Browse publications by year: 2023

Toxicity and teratogenicity effects of valproic acid on zebrafish (Danio rerio) embryos in relation to autism spectrum disorder

Saleh Hodin NA, Chong SG, Bakar NA, Fahmi MSAM, Ramlan NF, Hamid NNAZZ, et al.

Birth Defects Res, 2023 Oct 01;115(16):1475-1485.
PMID: 37507847 DOI: 10.1002/bdr2.2227

Valproic acid (VPA) is a widely prescribed antiepileptic drug with various medicinal efficacies. Accumulated evidence implied that prenatal exposure to VPA is highly associated with autism spectrum disorder (ASD). In this study, the zebrafish were exposed to a set of VPA concentrations (0, 5, 10, 20, 40, 80, 160, 320, 640, 1280, and 2560 μM) at 5 h post fertilization (hpf) to 120 hpf. The adverse effects of VPA were extensively studied through the evaluations on the mortality, heartbeats, spontaneous tail coiling, and hatching rate. Morphological observations were conducted at 120 hpf, following the exposure termination. Basic locomotor responses and anxiety-like behavioral alterations evaluated for behavioral impairments are the hallmark feature of ASD. The exposure to VPA at teratogenic concentrations reduced the aforementioned parameters in a dose-dependent manner (p ≤ .05). At the selected non-teratogenic concentrations of VPA, the treated larvae demonstrated profound alterations of basic locomotor responses. No significant changes of anxiety and thigmotactic behaviors were observed on the VPA-treated fish compared to the control (p ≥ .005). This study depicted that embryonic zebrafish exposure to VPA produced significant toxicity and teratogenicity effects as well as the alterations of basic behavioral responses. Overall, this study provides a fundamental insight of the toxicity effects at morphological and behavioral levels to facilitate the understanding of ASD mechanisms at different molecular levels.

MeSH terms: Autism Spectrum Disorder*; Animals; Anticonvulsants/toxicity; Behavior, Animal; Teratogens/toxicity; Valproic Acid/toxicity; Zebrafish; Teratogenesis*
Fulltext Astaxanthin as a Potent Antioxidant for Promoting Bone Health: An Up-to-Date Review

Davan I, Fakurazi S, Alias E, Ibrahim N', Hwei NM, Hassan H

Antioxidants (Basel), 2023 Jul 24;12(7).
PMID: 37508018 DOI: 10.3390/antiox12071480

In recent years, bone loss and its associated diseases have become a significant public health concern due to increased disability, morbidity, and mortality. Oxidative stress and bone loss are correlated, where oxidative stress suppresses osteoblast activity, resulting in compromised homeostasis between bone formation and resorption. This event causes upregulation of bone remodeling turnover rate with an increased risk of fractures and bone loss. Therefore, supplementation of antioxidants can be proposed to reduce oxidative stress, facilitate the bone remodeling process, suppress the initiation of bone diseases, and improve bone health. Astaxanthin (3,3'-dihydroxy-4-4'-diketo-β-β carotene), a potent antioxidant belonging to the xanthophylls family, is a potential ROS scavenger and could be a promising therapeutic nutraceutical possessing various pharmacological properties. In bone, astaxanthin enhances osteoblast differentiation, osteocytes numbers, and/or differentiation, inhibits osteoclast differentiation, cartilage degradation markers, and increases bone mineral density, expression of osteogenic markers, while reducing bone loss. In this review, we presented the up-to-date findings of the potential anabolic effects of astaxanthin on bone health in vitro, animal, and human studies by providing comprehensive evidence for its future clinical application, especially in treating bone diseases.
Fulltext Ginger-Enriched Honey Attenuates Antibiotic Resistant Pseudomonas aeruginosa Quorum Sensing Virulence Factors and Biofilm Formation

Ng WJ, Hing CL, Loo CB, Hoh EK, Loke IL, Ee KY

Antibiotics (Basel), 2023 Jun 28;12(7).
PMID: 37508219 DOI: 10.3390/antibiotics12071123

