Category: Statistics

G3 (Bethesda). 2022 Aug 11:jkac205. doi: 10.1093/g3journal/jkac205. Online ahead of print.

ABSTRACT

Properties of gene genealogies such as tree height (H), total branch length (L), total lengths of external (E) and internal (I) branches, mean length of basal branches (B), and the underlying coalescence times (T) can be used to study population-genetic processes and to develop statistical tests of population-genetic models. Uses of tree features in statistical tests often rely on predictions that depend on pairwise relationships among such features. For genealogies under the coalescent, we provide exact expressions for Taylor approximations to expected values and variances of ratios Xn/Yn, for all 15 pairs among the variables {Hn, Ln, En, In, Bn, Tk}, considering n leaves and 2 ≤ k ≤ n. For expected values of the ratios, the approximations match closely with empirical simulation-based values. The approximations to the variances are not as accurate, but they generally match simulations in their trends as n increases. Although En has expectation 2 and Hn has expectation 2 in the limit as n → ∞, the approximation to the limiting expectation for En/Hn is not 1, instead equaling π2/3-2 ≈ 1.28987. The new approximations augment fundamental results in coalescent theory on the shapes of genealogical trees.

PMID:35951748 | DOI:10.1093/g3journal/jkac205

Rheumatology (Oxford). 2022 Aug 11:keac448. doi: 10.1093/rheumatology/keac448. Online ahead of print.

ABSTRACT

OBJECTIVES: The primary objective was to compare the effect of cognitive behavioural therapy for insomnia (CBT-I) to usual care on sleep efficiency, measured by polysomnography (PSG) immediately after the intervention at week 7. Secondary objectives included comparing the longer-term effect on sleep- and RA-related outcomes at week 26.

METHODS: In a randomised controlled trial using a parallel group design, the experimental intervention was six weeks’ nurse-led group-based CBT-I; the comparator was usual care. Analyses were based on the intention-to-treat (ITT) principle; missing data were statistically modelled using repeated-measures linear mixed effects models adjusted for the level at baseline.

RESULTS: The ITT population consisted of 62 patients (89% women), with an average age of 58 years and an average sleep efficiency of 83.1%. At primary end point, sleep efficiency was 88.7% in the CBT-I group, compared with 83.7% in the control group (difference: 5.03 [95% CI -0.37-10.43]; p = 0.068) measured by PSG at week 7. Key secondary outcomes measured with PSG had not improved at week 26. However, for all the patient-reported key secondary sleep- and RA-related outcomes, there were statistically highly significant differences between CBT-I and usual care (p < 0.0001), e.g. insomnia (Insomnia Severity Index: -9.85 [95% CI -11.77 to -7.92]), and the RA impact of disease (RAID: -1.36 [95% CI-1.92 to -0.80]) at week 26.

CONCLUSION: Nurse-led group-based CBT-I did not lead to an effect on sleep efficiency objectively measured with PSG. However, CBT-I showed improvement on all patient-reported key secondary sleep- and RA-related outcomes measured at week 26.Trial registrationClinicalTrials.gov, https://clinicaltrials.gov, NCT03766100.

PMID:35951745 | DOI:10.1093/rheumatology/keac448

J Appl Microbiol. 2022 Aug 11. doi: 10.1111/jam.15774. Online ahead of print.

ABSTRACT

AIMS: In the current study the anti-virulence and anti-biofilm activities of the cinnamic acid derivative, 3-methoxycinnamic acid, was investigated against Agrobacterium tumefaciens.

