Browse publications by year: 2022

  1. Nahar N, Mohamed S, Mustapha NM, Fong LS
    J Diabetes Metab Disord, 2022 Jun;21(1):1-11.
    PMID: 35673507 DOI: 10.1007/s40200-021-00905-0
    PURPOSE: Diabetes accelerates peripheral, distal symmetric polyneuropathy, small fiber predominant neuropathy, radiculoplexopathy, and autonomic neuropathy. This study investigated the neuroprotective effects of gallic acid and myricetin-rich Labisia pumila extract in a diabetic neuropathy rat model and evaluated the neuropathy correlationship with serum inflammatory biomarkers.

    METHODS: Thirty male rats were divided into 5 groups (n = 6), namely: healthy control; non-treated diabetic control; and diabetic-rats treated with 200 mg/kg metformin; Labisia pumila ethanol extract (LP) at 150 mg/kg or 300 mg/kg doses. Diabetes was induced by 60 mg streptozotocin /kg intraperitoneal injection. Rats were orally treated daily for ten weeks. Their fasting blood glucose (FBG), neurological functions (hot plate and tail immersion; thermal hyperalgesia; cold allodynia; motor walking function), biomarkers for inflammation and oxidative stress, the neuro-histopathological changes, and brain somatic index were measured.

    RESULTS: The extract significantly prevented abnormal increases in FBG and decreases in body weight gain. It attenuated behavioral dysfunctions (hot plate and tail immersion; thermal hyperalgesia; cold allodynia; motor walking function), systemic inflammation (serum TNF-α, prostaglandin-E2) oxidative tension (malondialdehyde), histological brain and sciatic nerve injuries in the diabetic-rats, better than Metformin.

    CONCLUSION: LP mitigated neural dysfunction better than metformin partly by amending diabetic systemic inflammation, oxidative tension, and diabetic abnormalities. The nerve injuries were strongly correlated to serum prostaglandin-E2, TNF-α levels, and walking functions. The motor function was correlated to sensory neuronal functions, inflammation, and oxidation. The sensory neuronal functions were more affected by TNF-α than prostaglandin-E2 or oxidation. Diabetic brain and sciatic nerve deteriorations were influenced by serum TNF-α, PGE2, and MDA levels.

    SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00905-0.

  2. Mark JKK, Lim CSY, Nordin F, Tye GJ
    Mol Biol Rep, 2022 Nov;49(11):10593-10608.
    PMID: 35674877 DOI: 10.1007/s11033-022-07651-3
    BACKGROUND: Antibodies have proven to be remarkably successful for biomedical applications. They play important roles in epidemiology and medicine from diagnostics of diseases to therapeutics, treating diseases from incessant chronic diseases such as rheumatology to pandemic outbreaks. With no end in sight for the demand for antibody products, optimizations and new techniques must be expanded to accommodate this.

    METHODS AND RESULTS: This review discusses optimizations and techniques for antibody production through choice of discovery platforms, expression systems, cell culture mediums, and other strategies to increase expression yield. Each system has its own merits and demerits, and the strategy chosen is critical in addressing various biological aspects.

    CONCLUSIONS: There is still insufficient evidence to validate the efficacy of some of these techniques, and further research is needed to consolidate these industrial production systems. There is no doubt that more strategies, systems, and pipelines will contribute to enhance biopharmaceutical production.

    MeSH terms: Animals; Antibodies*; Mammals; Proteins*
  3. Rani MDM, Mohamed NA, Solehan HM, Ithnin M, Ariffien AR, Isahak I
    PLoS One, 2022;17(6):e0269059.
    PMID: 35700197 DOI: 10.1371/journal.pone.0269059
    INTRODUCTION: Several countries have started mass vaccination programs to halt the spread of the COVID-19 pandemic. With an R naught value of 2 to 3, about 70% of the population needs to be immunized to achieve herd immunity. This study aimed to investigate the reasons for acceptance or refusal of COVID-19 vaccines among the Malaysian population.

