A generalist medical language model for disease diagnosis assistance.

The delivery of accurate diagnoses is crucial in healthcare and represents the gateway to appropriate and timely treatment. Although recent large language models (LLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, their effectiveness in clinical diagnosis remains unproven. Here we present MedFound, a generalist medical language model with 176 billion parameters, pre-trained on a large-scale corpus derived from diverse medical text and real-world clinical records.

High Prevalence of 5'UTR Mutations in Anaplastic Thyroid Cancer.

Anaplastic thyroid cancer (ATC) is a rare but one of the most lethal types of human cancer. Although increasing evidence demonstrated that ATC tumors had a high mutation burden, little is known about the aberrancy of the noncoding genome of ATC except the well-investigated () promoter mutations. The mutational statuses of 5' untranslated region (5'UTR), intron 6, and promoters, as well as the promoter and mutations were determined using Sanger sequencing in 28 patients with ATC (19 women and 9 men) with a median (interquartile range) age of 64 (55-71) years, 14 thyroid cancer cell lines and a normal thyroid cell line.

Enhanced machine learning models for predicting one-year mortality in individuals suffering from type A aortic dissection.

Objective: The study objective was to develop and validate an interpretable machine learning model to predict 1-year mortality in patients with type A aortic dissection, improving risk classification and aiding clinical decision-making.

Methods: We enrolled 289 patients with type A aortic dissection, dividing them into a training cohort (202 patients) and a validation cohort (87 patients). The Least Absolute Shrinkage and Selection Operator method with 10-fold cross-validation identified 8 key factors related to 1-year mortality.

A generalized AI system for human embryo selection covering the entire IVF cycle via multi-modal contrastive learning.

fertilization (IVF) has revolutionized infertility treatment, benefiting millions of couples worldwide. However, current clinical practices for embryo selection rely heavily on visual inspection of morphology, which is highly variable and experience dependent. Here, we propose a comprehensive artificial intelligence (AI) system that can interpret embryo-developmental knowledge encoded in vast unlabeled multi-modal datasets and provide personalized embryo selection.

Therapeutic targeting of PLK1 in TERT promoter-mutant hepatocellular carcinoma.

Background: Hotspot mutations in the promoter of telomerase reverse transcriptase (TERT) gene are the most common genetic variants in hepatocellular carcinoma (HCC) and associated with poor prognosis of the disease. However, no drug was currently approved for treating TERT promoter mutation positive HCC patients. Here, we aim to explore the potential therapeutic strategy for targeting TERT promoter mutation in HCC.

The ERK inhibitor GDC-0994 selectively inhibits growth of BRAF mutant cancer cells.

BRAF or RAS mutation-induced aberrant activation of the mitogen-activated protein kinase (MAPK) pathway is frequently observed in human cancers. As the key downstream node of MAPK pathway, ERK1/2 is as an important therapeutic target. GDC-0994 (ravoxertinib), an orally bioavailable, highly selective small-molecule inhibitor of ERK1/2, showed acceptable safety and pharmacodynamic profile in a recent phase I clinical trial.

Risk stratification by combining common genetic mutations and TERT promoter methylation in papillary thyroid cancer.

Purpose: Risk stratification based on somatic mutations in TERT promoter and BRAF/RAS has been well established for papillary thyroid cancer (PTC), and there is emerging evidence showed that TERT promoter methylation was frequently observed in thyroid cancer patients with adverse features. This study was aimed to comprehensive explore the prognostic value of BRAF/RAS mutations, TERT promoter mutations, and TERT promoter methylation in PTC.

Methods: The relationships of BRAF/RAS mutations, TERT promoter mutations, and TERT promoter methylation with clinical characteristics and outcomes of PTC were analyzed in 382 patients with PTC.

Dendritic Cell-Mimicking Nanoparticles Promote mRNA Delivery to Lymphoid Organs.

Spleen and lymphoid organs are important targets for messenger RNA (mRNA) delivery in various applications. Current nanoparticle delivery methods rely on drainage to lymph nodes from intramuscular or subcutaneous injections. In difficult-to-transfect antigen-presenting cells (APCs), such as dendritic cells (DCs), effective mRNA transfection remains a significant challenge.

Methylation-Mediated Silencing of ATF3 Promotes Thyroid Cancer Progression by Regulating Prognostic Genes in the MAPK and PI3K/AKT Pathways.

Aberrant expression of oncogenes and/or tumor suppressor genes (TSGs) drives the tumorigenesis and development of thyroid cancer. We investigated the expression and function of a member of the activating transcription factor (ATF)/cAMP-responsive element-binding protein (CREB) transcription factor (TF) family, ATF3, in thyroid cancer. Data from 80 patients with papillary thyroid cancer (PTC) in the First Affiliated Hospital of Sun Yat-sen University and 510 PTC samples in The Cancer Genome Atlas thyroid cancer database were utilized for gene expression and prognosis analyses.

Streamlined and on-demand preparation of mRNA products on a universal integrated platform.

Vaccines are used to protect human beings from various diseases. mRNA vaccines simplify the development process and reduce the production cost of conventional vaccines, making it possible to respond rapidly to acute and severe diseases, such as coronavirus disease 2019. In this study, a universal integrated platform for the streamlined and on-demand preparation of mRNA products directly from DNA templates was established.

