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Fulltext Separation and Detection of Escherichia coli and Saccharomyces cerevisiae Using a Microfluidic Device Integrated with an Optical Fibre

Kamuri MF, Zainal Abidin Z, Yaacob MH, Hamidon MN, Md Yunus NA, Kamarudin S

Biosensors (Basel), 2019 Mar 14;9(1).
PMID: 30875829 DOI: 10.3390/bios9010040

This paper describes the development of an integrated system using a dry film resistant (DFR) microfluidic channel consisting of pulsed field dielectrophoretic field-flow-fractionation (DEP-FFF) separation and optical detection. The prototype chip employs the pulse DEP-FFF concept to separate the cells (Escherichia coli and Saccharomyces cerevisiae) from a continuous flow, and the rate of release of the cells was measured. The separation experiments were conducted by changing the pulsing time over a pulsing time range of 2⁻24 s and a flow rate range of 1.2⁻9.6 μ L min - 1 . The frequency and voltage were set to a constant value of 1 M Hz and 14 V pk-pk, respectively. After cell sorting, the particles pass the optical fibre, and the incident light is scattered (or absorbed), thus, reducing the intensity of the transmitted light. The change in light level is measured by a spectrophotometer and recorded as an absorbance spectrum. The results revealed that, generally, the flow rate and pulsing time influenced the separation of E. coli and S. cerevisiae. It was found that E. coli had the highest rate of release, followed by S. cerevisiae. In this investigation, the developed integrated chip-in-a lab has enabled two microorganisms of different cell dielectric properties and particle size to be separated and subsequently detected using unique optical properties. Optimum separation between these two microorganisms could be obtained using a longer pulsing time of 12 s and a faster flow rate of 9.6 μ L min - 1 at a constant frequency, voltage, and a low conductivity.

Matched MeSH terms: Cell Separation/methods*; Fiber Optic Technology/methods*; Microfluidics/methods*
Automated Breast Ultrasound Provides Comparable Diagnostic Performance in Opportunistic Screening and Diagnostic Assessment

Rahmat K, Ab Mumin N, Ng WL, Mohd Taib NA, Chan WY, Ramli Hamid MT

Ultrasound Med Biol, 2024 Jan;50(1):112-118.
PMID: 37839984 DOI: 10.1016/j.ultrasmedbio.2023.09.011

OBJECTIVE: The aim of the work described here was to assess the performance of automated breast ultrasound (ABUS) as an adjunct to digital breast tomosynthesis (DBT) in the screening and diagnostic setting.
METHODS: This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.
RESULTS: A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.
CONCLUSION: ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.

Matched MeSH terms: Mammography/methods; Mass Screening/methods; Early Detection of Cancer/methods
Fulltext On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data

Ng GYL, Tan SC, Ong CS

PLoS One, 2023;18(10):e0292961.
PMID: 37856458 DOI: 10.1371/journal.pone.0292961

Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell types. Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. Generally speaking, feature selection methods are categorized into filter-, wrapper-, and embedded-based approaches. From the existing literature, methods from filter- and embedded-based approaches are widely applied in scRNA-seq gene selection tasks. The wrapper-based method that gives promising results in other fields has yet been extensively utilized for selecting gene features from scRNA-seq data; in addition, most of the existing wrapper methods used in this field are clustering instead of classification-based. With a large number of annotated data available today, this study applied a classification-based approach as an alternative to the clustering-based wrapper method. In our work, a quantum-inspired differential evolution (QDE) wrapped with a classification method was introduced to select a subset of genes from twelve well-known scRNA-seq transcriptomic datasets to identify cell types. In particular, the QDE was combined with different machine-learning (ML) classifiers namely logistic regression, decision tree, support vector machine (SVM) with linear and radial basis function kernels, as well as extreme learning machine. The linear SVM wrapped with QDE, namely QDE-SVM, was chosen by referring to the feature selection results from the experiment. QDE-SVM showed a superior cell type classification performance among QDE wrapping with other ML classifiers as well as the recent wrapper methods (i.e., FSCAM, SSD-LAHC, MA-HS, and BSF). QDE-SVM achieved an average accuracy of 0.9559, while the other wrapper methods achieved average accuracies in the range of 0.8292 to 0.8872.