METHODS AND RESULTS: Based on the disc diffusion test and β-galactosidase activity assay, 3-methoxycinnamic acid was shown to interfere with the quorum sensing (QS) system of A. tumefaciens. Crystal violet staining assay, phenol-sulfuric acid method, Bradford protein assay and confocal laser scanning microscopy (CLSM) revealed that the biofilm formation of A. tumefaciens was inhibited after the treatment of 3-methoxycinnamic acid. Employing high performance liquid chromatography (HPLC) analysis of culture supernatant revealed that the production of 3-oxo-octanoylhomoserine lactone (3-oxo-C8-HSL) decreased concentration-dependently after treatment with 3-methoxycinnamic acid. Swimming and chemotaxis assays also indicated that 3-methoxycinnamic acid had a good effect on reducing the motility and chemotaxis of A. tumefaciens. In addition, the RT-qPCR, molecular docking and simulations further demonstrated that 3-methoxycinnamic acid could competitively inhibit the binding of 3-oxo-C8-HSL to TraR and down-regulate virulence-related genes.

CONCLUSIONS: 3-Methoxycinnamic acid is proved to have good anti-virulence and anti-biofilm activities against A. tumefaciens.

SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first study that investigates the anti-virulence and anti-biofilm activities of 3-methoxycinnamic acid against A. tumefaciens. With its potential QS-related virulence and biofilm inhibitory activities, 3-methoxycinnamic acid is expected to be developed as a potent pesticide or adjuvant for the prevention and treatment of crown gall caused by A. tumefaciens.

PMID:35951737 | DOI:10.1111/jam.15774

Science. 2022 Aug 11:eabk3512. doi: 10.1126/science.abk3512. Online ahead of print.

ABSTRACT

Mammalian genomes possess multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, yet it is unclear how these enhancers coordinate to achieve this task. Here, we combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network possesses a nested multi-layer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify non-coding variant pairs associated with pathogenic genes in diseases beyond Genome-Wide Association Studies (GWAS) analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases.

PMID:35951677 | DOI:10.1126/science.abk3512

Ophthalmic Surg Lasers Imaging Retina. 2022 Aug;53(8):430-438. doi: 10.3928/23258160-20220725-02. Epub 2022 Aug 1.

ABSTRACT

BACKGROUND AND OBJECTIVE: To explore the association between best-corrected visual acuity (BCVA) improvement and changes in microperimetry (MP) and color vision in patients with nonexudative age-related macular degeneration following administration of two 1.0-mg intravitreal doses of risuteganib.

PATIENTS AND METHODS: In a phase 2a, prospective, double-masked, sham-controlled study, eyes with nonexudative age-related macular degeneration and Early Treatment Diabetic Retinopathy Study BCVA between 20/40 and 20/200 were randomized to intravitreal risuteganib (1.0 mg) or sham injection. The risuteganib group received a second 1.0-mg dose, and patients in the sham group crossed over to receive 1.0 mg of risuteganib at week 16. Exploratory endpoints included changes in color vision and mesopic MP.

RESULTS: Thirty-nine patients (risuteganib, n = 25; sham, n = 14) completed the study. There was a significant (P < .05) correlation between BCVA and the total error score (TES) for both Lanthony and Hue Style. Confusion index was close to the criterion for significance (P = .056) in the risuteganib group. All color vision metrics demonstrated a trend toward improvement in risuteganib responders (BCVA letter gain ≥8 letters) and no change in the nonresponders, with significant differences seen in confusion index between the risuteganib and control group (P = .0493) and between responders and nonresponders (P = .0478). MP showed that risuteganib responders improved in mean sensitivity and change in number of loci ≤11 dB and ≤0 dB, whereas nonresponders worsened.

CONCLUSION: All color vision and MP parameters tested trended toward improvement in risuteganib-treated patients and risuteganib responders. Statistically significant improvement was evident in two metrics: confusion index (in risuteganib-treated patients and responders) and number of loci with decreased sensitivity (in responders). A significant correlation between BCVA and both TES Lanthony and TES Hue Style in risuteganib patients provides concurrent evidence of objective and subjective improvement of retinal function. [Ophthalmic Surg Lasers Imaging Retina 2022;53:430-438.].

PMID:35951718 | DOI:10.3928/23258160-20220725-02

PLoS One. 2022 Aug 11;17(8):e0272538. doi: 10.1371/journal.pone.0272538. eCollection 2022.

