Toward confident prostate cancer detection using ultrasound: a multi-center study.

Purpose: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model should confidently identify cancer while responding with appropriate uncertainty when presented with out-of-distribution inputs that arise during deployment due to imaging artifacts and the biological heterogeneity of patients and prostatic tissue.

Methods: Using micro-ultrasound data from 693 patients across 5 clinical centers who underwent micro-ultrasound guided prostate biopsy, we train and evaluate convolutional neural network models for PCa detection.

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

Purpose: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direct PCa detection from TRUS, which allows targeted biopsy and subsequently enhances outcomes. Yet, there are ongoing challenges with training robust models, stemming from issues such as noisy labels, out-of-distribution (OOD) data, and limited labeled data.

Association Between Influenza Vaccine Uptake and Health Awareness: A Cross-Sectional Questionnaire-Based Study Among Medical Students and Healthcare Workers in Northern Vietnam.

BACKGROUND Seasonal influenza poses a significant global health concern. Despite the proven effectiveness of the influenza vaccine, its uptake remains low in Vietnam. This study aimed to assess the knowledge, attitudes, and practices of medical students and healthcare workers on influenza vaccine uptake in northern Vietnam.

Clinical and Laboratory Characteristics of Kawasaki Disease and COVID-19-Related Multisystem Inflammatory Syndrome in Children.

Geographical and racial factors constitute important distinctions between Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C), but no study has been conducted in Vietnam. Forty-one children with KD from January 2018 to July 2020 and 42 with KD/MIS-C from August 2020 to December 2022 were included in this study. Of the patients, 52.

Self-Supervised Learning With Limited Labeled Data for Prostate Cancer Detection in High-Frequency Ultrasound.

Deep learning-based analysis of high-frequency, high-resolution micro-ultrasound data shows great promise for prostate cancer (PCa) detection. Previous approaches to analysis of ultrasound data largely follow a supervised learning (SL) paradigm. Ground truth labels for ultrasound images used for training deep networks often include coarse annotations generated from the histopathological analysis of tissue samples obtained via biopsy.

TRUSformer: improving prostate cancer detection from micro-ultrasound using attention and self-supervision.

Purpose: A large body of previous machine learning methods for ultrasound-based prostate cancer detection classify small regions of interest (ROIs) of ultrasound signals that lie within a larger needle trace corresponding to a prostate tissue biopsy (called biopsy core). These ROI-scale models suffer from weak labeling as histopathology results available for biopsy cores only approximate the distribution of cancer in the ROIs. ROI-scale models do not take advantage of contextual information that are normally considered by pathologists, i.

Outbreak of central nervous system infections among children in Thai Binh, Viet Nam.

From July to October 2020, 99 cases of central nervous system (CNS) infections were identified in Thai Binh Pediatric Hospital, Viet Nam, representing a five-fold increase compared to the baseline incidence during the previous five years. Clinical data were retrospectively collected. Cerebrospinal fluid specimens (CSF) were secondarily tested for pathogens using viral culture and PCR assays.

Mapping COVID-19 related research from Vietnam: a scoping review.

Introduction: The situation of COVID-19 pandemic is becoming more complex. The research institutes should focus on the most important challenge related to this outbreak at the national level. We aim to realize this scoping review to map publications on COVID-19 in Vietnam in order to guide research priorities and policies in the country.

Biparametric MR signal characteristics can predict histopathological measures of prostate cancer.

Objectives: The aim of this study was to establish a new data-driven metric from MRI signal intensity that can quantify histopathological characteristics of prostate cancer.

Methods: This retrospective study was conducted on 488 patients who underwent biparametric MRI (bp-MRI), including T2-weighted imaging (T2W) and apparent diffusion coefficient (ADC) of diffusion-weighted imaging, and having biopsy-proven prostate cancer between August 2011 and July 2015. Forty-two of the patients who underwent radical prostatectomy and the rest of 446 patients constitute the labeled and unlabeled datasets, respectively.

Coarse label refinement for improving prostate cancer detection in ultrasound imaging.

Purpose: Ultrasound-guided biopsy plays a major role in prostate cancer (PCa) detection, yet is limited by a high rate of false negatives and low diagnostic yield of the current systematic, non-targeted approaches. Developing machine learning models for accurately identifying cancerous tissue in ultrasound would help sample tissues from regions with higher cancer likelihood. A plausible approach for this purpose is to use individual ultrasound signals corresponding to a core as inputs and consider the histopathology diagnosis for the entire core as labels.

Fine-tuned long-acting interleukin-2 superkine potentiates durable immune responses in mice and non-human primate.

Background: Recombinant human interleukin-2 (rhIL-2, aldesleukin) is Food and Drug Administration approved for the treatment of metastatic melanoma and renal cell carcinoma and has achieved durable response in a subset of patients. However, its utility as an immunotherapeutic drug is limited by undesirable activation of immune suppressive regulatory T cells (Tregs) and a short half-life requiring frequent high dose administration, leading to unacceptable toxicities. We have engineered MDNA11, a long-acting IL-2 superkine, to overcome these limitations by (1) modifying receptor selectivity in favor of anti-cancer immune cells to increase therapeutic efficacy and (2) fusion to human albumin to extend the pharmacokinetic (PK) profile, circumventing the need for frequent dosing.

