Displaying publications 101 - 120 of 9849 in total

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  1. Guo L, Zhu J, Wang K, Cheng KK, Xu J, Dong L, et al.
    Anal Chem, 2023 Jun 27;95(25):9714-9721.
    PMID: 37296503 DOI: 10.1021/acs.analchem.3c02002
    High-resolution reconstruction has attracted increasing research interest in mass spectrometry imaging (MSI), but it remains a challenging ill-posed problem. In the present study, we proposed a deep learning model to fuse multimodal images to enhance the spatial resolution of MSI data, namely, DeepFERE. Hematoxylin and eosin (H&E) stain microscopy imaging was used to pose constraints in the process of high-resolution reconstruction to alleviate the ill-posedness. A novel model architecture was designed to achieve multi-task optimization by incorporating multi-modal image registration and fusion in a mutually reinforced framework. Experimental results demonstrated that the proposed DeepFERE model is able to produce high-resolution reconstruction images with rich chemical information and a detailed structure on both visual inspection and quantitative evaluation. In addition, our method was found to be able to improve the delimitation of the boundary between cancerous and para-cancerous regions in the MSI image. Furthermore, the reconstruction of low-resolution spatial transcriptomics data demonstrated that the developed DeepFERE model may find wider applications in biomedical fields.
    Matched MeSH terms: Mass Spectrometry/methods
  2. Dutta S, Singhal S, Shah RB, Haque M
    Crit Rev Oncog, 2022;27(4):23-37.
    PMID: 37199300 DOI: 10.1615/CritRevOncog.2022046361
    Oral cancers (OCs), being one of the frequent malignancies in the head and neck region, need prompt diagnosis and treatment. Apart from basic therapeutic modalities, immunotherapy has now been utilized as a novel approach to combat the disease. With the comprehension of the strategies adopted by cancer cells to evade the immune elimination by the body's immune system, targeted immunotherapies have now become the core area of research. The immune expression of epidermal growth factor receptor (EGFR), programmed cell death protein ligand-1 (PDL-1), etc., are enhanced in OC and have been associated with evasion of the immune system. Targeted immunotherapies now include monoclonal antibodies targeting EGFR like cetuximab and panitumumab, programmed cell death-1 (PD-1) inhibitors like pembrolizumab, cemiplimab, and nivolumab, and PD-L1 inhibitors like atezolizumab, avelumab, and durvalumab. Targeted immunotherapies like chimeric antigen receptor T-cell treatment and small molecule inhibitors are in several clinical trials tried as monotherapy and adjuvant immunotherapy and have shown promising results. Other immunothera-peutic approaches such as cytokines like interferons or interleukins, vaccines, and gene therapy have also been an area of research for the management of OC. However, the cautious selection of appropriate patients with specific immune characteristics as a candidate for immunotherapeutic agents is a crucial component of targeted immunotherapy. This article elaborates on the immune contexture of oral cancer cells, the mechanism of immune evasion by cancer cells, targets for immunotherapies, existent immunotherapeutic agents, and prospects in the field of immunotherapy.
