Displaying publications 2701 - 2720 of 9866 in total

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  1. Otuyo MK, Nadzir MSM, Latif MT, Din SAM
    Environ Sci Pollut Res Int, 2023 Dec;30(58):121306-121337.
    PMID: 37993649 DOI: 10.1007/s11356-023-30923-9
    This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.
    Matched MeSH terms: Environmental Monitoring/methods
  2. Bal PK, Nah SA, Wan Mohamad Noor WMR, Md Nor MT, Singaravel S, Tan WS, et al.
    Malays J Pathol, 2023 Dec;45(3):457-462.
    PMID: 38155386
    Hirschsprung's Disease (HD) is a congenital disorder causing severe constipation in infants and children. Suction rectal biopsy (SRB) is the preferred technique for obtaining tissue samples for histopathological evaluation. In low-resource settings like Malaysia, cost-effective diagnostic approaches are necessary, making single sample SRB valuable. This study evaluates the diagnostic accuracy and sufficiency of a single macroscopically adequate sample in suction rectal biopsies for the histopathological confirmation of HD. We conducted a retrospective study of children who underwent suction rectal biopsies for the diagnosis of HD at Hospital Raja Perempuan Zainab II (HRPZII), Kota Bharu, Kelantan. A total of 68 patients were included in the study. The inadequacy rate for bedside SRB was 14%, comparable to current literature. Our study found no statistically significant association between sample inadequacy and gestational age, gender, birth weight, or weight at biopsy. Complication rates were 0%, consistent with literature reports. Calretinin staining, an additional technique, was performed in 23 biopsy episodes, with a 4.3% inadequacy rate, compared to 20% in specimens not subjected to calretinin staining. The cost of SRB almost doubled with each additional sample taken, significant in low-resource environments. In conclusion, single sample SRBs can be adequately diagnostic and cost-effective in low-resource settings, providing valuable insights for healthcare facilities in Malaysia and other developing countries. The use of adjunctive techniques such as calretinin staining may improve diagnostic accuracy while maintaining cost-effectiveness. Further prospective studies with larger sample sizes are needed to validate these findings.
    Matched MeSH terms: Biopsy/methods
  3. Abdul Aziz SFN, Hui OS, Salleh AB, Normi YM, Yusof NA, Ashari SE, et al.
    Anal Bioanal Chem, 2024 Jan;416(1):227-241.
    PMID: 37938411 DOI: 10.1007/s00216-023-05011-z
    This study aims to investigate the influence of copper(II) ions as a cofactor on the electrochemical performance of a biocomposite consisting of a mini protein mimicking uricase (mp20) and zeolitic immidazolate framework-8 (ZIF-8) for the detection of uric acid. A central composite design (CCD) was utilized to optimize the independent investigation, including pH, deposition potential, and deposition time, while the current response resulting from the electrocatalytic oxidation of uric acid was used as the response. The statistical analysis of variance (ANOVA) showed a good correlation between the experimental and predicted data, with a residual standard error percentage (RSE%) of less than 2% for predicting optimal conditions. The synergistic effect of the nanoporous ZIF-8 host, Cu(II)-activated mp20, and reduced graphene oxide (rGO) layer resulted in a highly sensitive biosensor with a limit of detection (LOD) of 0.21 μM and a reproducibility of the response (RSD = 0.63%). The Cu(II)-activated mp20@ZIF-8/rGO/SPCE was highly selective in the presence of common interferents, and the fabricated layer exhibited remarkable stability with signal changes below 4.15% after 60 days. The biosensor's reliable performance was confirmed through real sample analyses of human serum and urine, with comparable recovery values to conventional HPLC.
    Matched MeSH terms: Electrochemical Techniques/methods
  4. Siddiqui MB, Ng CW, Low WY, Abid K
    PLoS One, 2023;18(12):e0278149.
    PMID: 38109305 DOI: 10.1371/journal.pone.0278149
    The majority (40%) of the world's under-five mortality burden is concentrated in nations like Nigeria (16.5%), India (16%), Pakistan (8%), and the Democratic Republic of the Congo (6%), where an undetermined number of under-five deaths go unrecorded. In low-resource settings throughout the world, the Verbal Autopsy-Social Autopsy (VASA) technique may assist assess under-five mortality estimates, assigning medical and social causes of death, and identifying relevant determinants. Uncertainty regarding missing data in high-burden nations like Pakistan necessitates a valid and reliable VASA instrument. This is the first study to validate Child Health Epidemiology Reference Group-CHERG's VASA tool globally. In Pakistan, data from such a valid and reliable tool is vital for policy. This paper reports on the VASA tool in Karachi, Pakistan. Validity and reliability of the CHERG VASA tool were tested using face, content, discriminant validation, and reliability tests on one hundred randomly selected mothers who had recently experienced an under-five child death event. Data were computed on SPSS (version-21) and R software. Testing revealed high Item-content Validity Index (I-CVI) (>81.43%); high Cronbach's Alpha (0.843); the accuracy of between 75-100% of the discriminants classifying births to live and stillbirths; and I-CVI (>82.07% and 88.98% respectively) with high accuracy (92% and 97% respectively) for assigning biological and social causes of child deaths, respectively. The CHERG VASA questionnaire was found relevant to the conceptual framework and valid in Pakistan. This valid tool can assign accurate medical and non-medical causes of child mortality cases occurring in Pakistan.
    Matched MeSH terms: Autopsy/methods
  5. Moosivand M, Kulemarzi MJB, Shirazi MS, Zaremohzzabieh Z
    BMC Psychol, 2024 Jan 18;12(1):34.
    PMID: 38238867 DOI: 10.1186/s40359-024-01531-0
    OBJECTIVES: Acceptance and Commitment Therapy (ACT) emphasizes the importance of psychological flexibility in promoting emotional, psychological, and social well-being, while also acknowledging rigidity as a precursor to psychological disorders. Analyzing the psychometric qualities based on the multidimensional Hexaflex model is critical for determining the efficiency of therapeutic interventions. Thus, the purpose of this study is to investigate the psychometric features of the Multidimensional Psychological Flexibility Inventory (MPFI) within the context of the Hexaflex model in a group of Iranian university students.

