CD47 and Calreticulin Expression in Breast Cancer Subtypes and Anti-CD47 Inhibitory Effects in Macrophage-mediated Phagocytosis.

Background/aim: Macrophage-mediated cancer immune evasion is modulated by the balance between "the cluster of differentiation 47 (CD47), an anti-phagocytic signal" and "calreticulin (CALR), a pro-phagocytic signal". CD47 is highly expressed in various types of cancer. However, the expression profiles of CD47 and CALR in breast cancer, especially in different hormone receptor subtypes, and the effects of CD47 blockade in macrophage-mediated therapy are not well understood.

Label-free quantitative proteomics reveals aberrant expression levels of LRG, C9, FN, A1AT and AGP1 in the plasma of patients with colorectal cancer.

Background: Colorectal cancer (CRC) is one of the major causes of cancer-related death worldwide. Although commercial biomarkers of CRC are currently available, they are still lacking in terms of sensitivity and specificity; thus, searching for reliable blood-based biomarkers are important for the primary screening of CRC.

Methods: Plasma samples of patients with non-metastatic (NM) and metastatic (M) CRC and healthy controls were fractionated using MARS-14 immunoaffinity chromatography.

Machine learning applications for transcription level and phenotype predictions.

Predicting phenotypes and complex traits from genomic variations has always been a big challenge in molecular biology, at least in part because the task is often complicated by the influences of external stimuli and the environment on regulation of gene expression. With today's abundance of omic data and advances in high-throughput computing and machine learning (ML), we now have an unprecedented opportunity to uncover the missing links and molecular mechanisms that control gene expression and phenotypes. To empower molecular biologists and researchers in related fields to start using ML for in-depth analyses of their large-scale data, here we provide a summary of fundamental concepts of machine learning, and describe a wide range of research questions and scenarios in molecular biology where ML has been implemented.

Three-Decade Successive Establishment of Care for Women/Girls from Families with Haemophilia.

Objective: The study aimed to report a 3-decade successive establishment of care for women/girls from families with haemophilia.

Methods: A retrospective analysis was conducted on 462 women/girls from 243 families from 1987 to 2021.

Results: Combining phenotypic analysis of coagulation factor and genotypic analysis of either linkage analysis or mutation detection confirmed the status of all obligate haemophilia carriers (A118, B19).

A Simple and Applicable Method for Human Platelet Lysate Preparation Using Citrate Blood.

Objectives: To determine and compare the platelet growth factors in human platelet lysate (HPL) prepared from citrated whole blood, with final centrifugations at 4oC and 25oC.

Methods: We collected specimens of citrated whole blood from 27 healthy volunteers. The platelet-rich plasma (PRP) was separated to prepare the HPL, which was further divided into 2 portions for the final centrifugation, at 4oC and 25oC, respectively.

Glycoproteomic Analysis Reveals Aberrant Expression of Complement C9 and Fibronectin in the Plasma of Patients with Colorectal Cancer.

Colorectal cancer (CRC) is a major cause of cancer mortality. Currently used CRC biomarkers provide insufficient sensitivity and specificity; therefore, novel biomarkers are needed to improve the CRC detection. Label-free quantitative proteomics were used to identify and compare glycoproteins, enriched by wheat germ agglutinin, from plasma of CRC patients and age-matched healthy controls.

Urinary biomarkers for the diagnosis of cervical cancer by quantitative label-free mass spectrometry analysis.

Due to the invasive procedure associated with Pap smears for diagnosing cervical cancer and the conservative culture of developing countries, identifying less invasive biomarkers is of great interest. Quantitative label-free mass spectrometry was performed to identify potential biomarkers in the urine samples of patients with cervical cancer. This technique was used to study the differential expression of urinary proteomes between normal individuals and cancer patients.