ABSTRACT

Movement of organisms plays a fundamental role in the evolution and diversity of life. Animals typically move at an irregular pace over time and space, alternating among movement states. Understanding movement decisions and developing mechanistic models of animal distribution dynamics can thus be contingent to adequate discrimination of behavioral phases. Existing methods to disentangle movement states typically require a follow-up analysis to identify state-dependent drivers of animal movement, which overlooks statistical uncertainty that comes with the state delineation process. Here, we developed population-level, multi-state step selection functions (HMM-SSF) that can identify simultaneously the different behavioral bouts and the specific underlying behavior-habitat relationship. Using simulated data and relocation data from mule deer (Odocoileus hemionus), plains bison (Bison bison bison) and plains zebra (Equus quagga), we illustrated the HMM-SSF robustness, versatility, and predictive ability for animals involved in distinct behavioral processes: foraging, migrating and avoiding a nearby predator. Individuals displayed different habitat selection pattern during the encamped and the travelling phase. Some landscape attributes switched from being selected to avoided, depending on the movement phase. We further showed that HMM-SSF can detect multi-modes of movement triggered by predators, with prey switching to the travelling phase when predators are in close vicinity. HMM-SSFs thus can be used to gain a mechanistic understanding of how animals use their environment in relation to the complex interplay between their needs to move, their knowledge of the environment and navigation capacity, their motion capacity and the external factors related to landscape heterogeneity.

PMID:35951664 | DOI:10.1371/journal.pone.0272538

PLoS One. 2022 Aug 11;17(8):e0272861. doi: 10.1371/journal.pone.0272861. eCollection 2022.

ABSTRACT

Kmeans clustering algorithm is an iterative unsupervised learning algorithm that tries to partition the given dataset into k pre-defined distinct non-overlapping clusters where each data point belongs to only one group. However, its performance is affected by its sensitivity to the initial cluster centroids with the possibility of convergence into local optimum and specification of cluster number as the input parameter. Recently, the hybridization of metaheuristics algorithms with the K-Means algorithm has been explored to address these problems and effectively improve the algorithm’s performance. Nonetheless, most metaheuristics algorithms require rigorous parameter tunning to achieve an optimum result. This paper proposes a hybrid clustering method that combines the well-known symbiotic organisms search algorithm with K-Means using the SOS as a global search metaheuristic for generating the optimum initial cluster centroids for the K-Means. The SOS algorithm is more of a parameter-free metaheuristic with excellent search quality that only requires initialising a single control parameter. The performance of the proposed algorithm is investigated by comparing it with the classical SOS, classical K-means and other existing hybrids clustering algorithms on eleven (11) UCI Machine Learning Repository datasets and one artificial dataset. The results from the extensive computational experimentation show improved performance of the hybrid SOSK-Means for solving automatic clustering compared to the standard K-Means, symbiotic organisms search clustering methods and other hybrid clustering approaches.

PMID:35951672 | DOI:10.1371/journal.pone.0272861

PLoS One. 2022 Aug 11;17(8):e0267705. doi: 10.1371/journal.pone.0267705. eCollection 2022.

ABSTRACT

INTRODUCTION: Genomic research and neurobiobanking are expanding globally. Empirical evidence on the level of awareness and willingness to donate/share biological samples towards the expansion of neurobiobanking in sub-Saharan Africa is lacking.

AIMS: To ascertain the awareness, perspectives and predictors regarding biological sample donation, sharing and informed consent preferences among community members in Ghana and Nigeria.

METHODS: A questionnaire cross-sectional survey was conducted among randomly selected community members from seven communities in Ghana and Nigeria.

