Tag: statistics

Comput Biol Med. 2021 Oct 5;138:104915. doi: 10.1016/j.compbiomed.2021.104915. Online ahead of print.

ABSTRACT

The SARS-CoV-2 virus like many other viruses has transformed in a continual manner to give rise to new variants by means of mutations commonly through substitutions and indels. These mutations in some cases can give the virus a survival advantage making the mutants dangerous. In general, laboratory investigation must be carried to determine whether the new variants have any characteristics that can make them more lethal and contagious. Therefore, complex and time-consuming analyses are required in order to delve deeper into the exact impact of a particular mutation. The time required for these analyses makes it difficult to understand the variants of concern and thereby limiting the preventive action that can be taken against them spreading rapidly. In this analysis, we have deployed a statistical technique Shannon Entropy, to identify positions in the spike protein of SARS Cov-2 viral sequence which are most susceptible to mutations. Subsequently, we also use machine learning based clustering techniques to cluster known dangerous mutations based on similarities in properties. This work utilizes embeddings generated using language modeling, the ProtBERT model, to identify mutations of a similar nature and to pick out regions of interest based on proneness to change. Our entropy-based analysis successfully predicted the fifteen hotspot regions, among which we were able to validate ten known variants of interest, in six hotspot regions. As the situation of SARS-COV-2 virus rapidly evolves we believe that the remaining nine mutational hotspots may contain variants that can emerge in the future. We believe that this may be promising in helping the research community to devise therapeutics based on probable new mutation zones in the viral sequence and resemblance in properties of various mutations.

PMID:34655896 | DOI:10.1016/j.compbiomed.2021.104915

Comput Biol Med. 2021 Oct 9;138:104929. doi: 10.1016/j.compbiomed.2021.104929. Online ahead of print.

ABSTRACT

Cholera is a severe small intestine bacterial disease caused by consumption of water and food contaminated with Vibrio cholera. The disease causes watery diarrhea leading to severe dehydration and even death if left untreated. In the past few decades, V. cholerae has emerged as multidrug-resistant enteric pathogen due to its rapid ability to adapt in detrimental environmental conditions. This research study aimed to design inhibitors of a master virulence gene expression regulator, HapR. HapR is critical in regulating the expression of several set of V. cholera virulence genes, quorum-sensing circuits and biofilm formation. A blind docking strategy was employed to infer the natural binding tendency of diverse phytochemicals extracted from medicinal plants by exposing the whole HapR structure to the screening library. Scoring function criteria was applied to prioritize molecules with strong binding affinity (binding energy < -11 kcal/mol) and as such two compounds: Strychnogucine A and Galluflavanone were filtered. Both the compounds were found favourably binding to the conserved dimerization interface of HapR. One rare binding conformation of Strychnogucine A was noticed docked at the elongated cavity formed by α1, α4 and α6 (binding energy of -12.5 kcal/mol). The binding stability of both top leads at dimer interface and elongated cavity was further estimated using long run of molecular dynamics simulations, followed by MMGB/PBSA binding free energy calculations to define the dominance of different binding energies. In a nutshell, this study presents computational evidence on antibacterial potential of phytochemicals capable of directly targeting bacterial virulence and highlight their great capacity to be utilized in the future experimental studies to stop the evolution of antibiotic resistance evolution.

PMID:34655900 | DOI:10.1016/j.compbiomed.2021.104929

Comput Biol Med. 2021 Oct 9;138:104936. doi: 10.1016/j.compbiomed.2021.104936. Online ahead of print.

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Reports of new variants that potentially increase virulence and viral transmission, as well as reduce the efficacy of available vaccines, have recently emerged. In this study, we computationally analyzed the N439K, S477 N, and T478K variants for their ability to bind Angiotensin-converting enzyme 2 (ACE2). We used the protein-protein docking approach to explore whether the three variants displayed a higher binding affinity to the ACE2 receptor than the wild type. We found that these variants alter the hydrogen bonding network and the cluster of interactions. Additional salt bridges, hydrogen bonds, and a high number of non-bonded contacts (i.e., non-bonded interactions between atoms in the same molecule and those in other molecules) were observed only in the mutant complexes, allowing efficient binding to the ACE2 receptor. Furthermore, we used a 2.0-μs all-atoms simulation approach to detect differences in the structural dynamic features of the resulting protein complexes. Our findings revealed that the mutant complexes possessed stable dynamics, consistent with the global trend of mutations yielding variants with improved stability and enhanced affinity. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) further revealed that electrostatic interactions principally increased net binding energies. The stability and binding energies of N439K, S477 N, and T478K variants were enhanced compared to the wild-type-ACE2 complex. The net binding energy of the systems was -31.86 kcal/mol for the wild-type-ACE2 complex, -67.85 kcal/mol for N439K, -69.82 kcal/mol for S477 N, and -69.64 kcal/mol for T478K. The current study provides a basis for exploring the enhanced binding abilities and structural features of SARS-CoV-2 variants to design novel therapeutics against the virus.