Quorum sensing (QS) in Pseudomonas aeruginosa plays an essential role in virulence factors, biofilm formation as well as antibiotic resistance. Approaches that target virulence factors are known to be more sustainable than antibiotics in weakening the infectivity of bacteria. Although honey has been shown to exert antipseudomonal activities, the enhancement of such activity in ginger-enriched honey is still unknown. The main objective of this study was to determine the impacts of honey and ginger-enriched honey on the QS virulence factors and biofilm formation of antibiotic resistant P. aeruginosa clinical isolates. Outcomes showed honey and/or ginger-enriched honey significantly reduced the protease activity, pyocyanin production and exotoxin A concentration of the isolates. The swarming and swimming motility together with biofilm formation in all clinical isolates were also significantly inhibited by both honey samples. Notable morphological alteration of bacterial cells was also observed using scanning electron microscopy. A principal component analysis (PCA) managed to distinguish the untreated group and treatment groups into two distinct clusters, although honey and ginger-enriched honey groups were not well differentiated. This study revealed the effectiveness of honey including ginger-enriched honey to attenuate QS virulence factors and biofilm formation of P. aeruginosa.
Fulltext Multivariable Projections of Caries-Free Prevalence and the Associated Factors from 2019 to 2030 among Schoolchildren Aged 6, 12 and 16-Year-Old in Malaysia

Najihah L, Wan Husin WZ, Marhazlinda J

Children (Basel), 2023 Jun 28;10(7).
PMID: 37508622 DOI: 10.3390/children10071125

This study identified caries-free associated factors and conducted multivariable projections of the caries-free prevalence until 2030 among six-, 12-, and 16-year-old schoolchildren in Malaysia. It was a secondary data analysis of caries-free prevalence and potential associated factors obtained from the Health Information Management System (HIMS), Department of Statistics Malaysia (DOSM), and Food Balance Sheets (FBS). Multiple linear regression and regression with ARMA errors were employed to determine the associated factors and predict the caries-free prevalence from 2019 or 2020 until 2030 for the six-, 12-, and 16-year-old groups, respectively. Gross Domestic Product (GDP) and household income, sugar consumption, and water fluoridation were significantly associated with caries-free status, with the most impactful in all age groups being water fluoridation. With the projected values of the associated factors, the caries-free prevalence in schoolchildren of all age groups in Malaysia is predicted to increase in the next decade. Similar to the past decade, the prevalence trend will remain the highest among the 12-year-olds and the lowest among six-year-olds. Caries-free prevalence was predicted to increase by 9.10%, 15.52%, and 15.10% in the six-, 12-, and 16-year-old groups, respectively. The prevalence multiplied the highest at four times greater than in the past ten years among 16-year-olds, compared with less than 2% in the six- and 12-year-old groups. In conclusion, by factoring in economic factors, sugar consumption, water fluoridation, and age groups, the caries-free prevalence of schoolchildren in Malaysia is projected to increase at different rates in the next decade until 2030. Thus, strategic oral health plans to recognise effective promotion programmes and strengthen others for each age group are crucial.
Fulltext Repeated Etching Cycles of Resin Infiltration up to Nine Cycles on Demineralized Enamel: Surface Roughness and Esthetic Outcomes-In Vitro Study

Ibrahim DFA, Hasmun NN, Liew YM, Venkiteswaran A

Children (Basel), 2023 Jun 30;10(7).
PMID: 37508644 DOI: 10.3390/children10071148

Resin infiltration (RI) is used to mask enamel opacities. There are three recommended etching cycles. However, anecdotal evidence suggests that favorable esthetics outcomes can be obtained by increasing the etching cycles. This study aimed to evaluate the effects of repeated etching cycles during RI application on esthetic changes and surface roughness of demineralized enamel at multiple treatment stages. Artificial demineralization was prepared on the buccal surface of ninety sound extracted premolars. The teeth were divided into nine groups (n = 10); with each consecutive group having one additional etching cycle up to nine etching cycles. Resin infiltrant was performed twice, first for 3 min (Resin 1) and again for 1 min (Resin 2). Surface roughness and esthetic changes were assessed using a profilometer (Ambios XP-200) and Minolta spectrophotometer, respectively, at baseline (sound enamel), etching, resin 1, resin 2, 7 days, and 28 days post resin applications. Data were analyzed with two-way ANOVA (p < 0.05). There was a significant interaction between the different stages and various groups of etching cycles on surface roughness, F(48, 126) = 3.48, p < 0.001. There was a significant interaction between the different stages and various groups of etching cycles on color changes, F(4, 126) = 1.177, p = 0.045. The surface roughness of demineralized enamel infiltrated with RI was less than that of sound enamel (baseline). There is a significant difference in color changes between resin 1 and resin 2 (p < 0.05). After five etching cycles, RI improved the esthetic of the color of teeth similar to the baseline. Surface roughness and color changes remained constant for 28 days. RI can be considered an effective and predictable treatment option for the restoration of early enamel lesions owing to its better surface characteristics and reliable masking effects. The color stability and surface roughness stay unaltered for up to 28 days.
Fulltext Optimization of a Luteolin-Loaded TPGS/Poloxamer 407 Nanomicelle: The Effects of Copolymers, Hydration Temperature and Duration, and Freezing Temperature on Encapsulation Efficiency, Particle Size, and Solubility