    METHODOLOGY: An exploratory, descriptive qualitative design was performed. The cross-sectional survey used a non-probability convenient sampling technique to recruit the respondents, who were required to answer an open-ended question: Either "If you are willing to get the vaccine, please state your reason" or "If you are not willing to get vaccinated, please state your reason." The survey also included questions on demography such as age, gender, and place of residence. According to the Health Belief Model, the data was transcribed, translated, and analyzed: perceived susceptibility, perceived severity, perceived barrier, and cues for action.

    RESULTS: A total of 1091 respondents who completed the online survey comprised 685 (62.8%) females, 406 (37.2%) males, with a mean age of 38.16 (SD = 16.44). The majority (81.1%) were willing to get vaccinated. Thematic analysis showed that most respondents perceived that the vaccine is safe, effective, protective and will provide herd immunity. Barriers to vaccination include unknown long-term side effects, rapid vaccine production, inadequate information and concerns regarding halal status. Cues to vaccination included individual desire, social responsibility, economic concerns and wait-and-see behavior.

    CONCLUSIONS: The public should be well informed about the vaccine, its efficacy, side effects, and halal status to increase vaccine acceptability and achieve herd immunity.

    MeSH terms: Adult; Cross-Sectional Studies; Female; Humans; Male; Vaccination; Pandemics/prevention & control
  4. Ibrahim MF, Wan Ismail WS, Nik Jaafar NR, Mohd Mokhtaruddin UK, Ong HY, Abu Bakar NH, et al.
    Front Psychiatry, 2022;13:913067.
    PMID: 35757216 DOI: 10.3389/fpsyt.2022.913067
    INTRODUCTION: Depression is a prevalent mental health condition worldwide and in Malaysia. Depression among adolescents has been steadily increasing. Self-esteem has been known to be associated with depression. It has been postulated that a poor lifestyle among adolescents is associated with depression. This paper aims to study the correlation of self-esteem, lifestyle (eating behavior, physical activity, and internet usage) with depression among Malaysian youth.

    METHODOLOGY: This is a cross-sectional study among secondary school children from 5 random schools in an urban city of Kuala Lumpur, Malaysia. Those with intellectual disability and/or difficulty to comprehend Malay language, and without parental consent and assent, were excluded. Students from randomly selected classes aged 13-year-old to 17-year-old were invited to fill in these questionnaires: Socio-demographic Questionnaire, Rosenberg Self-esteem Questionnaire, Physical Activity Questionnaire (PAQ-A), Eating Disorder Examination Questionnaires (EDE-Q), Internet Addiction Test Scale (IAT), and Children's Depression Inventory (CDI).

    RESULT: 461 students participated in the study. 21.5% of the participating students were found to have depression (n = 99). Younger age and Chinese race showed significant association with adolescent depression with a p-value of 0.032 and 0.017 respectively. Other significant correlations with depression were self-esteem (p = 0.013), disordered eating (p = 0.000), lower physical activity (p = 0.014) and problematic internet usage (p = 0.000).

    DISCUSSION: The prevalence of depression among adolescents in this study (21.5%) is in line with previous prevalence studies in Malaysia. Self-esteem is postulated to be a moderating factor for depression hence explaining the significant association. A sedentary lifestyle may increase the risk of developing depression, The causal relationship between problematic internet usage and depression is complex and difficult to establish. This is similar to the relationship between problematic eating behavior and depression as well.

    CONCLUSION: There is still a need to explore the causal relationship between lifestyle factors and depression among youth. Despite that, the results from this paper have accentuated the gravity of the importance of a healthy lifestyle among adolescents. An appropriate preventive measure is governmental strategies and policies aiming at improving a healthier lifestyle in this age group.