    Matched MeSH terms: Immunotherapy/methods
  3. Wang Y, Liu X, Dong L, Cheng KK, Lin C, Wang X, et al.
    Anal Chem, 2023 Apr 18;95(15):6203-6211.
    PMID: 37023366 DOI: 10.1021/acs.analchem.2c04603
    Drug combinations are commonly used to treat various diseases to achieve synergistic therapeutic effects or to alleviate drug resistance. Nevertheless, some drug combinations might lead to adverse effects, and thus, it is crucial to explore the mechanisms of drug interactions before clinical treatment. Generally, drug interactions have been studied using nonclinical pharmacokinetics, toxicology, and pharmacology. Here, we propose a complementary strategy based on metabolomics, which we call interaction metabolite set enrichment analysis, or iMSEA, to decipher drug interactions. First, a digraph-based heterogeneous network model was constructed to model the biological metabolic network based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Second, treatment-specific influences on all detected metabolites were calculated and propagated across the whole network model. Third, pathway activity was defined and enriched to quantify the influence of each treatment on the predefined functional metabolite sets, i.e., metabolic pathways. Finally, drug interactions were identified by comparing the pathway activity enriched by the drug combination treatments and the single drug treatments. A data set consisting of hepatocellular carcinoma (HCC) cells that were treated with oxaliplatin (OXA) and/or vitamin C (VC) was used to illustrate the effectiveness of the iMSEA strategy for evaluation of drug interactions. Performance evaluation using synthetic noise data was also performed to evaluate sensitivities and parameter settings for the iMSEA strategy. The iMSEA strategy highlighted synergistic effects of combined OXA and VC treatments including the alterations in the glycerophospholipid metabolism pathway and glycine, serine, and threonine metabolism pathway. This work provides an alternative method to reveal the mechanisms of drug combinations from the viewpoint of metabolomics.
    Matched MeSH terms: Metabolomics/methods
  4. Al-Saffar Y, Moo EK, Pingguan-Murphy B, Matyas J, Korhonen RK, Herzog W
    Connect Tissue Res, 2023 May;64(3):294-306.
    PMID: 36853960 DOI: 10.1080/03008207.2023.2166500
    Cartilage cracks disrupt tissue mechanics, alter cell mechanobiology, and often trigger tissue degeneration. Yet, some tissue cracks heal spontaneously. A primary factor determining the fate of tissue cracks is the compression-induced mechanics, specifically whether a crack opens or closes when loaded. Crack deformation is thought to be affected by tissue structure, which can be probed by quantitative polarized light microscopy (PLM). It is unclear how the PLM measures are related to deformed crack morphology. Here, we investigated the relationship between PLM-derived cartilage structure and mechanical behavior of tissue cracks by testing if PLM-derived structural measures correlated with crack morphology in mechanically indented cartilages.