Mod Razif MRF, Chan SY, Widodo RT, Chew YL, Hassan M, Hisham SA, et al.

Cancers (Basel), 2023 Jul 24;15(14).
PMID: 37509402 DOI: 10.3390/cancers15143741

BACKGROUND: Luteolin is a flavonoid compound that has been widely studied for its various anti-cancer properties and sensitization to multidrug-resistant cells. However, the limited solubility and bioavailability of Lut hindered its potential clinical use. Theoretically, the combination of this compound with vitamin E TPGS and poloxamer 407 can produce a synergistic effect to enhance tumor apoptosis and P-glycoprotein inhibition. This study aimed to develop and optimize vitamin E TPGS/Poloxamer 407 micelles loaded with luteolin through investigating certain factors that can affect the encapsulation efficiency and particle size of the micelle.
METHODS: A micelle was prepared using the film hydration method, and the micellar solution was lyophilized. The cake formed was analyzed. The factors investigated include the concentrations of the surfactants, ratio of vitamin E TPGS/Poloxamer 407, temperature of the hydrating solution, duration of hydration, and freezing temperature before lyophilization. The effects of these factors on the encapsulation efficiency and particle size of the micelle were also studied. The encapsulation efficiency was measured using a UV-Vis spectrophotometer, while particle size was measured using dynamic light scattering.
RESULTS: The optimized micelle was found to have 90% encapsulation efficiency with a particle size of less than 40 nm, which was achieved using a 10% concentration of surfactants at a vitamin E TPGS/Poloxamer 407 ratio of 3:1. The optimized temperature for hydrating the micellar film was 40 °C, the optimized mixing time was 1 h, and the optimized freezing temperature was -80 °C. The solubility of the luteolin-loaded micelles increased 459-fold compared to pure Lut in water. The critical micelle concentration of the vitamin E TPGS/Poloxamer 407 micelle was 0.001 mg/mL, and the release study showed that luteolin-loaded micelles exhibited sustained release behavior. The release of luteolin from a micelle was found to be higher in pH 6.8 compared to pH 7.4, which signified that luteolin could be accumulated more in a tumor microenvironment compared to blood.
CONCLUSION: This study demonstrated that several factors need to be considered when developing such nanoparticles in order to obtain a well-optimized micelle.
Fulltext Hydrogen Therapy and Its Future Prospects for Ameliorating COVID-19: Clinical Applications, Efficacy, and Modality

Perveen I, Bukhari B, Najeeb M, Nazir S, Faridi TA, Farooq M, et al.

Biomedicines, 2023 Jul 04;11(7).
PMID: 37509530 DOI: 10.3390/biomedicines11071892

Molecular hydrogen is renowned as an odorless and colorless gas. The recommendations developed by China suggest that the inhalation of hydrogen molecules is currently advised in COVID-19 pneumonia treatment. The therapeutic effects of molecular hydrogens have been confirmed after numerous clinical trials and animal-model-based experiments, which have expounded that the low molecular weight of hydrogen enables it to easily diffuse and permeate through the cell membranes to produce a variety of biological impacts. A wide range of both chronic and acute inflammatory diseases, which may include sepsis, pancreatitis, respiratory disorders, autoimmune diseases, ischemia-reperfusion damages, etc. may be treated and prevented by using it. H2 can primarily be inoculated through inhalation, by drinking water (which already contains H2), or by administrating the injection of saline H2 in the body. It may play a pivotal role as an antioxidant, in regulating the immune system, in anti-inflammatory activities (mitochondrial energy metabolism), and cell death (apoptosis, pyroptosis, and autophagy) by reducing the formation of excessive reactive O2 species and modifying the transcription factors in the nuclei of the cells. However, the fundamental process of molecular hydrogen is still not entirely understood. Molecular hydrogen H2 has a promising future in therapeutics based on its safety and possible usefulness. The current review emphasizes the antioxidative, anti-apoptotic, and anti-inflammatory effects of hydrogen molecules along with the underlying principle and fundamental mechanism involved, with a prime focus on the coronavirus disease of 2019 (COVID-19). This review will also provide strategies and recommendations for the therapeutic and medicinal applications of the hydrogen molecule.
Fulltext Enhancing the Anti-Leukemic Potential of Thymoquinone/Sulfobutylether-β-cyclodextrin (SBE-β-CD) Inclusion Complexes

