Immune Checkpoint Blockade Delays Cancer Development and Extends Survival in DNA Polymerase Mutator Syndromes.

Mutations in the exonuclease domains of the replicative nuclear DNA polymerases POLD1 and POLE are associated with increased cancer incidence, elevated tumor mutation burden (TMB), and enhanced response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond, highlighting the need for a better understanding of how TMB affects tumor biology and subsequently immunotherapy response. To address this, we generated mice with germline and conditional mutations in the exonuclease domains of Pold1 and Pole.

Medulloblastomas Initiated by Homologous Recombination Defects in Mice.

Germline mutations of homologous-recombination (HR) genes are among the top contributors to medulloblastomas. A significant portion of human medulloblastomas exhibit genomic signatures of HR defects. Whether ablation of Brca2 and Palb2, and their related Brca1 and Bccip genes, in the mouse brain can differentially initiate medulloblastomas was explored here.

Immune Checkpoint Blockade Delays Cancer and Extends Survival in Murine DNA Polymerase Mutator Syndromes.

Unlabelled: Mutations in polymerases and exonuclease domains in humans are associated with increased cancer incidence, elevated tumor mutation burden (TMB) and response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond. Here we generated and proofreading mutator mice and show that ICB treatment of mice with high TMB tumors did not improve survival as only a subset of tumors responded.

RESPIRATION DEFECTS LIMIT SERINE SYNTHESIS REQUIRED FOR LUNG CANCER GROWTH AND SURVIVAL.

Unlabelled: Mitochondrial function is important for both energetic and anabolic metabolism. Pathogenic mitochondrial DNA (mtDNA) mutations directly impact these functions, resulting in the detrimental consequences seen in human mitochondrial diseases. The role of pathogenic mtDNA mutations in human cancers is less clear; while pathogenic mtDNA mutations are observed in some cancer types, they are almost absent in others.

Curvature generation based on weight-updated boosting using shoe last point-cloud measurements.

Lasts are foot-shaped forms made of plastic, wood, aluminum, or 3D-printed plastic. The last of a shoe determines not only its shape and style but also how well it fits and protects the foot. A weight-updated boosting-based ensemble learning (WUBEL) algorithm is presented in this paper to extract critical features (points) from plantar pressure imaging to optimize the shoe's last surface to satisfy a comfortable shoe's last surface optimization design.

Integrated metabolic and genetic analysis reveals distinct features of human differentiated thyroid cancer.

Background: Differentiated thyroid cancer (DTC) affects thousands of lives worldwide each year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis.

Identification of Suitable Biomarkers for Stress and Emotion Detection for Future Personal Affective Wearable Sensors.

Skin conductivity (i.e., sweat) forms the basis of many physiology-based emotion and stress detection systems.

Colored Video Analysis in Wireless Capsule Endoscopy: A Survey of State-of-the-Art.

Wireless Capsule Endoscopy (WCE) is a highly promising technology for gastrointestinal (GI) tract abnormality diagnosis. However, low image resolution and low frame rates are challenging issues in WCE. In addition, the relevant frames containing the features of interest for accurate diagnosis only constitute 1% of the complete video information.

RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields.

Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesions from MRI is still a challenging task. In this paper, we propose a two-stage supervised learning framework for automatic brain lesion segmentation.

Gaussian mixture model for texture characterization with application to brain DTI images.

A Gaussian mixture model (GMM)-based classification technique is employed for a quantitative global assessment of brain tissue changes by using pixel intensities and contrast generated by b-values in diffusion tensor imaging (DTI). A hemisphere approach is also proposed. A GMM identifies the variability in the main brain tissues at a macroscopic scale rather than searching for tumours or affected areas.

Medical cyber-physical systems: A survey.

Medical cyber-physical systems (MCPS) are healthcare critical integration of a network of medical devices. These systems are progressively used in hospitals to achieve a continuous high-quality healthcare. The MCPS design faces numerous challenges, including inoperability, security/privacy, and high assurance in the system software.

Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance.

Modified cuckoo search algorithm in microscopic image segmentation of hippocampus.

Microscopic image analysis is one of the challenging tasks due to the presence of weak correlation and different segments of interest that may lead to ambiguity. It is also valuable in foremost meadows of technology and medicine. Identification and counting of cells play a vital role in features extraction to diagnose particular diseases precisely.

Wireless Capsule Gastrointestinal Endoscopy: Direction-of-Arrival Estimation Based Localization Survey.

One of the significant challenges in capsule endoscopy (CE) is to precisely determine the pathologies location. The localization process is primarily estimated using the received signal strength (RSS) from sensors in the capsule system through its movement in the gastrointestinal (GI) tract. Consequently, the wireless CE (WCE) system requires improvement to handle the lack of the capsule instantaneous localization information and to solve the relatively low transmission data rate challenges.