    METHODS: Exploratory and confirmatory factor analyses were used in this study to evaluate the psychometric features of the flexibility/inflexibility scale (MPFI) in a sample of Iranian university students.

    FINDINGS: In the exploratory factor analysis involving a sample of 300 students, six factors were identified for flexibility and six for inflexibility (56.3% males and 43.7% females). In the confirmatory factor analysis with a sample of 388 participants, the results validated 60 items across a total of six flexibility and inflexibility factors. This outcome can serve as a robust estimate for flexibility, inflexibility, the second-order model, and the final model. Cronbach's alpha values for various components, including acceptance, present-moment awareness (or contact with the present moment), self as context, cognitive defusing, values, committed action, total flexibility, experiential avoidance, lack of present-moment awareness, self as content, fusion, lack of contact with values, inaction, and total inflexibility, were reported as follows: 0.818, 0.869, 0.862, 0.904, 0.935, 0.935, 0.942, 0.895, 0.839, 0.883, 0.904, 0.912, 0.941, and 0.941, respectively.

    CONCLUSIONS: The Farsi version of the MPFI for university students has great psychometric qualities, making it a reliable assessment instrument for the ACT.

    Matched MeSH terms: Psychometrics/methods
  6. Goh BL, Lim CTS
    Semin Dial, 2024;37(1):24-35.
    PMID: 35840130 DOI: 10.1111/sdi.13118
    Peritoneal dialysis (PD) catheter is the lifeline of PD patients, and despite the overall strength of the PD program in many countries, PD catheter survival remains the major weakness of the program. The prompt and effective implantation of the PD catheter, as well as speedy management of complications arising from catheter insertion, remains crucial for the success of the program.
    Matched MeSH terms: Catheterization/methods
  7. Aziz HA, Othman N, Yusuff MS, Basri DR, Ashaari FA, Adlan MN, et al.
    Environ Int, 2001 May;26(5-6):395-9.
    PMID: 11392757
    This paper discusses heavy metal removal from wastewater by batch study and filtration technique through low-cost coarse media. Batch study has indicated that more than 90% copper (Cu) with concentration up to 50 mg/l could be removed from the solution with limestone quantity above 20 ml (equivalent to 56 g), which indicates the importance of limestone media in the removal process. This indicates that the removal of Cu is influenced by the media and not solely by the pH. Batch experiments using limestone and activated carbon indicate that both limestone and activated carbon had similar metal-removal efficiency (about 95%). Results of the laboratory-scale filtration technique using limestone particles indicated that above 90% removal of Cu was achieved at retention time of 2.31 h, surface-loading rate of 4.07 m3/m2 per day and Cu loading of 0.02 kg/m3 per day. Analyses of the limestone media after filtration indicated that adsorption and absorption processes were among the mechanisms involved in the removal processes. This study indicated that limestone can be used as an alternative to replace activated carbon.
    Matched MeSH terms: Waste Disposal, Fluid/methods*
  8. Inayat-Hussain SH, Fukumura M, Muiz Aziz A, Jin CM, Jin LW, Garcia-Milian R, et al.
    Environ Int, 2018 08;117:348-358.
    PMID: 29793188 DOI: 10.1016/j.envint.2018.05.010
