LmRaC: a functionally extensible tool for LLM interrogation of user experimental results.

Motivation: Large Language Models (LLMs) have provided spectacular results across a wide variety of domains. However, persistent concerns about hallucination and fabrication of authoritative sources raise serious issues for their integral use in scientific research. Retrieval-augmented generation (RAG) is a technique for making data and documents, otherwise unavailable during training, available to the LLM for reasoning tasks.

RCPA: An Open-Source R Package for Data Processing, Differential Analysis, Consensus Pathway Analysis, and Visualization.

Identifying impacted pathways is important because it provides insights into the biology underlying conditions beyond the detection of differentially expressed genes. Because of the importance of such analysis, more than 100 pathway analysis methods have been developed thus far. Despite the availability of many methods, it is challenging for biomedical researchers to learn and properly perform pathway analysis.

Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges.

Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive.

A novel approach for predicting upstream regulators (PURE) that affect gene expression.

External factors such as exposure to a chemical, drug, or toxicant (CDT), or conversely, the lack of certain chemicals can cause many diseases. The ability to identify such causal CDTs based on changes in the gene expression profile is extremely important in many studies. Furthermore, the ability to correctly infer CDTs that can revert the gene expression changes induced by a given disease phenotype is a crucial step in drug repurposing.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer.

Introduction: Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment.

Plasma proteome of Long-COVID patients indicates HIF-mediated vasculo-proliferative disease with impact on brain and heart function.

Aims: Long-COVID occurs after SARS-CoV-2 infection and results in diverse, prolonged symptoms. The present study aimed to unveil potential mechanisms, and to inform prognosis and treatment.

Methods: Plasma proteome from Long-COVID outpatients was analyzed in comparison to matched acutely ill COVID-19 (mild and severe) inpatients and healthy control subjects.

Discovery of Novel Transketolase Epitopes and the Development of IgG-Based Tuberculosis Serodiagnostics.

Despite advances in rapid molecular techniques for tuberculosis (TB) diagnostics, there is an unmet need for a point-of-care, nonsputum-based test. Previously, through a T7 phage antigen display platform and immunoscreening, we identified that the serum IgGs of active TB patients differentially bind to several antigen-clones and that this immunoreactivity discriminates TB from other respiratory diseases. One of these high-performance clones has some homology to the transketolase of Mycobacterium tuberculosis ( TKT).

Integration of Multimodal Data from Disparate Sources for Identifying Disease Subtypes.

Studies over the past decade have generated a wealth of molecular data that can be leveraged to better understand cancer risk, progression, and outcomes. However, understanding the progression risk and differentiating long- and short-term survivors cannot be achieved by analyzing data from a single modality due to the heterogeneity of disease. Using a scientifically developed and tested deep-learning approach that leverages aggregate information collected from multiple repositories with multiple modalities (e.

Autoantibodies against cytoskeletons and lysosomal trafficking discriminate sarcoidosis from healthy controls, tuberculosis and lung cancers.

Sarcoidosis is a systemic granulomatous disease of unknown etiology. Hypergammaglobulinemia and the presence of autoantibodies in sarcoidosis suggest active humoral immunity to unknown antigen(s). We developed a complex cDNA library derived from tissues of sarcoidosis patients.

Molecular Markers for Long-term Survival in Stage IIIA (N2) NSCLC Patients.

Background: Survival rates among non-small cell lung cancer (NSCLC) stage IIIA (N2) patients are generally low and depend on the treatment.

Patients And Methods: We aimed to identify predictive markers for long term survival in responders and non-responders to chemotherapy, analyzing tumour and non-tumour samples by microarray (n=35) and whole exome sequencing (WES, n=25).

Results: WES data showed correlation of overall survival of all patients with rs9905892 in the SLFN12L gene.

SMRT: Randomized Data Transformation for Cancer Subtyping and Big Data Analysis.

Cancer is an umbrella term that includes a range of disorders, from those that are fast-growing and lethal to indolent lesions with low or delayed potential for progression to death. The treatment options, as well as treatment success, are highly dependent on the correct subtyping of individual patients. With the advancement of high-throughput platforms, we have the opportunity to differentiate among cancer subtypes from a holistic perspective that takes into consideration phenomena at different molecular levels (mRNA, methylation, etc.

Evaluation of Dispersion Methods and Mechanical Behaviour of Glass Fibre Composites with Embedded Self-Healing Systems.

