Preoperative evaluation of endoscopic thyroidectomy via the total areola approach (ETA): a fluid-structure interaction model for predicting lymph node clearance and surgical suitability.

The global increase in thyroid cancer incidence has driven the adoption of minimally invasive techniques, such as endoscopic thyroidectomy via the total areola approach (ETA), which is widely used in China. However, concerns persist regarding the completeness of central lymph node dissection (CLND) in ETA due to anatomical constraints (e.g.

Cell type proportions rather than DNA methylation in the cord blood show significant associations with severe preeclampsia.

Preeclampsia (PE) is a severe pregnancy complication that threatens maternal and neonatal health. Previous epigenome-wide association studies (EWAS) on PE have produced inconsistent results, possibly due to inadequate adjustment for confounders. Here, we analyzed DNA methylation changes in cord blood from newborns affected by PE, using a multi-ethnic cohort from Hawaii.

Identification and Validation of New Molecular Subtypes within the Early and Late Mild Cognitive Impairment Stages of Alzheimer's Disease.

Alzheimer's disease (AD) is a heterogeneous neurodegenerative condition. This study identifies clinically relevant new molecular subtypes of the early and late mild cognitive impairment (EMCI and LMCI) stages of AD from 401 patients in the ADNI consortium. Metabolomics and peripheral blood mononuclear cell (PBMC) transcriptomics data are integrated using Similarity Network Fusion (SNF), resulting in two molecular subtypes within EMCI (EMCI-1 and EMCI-2) and LMCI (LMCI-1 and LMCI-2), respectively.

Multiomics analysis of umbilical cord hematopoietic stem cells from a multiethnic cohort of Hawaii reveals the intergenerational effect of maternal prepregnancy obesity and risks for cancers.

Background: Maternal obesity is a health concern that may predispose newborns to a high risk of medical problems later in life. To understand the intergenerational effect of maternal obesity, we hypothesized that the maternal obesity effect is mediated by epigenetic changes in the CD34+/CD38-/Lin- hematopoietic stem cells (uHSCs) in the offspring. To investigate this, we conducted a DNA methylation centric multiomics study.

Toward Zero-Excess Alkali Metal Batteries: Bridging Experimental and Computational Insights.

This review introduces alkali metal (Li, Na, and K) anode-less and anode-free batteries and conveys a synopsis of the current challenges regarding anode-electrolyte interfaces. The review focuses on a critical analysis of the fundamental understanding of the (eletro)chemical and (electro)physical processes occurring at the anode, including metal nucleation and dendrite growth, the properties of liquid and solid electrolytes, and their roles in the metal stripping/deposition process and the formation of solid-electrolyte interphase, and the properties of separators and their role in inhibiting dendrite growth. Solutions to tackle the challenges for anode-less and anode-free batteries are discussed extensively in the aspects of the modifications of the anode substrate, novel electrolyte solutions and SEI structures, interface design, and novel separators/solid-state electrolytes to enable stable battery performances.

Multi-Omics Integration in Nephrology: Advances, Challenges, and Future Directions.

Omics technologies have transformed nephrology, providing deep insights into molecular mechanisms of kidney disease and enabling more precise diagnostic tools, therapeutic strategies, and prognostic markers. Multi-omics data integration, spanning bulk, single-cell, and spatial omics, offers a comprehensive view of kidney biology in health and disease. In this review, we explore methods and challenges for integrating transcriptomic, epigenomic, and spatial data.

Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual information.

Single-cell RNA sequencing (scRNA-seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. We propose a new computational framework, Originator, which deciphers single cells by genetic origin and separates immune cells of blood contamination from those of expected tissue-resident cells.

Multi-omics Analysis of Umbilical Cord Hematopoietic Stem Cells from a Multi-ethnic Cohort of Hawaii Reveals the Intergenerational Effect of Maternal Pre-Pregnancy Obesity and Risk Prediction for Cancers.

Background: Maternal obesity is a health concern that may predispose newborns to a high risk of medical problems later in life. To understand the intergenerational effect of maternal obesity, we hypothesized that the maternal obesity effect is mediated by epigenetic changes in the CD34+/CD38-/Lin- hematopoietic stem cells (uHSCs) in the offspring. Towards this, we conducted a DNA methylation centric multi-omics study.

Single-cell RNA-Seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-Seq by genetic and contextual information.

Single-cell RNA sequencing (scRNA-Seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. These issues demand rigorous preprocessing and filtering prior to the downstream functional analysis, to avoid biased conclusions due to cell types not of interest.

Deep learning and transfer learning identify breast cancer survival subtypes from single-cell imaging data.

Background: Single-cell multiplex imaging data have provided new insights into disease subtypes and prognoses recently. However, quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at a population scale are currently missing.

Methods: We quantified hundreds of single-cell resolution cell-cell interaction features through neighborhood calculation, in addition to cellular phenotypes.

Astaxanthin Synergizes with Ionizing Radiation (IR) in Oral Squamous Cell Carcinoma (OSCC).

Astaxanthin (ATX) is known for its antioxidant and anti-inflammation functions yet its role in cancers requires more research. This study is aimed to reveal the potential synergetic effect of ATX with ionizing radiation (IR) in OSCC. Cell survival was measured after human OSCC cells including CAL27 and SCC9, and normal human oral keratinocytes (NHOKs) were treated with different concentrations of ATX for 24 h.

Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case-cohort study.

Objectives: To identify and internally validate metabolites predictive of spontaneous preterm birth (sPTB) using multiple machine learning methods and sequential maternal serum samples, and to predict spontaneous early term birth (sETB) using these metabolites.

Design: Case-cohort design within a prospective cohort study.

Setting: Cambridge, UK.

Modifying to mimic for medical microbiology laboratory teaching: a new strategy to improve biosafety in class.

Introduction: Laboratory teaching of medical microbiology involves highly pathogenic microorganisms, thus posing potential biosafety risks to the students and the teacher. To address these risks, non/low-pathogenic microorganisms were modified to mimic highly pathogenic ones or highly pathogenic microorganisms were attenuated directly using the CRISPR/Cas9 technology. This study describes the modification of DH5α to mimic and its evaluation as a safe alternative for medical laboratory teaching.

Deep-learning and transfer learning identify new breast cancer survival subtypes from single-cell imaging data.

Unlabelled: Quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at population scale are currently missing. Here, we computationally extracted hundreds of features describing single-cell based cell-cell interactions and cellular phenotypes from a large, published cohort of cyto-images of breast cancer patients. We applied these features to a neural-network based Cox-nnet survival model and obtained high accuracy in predicting patient survival in test data (Concordance Index > 0.

Severe preeclampsia is not associated with significant DNA methylation changes but cell proportion changes in the cord blood - caution on the importance of confounding adjustment.

Epigenome-wide DNA methylation analysis (EWAS) is an important approach to identify biomarkers for early disease detection and prognosis prediction, yet its results could be confounded by other factors such as cell-type heterogeneity and patient characteristics. In this study, we address the importance of confounding adjustment by examining DNA methylation patterns in cord blood exposed to severe preeclampsia (PE), a prevalent and potentially fatal pregnancy complication. Without such adjustment, a misleading global hypomethylation pattern is obtained.

Exosome-mediated long noncoding RNA (lncRNA) PART1 suppresses malignant progression of oral squamous cell carcinoma via miR-17-5p/SOCS6 axis.

Background: Exosomes derived from oral squamous cell carcinoma (OSCC) could modulate OSCC development. This study aimed to explore effects of exosome-mediated lncRNA PART1 on OSCC cells.

Methods: This study was performed in Tianjin Medical University Cancer Institute from February 2021 to March 2022.

ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs.

Single-cell RNA sequencing technology has enabled in-depth analysis of intercellular heterogeneity in various diseases. However, its full potential for precision medicine has yet to be reached. Towards this, we propose A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD) that defines a drug score to recommend drugs by considering all cell clusters to address the intercellular heterogeneity within each patient.

CD73/NT5E is a Potential Biomarker for Cancer Prognosis and Immunotherapy for Multiple Types of Cancers.

Cluster of Differentiations 73 (CD73)/ecto-5'-nucleotidase (NT5E) is a novel type of immune molecular marker expressed on many tumor cells and involved in regulating the essential immune functions and affecting the prognosis of cancer patients. However, it is not clear how the NT5E is linked to the infiltration levels of the immune cells in pan-cancer patients and their final prognosis. This study explores the role of NT5E in 33 tumor types using GEPIA, TIMER, Oncomine, BioGPS databases, and several bioinformatic tools.

A Dual-Filtration System for Single-Cell Sequencing of Circulating Tumor Cells and Clusters in HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Identification and sequencing of circulating tumor (CT) cells and clusters may allow for noninvasive molecular characterization of HCC, which is an unmet need, as many patients with HCC do not undergo biopsy. We evaluated CT cells and clusters, collected using a dual-filtration system in patients with HCC.

ASGARD: A Single-cell Guided pipeline to Aid Repurposing of Drugs.

Intercellular heterogeneity is a major obstacle to successful precision medicine. Single-cell RNA sequencing (scRNA-seq) technology has enabled in-depth analysis of intercellular heterogeneity in various diseases. However, its full potential for precision medicine has yet to be reached.

Lilikoi V2.0: a deep learning-enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.

Background: previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software.

Results: here we report the next version of Lilikoi as a significant upgrade.

Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data.

Annotating cell types is a critical step in single-cell RNA sequencing (scRNA-seq) data analysis. Some supervised or semi-supervised classification methods have recently emerged to enable automated cell type identification. However, comprehensive evaluations of these methods are lacking.

Evaluation of STAR and Kallisto on Single Cell RNA-Seq Data Alignment.

Alignment of scRNA-Seq data are the first and one of the most critical steps of the scRNA-Seq analysis workflow, and thus the choice of proper aligners is of paramount importance. Recently, STAR an alignment method and Kallisto a pseudoalignment method have both gained a vast amount of popularity in the single cell sequencing field. However, an unbiased third-party comparison of these two methods in scRNA-Seq is lacking.

PLAGL2 and POFUT1 are regulated by an evolutionarily conserved bidirectional promoter and are collaboratively involved in colorectal cancer by maintaining stemness.

Background: Our previous study revealed that PLAGL2 or POFUT1 can promote tumorigenesis and maintain significant positive correlations in colorectal cancer (CRC). However, the mechanism leading to the co-expression and the underlying functional and biological implications remain unclear.

Methods: Clinical tumor tissues and TCGA dataset were utilized to analyze the co-expression of PLAGL2 and POFUT1.