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  1. Automated transtibial prosthesis alignment: A systematic review
    Khamis T, Khamis AA, Al Kouzbary M, Al Kouzbary H, Mokayed H, AbdRazak NA, et al.
    Artif Intell Med, 2024 Oct;156:102966.
    PMID: 39197376 DOI: 10.1016/j.artmed.2024.102966
    This comprehensive systematic review critically analyzes the current progress and challenges in automating transtibial prosthesis alignment. The manual identification of alignment changes in prostheses has been found to lack reliability, necessitating the development of automated processes. Through a rigorous systematic search across major electronic databases, this review includes the highly relevant studies out of an initial pool of 2111 records. The findings highlight the urgent need for automated alignment systems in individuals with transtibial amputation. The selected studies represent cutting-edge research, employing diverse approaches such as advanced machine learning algorithms and innovative alignment tools, to automate the detection and adjustment of prosthesis alignment. Collectively, this review emphasizes the immense potential of automated transtibial prosthesis alignment systems to enhance alignment accuracy and significantly reduce human error. Furthermore, it identifies important limitations in the reviewed studies, serving as a catalyst for future research to address these gaps and explore alternative machine learning algorithms. The insights derived from this systematic review provide valuable guidance for researchers, clinicians, and developers aiming to propel the field of automated transtibial prosthesis alignment forward.
    Matched MeSH terms: Prosthesis Fitting/methods
  2. Fulltext Air Quality Prediction Using the Fractional Gradient-Based Recurrent Neural Network
    Arora S, Sawaran Singh NS, Singh D, Rakesh Shrivastava R, Mathur T, Tiwari K, et al.
    Comput Intell Neurosci, 2022;2022:9755422.
    PMID: 36531923 DOI: 10.1155/2022/9755422
    In this study, the air quality index (AQI) of Indian cities of different tiers is predicted by using the vanilla recurrent neural network (RNN). AQI is used to measure the air quality of any region which is calculated on the basis of the concentration of ground-level ozone, particle pollution, carbon monoxide, and sulphur dioxide in air. Thus, the present air quality of an area is dependent on current weather conditions, vehicle traffic in that area, or anything that increases air pollution. Also, the current air quality is dependent on the climate conditions and industrialization in that area. Thus, the AQI is history-dependent. To capture this dependency, the memory property of fractional derivatives is exploited in this algorithm and the fractional gradient descent algorithm involving Caputo's derivative has been used in the backpropagation algorithm for training of the RNN. Due to the availability of a large amount of data and high computation support, deep neural networks are capable of giving state-of-the-art results in the time series prediction. But, in this study, the basic vanilla RNN has been chosen to check the effectiveness of fractional derivatives. The AQI and gases affecting AQI prediction results for different cities show that the proposed algorithm leads to higher accuracy. It has been observed that the results of the vanilla RNN with fractional derivatives are comparable to long short-term memory (LSTM).
    Matched MeSH terms: Environmental Monitoring/methods
  3. The influence of social support in the prevention and treatment of postpartum depression: An intervention-based narrative review
    Norazman CW, Lee LK
    Womens Health (Lond), 2024;20:17455057241275587.
    PMID: 39238240 DOI: 10.1177/17455057241275587
    Postpartum depression (PPD) is a mental health disorder that affects 10%-15% women globally. Longitudinal and meta-analyses have consistently demonstrated the negative impacts of PPD on both the affected mothers and subsequent infant development. Given the consideration that antidepressant side effects in breastfeeding infants and the cost-effectiveness considerations of psychotherapies, attention has been paid towards the promising role of social support interventions in order to prevent and reduce the PPD symptoms. Confirming the assertion, this narrative review examines the potential of five social support interventions to ameliorate PPD-related maternal and infant outcomes. The wide implications of psychoeducational strategy, nurses' supportive and non-directive counselling and home-visiting approach are outlined. Furthermore, the evidence underlying the role of peer support, culturally tailored intervention and community-based participatory approach in PPD is elucidated. In clinical practice, this review reinforce the roles of discharge educational intervention led by the experienced nurse during the postpartum stay, in order to maintain psychological mental health among the postpartum mothers. More importantly, the skilled and competence public health nurses act as valuable assets in treating PPD, and this effective treatment alternative should be considered by healthcare planners. In future, major investigations will be strategized to discover the synergistic effects of combined social support approaches to yield a better outcome in the prevention and treatment of PPD.
