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Displaying publications 61 - 65 of 65 in total

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Fulltext Novel Canine Coronavirus Isolated from a Hospitalized Patient With Pneumonia in East Malaysia

Vlasova AN, Diaz A, Damtie D, Xiu L, Toh TH, Lee JS, et al.

Clin Infect Dis, 2022 Feb 11;74(3):446-454.
PMID: 34013321 DOI: 10.1093/cid/ciab456

BACKGROUND: During the validation of a highly sensitive panspecies coronavirus (CoV) seminested reverse-transcription polymerase chain reaction (RT-PCR) assay, we found canine CoV (CCoV) RNA in nasopharyngeal swab samples from 8 of 301 patients (2.5%) hospitalized with pneumonia during 2017-2018 in Sarawak, Malaysia. Most patients were children living in rural areas with frequent exposure to domesticated animals and wildlife.
METHODS: Specimens were further studied with universal and species-specific CoV and CCoV 1-step RT-PCR assays, and viral isolation was performed in A72 canine cells. Complete genome sequencing was conducted using the Sanger method.
RESULTS: Two of 8 specimens contained sufficient amounts of CCoVs as confirmed by less-sensitive single-step RT-PCR assays, and 1 specimen demonstrated cytopathic effects in A72 cells. Complete genome sequencing of the virus causing cytopathic effects identified it as a novel canine-feline recombinant alphacoronavirus (genotype II) that we named CCoV-human pneumonia (HuPn)-2018. Most of the CCoV-HuPn-2018 genome is more closely related to a CCoV TN-449, while its S gene shared significantly higher sequence identity with CCoV-UCD-1 (S1 domain) and a feline CoV WSU 79-1683 (S2 domain). CCoV-HuPn-2018 is unique for a 36-nucleotide (12-amino acid) deletion in the N protein and the presence of full-length and truncated 7b nonstructural protein, which may have clinical relevance.
CONCLUSIONS: This is the first report of a novel canine-feline recombinant alphacoronavirus isolated from a human patient with pneumonia. If confirmed as a pathogen, it may represent the eighth unique coronavirus known to cause disease in humans. Our findings underscore the public health threat of animal CoVs and a need to conduct better surveillance for them.
Fulltext A pan-coronavirus RT-PCR assay for rapid viral screening of animal, human, and environmental specimens

Wang X, Xiu L, Binder RA, Toh TH, Lee JS, Ting J, et al.

One Health, 2021 Dec;13:100274.
PMID: 34124332 DOI: 10.1016/j.onehlt.2021.100274

We examined a collection of 386 animal, 451 human, and 109 archived bioaerosol samples with a new pan-species coronavirus molecular assay. Thirty-eight (4.02%) of 946 specimens yielded evidence of human or animal coronaviruses. Our findings demonstrate the utility of employing the pan-CoV RT-PCR assay in detecting varied coronavirus among human, animal, and environmental specimens. This RT-PCR assay might be employed as a screening diagnostic for early detection of coronaviruses incursions or prepandemic coronavirus emergence in animal or human populations.
Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Wijedasa LS, Jauhiainen J, Könönen M, Lampela M, Vasander H, Leblanc MC, et al.

Glob Chang Biol, 2017 03;23(3):977-982.
PMID: 27670948 DOI: 10.1111/gcb.13516
Fulltext Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease

Yun J, Cho YH, Lee SM, Hwang J, Lee JS, Oh YM, et al.

Sci Rep, 2021 07 26;11(1):15144.
PMID: 34312450 DOI: 10.1038/s41598-021-94535-4

Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratification, and management. Pulmonary function tests are used to diagnose and classify the severity of COPD, but they cannot fully represent the type or range of pathophysiologic abnormalities of the disease. To evaluate whether deep radiomics from chest computed tomography (CT) images can predict mortality in patients with COPD, we designed a convolutional neural network (CNN) model for extracting representative features from CT images and then performed random survival forest to predict survival in COPD patients. We trained CNN-based binary classifier based on six-minute walk distance results (> 440 m or not) and extracted high-throughput image features (i.e., deep radiomics) directly from the last fully connected layer of it. The various sizes of fully connected layers and combinations of deep features were experimented using a discovery cohort with 344 patients from the Korean Obstructive Lung Disease cohort and an external validation cohort with 102 patients from Penang General Hospital in Malaysia. In the integrative analysis of discovery and external validation cohorts, with combining 256 deep features from the coronal slice of the vertebral body and two sagittal slices of the left/right lung, deep radiomics for survival prediction achieved concordance indices of 0.8008 (95% CI, 0.7642-0.8373) and 0.7156 (95% CI, 0.7024-0.7288), respectively. Deep radiomics from CT images could be used to predict mortality in COPD patients.
Fulltext Fatty Acid Composition of Selected Street Foods Commonly Available in Malaysia

Zainal Arifen ZN, Shahril MR, Shahar S, Mohamad H, Mohd Yazid SFZ, Michael V, et al.

Foods, 2023 Mar 14;12(6).
PMID: 36981160 DOI: 10.3390/foods12061234

Despite growing evidence of increased saturated and trans fat contents in street foods, little is known about their fatty acid (FA) compositions. This study aimed to analyse the saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), and trans fatty acids (TFAs) content of 70 selected and most commonly available street foods in Malaysia. The street foods were categorised into main meals, snacks, and desserts. TFAs were not detected in any of the street foods. Descriptively, all three categories mainly contained SFAs, followed by MUFAs, and PUFAs. However, the one-way ANOVA testing showed that the differences between each category were insignificant (p > 0.05), and each FA was not significantly different (p > 0.05) from one to another. Nearly half of the deep-fried street foods contained medium to high SFAs content (1.7 g/100 g-24.3 g/100 g), while the MUFAs were also high (32.0-44.4%). The Chi-square test of association showed that the type of preparation methods (low or high fat) used was significantly associated (p < 0.05) with the number of SFAs. These findings provide valuable information about fat composition in local street foods for the Malaysian Food Composition Database and highlight the urgency to improve nutritional composition.