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Prevalence and subtypes of Blastocystis among migrant workers from different working sectors in Peninsular Malaysia

Sahimin N, Meor Termizi FH, Rajamanikam A, Mohd Nazri NA, Govind SK, Mohd Zain SN

Parasitol Res, 2020 Oct;119(10):3555-3558.
PMID: 32875397 DOI: 10.1007/s00436-020-06865-3

Blastocystis sp. is a common enteric parasite of humans and animals associated with inadequate sanitation and poor personal hygiene. Over the years, the Malaysian thriving economy has been facilitated largely by migrant workers from developing countries, and there is concern that diseases endemic to their countries may be imported. Therefore, this study aimed to determine the current status of Blastocystis infection as well as subtypes (STs) from fecal samples among migrant workers in Selangor and Kuala Lumpur, Malaysia. Overall, almost a third of the study cohort (30.9%; n = 68/220) screened were infected with Blastocystis sp. predominantly with ST3 (54.5%; n = 12), followed by ST1 (36.4%; n = 8) and ST2 (9.1%; n = 2). Infection levels was almost similar among the different sectors; manufacturing (32.8%), domestic service (32.3%), and food service (27.3%) with common symptoms for infection included stomach and abdominal pain or discomfort and diarrhea (48.5%; n = 33). None of the socio-demographic risk factors evaluated were significant. Therefore, this study warrants continuous monitoring as well as understanding the impact of transmission among the migrant community with the local population especially those involved in food service sector.
Nitrate Classification Based on Optical Absorbance Data Using Machine Learning Algorithms for a Hydroponics System

Sulaiman R, Azeman NH, Abu Bakar MH, Ahmad Nazri NA, Masran AS, Ashrif A Bakar A

Appl Spectrosc, 2023 Feb;77(2):210-219.
PMID: 36348500 DOI: 10.1177/00037028221140924

Nutrient solution plays an essential role in providing macronutrients to hydroponic plants. Determining nitrogen in the form of nitrate is crucial, as either a deficient or excessive supply of nitrate ions may reduce the plant yield or lead to environmental pollution. This work aims to evaluate the performance of feature reduction techniques and conventional machine learning (ML) algorithms in determining nitrate concentration levels. Two features reduction techniques, linear discriminant analysis (LDA) and principal component analysis (PCA), and seven ML algorithms, for example, k-nearest neighbors (KNN), support vector machine, decision trees, naïve bayes, random forest (RF), gradient boosting, and extreme gradient boosting, were evaluated using a high-dimensional spectroscopic dataset containing measured nitrate-nitrite mixed solution absorbance data. Despite the limited and uneven number of samples per class, this study demonstrated that PCA outperformed LDA on the high-dimensional spectroscopic dataset. The classification accuracy of ML algorithms combined with PCA ranged from 92.7% to 99.8%, whereas the classification accuracy of ML algorithms combined with LDA ranged from 80.7% to 87.6%. The PCA with the RF algorithm exhibited the best performance with 99.8% accuracy.
Fulltext Pereskia bleo augments NK cell cytotoxicity against triple-negative breast cancer cells (MDA-MB-231)

Khalaf TK, Ismail N, Nazri NA, Ahmed N, Yajid AI, Mohamud R, et al.

PeerJ, 2024;12:e18420.
PMID: 39619199 DOI: 10.7717/peerj.18420

BACKGROUND: Natural killer cells (NK cells) are essential in cancer immunosurveillance in the body as they can recognize cancer cells that lacking MHC class 1 on their surface. Regulatory cytokines, including interleukin (IL)-18, IL-12, IL-10, IL-8, interferon-γ (IFN-γ), and secretory granules like perforin and granzyme are involved in NK cell-mediated cytotoxicity. Stimulating NK cells cytotoxicity towards cancer cells is an ideal strategy to combat cancer naturally. Medicinal plants have been reported to enhance immunity, with Pereskia bleo (P. bleo) particularly noteworthy due to its abundant bioactive compounds and ability to activate immune cells. This study aimed to evaluate the potential of methanol extract of P. bleo leaves (MEPB) for enhancing NK cell cytotoxicity against triple-negative human breast cancer cells (MDA-MB-231).
METHODS: The optimal concentration of MEPB to activate NK cells was determined using healthy blood samples, assessing the expression of IL-12, IL-18, IL-10, IL-8, IFN-γ, perforin, and granzyme B via an enzyme-linked immunosorbent assay (ELISA). NK cell purity from healthy donors and breast cancer patients was determined using specific antibodies, and the number of NK cells was assessed using flow cytometry and a hemocytometer. A co-culture experiment, ELISA, and apoptosis assay were used to evaluate NK-mediated cytotoxicity pathways.
RESULTS: ELISA data indicated that MEPB at 7.5 µg/ml significantly increased the expression of IFN-γ, IL-12, IL-18, perforin, and granzyme B while decreasing IL-8 and IL-10 expression after 20 hrs of incubation. The average NK cell purity was 87.09 ± 0.043%. Breast cancer patients exhibited lower NK cell counts than healthy donors. Co-culture experiments demonstrated that NK cells induced apoptosis in MDA-MB-231 breast cancer cells in the presence of MEPB by increasing perforin, granzyme B, and IFN-γ expression in both healthy donors and breast cancer patients-experimental groups. P. bleo enhances NK cell activation, promoting the apoptosis of triple-negative human breast cancer cells (MDA-MB-231), suggesting the potential use of MEPB leaves as an anti-cancer immunostimulant.
Fulltext Succinyl-κ-carrageenan Silver Nanotriangles Composite for Ammonium Localized Surface Plasmon Resonance Sensor

Abu Bakar MH, Azeman NH, Mobarak NN, Ahmad Nazri NA, Tengku Abdul Aziz TH, Md Zain AR, et al.

Polymers (Basel), 2022 Jan 14;14(2).
PMID: 35054734 DOI: 10.3390/polym14020329

This research investigates the physicochemical properties of biopolymer succinyl-κ-carrageenan as a potential sensing material for NH4+ Localized Surface Plasmon Resonance (LSPR) sensor. Succinyl-κ-carrageenan was synthesised by reacting κ-carrageenan with succinic anhydride. FESEM analysis shows succinyl-κ-carrageenan has an even and featureless topology compared to its pristine form. Succinyl-κ-carrageenan was composited with silver nanoparticles (AgNP) as LSPR sensing material. AFM analysis shows that AgNP-Succinyl-κ-carrageenan was rougher than AgNP-Succinyl-κ-carrageenan, indicating an increase in density of electronegative atom from oxygen compared to pristine κ-carrageenan. The sensitivity of AgNP-Succinyl-κ-carrageenan LSPR is higher than AgNP-κ-carrageenan LSPR. The reported LOD and LOQ of AgNP-Succinyl-κ-carrageenan LSPR are 0.5964 and 2.7192 ppm, respectively. Thus, AgNP-Succinyl-κ-carrageenan LSPR has a higher performance than AgNP-κ-carrageenan LSPR, broader detection range than the conventional method and high selectivity toward NH4+. Interaction mechanism studies show the adsorption of NH4+ on κ-carrageenan and succinyl-κ-carrageenan were through multilayer and chemisorption process that follows Freundlich and pseudo-second-order kinetic model.