  5. Awasthi A, Gulati M, Kumar B, Kaur J, Vishwas S, Khursheed R, et al.
    Biomed Res Int, 2022;2022:1659338.
    PMID: 35832856 DOI: 10.1155/2022/1659338
    Diabetic wound (DW) is a secondary application of uncontrolled diabetes and affects about 42.2% of diabetics. If the disease is left untreated/uncontrolled, then it may further lead to amputation of organs. In recent years, huge research has been done in the area of wound dressing to have a better maintenance of DW. These include gauze, films, foams or, hydrocolloid-based dressings as well as polysaccharide- and polymer-based dressings. In recent years, scaffolds have played major role as biomaterial for wound dressing due to its tissue regeneration properties as well as fluid absorption capacity. These are three-dimensional polymeric structures formed from polymers that help in tissue rejuvenation. These offer a large surface area to volume ratio to allow cell adhesion and exudate absorbing capacity and antibacterial properties. They also offer a better retention as well as sustained release of drugs that are directly impregnated to the scaffolds or the ones that are loaded in nanocarriers that are impregnated onto scaffolds. The present review comprehensively describes the pathogenesis of DW, various dressings that are used so far for DW, the limitation of currently used wound dressings, role of scaffolds in topical delivery of drugs, materials used for scaffold fabrication, and application of various polymer-based scaffolds for treating DW.
    MeSH terms: Amputation; Humans; Polymers/therapeutic use; Wound Healing; Bandages, Hydrocolloid
  6. Liu D, Yu X, Huang M, Yang S, Isa SM, Hu M
    Front Psychol, 2022;13:830716.
    PMID: 35837635 DOI: 10.3389/fpsyg.2022.830716
    To demonstrate how green innovation (GI) effectively occurs, this study examines the effects of green intellectual capital (GIC) on GI from the perspective of green supply chain integration (GSCI). Based on a natural-resource-based view and knowledge-based view, the authors constructed an intermediary model of GIC-GSCI-GI, and analyzed the effects of green absorptive ability (GAA) and relationship learning ability (RLA) as moderators. An empirical survey of 328 Chinese manufacturing companies was conducted. Our results indicate that three dimensions of GIC positively impact GI. The mediating effects of internal and external GSCI exist in the relationship between GIC and GI. The moderating effects of GAA and RLA in these effects were also verified. Our study provides further empirical evidence for the relationship between GIC and GI, highlights the effects of companies' internal and external abilities on GI, and suggests new ways and implementation contexts for GI.
  7. Li L, Wu B, Patwary AK
    Front Psychol, 2022;13:872516.
    PMID: 36017423 DOI: 10.3389/fpsyg.2022.872516
    COVID-19 has affected every aspect of our life, including economic, social, and academic. Exchange and mobility students face more difficulties overseas, and Chinese students are no exception. However, e-learning has been introduced by institutions in many countries. The present study examines the psychosocial factors affecting the academic performance of Chinese outbound exchange and mobility students during the COVID-19 pandemic. The study surveys about 186 Chinese outbound exchange and mobility students. The present study performs the quantitative data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) through the Smart PLS software version 3. By confirming the measurement model and structural model assessments, the study finds that personality, social support, and language fluency are psychosocial factors that significantly influence the exchange and mobility students' academic performance. This study contributes by establishing relationships among psychosocial factors, language fluency and academic performance. Besides, practitioners can be benefitted by understanding students' psychosocial factors and its relation to academic performance during COVID-19 pandemic.
  8. Islam F, Bepary S, Nafady MH, Islam MR, Emran TB, Sultana S, et al.
    Oxid Med Cell Longev, 2022;2022:8741787.