Eid EEM, Alshehade SA, Almaiman AA, Kamran S, Lee VS, Alshawsh MA

Biomedicines, 2023 Jul 04;11(7).
PMID: 37509531 DOI: 10.3390/biomedicines11071891

Leukemia, a condition characterized by the abnormal proliferation of blood cells, poses significant challenges in cancer treatment. Thymoquinone (TQ), a bioactive compound derived from black seed, has demonstrated anticancer properties, including telomerase inhibition and the induction of apoptosis. However, TQ's poor solubility and limited bioavailability hinder its clinical application. This study explored the use of Sulfobutylether-β-cyclodextrin (SBE-β-CD), a cyclodextrin derivative, to enhance the solubility and stability of TQ for leukemia treatment. SBE-β-CD offers low hemolytic activity and has been successfully employed in controlled drug release systems. The study investigated the formation of inclusion complexes between TQ and SBE-β-CD and evaluated their effects on leukemia cell growth and telomerase activity. The results indicated that the TQ/SBE-β-CD complex exhibited improved solubility and enhanced cytotoxic effects against K-562 leukemia cells compared to TQ alone, suggesting the potential of SBE-β-CD as a drug delivery system for TQ. The annexin V-FITC assay demonstrated increased apoptosis, while the qPCR quantification assay revealed reduced telomerase activity in leukemia cells treated with TQ/SBE-β-CD, supporting its anti-leukemic potential. The molecular docking analysis indicated a strong binding affinity between TQ and telomerase. However, further research is needed to optimize the apoptotic effects and minimize necrosis induction. In conclusion, TQ/SBE-β-CD shows promise as a novel strategy for leukemia treatment by inhibiting telomerase and enhancing the cytotoxic effects of TQ, offering a potential solution to overcome the limitations of TQ's poor solubility and bioavailability.
Fulltext Impact and Advances in the Role of Bacterial Extracellular Vesicles in Neurodegenerative Disease and Its Therapeutics

Iyaswamy A, Lu K, Guan XJ, Kan Y, Su C, Liu J, et al.

Biomedicines, 2023 Jul 21;11(7).
PMID: 37509695 DOI: 10.3390/biomedicines11072056

Bacterial Extracellular Vesicles (BEVs) possess the capability of intracellular interactions with other cells, and, hence, can be utilized as an efficient cargo for worldwide delivery of therapeutic substances such as monoclonal antibodies, proteins, plasmids, siRNA, and small molecules for the treatment of neurodegenerative diseases (NDs). BEVs additionally possess a remarkable capacity for delivering these therapeutics across the blood-brain barrier to treat Alzheimer's disease (AD). This review summarizes the role and advancement of BEVs for NDs, AD, and their treatment. Additionally, it investigates the critical BEV networks in the microbiome-gut-brain axis, their defensive and offensive roles in NDs, and their interaction with NDs. Furthermore, the part of BEVs in the neuroimmune system and their interference with ND, as well as the risk factors made by BEVs in the autophagy-lysosomal pathway and their potential outcomes on ND, are all discussed. To conclude, this review aims to gain a better understanding of the credentials of BEVs in NDs and possibly discover new therapeutic strategies.
Fulltext Mechanism of Anti-Diabetic Activity from Sweet Potato (Ipomoea batatas): A Systematic Review