    METHODS: Knee joint cartilages harvested from mature and immature animals were used for their distinct collagenous fibrous structure and composition. The cartilages were cut through thickness, indented over the cracked region, and processed histologically. Sample-specific birefringence was quantified as two-dimensional (2D) maps of azimuth and retardance, two measures related to local orientation and degree of alignment of the collagen fibers, respectively. The shape of mechanically indented tissue cracks, measured as depth-dependent crack opening, were compared with azimuth, retardance, or "PLM index," a new parameter derived by combining azimuth and retardance.

    RESULTS: Of the three parameters, only the PLM index consistently correlated with the crack shape in immature and mature tissues.

    CONCLUSION: In conclusion, we identified the relative roles of azimuth and retardance on the deformation of tissue cracks, with azimuth playing the dominant role. The applicability of the PLM index should be tested in future studies using naturally-occurring tissue cracks.

    Matched MeSH terms: Microscopy, Polarization/methods
  5. Yeoh KL, Puay HT, Abdullah R, Abd Manan TS
    Water Sci Technol, 2023 Jul;88(1):75-91.
    PMID: 37452535 DOI: 10.2166/wst.2023.193
    Short-term streamflow prediction is essential for managing flood early warning and water resources systems. Although numerical models are widely used for this purpose, they require various types of data and experience to operate the model and often tedious calibration processes. Under the digital revolution, the application of data-driven approaches to predict streamflow has increased in recent decades. In this work, multiple linear regression (MLR) and random forest (RF) models with three different input combinations are developed and assessed for multi-step ahead short-term streamflow predictions, using 14 years of hydrological datasets from the Kulim River catchment, Malaysia. Introducing more precedent streamflow events as predictor improves the performance of these data-driven models, especially in predicting peak streamflow during the high-flow event. The RF model (Nash-Sutcliffe efficiency (NSE): 0.599-0.962) outperforms the MLR model (NSE: 0.584-0.963) in terms of overall prediction accuracy. However, with the increasing lead-time length, the models' overall prediction accuracy on the arrival time and magnitude of peak streamflow decrease. These findings demonstrate the potential of decision tree-based models, such as RF, for short-term streamflow prediction and offer insights into enhancing the accuracy of these data-driven models.
    Matched MeSH terms: Hydrology/methods
  6. Rizka H, Diyah EA
    Med J Malaysia, 2023 Jul;78(4):541-546.
    PMID: 37518930
    Malnutrition is one of the most frequent effects of an enterocutaneous fistula (ECF). There are some factors that contribute to it including inadequate intake, fluid loss via fistula and underlying disease. The role of nutrition is very important as a part of ECF therapy to give adequate nutrition, maintain fluid and electrolyte state and increase the likelihood of fistula closure spontaneously. Therefore, it is anticipated that adequate nutrition management will lower morbidity and mortality while enhancing clinical results. Nutritional requirements and nutritional route, whether oral, enteral and parenteral nutrition in ECF management, are influenced by the anatomical, physiological and aetiology of the fistula. The purpose of this review was to highlight the evidence based on nutritional therapy in ECF patients by calling attention to nutritional route selection based on the anatomy and physiology fistula to prevent malnutrition.
    Matched MeSH terms: Enteral Nutrition/methods
  7. Jamil N, Zainal ZA, Alias SH, Chong LY, Hashim R
    Res Social Adm Pharm, 2023 Aug;19(8):1131-1145.
    PMID: 37202279 DOI: 10.1016/j.sapharm.2023.05.006
    BACKGROUND: Self-management interventions often employ behaviour change techniques in order to produce desired target behaviours that are necessary for day-to-day living with a chronic disease. Despite the large number of self-management interventions for patients with chronic obstructive pulmonary disease (COPD), previously reported interventions have been typically delivered by healthcare providers other than the pharmacist.

    OBJECTIVE: This systematic review examined the components of pharmacists-delivered COPD self-management interventions according to an established taxonomy of behaviour change techniques (BCTs).

    METHODS: A systematic search was conducted on PubMed, ScienceDirect, OVID, and Google Scholar from January 2011 to December 2021 for studies of pharmacist-delivered self-management interventions in COPD patients.

    RESULTS: A total of seventeen studies of intervention were eligible for inclusion in the narrative review. Interventions were educational and were delivered individually and face-to-face for the first session. Across studies, pharmacists spent an average of 35 min on the first meeting and had an average of 6 follow-up sessions. Recurrent BCTs in pharmacist interventions were "Information on the health consequence", "Feedback on behaviour", "Instruction on how to perform a behaviour", "Demonstration of the behaviour" and "Behavioural practice/rehearsal".

    CONCLUSIONS: Pharmacists have provided interventions towards improving health behaviours, especially on adherence and usage of inhaler devices for patients with COPD. Future self-management interventions should be designed using the identified BCTs for the improvement of COPD self-management and disease outcomes.

    Matched MeSH terms: Behavior Therapy/methods
  8. Voon NS, Manan HA, Yahya N
    Strahlenther Onkol, 2023 Aug;199(8):706-717.
    PMID: 37280382 DOI: 10.1007/s00066-023-02089-3
    PURPOSE: Increasing evidence implicates changes in brain function following radiotherapy for head and neck cancer as precursors for brain dysfunction. These changes may thus be used as biomarkers for early detection. This review aimed to determine the role of resting-state functional magnetic resonance imaging (rs-fMRI) in detecting brain functional changes.

    METHODS: A systematic search was performed in the PubMed, Scopus, and Web of Science (WoS) databases in June 2022. Patients with head and neck cancer treated with radiotherapy and periodic rs-fMRI assessments were included. A meta-analysis was performed to determine the potential of rs-fMRI for detecting brain changes.