    Matched MeSH terms: Counseling/methods
  4. Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique
    Zia-Ur-Rehman, Awang MK, Rashid J, Ali G, Hamid M, Mahmoud SF, et al.
    PLoS One, 2024;19(9):e0304995.
    PMID: 39240975 DOI: 10.1371/journal.pone.0304995
    Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no treatment and cannot be cured, so early detection is critical. Various AD diagnosis approaches are used in this regard, but Magnetic Resonance Imaging (MRI) provides the most helpful neuroimaging tool for detecting AD. In this paper, we employ a DenseNet-201 based transfer learning technique for diagnosing different Alzheimer's stages as Non-Demented (ND), Moderate Demented (MOD), Mild Demented (MD), Very Mild Demented (VMD), and Severe Demented (SD). The suggested method for a dataset of MRI scans for Alzheimer's disease is divided into five classes. Data augmentation methods were used to expand the size of the dataset and increase DenseNet-201's accuracy. It was found that the proposed strategy provides a very high classification accuracy. This practical and reliable model delivers a success rate of 98.24%. The findings of the experiments demonstrate that the suggested deep learning approach is more accurate and performs well compared to existing techniques and state-of-the-art methods.
    Matched MeSH terms: Neuroimaging/methods
  5. Transcriptome dataset of Metroxylon sagu palms from multiple sago plantations in Sarawak
    Pendi FH, Hussain H
    BMC Res Notes, 2024 Sep 05;17(1):251.
    PMID: 39238033 DOI: 10.1186/s13104-024-06924-3
    OBJECTIVE: Sago palm (Metroxylon sagu Rottb.) is one of the most important economic crops abundantly found in Mukah, Sarawak, Malaysia. The robustness of the palm triggered the Sarawak government's selection as one of the state's commodity crops, with the opening of several sago palm plantations. However, stunted (non-trunking) palms were reported in several sago palm plantations despite attaining a maturity period of more than ten years after cultivation. Research targeting this problem has been conducted in various fields, yet information on molecular mechanisms is still scarce. This study aimed to determine the genes responsible for sago palm's normal phenotype (trunking) by attaining leaf transcriptomes from samples of all trunking sago palms from different sago palm plantations.

    DATA DESCRIPTION: The conventional CTAB method was employed in the present investigation to extract total RNA from leaf tissues. Transcriptome sequencing was conducted on the Illumina NovaSeq 6000 platform. Differential expression analysis was performed using the DESeq2 package. A total of 6,119 differentially expressed genes, comprising 4,384 downregulated and 1,735 upregulated genes, were expressed in all three sago palm datasets. The datasets provide insights into the commonly expressed genes among trunking sago palms.

    Matched MeSH terms: Gene Expression Profiling/methods
  6. Fulltext A pilot implementation study to scale-up methadone in incarcerated persons with opioid use disorder and retain them on treatment after release in Moldova
    Dorgay CE, Bromberg DJ, Doltu S, Litz T, Galvez S, Polonsky M, et al.
    Int J Drug Policy, 2022 Jun;104:103683.
    PMID: 35417790 DOI: 10.1016/j.drugpo.2022.103683
    BACKGROUND: Eastern Europe and Central Asia have intertwined HIV and incarceration epidemics, concentrated in people who inject drugs. Moldova is one of the few countries in this region that offers methadone within prisons, but uptake and post-release retention remains suboptimal. Screening, brief intervention, and referral to treatment (SBIRT) procedures are a potential implementation strategy to address this problem.

    METHODS: From June 1, 2017 to March 3, 2018, we conducted a 2-stage SBIRT strategy in nine prisons and four pre-trial detention facilities in Moldova among incarcerated persons with opioid use disorder (OUD; N = 121) and within 90 days of release. Survey results were analyzed to evaluate the effect of the SBIRT strategy on the uptake of and post-release retention on methadone maintenance treatment (MMT).

    RESULTS: Among the 121 screened with OUD, 27 were on MMT at baseline within the prison and this number increased to 41 after the two-step SBIRT intervention, reflecting a 51.9% increase over baseline. Eleven (78.6%) of the 14 participants that newly started MMT did so only after completing both SBIRT sessions. The brief intervention did not significantly improve knowledge about methadone but did improve attitudes towards it. Among the 41 participants who received methadone during this trial, 40 (97.6%) were retained 6 months after release; the one participant not retained was on methadone at the time of the intervention and had planned to taper off.