Arisanti CIS, Wirasuta IMAG, Musfiroh I, Ikram EHK, Muchtaridi M

Foods, 2023 Jul 24;12(14).
PMID: 37509903 DOI: 10.3390/foods12142810

This study aims to provide an overview of the compounds found in sweet potato (Ipomoea batatas) that contribute to its anti-diabetic activity and the mechanisms by which they act. A comprehensive literature search was conducted using electronic databases, such as PubMed, Scopus, and Science Direct, with specific search terms and Boolean operators. A total of 269 articles were initially retrieved, but after applying inclusion and exclusion criteria only 28 articles were selected for further review. Among the findings, four varieties of sweet potato were identified as having potential anti-diabetic properties. Phenolic acids, flavonols, flavanones, and anthocyanidins are responsible for the anti-diabetic activity of sweet potatoes. The anti-diabetic mechanism of sweet potatoes was determined using a combination of components with multi-target actions. The results of these studies provide evidence that Ipomoea batatas is effective in the treatment of type 2 diabetes.
Fulltext Asynchronous Federated Learning for Improved Cardiovascular Disease Prediction Using Artificial Intelligence

Khan MA, Alsulami M, Yaqoob MM, Alsadie D, Saudagar AKJ, AlKhathami M, et al.

Diagnostics (Basel), 2023 Jul 11;13(14).
PMID: 37510084 DOI: 10.3390/diagnostics13142340

Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model. To evaluate the effectiveness of the proposed AFLCP method, two datasets with various DNN architectures are tested, and the results demonstrate that the AFLCP approach outperforms the baseline method in terms of both communication cost and model accuracy.
Fulltext Comparative Analysis of Image Processing Techniques for Enhanced MRI Image Quality: 3D Reconstruction and Segmentation Using 3D U-Net Architecture

Lim CC, Ling AHW, Chong YF, Mashor MY, Alshantti K, Aziz ME

Diagnostics (Basel), 2023 Jul 14;13(14).
PMID: 37510120 DOI: 10.3390/diagnostics13142377

Osteosarcoma is a common type of bone tumor, particularly prevalent in children and adolescents between the ages of 5 and 25 who are experiencing growth spurts during puberty. Manual delineation of tumor regions in MRI images can be laborious and time-consuming, and results may be subjective and difficult to replicate. Therefore, a convolutional neural network (CNN) was developed to automatically segment osteosarcoma cancerous cells in three types of MRI images. The study consisted of five main stages. First, 3692 DICOM format MRI images were acquired from 46 patients, including T1-weighted, T2-weighted, and T1-weighted with injection of Gadolinium (T1W + Gd) images. Contrast stretching and median filter were applied to enhance image intensity and remove noise, and the pre-processed images were reconstructed into NIfTI format files for deep learning. The MRI images were then transformed to fit the CNN's requirements. A 3D U-Net architecture was proposed with optimized parameters to build an automatic segmentation model capable of segmenting osteosarcoma from the MRI images. The 3D U-Net segmentation model achieved excellent results, with mean dice similarity coefficients (DSC) of 83.75%, 85.45%, and 87.62% for T1W, T2W, and T1W + Gd images, respectively. However, the study found that the proposed method had some limitations, including poorly defined borders, missing lesion portions, and other confounding factors. In summary, an automatic segmentation method based on a CNN has been developed to address the challenge of manually segmenting osteosarcoma cancerous cells in MRI images. While the proposed method showed promise, the study revealed limitations that need to be addressed to improve its efficacy.
Fulltext Diagnosis of Obstructive Sleep Apnea Using Feature Selection, Classification Methods, and Data Grouping Based Age, Sex, and Race

Sheta A, Thaher T, Surani SR, Turabieh H, Braik M, Too J, et al.

Diagnostics (Basel), 2023 Jul 20;13(14).
PMID: 37510161 DOI: 10.3390/diagnostics13142417

