal lobes and clinically manifest with seizure semiology specific to these areas. We report the case of a 19-year-old male patient who presented with complaints of left-sided hemimotor tonic-clonic focal seizures of the limbs occurring three times per day. Neuroimaging showed cortical-subcortical right posterior insular cortex hyperintensities on fluid-attenuated inversion recovery (FLAIR) sequence and T2-weighted MRI with no significant diffusion restriction on apparent diffusion coefficient (ADC) and no post-contrast enhancement, suggesting focal cortical dysplasia of right posterior insular cortex. Electroencephalogram (EEG) showed right frontal epileptiform activity with secondary bilateral synchrony. The patient's atypical hemimotor tonic-clonic focal seizure, the conventional video EEG showing right frontal spikes synchronizing with bilateral temporal ictal spikes, and insular cortical dysplasia on MRI led us to a diagnosis of insular epilepsy.

Transitioning from Soil to Host: Comparative Transcriptome Analysis Reveals the Burkholderia pseudomallei Response to Different Niches.

Burkholderia pseudomallei, a soil and water saprophyte, is responsible for the tropical human disease melioidosis. A hundred years since its discovery, there is still much to learn about B. pseudomallei proteins that are essential for the bacterium's survival in and interaction with the infected host, as well as their roles within the bacterium's natural soil habitat. To address this gap, bacteria grown under conditions mimicking the soil environment were subjected to transcriptome sequencing (RNA-seq) analysis. A dual RNA-seq approach was used on total RNA from spleens isolated from a B. pseudomallei mouse infection model at 5 days postinfection. Under these conditions, a total of 1,434 bacterial genes were induced, with 959 induced in the soil environment and 475 induced in bacteria residing within the host. Genes encoding metabolism and transporter proteins were induced when the bacteria were present in soil, while virulence factors, metabolism, and bacterial defense mechanisms were upregulated during active infection of mice. On the other hand, capsular polysaccharide and quorum-sensing pathways were inhibited during infection. In addition to virulence factors, reactive oxygen species, heat shock proteins, siderophores, and secondary metabolites were also induced to assist bacterial adaptation and survival in the host. Overall, this study provides crucial insights into the transcriptome-level adaptations which facilitate infection by soil-dwelling B. pseudomallei. Targeting novel therapeutics toward B. pseudomallei proteins required for adaptation provides an alternative treatment strategy given its intrinsic antimicrobial resistance and the absence of a vaccine. IMPORTANCE Burkholderia pseudomallei, a soil-dwelling bacterium, is the causative agent of melioidosis, a fatal infectious disease of humans and animals. The bacterium has a large genome consisting of two chromosomes carrying genes that encode proteins with important roles for survival in diverse environments as well as in the infected host. While a general mechanism of pathogenesis has been proposed, it is not clear which proteins have major roles when the bacteria are in the soil and whether the same proteins are key to successful infection and spread. To address this question, we grew the bacteria in soil medium and then in infected mice. At 5 days postinfection, bacteria were recovered from infected mouse organs and their gene expression was compared against that of bacteria grown in soil medium. The analysis revealed a list of genes expressed under soil growth conditions and a different set of genes encoding proteins which may be important for survival, replication, and dissemination in an infected host. These proteins are a potential resource for understanding the full adaptation mechanism of this pathogen. In the absence of a vaccine for melioidosis and with treatment being reliant on combinatorial antibiotic therapy, these proteins may be ideal targets for designing antimicrobials to treat melioidosis.

Annona muricata: Comprehensive Review on the Ethnomedicinal, Phytochemistry, and Pharmacological Aspects Focusing on Antidiabetic Properties.