Matched MeSH terms: Sequence Analysis, RNA/methods; Gene Expression Profiling/methods; Single-Cell Analysis/methods
Fulltext A Comprehensive Review of Cervical Cancer Screening Devices: The Pros and the Cons

Hon HJ, Chong PP, Choo HL, Khine PP

Asian Pac J Cancer Prev, 2023 Jul 01;24(7):2207-2215.
PMID: 37505749 DOI: 10.31557/APJCP.2023.24.7.2207

OBJECTIVE: The low screening coverage and reluctance of women in participation lead to low uptake in cervical screening tests. Hence the majority of cervical cancer patients visiting the hospitals are diagnosed at advanced stage, often leading to poor survival rate. This paper aims to review and compile available cancer screening devices so that more people in this field will adopt suitable devices in cervical cancer screening routine depending on requirements which may encourage the uptake in cervical screening tests.
METHODS: This paper reviews devices invented for different cervical cancer screening methods, which are Pap smear test, visual inspection with acetic acid (VIA) or Lugol's iodine (VILI), and HPV (human papillomavirus)-DNA (deoxyribonucleic acid) self-test in terms of functionality, performance in solving the limitations of screening procedure and additionally where applicable, the cervical cell collection efficacy and abnormality detection accuracy. The devices are either available in the market, published in research articles or published in international patent databases.
RESULT: The reviewed devices either simplified the screening procedure to improve the clinical efficiency and accuracy in screening, reduced the pain and discomfort experienced by women during screening procedures, or achieved both outcomes.
CONCLUSION: Many devices have been invented to improve the screening procedures which may potentially improve the uptake in cervical screening tests and encourage the organization of screening campaigns to reduce cervical cancer incidence.

Matched MeSH terms: Mass Screening/methods; Vaginal Smears/methods; Early Detection of Cancer/methods
A highly selective two-way purification method using liquid chromatography for isolating αS2-casein from goat milk of five different breeds

Mohsin AZ, Sukor R, Selamat J, Meor Hussin AS, Ismail IH, Jambari NN, et al.

J Chromatogr B Analyt Technol Biomed Life Sci, 2020 Dec 01;1160:122380.
PMID: 32971369 DOI: 10.1016/j.jchromb.2020.122380

The main challenges in the purification of αS2-casein are due to the low quantity in milk and high homology with other casein subunits, i.e., αS1-casein, β-casein, and κ-casein. To overcome these challenges, the aim of this study was to develop a two-step purification to isolate native αS2-casein in goat milk from five different breeds; British Alpine, Jamnapari, Saanen, Shami, and Toggenburg. The first step of the purification was executed by anion-exchange chromatography under optimal elution conditions followed by size exclusion chromatography. Tryptic peptides from in-gel digestion of purified αS2-casein were sequenced and analyzed by LC-ESI-MS/MS. From 1.05 g of whole casein, the highest yield of αS2-casein (6.7 mg/mL) was obtained from Jamnapari and the lowest yield (2.2 mg/mL) was from Saanen. A single band of pure αS2-casein was observed on SDS-PAGE for all breeds. The αS2-casein showed coverage percentage of amino acid sequence from 76.68 to 92.83%. The two-step purification process developed herein was successfully applied for isolating native αS2-casein from goat milk with high purity, which will allow for future in vitro studies to be conducted on this protein.

Matched MeSH terms: Chromatography, Liquid/methods*; Spectrometry, Mass, Electrospray Ionization/methods; Tandem Mass Spectrometry/methods
Immunoaffinity extraction and tandem mass spectrometric analysis of human chorionic gonadotropin in doping analysis

Gam LH, Tham SY, Latiff A

J Chromatogr B Analyt Technol Biomed Life Sci, 2003 Jul 25;792(2):187-96.
PMID: 12860026

A confirmatory and quantitative HPLC-tandem mass spectrometry (MS-MS) method for human chorionic gonadotropin hormone (hCG) at concentrations as low as 5 IU/l following immunoaffinity extraction of the glycoprotein from urine was developed. The extraction method involved retention of urinary hCG in the immunoaffinity column via specific antigen-antibody interaction. A variety of eluents were then used to quantitatively elute hCG from the immunoaffinity column. Qualitative and quantitative analysis of hCG were undertaken using MS-MS by identifying the amino acid sequence of the marker peptide betaT5 obtained from hCG by tryptic digestion and the peak areas of three product ions b(6)(+), b(9)(+) and y(11)(+), respectively.