    BACKGROUND: Recent trends have witnessed the global growth of unconventional oil and gas (UOG) production. Epidemiologic studies have suggested associations between proximity to UOG operations with increased adverse birth outcomes and cancer, though specific potential etiologic agents have not yet been identified. To perform effective risk assessment of chemicals used in UOG production, the first step of hazard identification followed by prioritization specifically for reproductive toxicity, carcinogenicity and mutagenicity is crucial in an evidence-based risk assessment approach. To date, there is no single hazard classification list based on the United Nations Globally Harmonized System (GHS), with countries applying the GHS standards to generate their own chemical hazard classification lists. A current challenge for chemical prioritization, particularly for a multi-national industry, is inconsistent hazard classification which may result in misjudgment of the potential public health risks. We present a novel approach for hazard identification followed by prioritization of reproductive toxicants found in UOG operations using publicly available regulatory databases.

    METHODS: GHS classification for reproductive toxicity of 157 UOG-related chemicals identified as potential reproductive or developmental toxicants in a previous publication was assessed using eleven governmental regulatory agency databases. If there was discordance in classifications across agencies, the most stringent classification was assigned. Chemicals in the category of known or presumed human reproductive toxicants were further evaluated for carcinogenicity and germ cell mutagenicity based on government classifications. A scoring system was utilized to assign numerical values for reproductive health, cancer and germ cell mutation hazard endpoints. Using a Cytoscape analysis, both qualitative and quantitative results were presented visually to readily identify high priority UOG chemicals with evidence of multiple adverse effects.

    RESULTS: We observed substantial inconsistencies in classification among the 11 databases. By adopting the most stringent classification within and across countries, 43 chemicals were classified as known or presumed human reproductive toxicants (GHS Category 1), while 31 chemicals were classified as suspected human reproductive toxicants (GHS Category 2). The 43 reproductive toxicants were further subjected to analysis for carcinogenic and mutagenic properties. Calculated hazard scores and Cytoscape visualization yielded several high priority chemicals including potassium dichromate, cadmium, benzene and ethylene oxide.

    CONCLUSIONS: Our findings reveal diverging GHS classification outcomes for UOG chemicals across regulatory agencies. Adoption of the most stringent classification with application of hazard scores provides a useful approach to prioritize reproductive toxicants in UOG and other industries for exposure assessments and selection of safer alternatives.

    Matched MeSH terms: Risk Assessment/methods*
  9. Haqshenas G, Molano M, Phillips S, Balgovind P, Garland SM, Hawkes D, et al.
    Arch Pathol Lab Med, 2024 Mar 01;148(3):353-358.
    PMID: 37226838 DOI: 10.5858/arpa.2022-0317-OA
    CONTEXT.—: Detection of human papillomavirus (HPV) in formalin-fixed, paraffin-embedded (FFPE) tissues may identify the cause of lesions and has value for the development of new diagnostic assays and epidemiologic studies. Seegene Anyplex II assays are widely used for HPV screening, but their performance using FFPE samples has not been fully explored.