    PMID: 36046682 DOI: 10.1155/2022/8741787
    A spinal cord injury (SCI) occurs when the spinal cord is deteriorated or traumatized, leading to motor and sensory functions lost even totally or partially. An imbalance within the generation of reactive oxygen species and antioxidant defense levels results in oxidative stress (OS) and neuroinflammation. After SCI, OS and occurring pathways of inflammations are significant strenuous drivers of cross-linked dysregulated pathways. It emphasizes the significance of multitarget therapy in combating SCI consequences. Polyphenols, which are secondary metabolites originating from plants, have the promise to be used as alternative therapeutic agents to treat SCI. Secondary metabolites have activity on neuroinflammatory, neuronal OS, and extrinsic axonal dysregulated pathways during the early stages of SCI. Experimental and clinical investigations have noted the possible importance of phenolic compounds as important phytochemicals in moderating upstream dysregulated OS/inflammatory signaling mediators and axonal regeneration's extrinsic pathways after the SCI probable significance of phenolic compounds as important phytochemicals in mediating upstream dysregulated OS/inflammatory signaling mediators. Furthermore, combining polyphenols could be a way to lessen the effects of SCI.
    MeSH terms: Antioxidants/metabolism; Antioxidants/pharmacology; Antioxidants/therapeutic use; Humans; Spinal Cord/metabolism; Oxidative Stress
  9. Hassan S, Suki NM
    Front Psychol, 2022;13:917434.
    PMID: 36118428 DOI: 10.3389/fpsyg.2022.917434
    The aim of this research is to investigate the mediating role of relationship quality in the relationship between relational benefits and customer citizenship behavior. Data were gathered through a systematic sampling from 334 passengers. A Survey technique was used to collect the data from respondents from multiple airports. Data were analyzed through partial least square structural equation modeling (PLS-SEM) using SmartPLS 3.3. The results of the study reveal that altruistic benefits, confidence, and self-expression benefits have a positive relationship with relationship quality while socialization benefits have a non-significant relationship with relationship quality. Similarly, relationship quality mediates the relationship between altruistic benefits, confidence and self-expression benefits, and customer citizenship behavior while relationship quality does not mediate the relationship between socialization benefits and customer citizenship behavior. This study uncovers the relational benefits and its role in the generation of customer citizenship behavior in the aviation sector and the role of relationship quality that could help managers to cultivate the benefits of customer citizenship behaviors.
  10. Ikram M, Abid N, Haider A, Ul-Hamid A, Haider J, Shahzadi A, et al.
    Nanoscale Adv, 2022 Feb 01;4(3):926-942.
    PMID: 36131827 DOI: 10.1039/d1na00802a
    In this study, different concentrations (0, 0.02, 0.04, and 0.06 wt%) of Mo doped onto La2O3 nanostructures were synthesized using a one-pot co-precipitation process. The aim was to study the ability of Mo-doped La2O3 samples to degrade toxic methylene blue dye in different pH media. The bactericidal potential of synthesized samples was also investigated. The structural properties of prepared samples were examined by XRD. The observed XRD spectrum of La2O3 showed a cubic and hexagonal structure, while no change was recorded in Mo-doped La2O3 samples. Doping with Mo improved the crystallinity of the samples. UV-Vis spectrophotometry and density functional theory calculations were used to assess the optical characteristics of Mo-La2O3. The band gap energy was reduced while the absorption spectra showed prominent peaks due to Mo doping. The HR-TEM results revealed the rod-like morphology of La2O3. The rod-like network appeared to become dense upon doping. A significant degradation of MB was confirmed with Mo; furthermore, the bactericidal activities against S. aureus and E. coli were measured as 5.05 mm and 5.45 mm inhibition zones, respectively, after doping with a high concentration (6%) of Mo.