    CONCLUSION: The SBIRT strategy significantly improved participant attitudes, but treatment initiation mostly occurred after completing both sessions, including soon after release, but remained low overall. Work within the Moldovan prison subculture to dispel negative myths and misinformation is needed to further scale-up OAT in Moldova.

    Matched MeSH terms: Opiate Substitution Treatment/methods
  7. Development and validation of a selective, sensitive and stability indicating UPLC-MS/MS method for rapid, simultaneous determination of six process related impurities in darunavir drug substance
    A VBR, Yusop Z, Jaafar J, Aris AB, Majid ZA, Umar K, et al.
    J Pharm Biomed Anal, 2016 Sep 05;128:141-148.
    PMID: 27262107 DOI: 10.1016/j.jpba.2016.05.026
    In this study a sensitive and selective gradient reverse phase UPLC-MS/MS method was developed for the simultaneous determination of six process related impurities viz., Imp-I, Imp-II, Imp-III, Imp-IV, Imp-V and Imp-VI in darunavir. The chromatographic separation was performed on Acquity UPLC BEH C18 (50 mm×2.1mm, 1.7μm) column using gradient elution of acetonitrile-methanol (80:20, v/v) and 5.0mM ammonium acetate containing 0.01% formic acid at a flow rate of 0.4mL/min. Both negative and positive electrospray ionization (ESI) modes were operated simultaneously using multiple reaction monitoring (MRM) for the quantification of all six impurities in darunavir. The developed method was fully validated following ICH guidelines with respect to specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, robustness and sample solution stability. The method was able to quantitate Imp-I, Imp-IV, Imp-V at 0.3ppm and Imp-II, Imp-III, and Imp-VI at 0.2ppm with respect to 5.0mg/mL of darunavir. The calibration curves showed good linearity over the concentration range of LOQ to 250% for all six impurities. The correlation coefficient obtained was >0.9989 in all the cases. The accuracy of the method lies between 89.90% and 104.60% for all six impurities. Finally, the method has been successfully applied for three formulation batches of darunavir to determine the above mentioned impurities, however no impurity was found beyond the LOQ. This method is a good quality control tool for the trace level quantification of six process related impurities in darunavir during its synthesis.
    Matched MeSH terms: Chemistry, Pharmaceutical/methods; Chromatography, High Pressure Liquid/methods; Tandem Mass Spectrometry/methods
  8. Vision 20/20: Mammographic breast density and its clinical applications
    Ng KH, Lau S
    Med Phys, 2015 Dec;42(12):7059-77.
    PMID: 26632060 DOI: 10.1118/1.4935141
    Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are "dense" and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believe there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component.
    Matched MeSH terms: Mammography/methods*; Radiographic Image Interpretation, Computer-Assisted/methods*; Early Detection of Cancer/methods*
  9. Computerized segmentation and measurement of chronic wound images
    Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN
    Comput Biol Med, 2015 May;60:74-85.
    PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015
    An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.
    Matched MeSH terms: Diagnosis, Computer-Assisted/methods*; Image Processing, Computer-Assisted/methods*; Medical Informatics/methods
  10. A new mechanism of thermal sensitivity for rapid drug release and low systemic toxicity in hyperthermia and thermal ablation temperature ranges
    Dabbagh A, Abdullah BJ, Abu Kasim NH, Abdullah H, Hamdi M
    Int J Hyperthermia, 2015 Jun;31(4):375-85.
    PMID: 25716769 DOI: 10.3109/02656736.2015.1006268
    The aim of this paper was to introduce a new mechanism of thermal sensitivity in nanocarriers that results in a relatively low drug release at physiological temperature and rapid release of the encapsulated drug at hyperthermia and thermal ablation temperature range (40-60 °C).
    Matched MeSH terms: Hyperthermia, Induced/methods*; Drug Delivery Systems/methods*; High-Intensity Focused Ultrasound Ablation/methods*
  11. Fulltext Mechanomyographic parameter extraction methods: an appraisal for clinical applications
    Ibitoye MO, Hamzaid NA, Zuniga JM, Hasnan N, Wahab AK
    Sensors (Basel), 2014;14(12):22940-70.
    PMID: 25479326 DOI: 10.3390/s141222940
    The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.
    Matched MeSH terms: Diagnosis, Computer-Assisted/methods; Myography/methods*; Pattern Recognition, Automated/methods*
  12. Distress Reduction for Palliative Care Patients and Families With 5-Minute Mindful Breathing: A Pilot Study
    Beng TS, Ahmad F, Loong LC, Chin LE, Zainal NZ, Guan NC, et al.