    OBJECTIVE.—: To validate Anyplex II HPV HR Detection (Anyplex II, Seegene) using FFPE samples.

    DESIGN.—: We used 248 stored DNA extracts from cervical cancer FFPE samples collected during 2005-2015 that tested HPV positive using the RHA kit HPV SPF10-LiPA25, v1 (SPF10, Labo Biomedical Products) HPV genotyping assay, manufacturer-validated for FFPE samples.

    RESULTS.—: Of the selected 248 samples, 243 were used in our analysis. Consistent with SPF10 genotyping results, Anyplex II detected all 12 oncogenic types and had an overall HPV detection rate of 86.4% (210 of 243 samples). Anyplex II and SPF10 showed very high agreement for the detection of the 2 most important oncogenic genotypes: HPV 16 (219 of 226; 96.9%; 95% CI, 93.7-98.75) and HPV 18 (221 of 226; 97.8%; 95% CI, 94.9-99.3).

    CONCLUSIONS.—: Overall results showed that both platforms produced comparable HPV genotyping results, indicating the suitability of Anyplex II for FFPE samples. The Anyplex II assay has the added convenience of being an efficient, single-well semiquantitative polymerase chain reaction assay. Further optimization of Anyplex II may enhance its performance using FFPE samples by improving the detection limit.