Matched MeSH terms: Chromatography, Affinity/methods*; Chromatography, High Pressure Liquid/methods*; Spectrometry, Mass, Electrospray Ionization/methods*
Fulltext Comparison of the Parker flex tip and the unoflex reinforced endotracheal tube for orotracheal fibreoptic intubation in simulated difficult intubation patients

Narhari R, Nazaruddin Wan Hassan WM, Mohamad Zaini RH, Che Omar S, Abdullah Nik Mohamad N, Seevaunnamtum P

Anaesthesiol Intensive Ther, 2020;52(5):377-382.
PMID: 33327695 DOI: 10.5114/ait.2020.101387

INTRODUCTION: The choice of endotracheal tube (ETT) is important for successful orotracheal fibreoptic intubation (OFI). The aim of this study was to compare the use of the Parker flex tip (PFT) with the unoflex reinforced (UFR) ETT during OFI.
MATERIAL AND METHODS: A total of 58 patients who underwent elective surgery under general anaesthesia were randomised to two ETT groups, the PFT group (n = 29) and the UFR group (n = 29), for OFI in simulated difficult intubation patients using a rigid cervical collar. After successful standardised induction and relaxation, OFI and railroading of selected ETT were subsequently performed by a similarly experienced practitioner. Ease of insertion, degree of manipulation, time to successful intubation, post-intubation complications and haemodynamic changes were recorded for both groups.
RESULTS: he percentage of easy intubation was comparable between both groups with a slightly higher percentage in the UFR group than the PFT group (69.0% vs. 62.0%; P = 0.599). Degree of manipulation was also comparable between the two groups; the percentage of cases in which manipulation was not required was slightly higher in the UFR group than the PFT group (69.0% vs. 62.1%; P = 0.849). Time to successful intubation was also comparable between the groups, although the time was slightly shorter for the UFR group than the PFT group (56.9 s ± 39.7 s vs. 63.9 s ± 36.9 s; P = 0.488). There were also no significant differences in other parameters.
CONCLUSIONS: The Parker flex tip ETT was comparable to the unoflex reinforced ETT for OFI in simulated difficult airway patients.

Matched MeSH terms: Bronchoscopy/methods*; Fiber Optic Technology/methods*; Intubation, Intratracheal/methods*
Fulltext Multi-organ point-of-care ultrasound for COVID-19 (PoCUS4COVID): international expert consensus

Hussain A, Via G, Melniker L, Goffi A, Tavazzi G, Neri L, et al.

Crit Care, 2020 12 24;24(1):702.
PMID: 33357240 DOI: 10.1186/s13054-020-03369-5

COVID-19 has caused great devastation in the past year. Multi-organ point-of-care ultrasound (PoCUS) including lung ultrasound (LUS) and focused cardiac ultrasound (FoCUS) as a clinical adjunct has played a significant role in triaging, diagnosis and medical management of COVID-19 patients. The expert panel from 27 countries and 6 continents with considerable experience of direct application of PoCUS on COVID-19 patients presents evidence-based consensus using GRADE methodology for the quality of evidence and an expedited, modified-Delphi process for the strength of expert consensus. The use of ultrasound is suggested in many clinical situations related to respiratory, cardiovascular and thromboembolic aspects of COVID-19, comparing well with other imaging modalities. The limitations due to insufficient data are highlighted as opportunities for future research.

Matched MeSH terms: Echocardiography/methods; Expert Testimony/methods; Triage/methods
Fulltext Recent Advances in Biopolymeric Composite Materials for Tissue Engineering and Regenerative Medicines: A Review

Aslam Khan MU, Abd Razak SI, Al Arjan WS, Nazir S, Sahaya Anand TJ, Mehboob H, et al.