PMID:34655895 | DOI:10.1016/j.compbiomed.2021.104936

Med Image Anal. 2021 Sep 12;74:102233. doi: 10.1016/j.media.2021.102233. Online ahead of print.

ABSTRACT

Understanding which brain regions are related to a specific neurological disorder or cognitive stimuli has been an important area of neuroimaging research. We propose BrainGNN, a graph neural network (GNN) framework to analyze functional magnetic resonance images (fMRI) and discover neurological biomarkers. Considering the special property of brain graphs, we design novel ROI-aware graph convolutional (Ra-GConv) layers that leverage the topological and functional information of fMRI. Motivated by the need for transparency in medical image analysis, our BrainGNN contains ROI-selection pooling layers (R-pool) that highlight salient ROIs (nodes in the graph), so that we can infer which ROIs are important for prediction. Furthermore, we propose regularization terms-unit loss, topK pooling (TPK) loss and group-level consistency (GLC) loss-on pooling results to encourage reasonable ROI-selection and provide flexibility to encourage either fully individual- or patterns that agree with group-level data. We apply the BrainGNN framework on two independent fMRI datasets: an Autism Spectrum Disorder (ASD) fMRI dataset and data from the Human Connectome Project (HCP) 900 Subject Release. We investigate different choices of the hyper-parameters and show that BrainGNN outperforms the alternative fMRI image analysis methods in terms of four different evaluation metrics. The obtained community clustering and salient ROI detection results show a high correspondence with the previous neuroimaging-derived evidence of biomarkers for ASD and specific task states decoded for HCP. Our code is available at https://github.com/xxlya/BrainGNN_Pytorch.

PMID:34655865 | DOI:10.1016/j.media.2021.102233

J Hazard Mater. 2021 Oct 8;424(Pt B):127456. doi: 10.1016/j.jhazmat.2021.127456. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

PMID:34655869 | DOI:10.1016/j.jhazmat.2021.127456

Cancer Treat Res Commun. 2021 Sep 25;29:100466. doi: 10.1016/j.ctarc.2021.100466. Online ahead of print.

ABSTRACT

Evidence-based US guidelines provide recommendations for the use of granulocyte colony-stimulating factor (G-CSF) as supportive therapy in patients with cancer receiving chemotherapy. Pegfilgrastim is recommended for FN prophylaxis in patients with non-myeloid malignancies receiving a high-risk chemotherapy regimen, or an intermediate-risk regimen if one or more risk factors are present. The guidelines highlight the patient characteristics and chemotherapy regimens for solid tumors and hematologic malignancies that may influence a patient’s overall risk of FN and may benefit from pegfilgrastim support. This review aimed to evaluate how pegfilgrastim use in patients with cancer receiving myelosuppressive chemotherapy in routine clinical practice aligns with evidence-based US guidelines. Examination of the literature revealed widespread deviation in relation to under- and over-prescribing, and timing of administration in US clinical practice. Pegfilgrastim is often over-prescribed in patients receiving palliative chemotherapy and those at low risk of FN. Potential under-prescribing of pegfilgrastim was also observed. In this literature search, data that appear to support same-day administration of pegfilgrastim were from uncontrolled studies that were limited in size. Analyses of healthcare claims data clearly favored next-day use, with statistically significant increases in FN incidence among patients receiving same-day pegfilgrastim versus those treated 1-4 days post-chemotherapy. Earlier-than-recommended administration typically occurs at the physician’s discretion where next-day administration might present barriers to the patient receiving supportive therapy.There is a need to ensure appropriate prescribing to optimize patient outcomes, as deviation from the guideline recommendations was associated with increased incidence of FN and hospitalization.

PMID:34655862 | DOI:10.1016/j.ctarc.2021.100466

Transbound Emerg Dis. 2021 Oct 16. doi: 10.1111/tbed.14345. Online ahead of print.

ABSTRACT

Since the outbreak of African swine fever (ASF) in Shengyang, it has kept spreading in China. In the early stage of the epidemic, multi-point and concentrated outbreaks were mainly in the swill feeding areas. In this paper, we developed compartmental models to investigate the transmission of ASF in several raising units including Guquan, Jinba and Liancheng. Using the data collected from these three infected premises, we calibrated the models to estimate that the average incubation period was between 8-11 days, the onset period was about 2-3 days, and the basic reproductive number was about 4.83-11.90. We also estimated the infection on the day before culling to be 45.24% (Guquan), 89.20% (Jinba), and 16.35% (Liancheng), respectively. The infection rate of Guquan could reach about 74.8% if culling were postponed two days. We found that the infection was significantly higher than the morbidities (22.11% (Guquan), 49.35% (Jinba), and 12.94% (Liancheng)) calculated by actual statistical data. Besides, we simulated and compared the control effect of stopping transport, disinfecting, stopping swill, and culling. Our findings suggest that any single measure was not enough to prevent the spread of ASF on a regional level but the combined measures is the key. Under the current situation, fully culling was recognized as most effective in controlling the epidemic, despite the culling of innocent pigs. This article is protected by copyright. All rights reserved.

PMID:34655504 | DOI:10.1111/tbed.14345

Trop Med Int Health. 2021 Oct 16. doi: 10.1111/tmi.13695. Online ahead of print.