    Matched MeSH terms: Paraffin Embedding/methods
  10. Shahab M, Iqbal MW, Ahmad A, Alshabrmi FM, Wei DQ, Khan A, et al.
    Comput Biol Med, 2024 Mar;170:108056.
    PMID: 38301512 DOI: 10.1016/j.compbiomed.2024.108056
    The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response. In conclusion, the immunogenic construct shows promise in providing protection against NPV, However, further experimental validation is required before moving to clinical trials.
    Matched MeSH terms: Computational Biology/methods
  11. Lau WN, Mohammadi Nafchi A, Zargar M, Rozalli NHM, Mat Easa A
    Int J Biol Macromol, 2024 Mar;260(Pt 2):129589.
    PMID: 38296665 DOI: 10.1016/j.ijbiomac.2024.129589
    The aim of this work was to fabricate an intelligent film using sago starch incorporated with the natural source of anthocyanins from the Bauhinia Kockiana flower and use it to monitor the freshness of coconut milk. The films were developed using the casting method that included the addition of the different concentrations (0, 5, 10, 15 mg) of Bauhinia Kockiana extract (BKE) obtained using a solvent. The anthocyanin content of Bauhinia Kockiana was 262.17 ± 9.28 mg/100 g of fresh flowers. The spectral characteristics of BKE solutions, cross-section morphology, physiochemical, barrier, and mechanical properties, and the colour variations of films in different pH buffers were investigated. Films having the highest BKE concentration demonstrated the roughest structure and highest thickness (0.16 mm), moisture content (9.72 %), swelling index (435.83 %), water solubility (31.20 %), and elongation at break (262.32 %) compared to the other films. While monitoring the freshness of coconut milk for 16 h, BKE15 showed remarkable visible colour changes (from beige to dark brown), and the pH of coconut milk dropped from 6.21 to 4.56. Therefore, sago starch film incorporated with BKE has excellent potential to act as an intelligent pH film in monitoring the freshness of coconut milk.
    Matched MeSH terms: Food Packaging/methods
  12. Mustapa MA, Yuzir A, Latif AA, Ambran S, Abdullah N
    PMID: 38310743 DOI: 10.1016/j.saa.2024.123977
    A rapid, simple, sensitive, and selective point-of-care diagnosis tool kit is vital for detecting the coronavirus disease (COVID-19) based on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain. Currently, the reverse transcriptase-polymerase chain reaction (RT-PCR) is the best technique to detect the disease. Although a good sensitivity has been observed in RT-PCR, the isolation and screening process for high sample volume is limited due to the time-consuming and laborious work. This study introduced a nucleic acid-based surface-enhanced Raman scattering (SERS) sensor to detect the nucleocapsid gene (N-gene) of SARS-CoV-2. The Raman scattering signal was amplified using gold nanoparticles (AuNPs) possessing a rod-like morphology to improve the SERS effect, which was approximately 12-15 nm in diameter and 40-50 nm in length. These nanoparticles were functionalised with the single-stranded deoxyribonucleic acid (ssDNA) complemented with the N-gene. Furthermore, the study demonstrates method selectivity by strategically testing the same virus genome at different locations. This focused approach showcases the method's capability to discern specific genetic variations, ensuring accuracy in viral detection. A multivariate statistical analysis technique was then applied to analyse the raw SERS spectra data using the principal component analysis (PCA). An acceptable variance amount was demonstrated by the overall variance (82.4 %) for PC1 and PC2, which exceeded the desired value of 80 %. These results successfully revealed the hidden information in the raw SERS spectra data. The outcome suggested a more significant thymine base detection than other nitrogenous bases at wavenumbers 613, 779, 1219, 1345, and 1382 cm-1. Adenine was also less observed at 734 cm-1, and ssDNA-RNA hybridisations were presented in the ketone with amino base SERS bands in 1746, 1815, 1871, and 1971 cm-1 of the fingerprint. Overall, the N-gene could be detected as low as 0.1 nM within 10 mins of incubation time. This approach could be developed as an alternative point-of-care diagnosis tool kit to detect and monitor the COVID-19 disease.
    Matched MeSH terms: Spectrum Analysis, Raman/methods
  13. Kume T, Ohashi M, Makita N, Kho LK, Katayama A, Endo I, et al.
    Tree Physiol, 2018 12 01;38(12):1927-1938.
    PMID: 30452737 DOI: 10.1093/treephys/tpy124
    Clarifying the dynamics of fine roots is critical to understanding carbon and nutrient cycling in forest ecosystems. An optical scanner can potentially be used in studying fine-root dynamics in forest ecosystems. The present study examined image analysis procedures suitable for an optical scanner having a large (210 mm × 297 mm) root-viewing window. We proposed a protocol for analyzing whole soil images obtained by an optical scanner that cover depths of 0-210 mm. We tested our protocol using six observers with different experience in studying roots. The observers obtained data from the manual digitization of sequential soil images recorded for a Bornean tropical forest according to the protocol. Additionally, the study examined the potential tradeoff between the soil image size and accuracy of estimates of fine-root dynamics in a simple exercise. The six observers learned the protocol and obtained similar temporal patterns of fine-root growth and biomass with error of 10-20% regardless of their experience. However, there were large errors in decomposition owing to the low visibility of decomposed fine roots. The simple exercise revealed that a smaller root-viewing window (smaller than 60% of the original window) produces patterns of fine-root dynamics that are different from those for the original window size. The study showed the high applicability of our image analysis approach for whole soil images taken by optical scanners in estimating the fine-root dynamics of forest ecosystems.
    Matched MeSH terms: Diagnostic Imaging/methods
  14. Morales Berstein F, McCartney DL, Lu AT, Tsilidis KK, Bouras E, Haycock P, et al.
    Elife, 2022 Mar 29;11.
    PMID: 35346416 DOI: 10.7554/eLife.75374
    BACKGROUND: Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