    RESULTS: Ten studies with a total of 513 subjects (head and neck cancer patients, n = 437; healthy controls, n = 76) were included. A significance of rs-fMRI for detecting brain changes in the temporal and frontal lobes, cingulate cortex, and cuneus was demonstrated in most studies. These changes were reported to be associated with dose (6/10 studies) and latency (4/10 studies). A strong effect size (r = 0.71, p 

    Matched MeSH terms: Magnetic Resonance Imaging/methods
  9. Yung YL, Lakshmanan S, Chu CM, Kumaresan S, Tham HJ
    PMID: 37549246 DOI: 10.1080/19440049.2023.2235608
    The rising concern about the presence of 3-monochloropropane 1,2 diol ester (3-MCPDE) and glycidyl ester (GE) in food has prompted much research to be conducted. Some process modifications and the use of specific chemicals have been employed to mitigate both 3-MCPDE and GE. Alkalisation using NaOH, KOH, alkali metals or alkaline earth metals and post sparging with steam or ethanol and short path distillation have shown simultaneous mitigation of 51-91% in 3-MCPDE and of 13-99% in GE, both contaminants achieved below 1000 µg/kg. Some of the mitigation methods have resulted in undesirable deterioration in other parameters of the refined oil. When the processed oil is used in food processing, it results in changes to 3-MCPDE and GE. Repeated deep frying above 170 °C in the presence of NaCl and baking at 200 °C with flavouring (dried garlic and onion), resulted in increased 3-MCPDE. Repeated frying in the presence of antioxidants (TBHQ, rosemary and phenolics) decreased 3-MCPDE in processed food. The GE content in foods tends to decline with time, indicating instability of GE's epoxide ring.
    Matched MeSH terms: Food Handling/methods
  10. Wong YJ, Ng KY, Lee SWH
    J Public Health (Oxf), 2023 Aug 28;45(3):e447-e466.
    PMID: 37147919 DOI: 10.1093/pubmed/fdad051
    BACKGROUND: To ensure the effective delivery of latent tuberculosis infection (LTBI) care, it is vital to overcome potential challenges in LTBI management. This systematic review aims to identify the barriers and interventions to improve LTBI management using the Capability, Opportunity, and Motivation-Behaviour (COM-B) model and Behaviour Change Wheel (BCW).

    METHODS: A systematic literature search was performed on five electronic databases from database inception to 3 November 2021. A two-step technique was used in the data synthesis process: (i) the barriers of LTBI management were identified using the COM-B model, followed by (ii) mapping of intervention functions from BCW to address the identified barriers.

    RESULTS: Forty-seven eligible articles were included in this review. The findings highlighted the need for a multifaceted approach in tackling the barriers in LTBI management across the public, provider and system levels. The barriers were summarized into suboptimal knowledge and misperception of LTBI, as well as stigma and psychosocial burden, which could be overcome with a combination of intervention functions, targeting education, environment restructuring, persuasion, modelling, training, incentivization and enablement.

    CONCLUSIONS: The remedial strategies using BCW to facilitate policy reforms in LTBI management could serve as a value-added initiative in the global tuberculosis control and prevention program.

