Comparative evaluation of ACetic - MEthanol high salt dissociation approach for single-cell transcriptomics of frozen human tissues.

Current dissociation methods for solid tissues in scRNA-seq studies do not guarantee intact single-cell isolation, especially for sensitive and complex human endocrine tissues. Most studies rely on enzymatic dissociation of fresh samples or nuclei isolation from frozen samples. Dissociating whole intact cells from fresh-frozen samples, commonly collected by biobanks, remains a challenge.

Exploring treatment-driven subclonal evolution of prognostic triple biomarkers: Dual gene fusions and chimeric RNA variants in novel subtypes of acute myeloid leukemia patients with KMT2A rearrangement.

Chromosomal rearrangements (CR) initiate leukemogenesis in approximately 50 % of acute myeloid leukemia (AML) patients; however, limited targeted therapies exist due to a lack of accurate molecular and genetic biomarkers of refractory mechanisms during treatment. Here, we investigated the pathological landscape of treatment resistance and relapse in 16 CR-AML patients by monitoring cytogenetic, RNAseq, and genome-wide changes among newly diagnosed, refractory, and relapsed AML. First, in FISH-diagnosed KMT2A (MLL gene, 11q23)/AFDN (AF6, 6q27)-rearrangement, RNA-sequencing identified an unknown CCDC32 (15q15.

General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals.

Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.

Asymmetrical evolution of promoter methylation of mammalian genes after duplication.

Even though gene duplication is a key source of new genes and evolutionary innovation, it is unclear how duplicates survive the period immediately following gene duplication, in which both copies are functionally redundant. In the absence of epigenetic silencing, the abundance of the gene product would double after gene duplication, which would often have deleterious effects. However, recent duplicates exhibit low expression levels, which could be at least partially explained by high levels of promoter methylation.

Differential gene expression analysis shows that cephalosporin resistance is intrinsic to Clostridioides difficile strain 630.

Clostridioides difficile infection (CDI) is the most common nosocomial infection in the US. CDI has become a growing concern due to C. difficile's resistance to several antibiotics, including cephalosporins.

Insights into chemoautotrophic traits of a prevalent bacterial phylum CSP1-3, herein .

Candidate bacterial phylum CSP1-3 has not been cultivated and is poorly understood. Here, we analyzed 112 CSP1-3 metagenome-assembled genomes and showed they are likely facultative anaerobes, with 3 of 5 families encoding autotrophy through the reductive glycine pathway (RGP), Wood-Ljungdahl pathway (WLP) or Calvin-Benson-Bassham (CBB), with hydrogen or sulfide as electron donors. Chemoautotrophic enrichments from hot spring sediments and fluorescence hybridization revealed enrichment of six CSP1-3 genera, and both transcribed genes and DNA-stable isotope probing were consistent with proposed chemoautotrophic metabolisms.

A fundamental and theoretical framework for mutation interactions and epistasis.

Many pathological conditions are a result of intragenic epistasis; however, there are ambiguities in current epistasis models. Herein, the new Mutation Interaction Spectrum model defines a discrete outcome, named a Mutation Interaction, for each double point mutation in a gene and its component single mutations. The model is a universal genetic model of all types of mutation interactions and their functional outcomes and is derived from digital logic, commonly used in electrical engineering.

A strategy for cost-effective large language model use at health system-scale.

Large language models (LLMs) can optimize clinical workflows; however, the economic and computational challenges of their utilization at the health system scale are underexplored. We evaluated how concatenating queries with multiple clinical notes and tasks simultaneously affects model performance under increasing computational loads. We assessed ten LLMs of different capacities and sizes utilizing real-world patient data.

Marginal interaction test for detecting interactions between genetic marker sets and environment in genome-wide studies.

As human complex diseases are influenced by the interaction between genetics and the environment, identifying gene-environment interactions (G×E) is crucial for understanding disease mechanisms and predicting risk. Developing robust quantitative tools for G×E analysis can enhance the study of complex diseases. However, many existing methods that explore G×E focus on the interplay between an environmental factor and genetic variants, exclusively for common or rare variants.

Evaluating ten years of breast cancer screening with contrast enhanced mammography in women with Intermediate-high risk.

Purpose: While mammography is considered the gold standard for screening women for breast cancer, its accuracy declines in women with dense breasts. The purpose of the study is to evaluate the diagnostic accuracy of contrast enhanced mammography (CEM) for detecting breast cancer in intermediate and high-risk women, including those with genetic predispositions, over a decade-long cohort at a tertiary center.

Methods: We retrospectively analyzed all CEM examinations performed for screening purposes at a tertiary center between 2012 and 2023.

Advancing Clinical Practice: The Potential of Multimodal Technology in Modern Medicine.

Multimodal technology is poised to revolutionize clinical practice by integrating artificial intelligence with traditional diagnostic modalities. This evolution traces its roots from Hippocrates' humoral theory to the use of sophisticated AI-driven platforms that synthesize data across multiple sensory channels. The interplay between historical medical practices and modern technology challenges conventional patient-clinician interactions and redefines diagnostic accuracy.

Genome wide clustering on integrated chromatin states and Micro-C contacts reveals chromatin interaction signatures.

We can now analyze 3D physical interactions of chromatin regions with chromatin conformation capture technologies, in addition to the 1D chromatin state annotations, but methods to integrate this information are lacking. We propose a method to integrate the chromatin state of interacting regions into a vector representation through the contact-weighted sum of chromatin states. Unsupervised clustering on integrated chromatin states and Micro-C contacts reveals common patterns of chromatin interaction signatures.

Economic Impact of Postoperative Urinary Retention in the US Hospital Setting.

Postoperative urinary retention (POUR) is a common and distressing surgical complication that may be associated with the pharmacological reversal technique of neuromuscular blockade (NMB). This study aimed to investigate the impact that POUR has on medical charges. This was a retrospective observational study of adult patients undergoing select surgeries who were administered neuromuscular blockade agent (NMBA), which was pharmacologically reversed between February 2017 and November 2021 using data from the PINC-AI™ Healthcare Database.

Variable calling of m6A and associated features in databases: a guide for end-users.

N6-methyladenosine (m$^{6}$A) is a widely-studied methylation to messenger RNAs, which has been linked to diverse cellular processes and human diseases. Numerous databases that collate m$^{6}$A profiles of distinct cell types have been created to facilitate quick and easy mining of m$^{6}$A signatures associated with cell-specific phenotypes. However, these databases contain inherent complexities that have not been explicitly reported, which may lead to inaccurate identification and interpretation of m$^{6}$A-associated biology by end-users who are unaware of them.

Exploring the role of Large Language Models in haematology: A focused review of applications, benefits and limitations.

Large language models (LLMs) have significantly impacted various fields with their ability to understand and generate human-like text. This study explores the potential benefits and limitations of integrating LLMs, such as ChatGPT, into haematology practices. Utilizing systematic review methodologies, we analysed studies published after 1 December 2022, from databases like PubMed, Web of Science and Scopus, and assessing each for bias with the QUADAS-2 tool.

Assessing GPT-4 multimodal performance in radiological image analysis.

Objectives: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical regions, and pathologies to explore the potential of zero-shot generative AI in enhancing diagnostic processes in radiology.

Methods: We analyzed 230 anonymized emergency room diagnostic images, consecutively collected over 1 week, using GPT-4V.