Monkeypox virus quadrivalent mRNA vaccine induces immune response and protects against vaccinia virus.

Monkeypox has been declared a public health emergency by the World Health Organization. There is an urgent need for efficient and safe vaccines against the monkeypox virus (MPXV) in response to the rapidly spreading monkeypox epidemic. In the age of COVID-19, mRNA vaccines have been highly successful and emerged as platforms enabling rapid development and large-scale preparation.

Novel Ionizable Lipid Nanoparticles for SARS-CoV-2 Omicron mRNA Delivery.

mRNA-based therapy has emerged as the most promising nucleic acid therapy in the fight against COVID-19. However, a safe and efficacious systemic delivery remains a challenge for mRNA therapy. Lipid nanoparticles (LNPs) are currently widely used in mRNA delivery vehicles.

Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames.

Recent developments of deep learning methods have demonstrated their feasibility in liver malignancy diagnosis using ultrasound (US) images. However, most of these methods require manual selection and annotation of US images by radiologists, which limit their practical application. On the other hand, US videos provide more comprehensive morphological information about liver masses and their relationships with surrounding structures than US images, potentially leading to a more accurate diagnosis.

Mitochondrial Micropeptide STMP1 Enhances Mitochondrial Fission to Promote Tumor Metastasis.

Unlabelled: Micropeptides are a recently discovered class of molecules that play vital roles in various cellular processes, including differentiation, proliferation, and apoptosis. Here, we sought to identify cancer-associated micropeptides and to uncover their mechanistic functions. A micropeptide named short transmembrane protein 1 (STMP1) that localizes at the inner mitochondrial membrane was identified to be upregulated in various cancer types and associated with metastasis and recurrence of hepatocellular carcinoma.

Mitochondrial micropeptide STMP1 promotes G1/S transition by enhancing mitochondrial complex IV activity.

The roles of micropeptides in cell cycle regulation and cancer development remain largely unknown. Here we found that a micropeptide STMP1 (small transmembrane protein 1) was up-regulated in multiple malignancies including hepatocellular carcinoma (HCC), and its high level was associated with short recurrence-free survival of HCC patients. Gain- and loss-of-function analyses revealed that STMP1 accelerated cell proliferation and clonogenicity in vitro and tumor growth in vivo, and silencing STMP1 blocked G1/S transition.

A long non-coding RNA-based signature predicts early recurrence in hepatocellular carcinoma.

Background: Early recurrence is the main obstacle for long-term survival of hepatocellular carcinoma (HCC) patients after curative resection.

Objective: We aimed to develop a long non-coding RNA (lncRNA) based signature to predict early recurrence.

Methods: Using bioinformatics analysis and quantitative reverse transcription PCR (RT-qPCR), we screened for lncRNA candidates that were abnormally expressed in HCC.

UHPLC-MS/MS Method for Quantifying Fangchinoline, Tetrandrine and Calycosin-7-O-β-D-Glucoside of Fangji Huangqi Decoction in Rat Plasma and Its Application to a Pharmacokinetic Study.

Fangji Huangqi Decoction is composed of Stephaniae Tetrandrae Radix, Astragli Radix, Atractylodis Macrocephalae Rhizoma and Glycyrrhizae Radix Et Rhizoma. It is a classic traditional Chinese medicine formula for the treatment of chronic glomerulonephritis in China. However, its pharmacokinetic characteristics in vivo are still unclear.

Rational preparation and application of a mRNA delivery system with cytidinyl/cationic lipid.

The messenger RNA (mRNA)-based therapy, especially mRNA vaccines, has shown its superiorities in versatile design, rapid development and scale production, since the outbreak of coronavirus disease 2019 (COVID-19). Although the Pfizer-BioNTech and Moderna COVID-19 mRNA vaccines had been approved for application, unexpected adverse events were reported to be most likely associated with the mRNA delivery systems. Thus, the development of mRNA delivery system with good efficacy and safety remains a challenge.

Genome-Wide Histone H3K27 Acetylation Profiling Identified Genes Correlated With Prognosis in Papillary Thyroid Carcinoma.

Thyroid carcinoma (TC) is the most common endocrine malignancy, and papillary TC (PTC) is the most frequent subtype of TC, accounting for 85-90% of all the cases. Aberrant histone acetylation contributes to carcinogenesis by inducing the dysregulation of certain cancer-related genes. However, the histone acetylation landscape in PTC remains elusive.

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries.

Clinical longitudinal evaluation of COVID-19 patients and prediction of organ-specific recovery using artificial intelligence.

Within COVID-19 there is an urgent unmet need to predict at the time of hospital admission which COVID-19 patients will recover from the disease, and how fast they recover to deliver personalized treatments and to properly allocate hospital resources so that healthcare systems do not become overwhelmed. To this end, we have combined clinically salient CT imaging data synergistically with laboratory testing data in an integrative machine learning model to predict organ-specific recovery of patients from COVID-19. We trained and validated our model in 285 patients on each separate major organ system impacted by COVID-19 including the renal, pulmonary, immune, cardiac, and hepatic systems.