The present paper is focused on evaluating the most suitable dispersion method in the epoxy matrix of two self-healing systems containing dicyclopentadiene (DCPD) and 5-ethylidene-2-norbornene (ENB) monomers encapsulated in a urea-formaldehyde (UF) shell, prior to integration, fabrication and impact testing of specimens. Both microstructural analysis and three-point bending tests were performed to evaluate and assess the optimum dispersion method. It was found that ultrasonication damages the microcapsules of both healing systems, thus magnetic stirring was used for the dispersion of both healing systems in the epoxy matrix.

CPA: a web-based platform for consensus pathway analysis and interactive visualization.

In molecular biology and genetics, there is a large gap between the ease of data collection and our ability to extract knowledge from these data. Contributing to this gap is the fact that living organisms are complex systems whose emerging phenotypes are the results of multiple complex interactions taking place on various pathways. This demands powerful yet user-friendly pathway analysis tools to translate the now abundant high-throughput data into a better understanding of the underlying biological phenomena.

COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases.

Motivation: COVID-19 has several distinct clinical phases: a viral replication phase, an inflammatory phase and in some patients, a hyper-inflammatory phase. High mortality is associated with patients developing cytokine storm syndrome. Treatment of hyper-inflammation in these patients using existing approved therapies with proven safety profiles could address the immediate need to reduce mortality.

Automated Assay of a Four-Protein Biomarker Panel for Improved Detection of Ovarian Cancer.

: Mortality from ovarian cancer remains high due to the lack of methods for early detection. The difficulty lies in the low prevalence of the disease necessitating a significantly high specificity and positive-predictive value (PPV) to avoid unneeded and invasive intervention. Currently, cancer antigen- 125 (CA-125) is the most commonly used biomarker for the early detection of ovarian cancer.

Identification of key signaling pathways induced by SARS-CoV2 that underlie thrombosis and vascular injury in COVID-19 patients.

The SARS-CoV-2 pandemic has led to hundreds of thousands of deaths and billions of dollars in economic damage. The immune response elicited from this virus is poorly understood. An alarming number of cases have arisen where COVID-19 patients develop complications on top of the symptoms already associated with SARS, such as thrombosis, injuries of vascular system, kidney, and liver, as well as Kawasaki disease.

Platelets and renal failure in the SARS-CoV-2 syndrome.

The coronavirus disease 19 (COVID-19) is a highly transmittable viral infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 utilizes metallocarboxyl peptidase angiotensin receptor (ACE) 2 to gain entry into human cells. Activation of several proteases facilitates the interaction of viral spike proteins (S1) and ACE2 receptor.

MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.

In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this information is a challenging task due to: (i) the complexity of natural language processing, (ii) inconsistent use of standard recommendations for variant description, and (iii) the lack of clarity and consistency in describing the variant-genotype-phenotype associations in the biomedical literature. In this article, we employ text mining and word cloud analysis techniques to address these challenges.

Identification of cell types from single cell data using stable clustering.

Single-cell RNA-seq (scRNASeq) has become a powerful technique for measuring the transcriptome of individual cells. Unlike the bulk measurements that average the gene expressions over the individual cells, gene measurements at individual cells can be used to study several different tissues and organs at different stages. Identifying the cell types present in the sample from the single cell transcriptome data is a common goal in many single-cell experiments.

Detecting qualitative changes in biological systems.

Currently, most diseases are diagnosed only after significant disease-associated transformations have taken place. Here, we propose an approach able to identify when systemic qualitative changes in biological systems happen, thus opening the possibility for therapeutic interventions before the occurrence of symptoms. The proposed method exploits knowledge from biological networks and longitudinal data using a system impact analysis.

NBIA: a network-based integrative analysis framework - applied to pathway analysis.

With the explosion of high-throughput data, effective integrative analyses are needed to decipher the knowledge accumulated in biological databases. Existing meta-analysis approaches in systems biology often focus on hypothesis testing and neglect real expression changes, i.e.

Placenta-Specific Genes, Their Regulation During Villous Trophoblast Differentiation and Dysregulation in Preterm Preeclampsia.

The human placenta maintains pregnancy and supports the developing fetus by providing nutrition, gas-waste exchange, hormonal regulation, and an immunological barrier from the maternal immune system. The villous syncytiotrophoblast carries most of these functions and provides the interface between the maternal and fetal circulatory systems. The syncytiotrophoblast is generated by the biochemical and morphological differentiation of underlying cytotrophoblast progenitor cells.