    METHODS: We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

    RESULTS: Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

    CONCLUSIONS: GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

    FUNDING: FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

    Matched MeSH terms: Genome-Wide Association Study/methods
  15. Peng P, Wu D, Huang LJ, Wang J, Zhang L, Wu Y, et al.
    Interdiscip Sci, 2024 Mar;16(1):39-57.
    PMID: 37486420 DOI: 10.1007/s12539-023-00580-0
    Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large, accurately labeled medical image datasets are difficult to obtain, traditional clustering algorithms are widely used in medical image segmentation as an unsupervised model. Traditional unsupervised clustering algorithms have limited learning knowledge. Moreover, some semi-supervised fuzzy clustering algorithms cannot fully mine the information of labeled samples, which results in insufficient supervision. When faced with complex mammography images, the above algorithms cannot accurately segment lesion areas. To address this, a semi-supervised fuzzy clustering based on knowledge weighting and cluster center learning (WSFCM_V) is presented. According to prior knowledge, three learning modes are proposed: a knowledge weighting method for cluster centers, Euclidean distance weights for unlabeled samples, and learning from the cluster centers of labeled sample sets. These strategies improve the clustering performance. On real breast molybdenum target images, the WSFCM_V algorithm is compared with currently popular semi-supervised and unsupervised clustering algorithms. WSFCM_V has the best evaluation index values. Experimental results demonstrate that compared with the existing clustering algorithms, WSFCM_V has a higher segmentation accuracy than other clustering algorithms, both for larger lesion regions like tumor areas and for smaller lesion areas like calcification point areas.
    Matched MeSH terms: Image Processing, Computer-Assisted/methods
  16. Alsaih K, Lemaitre G, Rastgoo M, Massich J, Sidibé D, Meriaudeau F
    Biomed Eng Online, 2017 Jun 07;16(1):68.
    PMID: 28592309 DOI: 10.1186/s12938-017-0352-9
    BACKGROUND: Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers.

    METHODS: The dataset used in this study has been acquired by the Singapore Eye Research Institute (SERI), using CIRRUS TM (Carl Zeiss Meditec, Inc., Dublin, CA, USA) SD-OCT device. The dataset consists of 32 OCT volumes (16 DME and 16 normal cases). Each volume contains 128 B-scans with resolution of 1024 px × 512 px, resulting in more than 3800 images being processed. All SD-OCT volumes are read and assessed by trained graders and identified as normal or DME cases based on evaluation of retinal thickening, hard exudates, intraretinal cystoid space formation, and subretinal fluid. Within the DME sub-set, a large number of lesions has been selected to create a rather complete and diverse DME dataset. This paper presents an automatic classification framework for SD-OCT volumes in order to identify DME versus normal volumes. In this regard, a generic pipeline including pre-processing, feature detection, feature representation, and classification was investigated. More precisely, extraction of histogram of oriented gradients and local binary pattern (LBP) features within a multiresolution approach is used as well as principal component analysis (PCA) and bag of words (BoW) representations.

    RESULTS AND CONCLUSION: Besides comparing individual and combined features, different representation approaches and different classifiers are evaluated. The best results are obtained for LBP[Formula: see text] vectors while represented and classified using PCA and a linear-support vector machine (SVM), leading to a sensitivity(SE) and specificity (SP) of 87.5 and 87.5%, respectively.