  11. Sekaran SD, Ismail AA, Thergarajan G, Chandramathi S, Rahman SKH, Mani RR, et al.
    PMID: 36159640 DOI: 10.3389/fcimb.2022.975222
    Dengue is a major public health concern, affecting almost 400 million people worldwide, with about 70% of the global burden of disease in Asia. Despite revised clinical classifications of dengue infections by the World Health Organization, the wide spectrum of the manifestations of dengue illness continues to pose challenges in diagnosis and patient management for clinicians. When the Zika epidemic spread through the American continent and then later to Africa and Asia in 2015, researchers compared the characteristics of the Zika infection to Dengue, considering both these viruses were transmitted primarily through the same vector, the Aedes aegypti female mosquitoes. An important difference to note, however, was that the Zika epidemic diffused in a shorter time span compared to the persisting feature of Dengue infections, which is endemic in many Asian countries. As the pathogenesis of viral illnesses is affected by host immune responses, various immune modulators have been proposed as biomarkers to predict the risk of the disease progression to a severe form, at a much earlier stage of the illness. However, the findings for most biomarkers are highly discrepant between studies. Meanwhile, the cross-reactivity of CD8+ and CD4+ T cells response to Dengue and Zika viruses provide important clues for further development of potential treatments. This review discusses similarities between Dengue and Zika infections, comparing their disease transmissions and vectors involved, and both the innate and adaptive immune responses in these infections. Consideration of the genetic identity of both the Dengue and Zika flaviviruses as well as the cross-reactivity of relevant T cells along with the actions of CD4+ cytotoxic cells in these infections are also presented. Finally, a summary of the immune biomarkers that have been reported for dengue and Zika viral infections are discussed which may be useful indicators for future anti-viral targets or predictors for disease severity. Together, this information appraises the current understanding of both Zika and Dengue infections, providing insights for future vaccine design approaches against both viruses.
    MeSH terms: Zika Virus Infection*; Zika Virus*; Aedes*; Animals; Cross Reactions; Dengue*; Dengue Virus*; Female; Humans; Vaccines*; Immunity, Humoral; Mosquito Vectors
  12. Wang X, Yu L, Wang Z
    J Environ Public Health, 2022;2022:9602876.
    PMID: 36200091 DOI: 10.1155/2022/9602876
    Blended learning has become the dominant teaching approach in colleges and universities as they evolve. A good learning environment design can represent college and university teaching quality, improve undergraduates' literacy, and boost talent training. This paper introduces the data mining method of undergraduate comprehensive literacy education, discovers the association rules of the evaluation data, and introduces the undergraduate comprehensive literacy evaluation model and BP neural network model driven by theory and technology in a mixed learning environment, which promotes students' comprehensive literacy evaluation and builds a good learning environment. The results demonstrate that undergraduate classification prediction accuracy is similar by data mining, and most reach 99.58 percent. So, whether it is the training sample or the test sample, the prediction result of undergraduate comprehensive literacy is acceptable, which illustrates the validity of the data mining algorithm model and has strong application importance for developing a better learning environment.
    MeSH terms: Literacy*; Humans; Learning*; Surveys and Questionnaires; Students; Universities
  13. AlMohammed HI, A Alanazi N, Maghrabi EF, A Alotaibi M
    PMID: 35646155 DOI: 10.1155/2022/4543078
    BACKGROUND: The purpose of this study was a comprehensive review of studies on the effect of aromatherapy with plant essential oils on the improvement of some conditions, for example, anxiety, stress, sleep quality, fatigue, and pain in people with cardiovascular disease.