Molecules, 2021 Jan 25;26(3).
PMID: 33504080 DOI: 10.3390/molecules26030619

The polymeric composite material with desirable features can be gained by selecting suitable biopolymers with selected additives to get polymer-filler interaction. Several parameters can be modified according to the design requirements, such as chemical structure, degradation kinetics, and biopolymer composites' mechanical properties. The interfacial interactions between the biopolymer and the nanofiller have substantial control over biopolymer composites' mechanical characteristics. This review focuses on different applications of biopolymeric composites in controlled drug release, tissue engineering, and wound healing with considerable properties. The biopolymeric composite materials are required with advanced and multifunctional properties in the biomedical field and regenerative medicines with a complete analysis of routine biomaterials with enhanced biomedical engineering characteristics. Several studies in the literature on tissue engineering, drug delivery, and wound dressing have been mentioned. These results need to be reviewed for possible development and analysis, which makes an essential study.

Matched MeSH terms: Drug Delivery Systems/methods; Tissue Engineering/methods*; Regenerative Medicine/methods*
Fulltext An improved swarm optimization for parameter estimation and biological model selection

Abdullah A, Deris S, Mohamad MS, Anwar S

PLoS One, 2013;8(4):e61258.
PMID: 23593445 DOI: 10.1371/journal.pone.0061258

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Matched MeSH terms: Computational Biology/methods*; Systems Biology/methods*; Search Engine/methods
Immobilised Sarawak Malaysia yeast cells for production of bioethanol

Zain MM, Kofli NT, Rozaimah S, Abdullah S

Pak J Biol Sci, 2011 May 01;14(9):526-32.
PMID: 22032081

Bioethanol production using yeast has become a popular topic due to worrying depleting worldwide fuel reserve. The aim of the study was to investigate the capability of Malaysia yeast strains isolated from starter culture used in traditional fermented food and alcoholic beverages in producing Bioethanol using alginate beads entrapment method. The starter yeast consists of groups of microbes, thus the yeasts were grown in Sabouraud agar to obtain single colony called ST1 (tuak) and ST3 (tapai). The growth in Yeast Potatoes Dextrose (YPD) resulted in specific growth of ST1 at micro = 0.396 h-1 and ST3 at micro = 0.38 h-1, with maximum ethanol production of 7.36 g L-1 observed using ST1 strain. The two strains were then immobilized using calcium alginate entrapment method producing average alginate beads size of 0.51 cm and were grown in different substrates; YPD medium and Local Brown Sugar (LBS) for 8 h in flask. The maximum ethanol concentration measured after 7 h were at 6.63 and 6.59 g L-1 in YPD media and 1.54 and 1.39 g L-1in LBS media for ST1 and ST3, respectively. The use of LBS as carbon source showed higher yield of product (Yp/s), 0.59 g g-1 compared to YPD, 0.25 g g-1 in ST1 and (Yp/s), 0.54 g g-1 compared to YPD, 0.24 g g-1 in ST3 . This study indicated the possibility of using local strains (STI and ST3) to produce bioethanol via immobilization technique with local materials as substrate.

Matched MeSH terms: Industrial Microbiology/methods; Microscopy, Electron, Scanning/methods; Cell Culture Techniques/methods
Alzheimer's disease prediction algorithm based on de-correlation constraint and multi-modal feature interaction

Cheng J, Wang H, Wei S, Mei J, Liu F, Zhang G

Comput Biol Med, 2024 Mar;170:108000.
PMID: 38232453 DOI: 10.1016/j.compbiomed.2024.108000

Alzheimer's disease (AD) is a neurodegenerative disease characterized by various pathological changes. Utilizing multimodal data from Fluorodeoxyglucose positron emission tomography(FDG-PET) and Magnetic Resonance Imaging(MRI) of the brain can offer comprehensive information about the lesions from different perspectives and improve the accuracy of prediction. However, there are significant differences in the feature space of multimodal data. Commonly, the simple concatenation of multimodal features can cause the model to struggle in distinguishing and utilizing the complementary information between different modalities, thus affecting the accuracy of predictions. Therefore, we propose an AD prediction model based on de-correlation constraint and multi-modal feature interaction. This model consists of the following three parts: (1) The feature extractor employs residual connections and attention mechanisms to capture distinctive lesion features from FDG-PET and MRI data within their respective modalities. (2) The de-correlation constraint function enhances the model's capacity to extract complementary information from different modalities by reducing the feature similarity between them. (3) The mutual attention feature fusion module interacts with the features within and between modalities to enhance the modal-specific features and adaptively adjust the weights of these features based on information from other modalities. The experimental results on ADNI database demonstrate that the proposed model achieves a prediction accuracy of 86.79% for AD, MCI and NC, which is higher than the existing multi-modal AD prediction models.