Obstructive sleep apnea (OSA) is a prevalent sleep disorder that affects approximately 3-7% of males and 2-5% of females. In the United States alone, 50-70 million adults suffer from various sleep disorders. OSA is characterized by recurrent episodes of breathing cessation during sleep, thereby leading to adverse effects such as daytime sleepiness, cognitive impairment, and reduced concentration. It also contributes to an increased risk of cardiovascular conditions and adversely impacts patient overall quality of life. As a result, numerous researchers have focused on developing automated detection models to identify OSA and address these limitations effectively and accurately. This study explored the potential benefits of utilizing machine learning methods based on demographic information for diagnosing the OSA syndrome. We gathered a comprehensive dataset from the Torr Sleep Center in Corpus Christi, Texas, USA. The dataset comprises 31 features, including demographic characteristics such as race, age, sex, BMI, Epworth score, M. Friedman tongue position, snoring, and more. We devised a novel process encompassing pre-processing, data grouping, feature selection, and machine learning classification methods to achieve the research objectives. The classification methods employed in this study encompass decision tree (DT), naive Bayes (NB), k-nearest neighbor (kNN), support vector machine (SVM), linear discriminant analysis (LDA), logistic regression (LR), and subspace discriminant (Ensemble) classifiers. Through rigorous experimentation, the results indicated the superior performance of the optimized kNN and SVM classifiers for accurately classifying sleep apnea. Moreover, significant enhancements in model accuracy were observed when utilizing the selected demographic variables and employing data grouping techniques. For instance, the accuracy percentage demonstrated an approximate improvement of 4.5%, 5%, and 10% with the feature selection approach when applied to the grouped data of Caucasians, females, and individuals aged 50 or below, respectively. Furthermore, a comparison with prior studies confirmed that effective data grouping and proper feature selection yielded superior performance in OSA detection when combined with an appropriate classification method. Overall, the findings of this research highlight the importance of leveraging demographic information, employing proper feature selection techniques, and utilizing optimized classification models for accurate and efficient OSA diagnosis.
Fulltext Detecting Diabetic Ketoacidosis with Infection: Combating a Life-Threatening Emergency with Practical Diagnostic Tools

Ahmad R, Narwaria M, Singh A, Kumar S, Haque M

Diagnostics (Basel), 2023 Jul 21;13(14).
PMID: 37510185 DOI: 10.3390/diagnostics13142441

BACKGROUND: Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes mellitus and can lead to patient demise if not immediately treated. From the recent literature, the diabetic ketoacidosis mortality rate, depending on age, is 2-5%. Insulin discontinuation and infection remain the two most common triggers for diabetic ketoacidosis. About 50% of cases of ketoacidosis result from bacterial infections like urinary tract infections and pneumonia. It is also important to diagnose the presence of infection in diabetic ketoacidosis patients to prevent the excessive use of antibiotics, which may lead to antibiotic resistance. Although performing bacterial culture is confirmatory for the presence or absence of bacterial infection, the time required to obtain the result is long. At the same time, emergency treatment needs to be started as early as possible.
METHODS: This narrative review examines various septic markers to identify the appropriate tools for diagnosis and to distinguish between diabetic ketoacidosis with and without infection. Electronic databases were searched using the Google engine with the keywords "Diabetes Mellitus", "Diabetic Ketoacidosis", "Infection with Diabetic Ketoacidosis", "biomarkers for infection in Diabetic Ketoacidosis", "Procalcitonin", "Inflammatory cytokines in DKA", "Lactic acidosis in DKA", and "White blood cell in infection in DKA".
RESULTS: This narrative review article presents the options for diagnosis and also aims to create awareness regarding the gravity of diabetic ketoacidosis with infection and emphasizes the importance of early diagnosis for appropriate management. Diabetes mellitus is a clinical condition that may lead to several acute and chronic complications. Acute diabetic ketoacidosis is a life-threatening condition in which an excess production of ketone bodies results in acidosis and hypovolemia. Infection is one of the most common triggers of diabetic ketoacidosis. When bacterial infection is present along with diabetic ketoacidosis, the mortality rate is even higher than for patients with diabetic ketoacidosis without infection. The symptoms and biomarkers of diabetic ketoacidosis are similar to that of infection, like fever, C reactive protein, and white blood cell count, since both create an environment of systemic inflammation. It is also essential to distinguish between the presence and absence of bacterial infection to ensure the appropriate use of antibiotics and prevent antimicrobial resistance. A bacterial culture report is confirmatory for the existence of bacterial infection, but this may take up to 24 h. Diagnosis needs to be performed approximately in the emergency room upon admission since there is a need for immediate management. Therefore, researching the possible diagnostic tools for the presence of infection in diabetic ketoacidosis patients is of great importance. Several of such biomarkers have been discussed in this research work.
Fulltext A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG

Aldughayfiq B, Ashfaq F, Jhanjhi NZ, Humayun M

Diagnostics (Basel), 2023 Jul 21;13(14).
PMID: 37510187 DOI: 10.3390/diagnostics13142442

Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and Photoplethysmogram, has gained attention due to their accessibility and ease of use. However, there are challenges associated with ECG-based AF detection, and the significance of PPG signals in this context has been increasingly recognized. The limitations of ECG and the untapped potential of PPG are taken into account as this work attempts to classify AF and non-AF using PPG time series data and deep learning. In this work, we emploted a hybrid deep neural network comprising of 1D CNN and BiLSTM for the task of AF classification. We addressed the under-researched area of applying deep learning methods to transmissive PPG signals by proposing a novel approach. Our approach involved integrating ECG and PPG signals as multi-featured time series data and training deep learning models for AF classification. Our hybrid 1D CNN and BiLSTM model achieved an accuracy of 95% on test data in identifying atrial fibrillation, showcasing its strong performance and reliable predictive capabilities. Furthermore, we evaluated the performance of our model using additional metrics. The precision of our classification model was measured at 0.88, indicating its ability to accurately identify true positive cases of AF. The recall, or sensitivity, was measured at 0.85, illustrating the model's capacity to detect a high proportion of actual AF cases. Additionally, the F1 score, which combines both precision and recall, was calculated at 0.84, highlighting the overall effectiveness of our model in classifying AF and non-AF cases.
Fulltext Exploring Extended White Blood Cell Parameters for the Evaluation of Sepsis among Patients Admitted to Intensive Care Units

Ho SF, Tan SJ, Mazlan MZ, Iberahim S, Lee YX, Hassan R

Diagnostics (Basel), 2023 Jul 21;13(14).
PMID: 37510189 DOI: 10.3390/diagnostics13142445

Sepsis is a major cause of mortality and morbidity in intensive care units. This case-control study aimed to investigate the haematology cell population data and extended inflammatory parameters for sepsis management. The study included three groups of patients: sepsis, non-sepsis, and healthy controls. Patients suspected of having sepsis underwent a Sequential Organ Failure Assessment (SOFA) evaluation and had blood drawn for blood cultures, complete peripheral blood counts (CBC), and measurements of various markers such as C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6). We observed significant changes in numerous CBC parameters and extended inflammation parameters (EIPs), in addition to significant biochemical analysis markers CRP and IL-6 in sepsis cohorts. Multiple logistic regression analyses showed that combining different CBC parameters and EIPs were effective to profile these patients. Two different models have been developed using white blood cell counts and their extended parameters. Our findings indicate that the absolute counts of white blood cells, and the EIPs which reflect their activation states, are important for the prediction and assessment of sepsis, as the body responds to an insult that triggers an immune response. In an emergency situation, having timely updates on patient conditions becomes crucial for guiding the management process. Identifying trends in these specific patient groups will aid early diagnosis, complementing clinical signs and symptoms, especially as CBC is the most commonly ordered test in a diagnostic workup.
Fulltext Reagent Effects on the Activated Partial Thromboplastin Time Clot Waveform Analysis: A Multi-Centre Study

Wong WH, Tan CW, Abdul Khalid NB, Dalimoenthe NZ, Yip C, Tantanate C, et al.

Diagnostics (Basel), 2023 Jul 22;13(14).
PMID: 37510191 DOI: 10.3390/diagnostics13142447

(1) Background: The activated partial thromboplastin time (APTT)- based clot waveform analysis (CWA) quantitatively extends information obtained from the APTT waveform through its derivatives. However, pre-analytical variables including reagent effects on the CWA parameters are poorly understood and must be standardized as a potential diagnostic assay. (2) Methods: CWA was first analysed with patient samples to understand reagent lot variation in three common APTT reagents: Pathromtin SL, Actin FS, and Actin FSL. A total of 1055 healthy volunteers were also recruited from seven institutions across the Asia-Pacific region and CWA data were collected with the Sysmex CS analysers. (3) Results: CWA parameters varied less than 10% between lots and the linear mixed model analysis showed few site-specific effects within the same reagent group. However, the CWA parameters were significantly different amongst all reagent groups and thus reagent-specific 95% reference intervals could be calculated using the nonparametric method. Post-hoc analysis showed some degree of influence by age and gender with weak correlation to the CWA (r < 0.3). (4) Conclusions: Reagent type significantly affects APTT-based CWA with minimal inter-laboratory variations with the same coagulometer series that allow for data pooling across laboratories with more evidence required for age- and gender-partitioning.
Fulltext Cat Scratch Disease-A Benign Disease with Thymic Hyperplasia Mimicking Lymphoma