    MATERIALS AND METHODS: We carried out this systematic review based on the instructions of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Ethical agreement was not necessary as main data have not been collected. During March 2022, we searched the main English databases, for example, Google Scholar, Web of Sciences, EMBASE, EBSCO, ScienceDirect, Scopus, and PubMed/MEDLINE, with limitation to human clinical trials. For this study, no time limit was applied for the publication of articles.

    RESULTS: Out of 1380 papers, 52 papers up to March 2022 were eligible for review in this systematic review. Based on the obtained results, the most widely used medicinal plants for aromatherapy in patients with cardiovascular diseases were Lavandula angustifolia (lavender, 55.7%), Rosa damascena (Damask rose, 11.5%), and Mentha piperita (peppermint, 5.8%), respectively. Most studies have been performed on the effect of aromatherapy on coronary angiography (21 papers, 40.4%), followed by artery bypass graft surgery (14 studies, 26.9%), and cardiac patients (5 studies, 9.6%). Most studies on the effect of aromatherapy in cardiovascular diseases were performed on anxiety (31 papers, 59.6%), sleep quality (8 studies, 15.4%), and hemodynamic parameters (6 studies, 11.5%), respectively.

    CONCLUSION: This study systematically reviewed the effects of aromatherapy in patients with cardiovascular diseases. The review of studies showed that lavender, Damask rose, and peppermint are the most frequents plants used for aromatherapy, whereas they significantly improved some illnesses and conditions, especially anxiety and sleep quality. Therefore, it can be concluded that cardiologist can used aromatherapy as a natural complementary and alternative therapy particularly with lavender, Damask rose, and peppermint to improve quality of life and some conditions such as anxiety and sleep quality.

  14. Hussein-Al-Ali SH, Abudoleh SM, Abualassal QIA, Abudayeh Z, Aldalahmah Y, Hussein MZ
    IET Nanobiotechnol, 2022 May;16(3):92-101.
    PMID: 35332980 DOI: 10.1049/nbt2.12081
    Silver nanoparticles (AgNPs) have shown potential applications in drug delivery. In this study, the AgNPs was prepared from silver nitrate in the presence of alginate as a capping agent. The ciprofloxacin (Cipro) was loaded on the surface of AgNPs to produce Cipro-AgNPs nanocomposite. The characteristics of the Cipro-AgNPs nanocomposite were studied by X-ray diffraction (XRD), UV-Vis, transmission electron microscopy (TEM), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), Fourier-transform infra-red analysis (FT-IR) and zeta potential analyses. The XRD of AgNPs and Cipro-AgNPs nanocomposite data showed that both have a crystalline structure in nature. The FT-IR data indicate that the AgNPs have been wrapped by the alginate and loaded with the Cipro drug. The TEM image showed that the Cipro-AgNPs nanocomposites have an average size of 96 nm with a spherical shape. The SEM image for AgNPs and Cipro-AgNPs nanocomposites confirmed the needle-lumpy shape. The zeta potential for Cipro-AgNPs nanocomposites exhibited a positive charge with a value of 6.5 mV. The TGA for Cipro-AgNPs nanocomposites showed loss of 79.7% in total mass compared to 57.6% for AgNPs which is due to the Cipro loaded in the AgNPs. The release of Cipro from Cipro-AgNPs nanocomposites showed slow release properties which reached 98% release within 750 min, and followed the Hixson-Crowell kinetic model. In addition, the toxicity of AgNPs and Cipro-AgNPs nanocomposites was evaluated using normal (3T3) cell line. The present work suggests that Cipro-AgNPs are suitable for drug delivery.
    MeSH terms: Alginates; Anti-Bacterial Agents/chemistry; Ciprofloxacin; Silver; X-Ray Diffraction; Spectroscopy, Fourier Transform Infrared
  15. Oyelade ON, Ezugwu AE, Almutairi MS, Saha AK, Abualigah L, Chiroma H
    Sci Rep, 2022 Apr 13;12(1):6166.