Matched MeSH terms: Magnetic Resonance Imaging/methods; Positron-Emission Tomography/methods; Neuroimaging/methods
Fulltext A Method for Quantifying, Visualising, and Analysing Gastropod Shell Form

Liew TS, Schilthuizen M

PLoS One, 2016;11(6):e0157069.
PMID: 27280463 DOI: 10.1371/journal.pone.0157069

Quantitative analysis of organismal form is an important component for almost every branch of biology. Although generally considered an easily-measurable structure, the quantification of gastropod shell form is still a challenge because many shells lack homologous structures and have a spiral form that is difficult to capture with linear measurements. In view of this, we adopt the idea of theoretical modelling of shell form, in which the shell form is the product of aperture ontogeny profiles in terms of aperture growth trajectory that is quantified as curvature and torsion, and of aperture form that is represented by size and shape. We develop a workflow for the analysis of shell forms based on the aperture ontogeny profile, starting from the procedure of data preparation (retopologising the shell model), via data acquisition (calculation of aperture growth trajectory, aperture form and ontogeny axis), and data presentation (qualitative comparison between shell forms) and ending with data analysis (quantitative comparison between shell forms). We evaluate our methods on representative shells of the genera Opisthostoma and Plectostoma, which exhibit great variability in shell form. The outcome suggests that our method is a robust, reproducible, and versatile approach for the analysis of shell form. Finally, we propose several potential applications of our methods in functional morphology, theoretical modelling, taxonomy, and evolutionary biology.

Matched MeSH terms: Image Processing, Computer-Assisted/methods*; Tomography, X-Ray Computed/methods*; Imaging, Three-Dimensional/methods
Fulltext The Application of Molecular Spectroscopy in Combination with Chemometrics for Halal Authentication Analysis: A Review

Rohman A, Windarsih A

Int J Mol Sci, 2020 Jul 21;21(14).
PMID: 32708254 DOI: 10.3390/ijms21145155

Halal is an Arabic term used to describe any components allowed to be used in any products by Muslim communities. Halal food and halal pharmaceuticals are any food and pharmaceuticals which are safe and allowed to be consumed according to Islamic law (Shariah). Currently, in line with halal awareness, some Muslim countries such as Indonesia, Malaysia, and Middle East regions have developed some standards and regulations on halal products and halal certification. Among non-halal components, the presence of pig derivatives (lard, pork, and porcine gelatin) along with other non-halal meats (rat meat, wild boar meat, and dog meat) is typically found in food and pharmaceutical products. This review updates the recent application of molecular spectroscopy, including ultraviolet-visible, infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies, in combination with chemometrics of multivariate analysis, for analysis of non-halal components in food and pharmaceutical products. The combination of molecular spectroscopic-based techniques and chemometrics offers fast and reliable methods for screening the presence of non-halal components of pig derivatives and non-halal meats in food and pharmaceutical products.

Matched MeSH terms: Magnetic Resonance Spectroscopy/methods*; Spectrum Analysis/methods*; Spectrum Analysis, Raman/methods*
Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases

Li CMY, Briggs MT, Lee YR, Tin T, Young C, Pierides J, et al.