    Matched MeSH terms: Health Promotion/methods
  11. Alkhadher SAA, Suratman S, Mohd Sallan MIB
    J Environ Manage, 2023 Nov 01;345:118464.
    PMID: 37454570 DOI: 10.1016/j.jenvman.2023.118464
    The spatial and temporal distributions of trace metals in dissolved forms mainly result from anthropogenic and lithogenic contributions. Surface water samples (∼0.5 m) were collected monthly at respective stations from Setiu Wetland. In this study, the behaviour of trace metals in the dissolved phases along the water column from sampling sites in the Setiu Wetland, Malaysia was investigated. In addition, dissolved organic carbon (DOC) and physical parameters such as salinity, temperature, pH and dissolved oxygen (DO) of the surface water were measured in order to evaluate the relationship between trace metals fractionation with different water quality parameters. Size fractionation study of dissolved trace metals using ultrafiltration technique were also carried out and analysed using inductively coupled plasma mass spectrometry (ICP-MS). Correlation of trace metals with other measured parameters was made to furthermore understand the dynamics of trace metals and its fractionated components in this area. The concentration of dissolved trace metals was in the range of 0.001-0.16 μg/L for Cd, 0.12-2.81 μg/L for Cu, 0.01-1.84 μg/L for Pb, 3-17 μg/L for Fe and 1-34 μg/L for Zn, suggesting the input of anthropogenic sources for trace metals such as municipal, industrial, agricultural and domestic discharge. The periodic monitoring and evaluation of trace metals in wetlands and protected tropical areas is highly recommended.
    Matched MeSH terms: Environmental Monitoring/methods
  12. Awan MJ, Mohd Rahim MS, Salim N, Rehman A, Nobanee H
    J Healthc Eng, 2022;2022:2550120.
    PMID: 35444781 DOI: 10.1155/2022/2550120
    In recent times, knee joint pains have become severe enough to make daily tasks difficult. Knee osteoarthritis is a type of arthritis and a leading cause of disability worldwide. The middle of the knee contains a vital portion, the anterior cruciate ligament (ACL). It is necessary to diagnose the ACL ruptured tears early to avoid surgery. The study aimed to perform a comparative analysis of machine learning models to identify the condition of three ACL tears. In contrast to previous studies, this study also considers imbalanced data distributions as machine learning techniques struggle to deal with this problem. The paper applied and analyzed four machine learning classification models, namely, random forest (RF), categorical boosting (Cat Boost), light gradient boosting machines (LGBM), and highly randomized classifier (ETC) on the balanced, structured dataset of ACL. After oversampling a hyperparameter adjustment, the above four models have achieved an average accuracy of 95.72%, 94.98%, 94.98%, and 98.26%. There are 2070 observations and eight features in the collection of three diagnosis ACL classes after oversampling. The area under curve value was approximately 0.998, respectively. Experiments were performed using twelve machine learning algorithms with imbalanced and balanced datasets. However, the accuracy of the imbalanced dataset has remained under 76% for all twelve models. After oversampling, the proposed model may contribute to the investigation of ACL tears on magnetic resonance imaging and other knee ligaments efficiently and automatically without involving radiologists.
    Matched MeSH terms: Magnetic Resonance Imaging/methods
  13. Wei Y, Wang D, Li G, Yu H, Dong X, Jiang H
    Water Sci Technol, 2023 Nov;88(10):2566-2580.
    PMID: 38017678 DOI: 10.2166/wst.2023.365
    In recent years, chemical water treatment equipment has gained significant attention due to its environmental-friendly features, multifunctionality, and broad applicability. Recognizing the limitations of existing chemical treatment equipment, such as challenges in scale removal and the high water content in scale deposits, we propose a novel drum design for both anode and cathode, enabling simultaneous scale suction and dehydration. We constructed a small experimental platform to validate the equipment's performance based on our model. Notably, under the optimal operating parameters, the hardness removal rate for circulating water falls within the range of 19.6-24.46%. Moreover, the scale accumulation rate per unit area and unit time reaches 13.7 g h-1 m-2. Additionally, the energy consumption per unit weight of the scale remains impressively low at 0.16 kWh g-1. Furthermore, the chemical oxygen demand (COD) concentration decreased from an initial 106.0 mg L-1 to a mere 18.8 mg L-1, resulting in a remarkable total removal rate of 82.26%. In conclusion, our innovative electrochemical water treatment equipment demonstrates exceptional performance in scale removal, organic matter degradation, and water resource conservation, offering valuable insights for future research and development in chemical treatment equipment and electrochemical theory.
    Matched MeSH terms: Waste Disposal, Fluid/methods
  14. Arends S, Drenthen J, van den Bergh P, Franssen H, Hadden RDM, Islam B, et al.
    Clin Neurophysiol, 2022 Jun;138:231-240.
    PMID: 35078730 DOI: 10.1016/j.clinph.2021.12.014
    OBJECTIVE: To describe the heterogeneity of electrodiagnostic (EDx) studies in Guillain-Barré syndrome (GBS) patients collected as part of the International GBS Outcome Study (IGOS).