Plants have played an important role over the centuries in providing products that have been used to help combat ailments and diseases. Many products originating from fresh, dried-plant materials, or extracts are utilized as community remedies in traditional practices or even in modern medicine. The Annonaceae family contains different types of bioactive chemical properties, such as alkaloids, acetogenins, flavonoids, terpenes, and essential oil, meaning the plants in this family are potential therapeutic agents. Belonging to the Annonaceae family, Annona muricata Linn. has recently attracted the attention of scientists for its medicinal value. It has been utilized as a medicinal remedy since ancient times to treat and improve various diseases, for example, diabetes mellitus, hypertension, cancer, and bacterial infections. This review, therefore, highlights the important characteristic and therapeutic effect of A. muricata along with future perspectives on its hypoglycemic effect. The most-common name is soursop, referring to its sour and sweet flavors, while in Malaysia, this tree is commonly called 'durian belanda'. Furthermore, A. muricata contains a high content of phenolic compounds in the roots and leaves. In vitro and in vivo studies have shown that A. muricata has the pharmacological effects of anti-cancer, anti-microbial, antioxidant, anti-ulcer, anti-diabetic, anti-hypertensive, and wound healing. With regard to its anti-diabetic effect, mechanisms of inhibiting glucose absorption via α-glucosidase and α-amylase activity inhibition, increasing glucose tolerance and glucose uptake by peripheral tissues, and stimulating insulin release or acting like insulin were deeply discussed. There is still a significant research gap, and future studies are required to conduct detailed investigations and gain a better molecular understanding of A. muricata's anti-diabetic potential, especially by using the metabolomics approach.

Deep Learning Approach for Predicting the Therapeutic Usages of Unani Formulas towards Finding Essential Compounds.

The use of herbal medicines in recent decades has increased because their side effects are considered lower than conventional medicine. Unani herbal medicines are often used in Southern Asia. These herbal medicines are usually composed of several types of medicinal plants to treat various diseases. Research on herbal medicine usually focuses on insight into the composition of plants used as ingredients. However, in the present study, we extended to the level of metabolites that exist in the medicinal plants. This study aimed to develop a predictive model of the Unani therapeutic usage based on its constituent metabolites using deep learning and data-intensive science approaches. Furthermore, the best prediction model was then utilized to extract important metabolites for each therapeutic usage of Unani. In this study, it was observed that the deep neural network approach provided a much better prediction model than other algorithms including random forest and support vector machine. Moreover, according to the best prediction model using the deep neural network, we identified 118 important metabolites for nine therapeutic usages of Unani.

A Review on Nonlocal Theories in Fatigue Assessment of Solids.

A review of nonlocal theories utilized in the fatigue and fracture modeling of solid structures is addressed in this paper. Numerous papers have been studied for this purpose, and various nonlocal theories such as the nonlocal continuum damage model, stress field intensity model, peridynamics model, elastic-plastic models, energy-based model, nonlocal multiscale model, microstructural sensitive model, nonlocal lattice particle model, nonlocal high cycle fatigue model, low cycle fatigue model, nonlocal and gradient fracture criteria, nonlocal coupled damage plasticity model and nonlocal fracture criterion have been reviewed and summarized in the case of fatigue and fracture of solid structures and materials.

Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions.

The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain-life models, i.e., Morrow and Smith-Watson-Topper, considered a mean stress effect and strain amplitude; nevertheless, it excluded the load sequence effect, which involves the fatigue crack closure that is subjected to overload or underload. A FESEM-EDX analysis is conducted to characterise the failure features that occurred on the leaf spring. A finite element is simulated to determine the critical region in order to obtain the strain load behaviour. In addition, the strain signal is captured experimentally at 500 Hz for 100 s under operating conditions for three different road loads based on the critical location obtained from the finite element analysis. The fatigue life correlation shows that the Pearson correlation coefficients are greater than 0.9, which indicates the effective strain damage model is linearly correlated with the strain-life models. The fatigue life data are modelled using extreme value distribution by considering the random strain loads as extreme data. The reliability rate for the fatigue life is reported to be more than 0.59 within the hazard rate range of 9.6 × 10-8 to 1.2 × 10-7 based on the mean cycle to the failure point. Hence, the effective strain damage model is proposed for a fatigue reliability assessment under extreme conditions with higher reliability and provides fatigue life prediction when subjected to cycle sequence effects.