Leong MH, Nabillah MJ, Rizuana IH, Asma A, Kew TY, Tan GC

Diagnostics (Basel), 2023 Jul 24;13(14).
PMID: 37510201 DOI: 10.3390/diagnostics13142457

Cat scratch disease (CSD) is a benign condition caused by the inoculation of Bartonella henselae. The imaging findings are non-specific, and it is difficult to diagnose the disease via imaging. However, imaging studies help exclude other differential diagnoses in diagnostic dilemmas. We encountered a case of a 17-year-old adolescent who presented with painful neck swelling. CT showed multiple bilateral cervical lymphadenopathies with triangular soft tissue mass at the anterior mediastinum likely to be thymic hyperplasia, which is unusual in CSD and was mistaken for a lymphoproliferative disorder. Tissue diagnosis with a thorough clinical history yielded the diagnosis of cat scratch disease, and follow-up imaging showed resolution of the cervical lymphadenopathy and thymic hyperplasia.
Fulltext Understanding Factors Associated with Motivation to Quit Vaping among Vapers in the Federal Territory of Kuala Lumpur, Malaysia

Wee LH, Galvan JAA, Patil SS, Madhavan P, Mahalingam D, Yeong CH, et al.

Healthcare (Basel), 2023 Jul 08;11(14).
PMID: 37510421 DOI: 10.3390/healthcare11141980

The prevalence of vaping worldwide is showing an upward trend. This study aimed to determine the factors associated with motivation to quit vaping among vapers in the Federal Territory of Kuala Lumpur, Malaysia, through a cross-sectional, purposive sampling study. Respondents were required to complete a questionnaire consisting of vapers' sociodemographic questions, habitual behavioral pattern questions, the e-Fagerström Test of Nicotine Dependence, the Glover-Nilsson Smoking Behavioral Dependence Questionnaire, perception questions, motivation to quit questions, and withdrawal symptom questions. A total of 311 vapers participated in this study. The majority of the vapers were male (84.6%), younger (18-25 years) (55.3%), and with monthly income less than RM 4000 (USD 868; 83.9%). The level of motivation to quit vaping was found to have a significant association with the perception of vaping being as satisfying as cigarette smoking (p = 0.006) and mild to very strong nicotine dependence (p = 0.001). Participants who recorded moderate and strong habitual vaping behaviors had lower odds of having high motivation to quit vaping compared to those recording slight habitual behaviors (OR = 0.279, 95%CI(0.110-0.708), p = 0.007 and OR = 0.185, 95%CI(0.052-0.654), p = 0.009, respectively). Factors associated with higher motivation to quit vaping could be explored to gain better understanding of how to increase their motivation level for future quit attempts.
Fulltext Beyond Patient Characteristics: A Narrative Review of Contextual Factors Influencing Involuntary Admissions in Mental Health Care

Aluh DO, Aigbogun O, Ukoha-Kalu BO, Silva M, Grigaitė U, Pedrosa B, et al.

Healthcare (Basel), 2023 Jul 09;11(14).
PMID: 37510426 DOI: 10.3390/healthcare11141986

Variations in the rates of involuntary admission (IA) reflect the influence of unexplained contextual variables that are typically too heterogeneous to be included in systematic reviews. This paper attempts to gather and analyze factors unrelated to the patients that have been linked to IA. The articles included in this review were selected by iteratively searching four electronic databases (PubMed, PsychINFO, EMBASE, and Web of Science). A total of 54 studies from 19 different countries and regions, including 14 European countries, the United States, Canada, China, Vietnam, and Taiwan, were selected. The factors were categorized as service-related factors, impactful events, seasonal and temporal factors, mental health legislation, staff factors, and public attitudes. The factors rarely act in isolation but rather interact and reinforce each other, causing a greater influence on IA. This paper explains how these factors present opportunities for robust and sustainable interventions to reduce IAs. The paper also identifies future directions for research, such as examining the effects of economic recessions. Enhancing global reporting standards is essential to validate future research and support further in-depth studies. The complexity of the factors influencing IA and the implicit role of society suggest that resolving it will require social change.

External Links