    Am J Hosp Palliat Care, 2016 Jul;33(6):555-60.
    PMID: 25632044 DOI: 10.1177/1049909115569048
    A pilot study was conducted to evaluate the efficacy of 5-minute mindful breathing in distress reduction. Twenty palliative care patients and family caregivers with a distress score ≥4 measured by the Distress Thermometer were recruited and randomly assigned to mindful breathing or "listening" (being listened to). Median distress reductions after 5 minutes were 2.5 for the mindful breathing group and 1.0 for the listening group. A significantly larger reduction in the distress score was observed in the mindful breathing group (Mann-Whitney U test: U = 8.0, n1 = n2 = 10, mean rank1 = 6.30, mean rank2 = 14.70, z = -3.208, P = .001). The 5-minute mindful breathing could be useful in distress reduction in palliative care.
    Matched MeSH terms: Palliative Care/methods*; Mind-Body Therapies/methods*; Mindfulness/methods*
  13. Automatic lung segmentation using control feedback system: morphology and texture paradigm
    Noor NM, Than JC, Rijal OM, Kassim RM, Yunus A, Zeki AA, et al.
    J Med Syst, 2015 Mar;39(3):22.
    PMID: 25666926 DOI: 10.1007/s10916-015-0214-6
    Interstitial Lung Disease (ILD) encompasses a wide array of diseases that share some common radiologic characteristics. When diagnosing such diseases, radiologists can be affected by heavy workload and fatigue thus decreasing diagnostic accuracy. Automatic segmentation is the first step in implementing a Computer Aided Diagnosis (CAD) that will help radiologists to improve diagnostic accuracy thereby reducing manual interpretation. Automatic segmentation proposed uses an initial thresholding and morphology based segmentation coupled with feedback that detects large deviations with a corrective segmentation. This feedback is analogous to a control system which allows detection of abnormal or severe lung disease and provides a feedback to an online segmentation improving the overall performance of the system. This feedback system encompasses a texture paradigm. In this study we studied 48 males and 48 female patients consisting of 15 normal and 81 abnormal patients. A senior radiologist chose the five levels needed for ILD diagnosis. The results of segmentation were displayed by showing the comparison of the automated and ground truth boundaries (courtesy of ImgTracer™ 1.0, AtheroPoint™ LLC, Roseville, CA, USA). The left lung's performance of segmentation was 96.52% for Jaccard Index and 98.21% for Dice Similarity, 0.61 mm for Polyline Distance Metric (PDM), -1.15% for Relative Area Error and 4.09% Area Overlap Error. The right lung's performance of segmentation was 97.24% for Jaccard Index, 98.58% for Dice Similarity, 0.61 mm for PDM, -0.03% for Relative Area Error and 3.53% for Area Overlap Error. The segmentation overall has an overall similarity of 98.4%. The segmentation proposed is an accurate and fully automated system.
    Matched MeSH terms: Diagnosis, Computer-Assisted/methods*; Pattern Recognition, Automated/methods*; Radiographic Image Interpretation, Computer-Assisted/methods*
  14. Fulltext Investigation of CPD and HMDS sample preparation techniques for cervical cells in developing computer-aided screening system based on FE-SEM/EDX
    Jusman Y, Ng SC, Abu Osman NA
    ScientificWorldJournal, 2014;2014:289817.
    PMID: 25610902 DOI: 10.1155/2014/289817
    This paper investigated the effects of critical-point drying (CPD) and hexamethyldisilazane (HMDS) sample preparation techniques for cervical cells on field emission scanning electron microscopy and energy dispersive X-ray (FE-SEM/EDX). We investigated the visualization of cervical cell image and elemental distribution on the cervical cell for two techniques of sample preparation. Using FE-SEM/EDX, the cervical cell images are captured and the cell element compositions are extracted for both sample preparation techniques. Cervical cell image quality, elemental composition, and processing time are considered for comparison of performances. Qualitatively, FE-SEM image based on HMDS preparation technique has better image quality than CPD technique in terms of degree of spread cell on the specimen and morphologic signs of cell deteriorations (i.e., existence of plate and pellet drying artifacts and membrane blebs). Quantitatively, with mapping and line scanning EDX analysis, carbon and oxygen element compositions in HMDS technique were higher than the CPD technique in terms of weight percentages. The HMDS technique has shorter processing time than the CPD technique. The results indicate that FE-SEM imaging, elemental composition, and processing time for sample preparation with the HMDS technique were better than CPD technique for cervical cell preparation technique for developing computer-aided screening system.