Cooperative Power-Domain NOMA Systems: An Overview.

Interference has been a key roadblock against the effectively deployment of applications for end-users in wireless networks including fifth-generation (5G) and beyond fifth-generation (B5G) networks. Protocols and standards for various communication types have been established and utilised by the community in the last few years. However, interference remains a key challenge, preventing end-users from receiving the quality of service (QoS) expected for many 5G applications. The increased need for better data rates and more exposure to multimedia information lead to a non-orthogonal multiple access (NOMA) scheme that aims to enhance spectral efficiency and link additional applications employing successive interference cancellation and superposition coding mechanisms. Recent work suggests that the NOMA scheme performs better when combined with suitable wireless technologies specifically by incorporating antenna diversity including massive multiple-input multiple-output architecture, data rate fairness, energy efficiency, cooperative relaying, beamforming and equalization, network coding, and space-time coding. In this paper, we discuss several cooperative NOMA systems operating under the decode-and-forward and amplify-and-forward protocols. The paper provides an overview of power-domain NOMA-based cooperative communication, and also provides an outlook of future research directions of this area.

A comprehensive review of anionic azo dyes adsorption on surface-functionalised silicas.

Surface -functionalised silica networks are advanced adsorbents. They have been given much attention for treating wastewater using the adsorption technique due to the silanol reactivity, resulting in strong binding affinities towards many pollutants. This review discusses the removal of anionic azo dyes utilising various functional groups such as amines, surfactants, polymers, macrocyclic, and other chelating groups functionalised on silica's surface. This review also reveals the steadily increasing interest in surface-functionalised silicas as adsorbents, emphasising the scholarly advancements in this field as a platform for future research. For that, adsorption capacities with different experimental conditions have been compared. The possible adsorption mechanisms, rate-limiting step, and factors affecting the anionic azo dye adsorption process have been comprehensively discussed. This review discloses that adsorbent characteristics such as porosity and functional groups, besides structural properties of an anionic azo dye, significantly affect adsorption. The adsorption process followed the Langmuir isotherm and pseudo-second-order models, with a predominantly spontaneous and endothermic nature. Multiple interactions, including electrostatic interaction, π-π interactions, and hydrogen bonding, are observed between dyes and functionalised silicas, indicating the adsorption process's complexity. Regeneration and cost-economic analysis are also presented to provide a roadmap for sustainable improvements. Chemical and biological regeneration techniques restore > 80% of the spent functionalised silicas. There is a significant opportunity to improve their efficiencies and regenerability, resulting in surface-functionalised silicas being used commercially instead of only in the laboratory. Finally, future research has been proposed by identifying current research gaps, particularly concerning the application of functionalised silicas in wastewater treatment.

Prediction of Potential Natural Antibiotics Plants Based on Jamu Formula Using Random Forest Classifier.

Jamu is the traditional Indonesian herbal medicine system that is considered to have many benefits such as serving as a cure for diseases or maintaining sound health. A Jamu medicine is generally made from a mixture of several herbs. Natural antibiotics can provide a way to handle the problem of antibiotic resistance. This research aims to discover the potential of herbal plants as natural antibiotic candidates based on a machine learning approach. Our input data consists of a list of herbal formulas with plants as their constituents. The target class corresponds to bacterial diseases that can be cured by herbal formulas. The best model has been observed by implementing the Random Forest (RF) algorithm. For 10-fold cross-validations, the maximum accuracy, recall, and precision are 91.10%, 91.10%, and 90.54% with standard deviations 1.05, 1.05, and 1.48, respectively, which imply that the model obtained is good and robust. This study has shown that 14 plants can be potentially used as natural antibiotic candidates. Furthermore, according to scientific journals, 10 of the 14 selected plants have direct or indirect antibacterial activity.