RESULTS: Of the 1015 respondents with mean age 39.3 years (SD 19.5), about a third had heard of blood donation (37.2%, M: 42.4%, F: 32.0%, p = 0.001) and a quarter were aware of blood sample storage for research (24.5%; M: 29.7%, F: 19.4%, p = 0.151). Two out of ten were willing to donate brain after death (18.8%, M: 22.6%, F: 15.0%, p<0.001). Main reasons for unwillingness to donate brain were; to go back to God complete (46.6%) and lack of knowledge related to brain donation (32.7%). Only a third of the participants were aware of informed consent (31.7%; M: 35.9%, F: 27.5%, p<0.001). Predictors of positive attitude towards biobanking and informed consent were being married, tertiary level education, student status, and belonging to select ethnic groups.

CONCLUSION: There is a greater need for research attention in the area of brain banking and informed consent. Improved context-sensitive public education on neurobiobanking and informed consent, in line with the sociocultural diversities, is recommended within the African sub region.

PMID:35951660 | DOI:10.1371/journal.pone.0267705

PLoS Comput Biol. 2022 Aug 11;18(8):e1010367. doi: 10.1371/journal.pcbi.1010367. Online ahead of print.

ABSTRACT

Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-based compound screening and drug repurposing. State-of-the-art machine learning methods use a small number of fixed cell lines as a surrogate for predicting actual expressions in a new cell type or tissue, although it is well known that drug responses depend on a cellular context. Thus, the existing approach has limitations when applied to personalized medicine, especially for many understudied diseases whose molecular profiles are dramatically different from those characterized in the training data. Besides the gene expression, dose-dependent cell viability is another important phenotype readout and is more informative than conventional summary statistics (e.g., IC50) for characterizing clinical drug efficacy and toxicity. However, few computational methods can reliably predict the dose-dependent cell viability. To address the challenges mentioned above, we designed a new deep learning model, MultiDCP, to predict cellular context-dependent gene expressions and cell viability on a specific dosage. The novelties of MultiDCP include a knowledge-driven gene expression profile transformer that enables context-specific phenotypic response predictions of novel cells or tissues, integration of multiple diverse labeled and unlabeled omics data, the joint training of the multiple prediction tasks, and a teacher-student training procedure that allows us to utilize unreliable data effectively. Comprehensive benchmark studies suggest that MultiDCP outperforms state-of-the-art methods with unseen cell lines that are dissimilar from the cell lines in the supervised training in terms of gene expressions. The predicted drug-induced gene expressions demonstrate a stronger predictive power than noisy experimental data for downstream tasks. Thus, MultiDCP is a useful tool for transcriptomics-based drug repurposing and compound screening that currently rely on noisy high-throughput experimental data. We applied MultiDCP to repurpose individualized drugs for Alzheimer’s disease in terms of efficacy and toxicity, suggesting that MultiDCP is a potentially powerful tool for personalized drug discovery.

PMID:35951653 | DOI:10.1371/journal.pcbi.1010367

PLoS One. 2022 Aug 11;17(8):e0272333. doi: 10.1371/journal.pone.0272333. eCollection 2022.

ABSTRACT

BACKGROUND/OBJECTIVE: To evaluate the development of intra- and post-operative retinal breaks after pars plana vitrectomy (PPV) for macular hole (MH) and/or vitreomacular traction (VMT).

SUBJECTS/METHODS: Medical records of patients who underwent PPV at Kellogg Eye Center between 1/1/2005-6/30/2018, were evaluated in three groups: group 1, MH/VMT (n = 136); group 2, epiretinal membrane (ERM) without VMT (n = 270); and group 3, diagnostic vitrectomy (DV) or vitreous opacities (n = 35). Statistical analyses were conducted using SAS.

RESULTS: 20.6% of patients with MH/VMT, 8.5% of patients with ERM, and 5.7% of patients with DV or vitreous opacities had either intra-operative or post-operative breaks. Indication of MH/VMT versus ERM was a significant predictor for this outcome (p = .0112). The incidence of retinal breaks was higher in operations using 23-gauge versus 25-gauge PPV (25.0% vs. 7.4%, p < .0001).

CONCLUSIONS: The presence of MH and/or VMT is a significant risk factor for retinal breaks from PPV, as is use of 23-gauge vitrectomy.

PMID:35951646 | DOI:10.1371/journal.pone.0272333