ABSTRACT

OBJECTIVE: Delays in seeking health care for dengue are associated with poor health outcomes. Despite this, the factors influencing such delays remain unclear, rendering interventions to improve health care-seeking for dengue ineffective. This systematic review aimed to synthesise the factors influencing health care-seeking of patients with dengue and form a comprehensive framework.

METHODS: This review included both qualitative and quantitative studies. Studies were obtained by searching five databases, contacting field experts, and performing backward reference searches. The best-fit meta-synthesis approach was used during data synthesis, where extracted data were fitted into the social-ecological model. Sub-analyses were conducted to identify the commonly reported factors and their level of statistical significance.

RESULTS: Twenty studies were selected for meta-synthesis. Eighteen factors influencing health care-seeking in dengue were identified and categorised under four domains: individual (11 factors), interpersonal (1 factor), organisational (4 factors), and community (2 factors). The most reported factors were knowledge of dengue, access to health care, quality of health service and resource availability. Overall, more barriers to dengue health seeking than facilitators were found. History of dengue infection and having knowledge of dengue were found to be ambiguous as they both facilitated and hindered dengue health care-seeking. Contrary to common belief, women were less likely to seek help for dengue than men.

CONCLUSIONS: The factors affecting dengue health care-seeking behaviour are diverse, can be ambiguous and are found across multiple social-ecological levels. Understanding these complexities is essential for the development of effective interventions to improve dengue health care-seeking behaviour.

PMID:34655508 | DOI:10.1111/tmi.13695

Mycoses. 2021 Oct 16. doi: 10.1111/myc.13380. Online ahead of print.

ABSTRACT

BACKGROUND: Several severity indexes have been reported for critically ill patients. The Pitt bacteremia score (PBS) is commonly used to predict the risk of mortality in patients with bacteremia.

OBJECTIVES: To develop a scoring system for predicting mortality in candidemia patients.

METHODS: Medical records at five Japanese tertiary hospitals were reviewed. Factors associated with mortality were analysed using logistic regression modelling. The discriminatory power of scoring models was evaluated by assessing the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS: In total, 422 candidemia patients were included. Higher PBS, dialysis, and retainment of central venous catheter were independent risk factors for all-cause 30-day mortality. However, among the five PBS components, fever was not associated with mortality; therefore, we developed a modified version of the PBS (mPBS) by replacing fever with dialysis. AUC for PBS and mPBS was 0.74 (95% confidence interval [CI]: 0.68-0.80) and 0.76 (95% CI: 0.71-0.82), respectively. The increase in predictive ability of mPBS for 30-day mortality was statistically significant as assessed by NRI (0.24, 95% CI: 0.01-0.46, P=0.04) and IRI (0.04, 95% CI: 0.02-0.06, P=0.0008). When patients were stratified by mPBS into low (scores 0-3), moderate (4-7), and high risk (≥8), there were significant differences among the survival curves (P<0.0001, log-rank test), and 30-day mortality rates were 13.8% (40/290), 36.8% (28/76), and 69.4% (34/49), respectively.

CONCLUSIONS: mPBS can be a useful tool for predicting mortality in candidemia patients.

PMID:34655487 | DOI:10.1111/myc.13380

Pediatr Allergy Immunol. 2021 Oct 16. doi: 10.1111/pai.13680. Online ahead of print.

ABSTRACT

BACKGROUND: Alexithymia is a multifaceted personality construct described as “a lack of words to express emotions” that includes difficulty identifying feelings, difficulty describing feelings and a concrete, externally oriented cognitive style. Among patients with FA, alexithymia has been found higher than in general population and associated with dysfunctional coping strategies. Childhood traumatic experiences and/or dysfunctional parent-child relationship can contribute to alexithymia. The study aimed to explore possible associations between child alexithymia and mother alexithymia and anxiety, as well as previous anaphylaxis.

METHODS: 65 mother-child pairs have been recruited. Children had a medical diagnosis of FA. The Toronto Alexithymia Scale-20 (TAS-20) was used to assess alexithymia in participants. The State-Trait Anxiety Inventory (STAI) was used to assess trait anxiety in mothers. Statistical analysis was performed to investigate the influence of variables sex, previous anaphylaxis and adrenaline auto-injector prescription on child and mother’s alexithymia and to explore possible association between maternal and child alexithymia.

RESULTS: A substantial percentage of children were alexithymic (21.5%) or borderline (33.8%), while mothers’ frequencies were lower and in line with prevalence in general population. Child alexithymia was positively associated with previous anaphylaxis and mothers’ trait anxiety (p < .05). Mother trait anxiety was also associated with maternal alexithymia. Furthermore, a positive association between child and mother alexithymia has been found.

CONCLUSIONS: Clinicians must be aware of the role of alexithymia and its association with maternal anxiety and previous anaphylaxis in children with FA, encouraging seeking psychological support when needed. A multidisciplinary patient-centered approach should be put in place for the effective care of FA.

PMID:34655502 | DOI:10.1111/pai.13680