8 research outputs found
Cocaine Use Prediction with Tensor-based Machine Learning on Multimodal MRI Connectome Data
This paper considers the use of machine learning algorithms for predicting
cocaine use based on magnetic resonance imaging (MRI) connectomic data. The
study utilized functional MRI (fMRI) and diffusion MRI (dMRI) data collected
from 275 individuals, which was then parcellated into 246 regions of interest
(ROIs) using the Brainnetome atlas. After data preprocessing, the datasets were
transformed into tensor form. We developed a tensor-based unsupervised machine
learning algorithm to reduce the size of the data tensor from
(individuals) (fMRI and dMRI) (ROIs)
(ROIs) to (individuals) (fMRI and dMRI) (clusters)
(clusters). This was achieved by applying the high-order Lloyd
algorithm to group the ROI data into 6 clusters. Features were extracted from
the reduced tensor and combined with demographic features (age, gender, race,
and HIV status). The resulting dataset was used to train a Catboost model using
subsampling and nested cross-validation techniques, which achieved a prediction
accuracy of 0.857 for identifying cocaine users. The model was also compared
with other models, and the feature importance of the model was presented.
Overall, this study highlights the potential for using tensor-based machine
learning algorithms to predict cocaine use based on MRI connectomic data and
presents a promising approach for identifying individuals at risk of substance
abuse
Prevalence and significance of clonal hematopoiesis of indeterminate potential in lung transplant recipients
Abstract Background Clonal hematopoiesis of indeterminate potential (CHIP), the age-related acquisition of somatic mutations that leads to an expanded blood cell clone, has been associated with development of a pro-inflammatory state. An enhanced or dysregulated inflammatory response may contribute to rejection after lung transplantation, however the prevalence of CHIP in lung recipients and influence of CHIP on allograft outcomes is unknown. Methods We analyzed whole-exome sequencing data in 279 lung recipients to detect CHIP, defined by pre-specified somatic mutations in 74 genes known to promote clonal expansion of hematopoietic stem cells. We compared the burden of acute rejection (AR) over the first post-transplant year in lung recipients with vs. without CHIP using multivariable ordinal regression. Multivariate Cox proportional hazards models were used to assess the association between CHIP and CLAD-free survival. An exploratory analysis evaluated the association between the number of CHIP-associated variants and chronic lung allograft dysfunction (CLAD)-free survival. Results We detected 64 CHIP-associated mutations in 45 individuals (15.7%), most commonly in TET2 (10.8%), DNMT3A (9.2%), and U2AF1 (9.2%). Patients with CHIP tended to be older but did not significantly differ from patients without CHIP in terms of race or native lung disease. Patients with CHIP did not have a higher incidence of AR over the first post-transplant year (p = 0.45) or a significantly increased risk of death or CLAD (adjusted HR 1.25, 95% CI 0.88–1.78). We did observe a significant association between the number of CHIP variants and CLAD-free survival, specifically patients with 2 or more CHIP-associated variants had an increased risk for death or CLAD (adjusted HR 3.79, 95% CI 1.98–7.27). Conclusions Lung recipients have a higher prevalence of CHIP and a larger variety of genes with CHIP-associated mutations compared with previous reports for the general population. CHIP did not increase the risk of AR, CLAD, or death in lung recipients
Gnidimacrin, a Potent Anti-HIV Diterpene, Can Eliminate Latent HIV‑1 Ex Vivo by Activation of Protein Kinase C β
HIV-1-latency-reversing
agents, such as histone deacetylase inhibitors
(HDACIs), were ineffective in reducing latent HIV-1 reservoirs ex
vivo using CD4 cells from patients as a model. This deficiency poses
a challenge to current pharmacological approaches for HIV-1 eradication.
The results of this study indicated that gnidimacrin (GM) was able
to markedly reduce the latent HIV-1 DNA level and the frequency of
latently infected cells in an ex vivo model using patients peripheral
blood mononuclear cells. GM induced approximately 10-fold more HIV-1
production than the HDACI SAHA or romidepsin, which may be responsible
for the effectiveness of GM in reducing latent HIV-1 levels. GM achieved
these effects at low picomolar concentrations by selective activation
of protein kinase C βI and βII. Notably, GM was able to
reduce the frequency of HIV-1 latently infected cells at concentrations
without global T cell activation or stimulating inflammatory cytokine
production. GM merits further development as a clinical trial candidate
for latent HIV-1 eradication