    METHODS: Prospectively collected clinical and EDx data were available in 957 IGOS patients from 115 centers. Only the first EDx study was included in the current analysis.

    RESULTS: Median timing of the EDx study was 7 days (interquartile range 4-11) from symptom onset. Methodology varied between centers, countries and regions. Reference values from the responding 103 centers were derived locally in 49%, from publications in 37% and from a combination of these in the remaining 15%. Amplitude measurement in the EDx studies (baseline-to-peak or peak-to-peak) differed from the way this was done in the reference values, in 22% of motor and 39% of sensory conduction. There was marked variability in both motor and sensory reference values, although only a few outliers accounted for this.

    CONCLUSIONS: Our study showed extensive variation in the clinical practice of EDx in GBS patients among IGOS centers across the regions.

    SIGNIFICANCE: Besides EDx variation in GBS patients participating in IGOS, this diversity is likely to be present in other neuromuscular disorders and centers. This underlines the need for standardization of EDx in future multinational GBS studies.

    Matched MeSH terms: Electrodiagnosis/methods
  15. Fum WKS, Md Shah MN, Raja Aman RRA, Abd Kadir KA, Wen DW, Leong S, et al.
    Phys Eng Sci Med, 2023 Dec;46(4):1535-1552.
    PMID: 37695509 DOI: 10.1007/s13246-023-01317-5
    In fluoroscopy-guided interventions (FGIs), obtaining large quantities of labelled data for deep learning (DL) can be difficult. Synthetic labelled data can serve as an alternative, generated via pseudo 2D projections of CT volumetric data. However, contrasted vessels have low visibility in simple 2D projections of contrasted CT data. To overcome this, we propose an alternative method to generate fluoroscopy-like radiographs from contrasted head CT Angiography (CTA) volumetric data. The technique involves segmentation of brain tissue, bone, and contrasted vessels from CTA volumetric data, followed by an algorithm to adjust HU values, and finally, a standard ray-based projection is applied to generate the 2D image. The resulting synthetic images were compared to clinical fluoroscopy images for perceptual similarity and subject contrast measurements. Good perceptual similarity was demonstrated on vessel-enhanced synthetic images as compared to the clinical fluoroscopic images. Statistical tests of equivalence show that enhanced synthetic and clinical images have statistically equivalent mean subject contrast within 25% bounds. Furthermore, validation experiments confirmed that the proposed method for generating synthetic images improved the performance of DL models in certain regression tasks, such as localizing anatomical landmarks in clinical fluoroscopy images. Through enhanced pseudo 2D projection of CTA volume data, synthetic images with similar features to real clinical fluoroscopic images can be generated. The use of synthetic images as an alternative source for DL datasets represents a potential solution to the application of DL in FGIs procedures.
    Matched MeSH terms: Fluoroscopy/methods
  16. Zainuddin MZ, Mohamad NS, Su Keng T, Mohd Yusof MYP
    J Forensic Sci, 2023 Nov;68(6):2048-2056.
    PMID: 37529884 DOI: 10.1111/1556-4029.15352
    Conventional dental age estimation relies on destructive methods such as sectioning and staining, which are unpreferable when the tooth is required for evidential or archeological preservation. MicroCT is a non-destructive, high-resolution imaging technique that allows for accurate morphometrical measurement. Although microCT technology has been applied in a variety of dental studies, studies focusing on dental age-related change and dental age estimation based on microCT imaging remain lacking. Based on the question: "How has microCT technology been applied in studying human age-related tooth morphological change and dental age estimation studies?", the authors conducted a scoping review in accordance with the Arksey and O'Malley (2005) and the PRISMA-ScR guidelines. A literature search using five major scientific databases identified 452 articles, with 11 full-text articles being eligible to be included in the scoping review. Furthermore, 6 out of the 11 studies performed dental age estimation modeling. An overview of the parameters used in the selected articles revealed a variety of tooth characteristics, such as pulp cavity to whole tooth volume ratio, secondary dentin, as well as the diameter of root canal orifice. The findings of this scoping review highlight the extent microCT is used in studying dental age-related changes, as well as the effectiveness of microCT in dental age estimation studies. This review serves as a guide for future forensic odontology age estimation studies.