    PMID: 35418566 DOI: 10.1038/s41598-022-09929-9
    Deep learning (DL) models are becoming pervasive and applicable to computer vision, image processing, and synthesis problems. The performance of these models is often improved through architectural configuration, tweaks, the use of enormous training data, and skillful selection of hyperparameters. The application of deep learning models to medical image processing has yielded interesting performance, capable of correctly detecting abnormalities in medical digital images, making them surpass human physicians. However, advancing research in this domain largely relies on the availability of training datasets. These datasets are sometimes not publicly accessible, insufficient for training, and may also be characterized by a class imbalance among samples. As a result, inadequate training samples and difficulty in accessing new datasets for training deep learning models limit performance and research into new domains. Hence, generative adversarial networks (GANs) have been proposed to mediate this gap by synthesizing data similar to real sample images. However, we observed that benchmark datasets with regions of interest (ROIs) for characterizing abnormalities in breast cancer using digital mammography do not contain sufficient data with a fair distribution of all cases of abnormalities. For instance, the architectural distortion and breast asymmetry in digital mammograms are sparsely distributed across most publicly available datasets. This paper proposes a GAN model, named ROImammoGAN, which synthesizes ROI-based digital mammograms. Our approach involves the design of a GAN model consisting of both a generator and a discriminator to learn a hierarchy of representations for abnormalities in digital mammograms. Attention is given to architectural distortion, asymmetry, mass, and microcalcification abnormalities so that training distinctively learns the features of each abnormality and generates sufficient images for each category. The proposed GAN model was applied to MIAS datasets, and the performance evaluation yielded a competitive accuracy for the synthesized samples. In addition, the quality of the images generated was also evaluated using PSNR, SSIM, FSIM, BRISQUE, PQUE, NIQUE, FID, and geometry scores. The results showed that ROImammoGAN performed competitively with state-of-the-art GANs. The outcome of this study is a model for augmenting CNN models with ROI-centric image samples for the characterization of abnormalities in breast images.
    MeSH terms: Female; Humans; Image Processing, Computer-Assisted/methods; Mammography; Neural Networks (Computer)*; Benchmarking
  16. Teoh YX, Lai KW, Usman J, Goh SL, Mohafez H, Hasikin K, et al.
    J Healthc Eng, 2022;2022:4138666.
    PMID: 35222885 DOI: 10.1155/2022/4138666
    Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.
    MeSH terms: Machine Learning; Humans; Magnetic Resonance Imaging; Pain; Reproducibility of Results
  17. Srie Rahayu SY, Aminingsih T, Fudholi A
    J Trace Elem Med Biol, 2022 May;71:126963.
    PMID: 35231878 DOI: 10.1016/j.jtemb.2022.126963
    BACKGROUND AND AIM: Freshwater clam shells nanoparticles powder is one of the uses of freshwater clams that can manufacture instant granular mineral supplements. This product can be used as a supplement to detoxify heavy metal toxins, such as Mercury. Mercury is an element that is detectable in all environmental media. Adults and children receive the most Mercury from food, air, and water intake. The majority of Mercury in the environment comes from the waste from mining activities and the metal industry. Mercury was found widely in the biosphere and is known as a dangerous hepatotoxicant. This study aimed to describe the hepatoprotective role of nano minerals (Ca, Mg, and Zn) produced from freshwater clam shells against mercury acetate poisoning in mice.

