Deep PIM kinase substrate profiling reveals new rational cotherapeutic strategies for acute myeloid leukemia.

Provirus integration site for Moloney murine leukemia virus (PIM) family serine/threonine kinases perform protumorigenic functions in hematologic malignancies and solid tumors by phosphorylating substrates involved in tumor metabolism, cell survival, metastasis, inflammation, and immune cell invasion. However, a comprehensive understanding of PIM kinase functions is currently lacking. Multiple small-molecule PIM kinase inhibitors are currently being evaluated as cotherapeutics in patients with cancer.

A Novel, Deep Learning-Based, Automatic Photometric Analysis Software for Breast Aesthetic Scoring.

 Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices.  S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split.

Aneurysmal bone cyst arising from the surgically removed craniofacial fibrous dysplasia in the long-term follow-up: a case report.

Fibrous dysplasia (FD) is a rare skeletal disorder characterized by abnormal fibro-osseous connective tissue replacing normal bone. Despite its benign behavior, craniofacial FD can cause morphological disfigurement, headache, and even blindness as a result of the produced mass effect. Surgical resection is recommended when the patient shows apparent clinical symptoms or aggravating facial asymmetry.

Negative Pressure Wound Therapy (NPWT) after Hybrid Reconstruction of Occipital Pressure Sore Using Local Flap and Skin Graft.

Pressure sores are a common medical burden among patients, particularly those who are bedridden or frail. Surgical management of occipital pressure sores poses unique challenges due to limited elasticity and the spherical shape of the scalp. This study aims to evaluate the efficacy and safety of a novel reconstruction method utilizing a local transpositional flap and split-thickness skin graft with negative pressure wound therapy (NPWT) for occipital pressure sore treatment.

Clinical evaluation of non-contact infrared thermometers.

Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model.

Revisit to functional data analysis of sleeping energy expenditure.

In this paper, we consider the classification problem of functional data including the sleeping energy expenditure (SEE) data, focusing on functional classification. Many existing classification rules are not effective in distinguishing the two classes of SEE data, because the trajectories of each observation have very different patterns for each class. It is often observed that some aspect of data such as the variability of paths is helpful in classification of functional data.

Using sufficient direction factor model to analyze latent activities associated with breast cancer survival.

High-dimensional gene expression data often exhibit intricate correlation patterns as the result of coordinated genetic regulation. In practice, however, it is difficult to directly measure these coordinated underlying activities. Analysis of breast cancer survival data with gene expressions motivates us to use a two-stage latent factor approach to estimate these unobserved coordinated biological processes.

Coarse-graining of protein structures for the normal mode studies.

The coarse-grained structural model such as Gaussian network has played a vital role in the normal mode studies for understanding protein dynamics related to biological functions. However, for the large proteins, the Gaussian network model is computationally unfavorable for diagonalization of Hessian (stiffness) matrix for the normal mode studies. In this article, we provide the coarse-graining method, referred to as "dynamic model condensation," which enables the further coarse-graining of protein structures consisting of small number of residues.