    Matched MeSH terms: X-Ray Microtomography/methods
  17. Jovanović V, Rudnev M, Abdelrahman M, Abdul Kadir NB, Adebayo DF, Akaliyski P, et al.
    Psychol Assess, 2024 Jan;36(1):14-29.
    PMID: 38010780 DOI: 10.1037/pas0001270
    Coronavirus Anxiety Scale (CAS) is a widely used measure that captures somatic symptoms of coronavirus-related anxiety. In a large-scale collaboration spanning 60 countries (Ntotal = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
    Matched MeSH terms: Psychometrics/methods
  18. Nanda A, Pandey P, Rajinikanth PS, Singh N
    Int J Biol Macromol, 2024 Mar;260(Pt 1):129416.
    PMID: 38224810 DOI: 10.1016/j.ijbiomac.2024.129416
    Zein, a protein-based biopolymer derived from corn, has garnered attention as a promising and eco-friendly choice for packaging food due to its favorable physical attributes. The introduction of electrospinning technology has significantly advanced the production of zein-based nanomaterials. This cutting-edge technique enables the creation of nanofibers with customizable structures, offering high surface area and adjustable mechanical and thermal attributes. Moreover, the electrospinning process allows for integrating various additives, such as antioxidants, antimicrobial agents, and flavoring compounds, into the zein nanofibers, enhancing their functionalities for food preservation. In this comprehensive review, the various electrospinning techniques employed for crafting zein-based nanofibers, and we delve into their enhanced properties. Furthermore, the review illuminates the potential applications of zein nanofibers in active and intelligent packaging materials by incorporating diverse constituents. Altogether, this review highlights the considerable prospects of zein-based nanocomposites in the realm of food packaging, offering sustainable and innovative solutions for food industry.
    Matched MeSH terms: Nanotechnology/methods
  19. Ng KH, Wong JHD, Leong SS
    Phys Eng Sci Med, 2024 Mar;47(1):17-29.
    PMID: 38078996 DOI: 10.1007/s13246-023-01358-w
    Chronic kidney disease is a leading public health problem worldwide. The global prevalence of chronic kidney disease is nearly five hundred million people, with almost one million deaths worldwide. Estimated glomerular filtration rate, imaging such as conventional ultrasound, and histopathological findings are necessary as each technique provides specific information which, when taken together, may help to detect and arrest the development of chronic kidney disease, besides managing its adverse outcomes. However, estimated glomerular filtration rate measurements are hampered by substantial error margins while conventional ultrasound involves subjective assessment. Although histopathological assessment is the best tool for evaluating the severity of the renal pathology, it may lead to renal insufficiency and haemorrhage if complications occurred. Ultrasound shear wave elastography, an emerging imaging that quantifies tissue stiffness non-invasively has gained interest recently. This method applies acoustic force pulses to generate shear wave within the tissue that propagate perpendicular to the main ultrasound beam. By measuring the speed of shear wave propagation, the tissue stiffness is estimated. This paper reviews the literature and presents our combined experience and knowledge in renal shear wave elastography research. It discusses and highlights the confounding factors on shear wave elastography, current and future possibilities in ultrasound renal imaging and is not limited to new sophisticated techniques.
    Matched MeSH terms: Ultrasonography/methods
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