    MATERIAL AND METHODS: The mice were divided randomly into a control group (aqua bidest and mercury acetate) and an experimental group for this purpose. The experimental mice group was given orally nano Ca supplementation in three dose groups (9 mg, 18 mg, and 27 mg/200 g animal body weight) once a day for 21 consecutive days. The mice are then given mercury acetate (1300 µg/200 g animal body weight intraperitoneally) on the 21st day. One hour after giving the nano Ca supplement, the mice's blood was taken. Liver and kidney were autopsied two days later to check quantitative and qualitative changes caused by mercury concentrations in liver and kidney histopathologies.

    RESULTS: The results demonstrated the importance of nano Ca supplementation before mercury acetate induction, which has been shown to reduce necrotic depletion and hepatocyte degeneration.

    CONCLUSION: Nano Ca supplementation has decreased the concentration of Hg in the blood of mice so that it can be used as a potential health supplement to detoxify mercury toxins.

    MeSH terms: Acetates; Animals; Body Weight; Calcium; Fresh Water; Kidney/pathology; Liver/pathology; Bivalvia*; Mice
  18. Abdulkareem KH, Mostafa SA, Al-Qudsy ZN, Mohammed MA, Al-Waisy AS, Kadry S, et al.
    J Healthc Eng, 2022;2022:5329014.
    PMID: 35368962 DOI: 10.1155/2022/5329014
    Coronavirus disease 2019 (COVID-19) is a novel disease that affects healthcare on a global scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) images are presently being employed to assist doctors in detecting COVID-19 in its early stages. In several scenarios, a combination of epidemiological criteria (contact during the incubation period), the existence of clinical symptoms, laboratory tests (nucleic acid amplification tests), and clinical imaging-based tests are used to diagnose COVID-19. This method can miss patients and cause more complications. Deep learning is one of the techniques that has been proven to be prominent and reliable in several diagnostic domains involving medical imaging. This study utilizes a convolutional neural network (CNN), stacked autoencoder, and deep neural network to develop a COVID-19 diagnostic system. In this system, classification undergoes some modification before applying the three CT image techniques to determine normal and COVID-19 cases. A large-scale and challenging CT image dataset was used in the training process of the employed deep learning model and reporting their final performance. Experimental outcomes show that the highest accuracy rate was achieved using the CNN model with an accuracy of 88.30%, a sensitivity of 87.65%, and a specificity of 87.97%. Furthermore, the proposed system has outperformed the current existing state-of-the-art models in detecting the COVID-19 virus using CT images.
    MeSH terms: Humans; Tomography, X-Ray Computed/methods; Neural Networks (Computer)
  19. Tobuse AJ, Ang CW, Yeong KY
    Life Sci, 2022 Aug 01;302:120660.
    PMID: 35642852 DOI: 10.1016/j.lfs.2022.120660
    With the continuous evolution of bacteria, the global antimicrobial resistance health threat is causing millions of deaths yearly. While depending on antibiotics as a primary treatment has its merits, there are no effective alternatives thus far in the pharmaceutical market against some drug-resistant bacteria. In recent years, vaccinology has become a key topic in scientific research. Combining with the growth of technology, vaccine research is seeing a new light where the process is made faster and more efficient. Although less discussed, bacterial vaccine is a feasible strategy to combat antimicrobial resistance. Some vaccines have shown promising results with good efficacy against numerous multidrug-resistant strains of bacteria. In this review, we aim to discuss the findings from studies utilizing reverse vaccinology for vaccine development against some multidrug-resistant bacteria, as well as provide a summary of multi-year bacterial vaccine studies in clinical trials. The advantages of reverse vaccinology in the generation of new bacterial vaccines are also highlighted. Meanwhile, the limitations and future prospects of bacterial vaccine concludes this review.
    MeSH terms: Bacteria; Bacterial Vaccines; Drug Resistance, Bacterial
  20. Guo R, Zheng K, Luo L, Liu Y, Shao H, Guo C, et al.
    Microbiol Spectr, 2022 Aug 31;10(4):e0058522.
    PMID: 35862991 DOI: 10.1128/spectrum.00585-22
    Vibrio parahaemolyticus, a widespread marine bacterium, is responsible for a variety of diseases in marine organisms. Consumption of raw or undercooked seafood contaminated with V. parahaemolyticus is also known to cause acute gastroenteritis in humans. While numerous dsDNA vibriophages have been isolated so far, there have been few studies of vibriophages belonging to the ssDNA Microviridae family. In this study, a novel ssDNA phage, vB_VpaM_PG19 infecting V. parahaemolyticus, with a 5,572 bp ssDNA genome with a G+C content of 41.31% and encoded eight open reading frames, was isolated. Genome-wide phylogenetic analysis of the total phage isolates in the GenBank database revealed that vB_VpaM_PG19 was only related to the recently deposited vibriophage vB_VpP_WS1. The genome-wide average nucleotide homology of the two phages was 89.67%. The phylogenetic tree and network analysis showed that vB_VpaM_PG19 was different from other members of the Microviridae family and might represent a novel viral genus, together with vibriophage vB_VpP_WS1, named Vimicrovirus. One-step growth curves showed that vB_VpaM_PG19 has a short incubation period, suggesting its potential as an antimicrobial agent for pathogenic V. parahaemolyticus. IMPORTANCE Vibriophage vB_VpaM_PG19 was distant from other isolated microviruses in the phylogenetic tree and network analysis and represents a novel microviral genus, named Vimicrovirus. Our report describes the genomic and phylogenetic features of vB_VpaM_PG19 and provides a potential antimicrobial candidate for pathogenic V. parahaemolyticus.
    MeSH terms: Phylogeny; Open Reading Frames; Genome, Viral*; Genomics
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