Clin Exp Med, 2024 Mar 16;24(1):53.
PMID: 38492056 DOI: 10.1007/s10238-024-01311-5

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Matched MeSH terms: Chromatography, Liquid/methods; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods; Proteomics/methods
Fulltext Gaussian smoothing and modified histogram normalization methods to improve neural-biomarker interpretations for dyslexia classification mechanism

Usman OL, Muniyandi RC, Omar K, Mohamad M

PLoS One, 2021;16(2):e0245579.
PMID: 33630876 DOI: 10.1371/journal.pone.0245579

Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heterogeneous sources with inconsistent scanner settings. This study presents a method of improving the biological interpretation of dyslexia's neural-biomarkers from MRI datasets sourced from publicly available open databases. The proposed system utilized a modified histogram normalization (MHN) method to improve dyslexia neural-biomarker interpretations by mapping the pixels' intensities of low-quality input neuroimages to range between the low-intensity region of interest (ROIlow) and high-intensity region of interest (ROIhigh) of the high-quality image. This was achieved after initial image smoothing using the Gaussian filter method with an isotropic kernel of size 4mm. The performance of the proposed smoothing and normalization methods was evaluated based on three image post-processing experiments: ROI segmentation, gray matter (GM) tissues volume estimations, and deep learning (DL) classifications using Computational Anatomy Toolbox (CAT12) and pre-trained models in a MATLAB working environment. The three experiments were preceded by some pre-processing tasks such as image resizing, labelling, patching, and non-rigid registration. Our results showed that the best smoothing was achieved at a scale value, σ = 1.25 with a 0.9% increment in the peak-signal-to-noise ratio (PSNR). Results from the three image post-processing experiments confirmed the efficacy of the proposed methods. Evidence emanating from our analysis showed that using the proposed MHN and Gaussian smoothing methods can improve comparability of image features and neural-biomarkers of dyslexia with a statistically significantly high disc similarity coefficient (DSC) index, low mean square error (MSE), and improved tissue volume estimations. After 10 repeated 10-fold cross-validation, the highest accuracy achieved by DL models is 94.7% at a 95% confidence interval (CI) level. Finally, our finding confirmed that the proposed MHN method significantly outperformed the normalization method of the state-of-the-art histogram matching.

Matched MeSH terms: Image Processing, Computer-Assisted/methods*; Magnetic Resonance Imaging/methods*; Neuroimaging/methods*
Fulltext Genetic analysis and selection of Bambara groundnut (Vigna subterranea [L.] Verdc.) landraces for high yield revealed by qualitative and quantitative traits

Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M

Sci Rep, 2021 Apr 07;11(1):7597.
PMID: 33828137 DOI: 10.1038/s41598-021-87039-8

As a crop for the new millennium Bambara groundnut (Vigna subterranea [L.] Verdc.) considered as leading legumes in the tropical regions due to its versatile advantages. The main intent of this study was to find out the high yielding potential genotypes and considering these genotypes to develop pure lines for commercial cultivation in Malaysia. Considering the 14 qualitative and 27 quantitative traits of fifteen landraces the variation and genetic parameters namely, variability, heritability, genetic advance, characters association, and cluster matrix were determined. ANOVA revealed significant variation for all the agronomic traits (except plant height). Among the accessions, highly significant differences (P ≤ 0.01) were found for almost all the traits excluding fifty percent flowering date, seed length, seed width. The 16 traits out of the 27 quantitative traits had a coefficient of variation (CV) ≥ 20%. A positive and intermediate to perfect highly significant association (r = 0.23 to 1.00; P

Matched MeSH terms: Plant Breeding/methods*; Agriculture/methods*; Genetic Testing/methods
Fulltext Concomitant fat embolism syndrome and pulmonary embolism in a patient with patent foramen ovale

Dk Yeak R, Liew SK

Acta Orthop Traumatol Turc, 2020 Jul;54(4):465-468.
PMID: 32812879 DOI: 10.5152/j.aott.2020.20035

We present a rare case of a patient with concurrent fat embolism and pulmonary embolism, in a closed femur fracture with patent foramen ovale (PFO). A 24-year-old man was involved in a motor vehicle accident with a closed left midshaft femur fracture. He developed fat embolism syndrome (FES) on day 3 of admission, and plating was performed. The D-dimer concentration was also high, which raised the suspicion of pulmonary artery embolism. Computed tomography pulmonary angiography (CTPA) revealed right inferior lobar pulmonary artery embolism and FES. A transthoracic echocardiogram (TEE) was performed, which showed a PFO. The presence of a PFO in patients with pulmonary embolism increases the risk of systemic embolism. Therefore, we recommend the routine echocardiogram for patients with pulmonary embolism to exclude any cardiac defect in causing right-to-left shunts, which predisposes the patient to paradoxical embolism.