    Matched MeSH terms: Image Processing, Computer-Assisted/methods*; Microscopy, Electron, Scanning/methods; Specimen Handling/methods*
  15. An improved stool concentration procedure for the detection of Cryptosporidium oocysts in Orang Asli stool samples
    Salleh FM, Moktar N, Yasin AM, Al-Mekhlafi HM, Anuar TS
    J Microbiol Methods, 2014 Nov;106:143-145.
    PMID: 25193442 DOI: 10.1016/j.mimet.2014.08.019
    To improve the stool concentration procedure, we modified different steps of the standard formalin-ether concentration technique and evaluated these modifications by examining stool samples collected in the field. Seven samples were found positive by the modified formalin-ether concentration technique (M-FECT). Therefore, the M-FECT procedure provides enhanced detection of Cryptosporidium oocysts.
    Matched MeSH terms: Microbiological Techniques/methods*; Parasitology/methods*; Specimen Handling/methods*
  16. Fulltext Enhanced ethanol gas sensing properties of SnO₂-core/ZnO-shell nanostructures
    Tharsika T, Haseeb AS, Akbar SA, Sabri MF, Hoong WY
    Sensors (Basel), 2014;14(8):14586-600.
    PMID: 25116903 DOI: 10.3390/s140814586
    An inexpensive single-step carbon-assisted thermal evaporation method for the growth of SnO2-core/ZnO-shell nanostructures is described, and the ethanol sensing properties are presented. The structure and phases of the grown nanostructures are investigated by field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) techniques. XRD analysis indicates that the core-shell nanostructures have good crystallinity. At a lower growth duration of 15 min, only SnO2 nanowires with a rectangular cross-section are observed, while the ZnO shell is observed when the growth time is increased to 30 min. Core-shell hierarchical nanostructures are present for a growth time exceeding 60 min. The growth mechanism for SnO2-core/ZnO-shell nanowires and hierarchical nanostructures are also discussed. The sensitivity of the synthesized SnO2-core/ZnO-shell nanostructures towards ethanol sensing is investigated. Results show that the SnO2-core/ZnO-shell nanostructures deposited at 90 min exhibit enhanced sensitivity to ethanol. The sensitivity of SnO2-core/ZnO-shell nanostructures towards 20 ppm ethanol gas at 400 °C is about ~5-times that of SnO2 nanowires. This improvement in ethanol gas response is attributed to high active sensing sites and the synergistic effect of the encapsulation of SnO2 by ZnO nanostructures.
    Matched MeSH terms: Equipment Design/methods; Microscopy, Electron, Scanning/methods; X-Ray Diffraction/methods
  17. Genetic improvement of purslane (Portulaca oleracea L.) and its future prospects
    Amirul Alam M, Juraimi AS, Rafii MY, Hamid AA, Kamal Uddin M, Alam MZ, et al.
    Mol Biol Rep, 2014 Nov;41(11):7395-411.
    PMID: 25085039 DOI: 10.1007/s11033-014-3628-1
    Common purslane (Portulaca oleracea), also known as pigweed, fatweed, pusle, and little hogweed, is an annual succulent herb in the family Portulacaceae that is found in most corners of the globe. From the ancient ages purslane has been treated as a major weed of vegetables as well as other crops. However, worldwide researchers and nutritionists have studied this plant as a potential vegetable crop for humans as well as animals. Purslane is a nutritious vegetable with high antioxidant properties and recently has been recognized as the richest source of α-linolenic acid, essential omega-3 and 6 fatty acids, ascorbic acid, glutathione, α-tocopherol and β-carotene. The lack of vegetable sources of ω-3 fatty acids has resulted in a growing level of attention to introduce purslane as a new cultivated vegetable. In the rapid-revolutionizing worldwide atmosphere, the ability to produce improved planting material appropriate to diverse and varying rising conditions is a supreme precedence. Though various published reports on morphological, physiological, nutritional and medicinal aspects of purslane are available, research on the genetic improvement of this promising vegetable crop are scant. Now it is necessary to conduct research for the genetic improvement of this plant. Genetic improvement of purslane is also a real scientific challenge. Scientific modernization of conventional breeding with the advent of advance biotechnological and molecular approaches such as tissue culture, protoplast fusion, genetic transformation, somatic hybridization, marker-assisted selection, qualitative trait locus mapping, genomics, informatics and various statistical representation have opened up new opportunities of revising the relationship between genetic diversity, agronomic performance and response to breeding for varietal improvement. This review is an attempt to amalgamate the assorted scientific information on purslane propagation, cultivation, varietal improvement, nutrient analyses, medicinal uses and to describe prospective research especially for genetic improvement of this crop.
