Diffuse Large B-Cell Lymphoma/High Grade B-Cell Lymphoma with MYC and BCL6 Rearrangements: a study of 60 Cases.

Classification of cases of diffuse large B-cell lymphoma (DLBCL)/high-grade B-cell lymphoma (HGBL) with MYC and BCL6 rearrangements, also known as BCL6 double hit lymphoma (DHL), is controversial. We assessed 60 cases of BCL6-DHL and compared this cohort to 224 cases of DHL with MYC and BCL2 rearrangements (BCL2-DHL) and 217 cases of DLBCL not otherwise specified. Compared with the DLBCL cohort, BCL6-DHL patients had more aggressive clinical features such as frequent extranodal involvement, high-stage disease, high IPI score and elevated serum lactate dehydrogenase level (p <0.

The Significance of Detecting an Unusual Myeloblast Immunophenotype in a Presumptive Clinical Diagnosis of Myelodysplastic Syndromes.

Context.—: Blasts in myelodysplastic syndromes (MDSs) typically have a primitive myeloid immunophenotype (CD34+CD117+CD13+CD33+HLA-DR+). On rare occasions, blasts were found to be CD34 negative or minimally expressed in a presumptive MDS.

Preimplantation genetic testing for structural rearrangements by genome-wide SNP genotyping and haplotype analysis: a prospective multicenter clinical study.

Background: Preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) has been widely utilized to select euploid embryos in patients carrying balanced chromosomal rearrangements (BCRs) by chromosome copy number analysis. However, reliable and extensively validated PGT-SR methods for selecting embryos without BCRs in large-cohort studies are lacking.

Methods: In this prospective, multicenter, cohort study, carriers with BCRs undergoing PGT-SR were recruited across 12 academic fertility centers within China.

Weak signal ultrafast interrogation of a micro-nano FBG probe sensor based on the hybrid amplified dispersion Fourier-transform method.

To elucidate the thermal transport mechanisms at interfaces in micro- and nanoscale electronic devices, real-time monitoring of temperature variations at the microscopic and nanoscopic levels is crucial. Micro-nano fiber Bragg grating (FBG) sensors have been demonstrated as effective in-situ optical temperature probes for measuring local temperatures. Time-stretch dispersion Fourier transform (TS-DFT) that enables fast, continuous, single-shot measurements in optical sensing has been integrated with a micro-nano FBG probe (FBG) for local temperature sensing.

Undetectable renal stone on computed tomography.

Noncontrast computed tomography(CT) is commonly recommended for the diagnosis of suspected renal stones. In this paper, we present a case of a renal stone that cannot be detected by CT. The stone was made of n-butyl α-cyanoacrylate, a kind of surgical adhesives commonly used in partial nephrotomy.

Systemic ALK-negative anaplastic large cell lymphoma: Insights into morphologic, immunophenotypic, genetic and molecular characteristics.

Anaplastic large cell lymphoma (ALCL) is a mature T-cell neoplasm characterized by large pleomorphic cells, often with horseshoe- or kidney-shaped nuclei and abundant cytoplasm (hallmark cells), and uniformly strong CD30 expression. Based on ALK expression or ALK rearrangement, ALCL is further classified into ALK-positive (ALK+) and ALK-negative types. This review focuses on the clinicopathologic, immunophenotypic, cytogenetic and molecular features of systemic ALK-negative ALCL.

Flow cytometric immunophenotypic features of acute myeloid leukemia with mast cell differentiation.

Objectives: Acute myeloid leukemia (AML) with mast cell (MC) differentiation was recently described as an aggressive subgroup of AML cases. The objectives of this study were to assess the flow cytometric immunophenotypic features of AML-MC cases.

Methods: We characterized the immunophenotypic features of 21 AML-MC cases by flow cytometry and compared them to 20 reactive/regenerating bone marrow specimens.

Accurate identification of genes associated with brain disorders by integrating heterogeneous genomic data into a Bayesian framework.

Background: Genome-wide association studies (GWAS) have revealed many brain disorder-associated SNPs residing in the noncoding genome, rendering it a challenge to decipher the underlying pathogenic mechanisms.

Methods: Here, we present an unsupervised Bayesian framework to identify disease-associated genes by integrating risk SNPs with long-range chromatin interactions (iGOAT), including SNP-SNP interactions extracted from ∼500,000 patients and controls from the UK Biobank, and enhancer-promoter interactions derived from multiple brain cell types at different developmental stages.

Findings: The application of iGOAT to three psychiatric disorders and three neurodegenerative/neurological diseases predicted sets of high-risk (HRGs) and low-risk (LRGs) genes for each disorder.

Integrative immunophenotypic and genetic characterization of acute myeloid leukemia with CBFB rearrangement.

Objectives: We sought to characterize the immunophenotype of acute myeloid leukemia (AML) with CBFB rearrangement and correlate the results with cytogenetic and molecular data.

Methods: Sixty-one cases of AML with CBFB rearrangement were evaluated.

Results: The sample population consisted of 33 men and 28 women, with a median age of 49 years.

TP53 mutation is frequent in mantle cell lymphoma with EZH2 expression and have dismal outcome when both are present.

Enhancer of zeste homolog 2 (EZH2) expression is found in about 40% of mantle cell lymphoma (MCL) patients, which is associated with aggressive histology, high Ki-67 proliferation rate, p53 mutant pattern and inferior overall survival (OS). We conducted 11-gene (ATM, BIRC3, CCND1, KMT2C, KMT2D, NOTCH1, NOTCH2, RB1, TP53, TRAF2 and UBR5) next generation sequencing panel to shed more light on MCL with EZH2 expression (EZH2+ MCL). EZH2+ MCL more frequently harbor TP53 mutation compared to EZH2(-) MCL (41.

[Analysis and clinical application of preimplantation genetic testing for monogenic disorders in a case with Spinal muscular atrophy "2+0" genotype].

Objective: To explore the clinical application of preimplantation genetic testing for monogenic disorders (PGT-M) in an unique case with Spinal muscular atrophy (SMA) type 2+0.

Methods: A special SMA family presented at the Third Affiliated Hospital of Guangzhou Medical University on October 19, 2020 was selected as the study subject. Multiple ligation-dependent probe amplification (MLPA) and molecular tagging linkage analysis were carried out to identify the SMN1 genotype of the couple and their fetus.

A comparison of invasive arterial blood pressure measurement with oscillometric non-invasive blood pressure measurement in patients with sepsis.

Purpose: This study aimed to compare non-invasive oscillometric blood pressure (NIBP) measurement with invasive arterial blood pressure (IBP) measurement in patients with sepsis.

Methods: We conducted a retrospective study to evaluate the agreement between IBP and NIBP using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Paired blood pressure measurements of mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were compared using Bland-Altman analysis and paired Student's t test.

Optical genomic mapping is a helpful tool for detecting CCND1 rearrangements in CD5-negative small B-cell lymphoma: Two cases of leukemic non-nodal mantle cell lymphoma.

Optical genome mapping (OGM) is a new DNA-based technology which provides comprehensive examination of the entire genome. We report two patients who presented with splenomegaly and leukocytosis with lymphocytosis including villous lymphocytes. Neither patient had lymphadenopathy.

Machine learning-based prediction model for myocardial ischemia under high altitude exposure: a cohort study.

High altitude exposure increases the risk of myocardial ischemia (MI) and subsequent cardiovascular death. Machine learning techniques have been used to develop cardiovascular disease prediction models, but no reports exist for high altitude induced myocardial ischemia. Our objective was to establish a machine learning-based MI prediction model and identify key risk factors.