Matched MeSH terms: Echocardiography/methods; Patient Care Management/methods; Computed Tomography Angiography/methods
Fulltext Advancing stem cell therapy from bench to bedside: lessons from drug therapies

Srijaya TC, Ramasamy TS, Kasim NH

J Transl Med, 2014;12:243.
PMID: 25182194 DOI: 10.1186/s12967-014-0243-9

The inadequacy of existing therapeutic tools together with the paucity of organ donors have always led medical researchers to innovate the current treatment methods or to discover new ways to cure disease. Emergence of cell-based therapies has provided a new framework through which it has given the human world a new hope. Though relatively a new concept, the pace of advancement clearly reveals the significant role that stem cells will ultimately play in the near future. However, there are numerous uncertainties that are prevailing against the present setting of clinical trials related to stem cells: like the best route of cell administration, appropriate dosage, duration and several other applications. A better knowledge of these factors can substantially improve the effectiveness of disease cure or organ repair using this latest therapeutic tool. From a certain perspective, it could be argued that by considering certain proven clinical concepts and experience from synthetic drug system, we could improve the overall efficacy of cell-based therapies. In the past, studies on synthetic drug therapies and their clinical trials have shown that all the aforementioned factors have critical ascendancy over its therapeutic outcomes. Therefore, based on the knowledge gained from synthetic drug delivery systems, we hypothesize that by employing many of the clinical approaches from synthetic drug therapies to this new regenerative therapeutic tool, the efficacy of stem cell-based therapies can also be improved.

Matched MeSH terms: Drug Therapy/methods; Specimen Handling/methods; Stem Cell Transplantation/methods
Potential Biomedical Applications of Terbium-Based Nanoparticles (TbNPs): A Review on Recent Advancement

Mohanto S, Biswas A, Gholap AD, Wahab S, Bhunia A, Nag S, et al.

ACS Biomater Sci Eng, 2024 May 13;10(5):2703-2724.
PMID: 38644798 DOI: 10.1021/acsbiomaterials.3c01969

The scientific world is increasingly focusing on rare earth metal oxide nanomaterials due to their consequential biological prospects, navigated by breakthroughs in biomedical applications. Terbium belongs to rare earth elements (lanthanide series) and possesses remarkably strong luminescence at lower energy emission and signal transduction properties, ushering in wide applications for diagnostic measurements (i.e., bioimaging, biosensors, fluorescence imaging, etc.) in the biomedical sectors. In addition, the theranostic applications of terbium-based nanoparticles further permit the targeted delivery of drugs to the specific site of the disease. Furthermore, the antimicrobial properties of terbium nanoparticles induced via reactive oxygen species (ROS) cause oxidative damage to the cell membrane and nuclei of living organisms, ion release, and surface charge interaction, thus further creating or exhibiting excellent antioxidant characteristics. Moreover, the recent applications of terbium nanoparticles in tissue engineering, wound healing, anticancer activity, etc., due to angiogenesis, cell proliferation, promotion of growth factors, biocompatibility, cytotoxicity mitigation, and anti-inflammatory potentials, make this nanoparticle anticipate a future epoch of nanomaterials. Terbium nanoparticles stand as a game changer in the realm of biomedical research, proffering a wide array of possibilities, from revolutionary imaging techniques to advanced drug delivery systems. Their unique properties, including luminescence, magnetic characteristics, and biocompatibility, have redefined the boundaries of what can be achieved in biomedicine. This review primarily delves into various mechanisms involved in biomedical applications via terbium-based nanoparticles due to their physicochemical characteristics. This review article further explains the potential biomedical applications of terbium nanoparticles with in-depth significant mechanisms from the individual literature. This review additionally stands as the first instance to furnish a "single-platted" comprehensive acquaintance of terbium nanoparticles in shaping the future of healthcare as well as potential limitations and overcoming strategies that require exploration before being trialed in clinical settings.

Matched MeSH terms: Theranostic Nanomedicine/methods; Drug Delivery Systems/methods; Tissue Engineering/methods

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