    Matched MeSH terms: Agriculture/methods*; Breeding/methods*; Genetic Engineering/methods*
  18. Validation of electrical impedance tomography qualitative and quantitative values and comparison of the numeric pain distress score against mammography
    Juliana N, Shahar S, Chelliah KK, Ghazali AR, Osman F, Sahar MA
    Asian Pac J Cancer Prev, 2014;15(14):5759-65.
    PMID: 25081698
    Electrical impedance tomography (EIT) is a potential supplement for mammogram screening. This study aimed to evaluate and feasibility of EIT as opposed to mammography and to determine pain perception with both imaging methods. Women undergoing screening mammography at the Radiology Department of National University of Malaysia Medical Centre were randomly selected for EIT imaging. All women were requested to give a pain score after each imaging session. Two independent raters were chosen to define the image findings of EIT. A total of 164 women in the age range from 40 to 65-year-old participated and were divided into two groups; normal and abnormal. EIT sensitivity and specificity for rater 1 were 69.4% and 63.3, whereas for rater 2 they were 55.3% and 57.0% respectively. The reliability for each rater ranged between good to very good (p<0.05). Quantitative values of EIT showed there were significant differences in all values between groups (ANCOVA, p<0.05). Interestingly, EIT scored a median pain score of 1.51±0.75 whereas mammography scored 4.15±0.87 (Mann Whitney U test, p<0.05). From these quantitative values, EIT has the potential as a health discriminating index. Its ability to replace image findings from mammography needs further investigation.
    Matched MeSH terms: Mammography/methods*; Tomography/methods*; Early Detection of Cancer/methods*
  19. Fulltext Improving RLRN image splicing detection with the Use of PCA and kernel PCA
    Moghaddasi Z, Jalab HA, Md Noor R, Aghabozorgi S
    ScientificWorldJournal, 2014;2014:606570.
    PMID: 25295304 DOI: 10.1155/2014/606570
    Digital image forgery is becoming easier to perform because of the rapid development of various manipulation tools. Image splicing is one of the most prevalent techniques. Digital images had lost their trustability, and researches have exerted considerable effort to regain such trustability by focusing mostly on algorithms. However, most of the proposed algorithms are incapable of handling high dimensionality and redundancy in the extracted features. Moreover, existing algorithms are limited by high computational time. This study focuses on improving one of the image splicing detection algorithms, that is, the run length run number algorithm (RLRN), by applying two dimension reduction methods, namely, principal component analysis (PCA) and kernel PCA. Support vector machine is used to distinguish between authentic and spliced images. Results show that kernel PCA is a nonlinear dimension reduction method that has the best effect on R, G, B, and Y channels and gray-scale images.
    Matched MeSH terms: Pattern Recognition, Automated/methods*; Photography/methods*; Principal Component Analysis/methods*
  20. Fulltext A selective ultrahigh responding high temperature ethanol sensor using TiO2 nanoparticles
    Arafat MM, Haseeb AS, Akbar SA
    Sensors (Basel), 2014;14(8):13613-27.
    PMID: 25072346 DOI: 10.3390/s140813613
    In this research work, the sensitivity of TiO2 nanoparticles towards C2H5OH, H2 and CH4 gases was investigated. The morphology and phase content of the particles was preserved during sensing tests by prior heat treatment of the samples at temperatures as high as 750 °C and 1000 °C. Field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) analysis were employed to characterize the size, morphology and phase content of the particles. For sensor fabrication, a film of TiO2 was printed on a Au interdigitated alumina substrate. The sensing temperature was varied from 450 °C to 650 °C with varying concentrations of target gases. Results show that the sensor has ultrahigh response towards ethanol (C2H5OH) compared to hydrogen (H2) and methane (CH4). The optimum sensing temperature was found to be 600 °C. The response and recovery times of the sensor are 3 min and 15 min, respectively, for 20 ppm C2H5OH at the optimum operating temperature of 600 °C. It is proposed that the catalytic action of TiO2 with C2H5OH is the reason for the ultrahigh response of the sensor.
    Matched MeSH terms: Microscopy, Electron, Scanning/methods; X-Ray Diffraction/methods; Microscopy, Electron, Transmission/methods
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