    Matched MeSH terms: Image Processing, Computer-Assisted/methods*
  17. Ali HH, Sunar MS, Kolivand H
    PLoS One, 2017;12(6):e0178415.
    PMID: 28632740 DOI: 10.1371/journal.pone.0178415
    Volumetric shadows often increase the realism of rendered scenes in computer graphics. Typical volumetric shadows techniques do not provide a smooth transition effect in real-time with conservation on crispness of boundaries. This research presents a new technique for generating high quality volumetric shadows by sampling and interpolation. Contrary to conventional ray marching method, which requires extensive time, this proposed technique adopts downsampling in calculating ray marching. Furthermore, light scattering is computed in High Dynamic Range buffer to generate tone mapping. The bilateral interpolation is used along a view rays to smooth transition of volumetric shadows with respect to preserving-edges. In addition, this technique applied a cube shadow map to create multiple shadows. The contribution of this technique isreducing the number of sample points in evaluating light scattering and then introducing bilateral interpolation to improve volumetric shadows. This contribution is done by removing the inherent deficiencies significantly in shadow maps. This technique allows obtaining soft marvelous volumetric shadows, having a good performance and high quality, which show its potential for interactive applications.
    Matched MeSH terms: Image Interpretation, Computer-Assisted/methods*
  18. Imron MF, Hestianingsi WOA, Putranto TWC, Citrasari N, Abdullah SRS, Hasan HA, et al.
    Chemosphere, 2024 Apr;353:141595.
    PMID: 38438021 DOI: 10.1016/j.chemosphere.2024.141595
    Increasing aquaculture cultivation produces large quantities of wastewater. If not handled properly, it can have negative impacts on the environment. Constructed wetlands (CWs) are one of the phytoremediation methods that can be applied to treat aquaculture effluent. This research was aimed at determining the performance of Cyperus rotundus in removing COD, BOD, TSS, turbidity, ammonia, nitrate, nitrite, and phosphate from the batch CW system. Treatment was carried out for 30 days with variations in the number of plants (10, 15, and 20) and variations in media height (10, 12, and 14 cm). The result showed that aquaculture effluent contains high levels of organic compounds and nutrients, and C. rotundus can grow and thrive in 100% of aquaculture effluent. Besides that, the use of C. rotundus in CWs with the effect of numbers of plants and media height showed performance of COD, BOD, TSS, turbidity, ammonia, nitrate, nitrite, and phosphate with 70, 79, 90, 96, 64, 82, 92, and 48% of removal efficacy, respectively. There was no negative impact observed on C. rotundus growth after exposure to aquaculture effluent, as indicated by the increase in wet weight, dry weight, and growth rate when compared to the control. Thus, adding aquaculture effluent to CWs planted with C. rotundus supports the growth and development of plants while also performing phytoremediation.
    Matched MeSH terms: Waste Disposal, Fluid/methods
  19. Kua KP, Lee SW
    PLoS One, 2017;12(2):e0172289.
    PMID: 28212381 DOI: 10.1371/journal.pone.0172289
    BACKGROUND: Bronchiolitis is a common cause of hospitalization among infants. The limited effectiveness of conventional medication has prompted the use of complementary and alternative medicine (CAM) as alternative or adjunctive therapy for the management of bronchiolitis.

    AIMS: To determine the effectiveness and safety of CAM for the treatment of bronchiolitis in infants aged less than 2 years.

    METHODS: A systematic electronic search was performed in Medline, Embase, CINAHL, AMED, and Cochrane Central Register of Controlled Trials (CENTRAL) from their respective inception to June 30, 2016 for studies evaluating CAM as an intervention to treat bronchiolitis in infants (1 month to 2 years of age). The CAM could be any form of treatment defined by the National Center for Complementary and Integrative Health (NCCIH) and was utilized either as a single agent or adjunctive therapy. The predefined primary outcome was length of hospital stay. Secondary outcomes were time to resolution of bronchiolitis symptoms, adverse events, and all other clinical outcomes reported by the included studies.

    RESULTS: The review identified 11 studies (8 randomized controlled trials and 3 cohort studies) examining four herbal preparations and four supplements used either as adjunctive or alternative therapy for bronchiolitis in 904 infants. Most studies were of moderate quality. Among six studies reporting on length of stay, a significant benefit was found for Chinese herbal medicine compared to ribavirin in one cohort study (n = 66) and vitamin D compared to placebo in one randomized controlled trial (n = 89). Studies of Chinese herbal medicine (4 studies, n = 365), vitamin D (1 study, n = 89), N-acetylcysteine (1 study, n = 100), and magnesium (2 studies, n = 176) showed some benefits with respect to clinical severity scores, oxygen saturation, and other symptoms, although data were sparse for any single intervention and the outcomes assessed and reported varied across studies. Only five studies reported on adverse events; no serious adverse events were reported.

    CONCLUSIONS: Among 11 studies examining the effect of CAM on inpatients with bronchiolitis, six reported on the review's primary outcome of length of hospital stay. In general, findings did not show a significant benefit associated with the primary outcome. Preliminary evidence indicated that Chinese herbal medicine mixtures, vitamin D, N-acetylcysteine, and magnesium might be useful in managing the symptoms of bronchiolitis. However, the evidence was not sufficient or rigorous enough to formulate recommendations for the use of any CAM. Among studies that reported adverse events, no serious harms were noted.

    Matched MeSH terms: Complementary Therapies/methods*
  20. Maruthapillai V, Murugappan M
    PLoS One, 2016;11(2):e0149003.
    PMID: 26859884 DOI: 10.1371/journal.pone.0149003
    In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.
    Matched MeSH terms: Biometric Identification/methods*
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