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Fulltext Emergence and adaptive evolution of Nipah virus

Li K, Yan S, Wang N, He W, Guan H, He C, et al.

Transbound Emerg Dis, 2020 Jan;67(1):121-132.
PMID: 31408582 DOI: 10.1111/tbed.13330

Since its first emergence in 1998 in Malaysia, Nipah virus (NiV) has become a great threat to domestic animals and humans. Sporadic outbreaks associated with human-to-human transmission caused hundreds of human fatalities. Here, we collected all available NiV sequences and combined phylogenetics, molecular selection, structural biology and receptor analysis to study the emergence and adaptive evolution of NiV. NiV can be divided into two main lineages including the Bangladesh and Malaysia lineages. We formly confirmed a significant association with geography which is probably the result of long-term evolution of NiV in local bat population. The two NiV lineages differ in many amino acids; one change in the fusion protein might be involved in its activation via binding to the G protein. We also identified adaptive and positively selected sites in many viral proteins. In the receptor-binding G protein, we found that sites 384, 386 and especially 498 of G protein might modulate receptor-binding affinity and thus contribute to the host jump from bats to humans via the adaption to bind the human ephrin-B2 receptor. We also found that site 1645 in the connector domain of L was positive selected and involved in adaptive evolution; this site might add methyl groups to the cap structure present at the 5'-end of the RNA and thus modulate its activity. This study provides insight to assist the design of early detection methods for NiV to assess its epidemic potential in humans.
Fulltext Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al.

Autophagy, 2021 Jan;17(1):1-382.
PMID: 33634751 DOI: 10.1080/15548627.2020.1797280

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
Fulltext Machine learning based predictive model of Type 2 diabetes complications using Malaysian National Diabetes Registry: A study protocol

Abas MZ, Li K, Hairi NN, Choo WY, Wan KS

J Public Health Res, 2024 Jan;13(1):22799036241231786.
PMID: 38434578 DOI: 10.1177/22799036241231786

BACKGROUND: The prevalence of diabetes in Malaysia is increasing, and identifying patients with higher risk of complications is crucial for effective management. The use of machine learning (ML) to develop prediction models has been shown to outperform non-ML models. This study aims to develop predictive models for Type 2 Diabetes (T2D) complications in Malaysia using ML techniques.
DESIGN AND METHODS: This 10-year retrospective cohort study uses clinical audit datasets from Malaysian National Diabetes Registry from 2011 to 2021. T2D patients who received treatment in public health clinics in the southern region of Malaysia with at least two data points in 10 years are included. Patients with diabetes complications at baseline are excluded to ensure temporality between predictors and the target variable. Appropriate methods are used to address issues related to data cleaning, missing data imputation, data splitting, feature selection, and class imbalance. The study uses 7 ML algorithms, including logistic regression, support vector machine, k-nearest neighbours, decision tree, random forest, extreme gradient boosting, and light gradient boosting machine, to develop predictive models for four target variables: nephropathy, retinopathy, ischaemic heart disease, and stroke. Hyperparameter tuning is performed for each algorithm. The model training is performed using a stratified k-fold cross-validation technique. The best model for each algorithm is evaluated on a hold-out dataset using multiple metrics.
EXPECTED IMPACT OF THE STUDY ON PUBLIC HEALTH: The prediction model may be a valuable tool for diabetes management and secondary prevention by enabling earlier interventions and optimal resource allocation, leading to better health outcomes.
Fulltext Iptacopan monotherapy in patients with paroxysmal nocturnal hemoglobinuria: a 2-cohort open-label proof-of-concept study

Jang JH, Wong L, Ko BS, Yoon SS, Li K, Baltcheva I, et al.

Blood Adv, 2022 08 09;6(15):4450-4460.
PMID: 35561315 DOI: 10.1182/bloodadvances.2022006960

Iptacopan (LNP023) is a novel, oral selective inhibitor of complement factor B under clinical development for paroxysmal nocturnal hemoglobinuria (PNH). In this ongoing open-label phase 2 study, PNH patients with active hemolysis were randomized to receive single-agent iptacopan twice daily at a dose of either 25 mg for 4 weeks followed by 100 mg for up to 2 years (cohort 1) or 50 mg for 4 weeks followed by 200 mg for up to 2 years (cohort 2). At the time of interim analysis, of 13 PNH patients enrolled, all 12 evaluable for efficacy achieved the primary endpoint of reduction in serum lactate dehydrogenase (LDH) levels by ≥60% by week 12 compared with baseline; mean LDH levels dropped rapidly and durably, namely by 77% and 85% at week 2 and by 86% and 86% at week 12 in cohorts 1 and 2, respectively. Most patients achieved a clinically meaningful improvement in hemoglobin (Hb) levels, and all but 1 patient remained transfusion-free up to week 12. Other markers of hemolysis, including bilirubin, reticulocytes, and haptoglobin, showed consistent improvements. No thromboembolic events were reported, and iptacopan was well tolerated, with no severe or serious adverse events reported until the data cutoff. In addition to the previously reported beneficial effect of iptacopan add-on therapy to eculizumab, this study showed that iptacopan monotherapy in treatment-naïve PNH patients resulted in normalization of hemolytic markers and rapid transfusion-free improvement of Hb levels in most patients. This trial was registered at www.clinicaltrials.gov as #NCT03896152.
Antioxidants improve β-cypermethrin degradation by alleviating oxidative damage and increasing bioavailability by Bacillus cereus GW-01

Xie Y, Gong L, Liu S, Yan J, Zhao S, Xia C, et al.

Environ Res, 2023 Nov 01;236(Pt 1):116680.
PMID: 37500036 DOI: 10.1016/j.envres.2023.116680

Microbial degradation of pesticide residues has the potential to reduce their hazards to human and environmental health. However, in some cases, degradation can activate pesticides, making them more toxic to microbes. Here we report on the β-cypermethrin (β-CY) toxicity to Bacillus cereus GW-01, a recently described β-CY degrader, and effects of antioxidants on β-CY degradation. GW-01 exposed to β-CY negatively affected the growth rate. The highest maximum specific growth rate (μm) appeared at 25 mg/L β-CY. β-CY induced the oxidative stress in GW-01. The activities of superoxide dismutase (SOD), catalyse (CAT), and glutathione-S-transferase (GST) were significantly higher than that in control (p
Fulltext Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Klionsky DJ, Abdelmohsen K, Abe A, Abedin MJ, Abeliovich H, Acevedo Arozena A, et al.

Autophagy, 2016;12(1):1-222.
PMID: 26799652 DOI: 10.1080/15548627.2015.1100356