Targeting KRAS4A splicing through the RBM39/DCAF15 pathway inhibits cancer stem cells.

The commonly mutated human KRAS oncogene encodes two distinct KRAS4A and KRAS4B proteins generated by differential splicing. We demonstrate here that coordinated regulation of both isoforms through control of splicing is essential for development of Kras mutant tumors. The minor KRAS4A isoform is enriched in cancer stem-like cells, where it responds to hypoxia, while the major KRAS4B is induced by ER stress.

Deep regression neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion in acute ischemic stroke.

Purpose: Acute ischemic stroke is one of the primary causes of death worldwide. Recent studies have shown that the assessment of collateral status could aid in improving the treatment for patients with acute ischemic stroke. We present a 3D deep regression neural network to automatically generate the collateral images from dynamic susceptibility contrast-enhanced magnetic resonance perfusion (DSC-MRP) in acute ischemic stroke.

BACH: Grand challenge on breast cancer histology images.

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results.

Methods for Segmentation and Classification of Digital Microscopy Tissue Images.

High-resolution microscopy images of tissue specimens provide detailed information about the morphology of normal and diseased tissue. Image analysis of tissue morphology can help cancer researchers develop a better understanding of cancer biology. Segmentation of nuclei and classification of tissue images are two common tasks in tissue image analysis.

Structure-guided design fine-tunes pharmacokinetics, tolerability, and antitumor profile of multispecific frizzled antibodies.

Aberrant activation of Wnt/β-catenin signaling occurs frequently in cancer. However, therapeutic targeting of this pathway is complicated by the role of Wnt in stem cell maintenance and tissue homeostasis. Here, we evaluated antibodies blocking 6 of the 10 human Wnt/Frizzled (FZD) receptors as potential therapeutics.

Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging.

Purpose: We propose an approach of 3D convolutional neural network to segment the prostate in MR images.

Methods: A 3D deep dense multi-path convolutional neural network that follows the framework of the encoder-decoder design is proposed. The encoder is built based upon densely connected layers that learn the high-level feature representation of the prostate.

K-Ras Promotes Tumorigenicity through Suppression of Non-canonical Wnt Signaling.

K-Ras and H-Ras share identical effectors and have similar properties; however, the high degree of tumor-type specificity associated with K-Ras and H-Ras mutations suggests that they have unique roles in oncogenesis. Here, we report that oncogenic K-Ras, but not H-Ras, suppresses non-canonical Wnt/Ca(2+) signaling, an effect that contributes strongly to its tumorigenic properties. K-Ras does this by binding to calmodulin and so reducing CaMKii activity and expression of Fzd8.

Genetic variation in the functional ENG allele inherited from the non-affected parent associates with presence of pulmonary arteriovenous malformation in hereditary hemorrhagic telangiectasia 1 (HHT1) and may influence expression of PTPN14.

HHT shows clinical variability within and between families. Organ site and prevalence of arteriovenous malformations (AVMs) depend on the HHT causative gene and on environmental and genetic modifiers. We tested whether variation in the functional ENG allele, inherited from the unaffected parent, alters risk for pulmonary AVM in HHT1 mutation carriers who are ENG haploinsufficient.

The mutational landscapes of genetic and chemical models of Kras-driven lung cancer.

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding the factors that induce driver mutations and the processes that shape mutation selection during tumorigenesis. Here we performed whole-exome sequencing on adenomas from three mouse models of non-small-cell lung cancer, which were induced either by exposure to carcinogens (methyl-nitrosourea (MNU) and urethane) or by genetic activation of Kras (Kras(LA2)). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the Kras(LA2) model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single-nucleotide variants, compared with only six in tumours from the Kras(LA2) model.

Rewiring of human lung cell lineage and mitotic networks in lung adenocarcinomas.

Analysis of gene expression patterns in normal tissues and their perturbations in tumours can help to identify the functional roles of oncogenes or tumour suppressors and identify potential new therapeutic targets. Here, gene expression correlation networks were derived from 92 normal human lung samples and patient-matched adenocarcinomas. The networks from normal lung show that NKX2-1 is linked to the alveolar type 2 lineage, and identify PEBP4 as a novel marker expressed in alveolar type 2 cells.

Inflammation and Hras signaling control epithelial-mesenchymal transition during skin tumor progression.

Epithelial-mesenchymal transition (EMT) is thought to be an important, possibly essential, component of the process of tumor dissemination and metastasis. About 20%-30% of Hras mutant mouse skin carcinomas induced by chemical initiation/promotion protocols have undergone EMT. Reduced exposure to TPA-induced chronic inflammation causes a dramatic reduction in classical papillomas and squamous cell carcinomas (SCCs), but the mice still develop highly invasive carcinomas with EMT properties, reduced levels of Hras and Egfr signaling, and frequent Ink4/Arf deletions.