Enhancing MAUDE Database Utility by GPT-4 and Cause-Effect Visualization.

The MAUDE database is a valuable public resource for understanding malfunctions and adverse events related to medical devices and health IT. However, its extensive data and complex structure pose challenges. To overcome this, we have developed an automated analytical pipeline using GPT-4, a cutting-edge large language model. This pipeline is intended to efficiently extract, categorize, and visualize safety events with minimal human annotation. In our analysis of 4,459 colonoscopy reports from MAUDE (2011-2021), the events were categorized into operational, human factor, and device-related. Ishikawa diagrams visualized a subset stored in a vector database for easy retrieval and comparison through a similarity search. This innovative approach streamlines access to vital safety insights, reducing the workload on human annotators, and holds promise to enhance the utility of the MAUDE database.

Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors.

BACKGROUND: Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) play a pivotal role in maintaining lifelong hematopoiesis. The distinction between stem cells and other progenitors, as well as the assessment of their functions, has long been a central focus in stem cell research. In recent years, deep learning has emerged as a powerful tool for cell image analysis and classification/prediction. METHODS: In this study, we explored the feasibility of employing deep learning techniques to differentiate murine HSCs and MPPs based solely on their morphology, as observed through light microscopy (DIC) images. RESULTS: After rigorous training and validation using extensive image datasets, we successfully developed a three-class classifier, referred to as the LSM model, capable of reliably distinguishing long-term HSCs, short-term HSCs, and MPPs. The LSM model extracts intrinsic morphological features unique to different cell types, irrespective of the methods used for cell identification and isolation, such as surface markers or intracellular GFP markers. Furthermore, employing the same deep learning framework, we created a two-class classifier that effectively discriminates between aged HSCs and young HSCs. This discovery is particularly significant as both cell types share identical surface markers yet serve distinct functions. This classifier holds the potential to offer a novel, rapid, and efficient means of assessing the functional states of HSCs, thus obviating the need for time-consuming transplantation experiments. CONCLUSION: Our study represents the pioneering use of deep learning to differentiate HSCs and MPPs under steady-state conditions. This novel and robust deep learning-based platform will provide a basis for the future development of a new generation stem cell identification and separation system. It may also provide new insight into the molecular mechanisms underlying stem cell self-renewal.

Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors.

Background: Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) play a pivotal role in maintaining lifelong hematopoiesis. The distinction between stem cells and other progenitors, as well as the assessment of their functions, has long been a central focus in stem cell research. In recent years, deep learning has emerged as a powerful tool for cell image analysis and classification/prediction. Methods: In this study, we explored the feasibility of employing deep learning techniques to differentiate murine HSCs and MPPs based solely on their morphology, as observed through light microscopy (DIC) images. Results: After rigorous training and validation using extensive image datasets, we successfully developed a three-class classifier, referred to as the LSM model, capable of reliably distinguishing long-term HSCs (LT-HSCs), short-term HSCs (ST-HSCs), and MPPs. The LSM model extracts intrinsic morphological features unique to different cell types, irrespective of the methods used for cell identification and isolation, such as surface markers or intracellular GFP markers. Furthermore, employing the same deep learning framework, we created a two-class classifier that effectively discriminates between aged HSCs and young HSCs. This discovery is particularly significant as both cell types share identical surface markers yet serve distinct functions. This classifier holds the potential to offer a novel, rapid, and efficient means of assessing the functional states of HSCs, thus obviating the need for time-consuming transplantation experiments. Conclusion: Our study represents the pioneering use of deep learning to differentiate HSCs and MPPs under steady-state conditions. With ongoing advancements in model algorithms and their integration into various imaging systems, deep learning stands poised to become an invaluable tool, significantly impacting stem cell research.

STING activation in TET2-mutated hematopoietic stem/progenitor cells contributes to the increased self-renewal and neoplastic transformation.

Somatic loss-of-function mutations of the dioxygenase Ten-eleven translocation-2 (TET2) occur frequently in individuals with clonal hematopoiesis (CH) and acute myeloid leukemia (AML). These common hematopoietic disorders can be recapitulated in mouse models. However, the underlying mechanisms by which the deficiency in TET2 promotes these disorders remain unclear. Here we show that the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway is activated to mediate the effect of TET2 deficiency in dysregulated hematopoiesis in mouse models. DNA damage arising in Tet2-deficient hematopoietic stem/progenitor cells (HSPCs) leads to activation of the cGAS-STING pathway which in turn promotes the enhanced self-renewal and development of CH. Notably, both pharmacological inhibition and genetic deletion of STING suppresses Tet2 mutation-induced aberrant hematopoiesis. In patient-derived xenograft (PDX) models, STING inhibition specifically attenuates the proliferation of leukemia cells from TET2-mutated individuals. These observations suggest that the development of CH associated with TET2 mutations is powered through chronic inflammation dependent on the activated cGAS-STING pathway and that STING may represent a potential target for intervention of relevant hematopoietic diseases.

Lamin A/C and Vimentin as a Coordinated Regulator during Amoeboid Migration in Microscale Confined Microenvironments.

Cell migration occurs in confined microenvironments, which plays a vital role in the process of tumor metastasis. However, it is challenging to study their behaviors in vivo. Here we developed a cell squeeze system that can be scaled down to micrometers to mimic native physical confined microenvironments, wherein degrees of surface adhesion and mechanical constraints could be manipulated in order to investigate cell-migrating behaviors. Based on the microscale cell squeeze system, we found the synergistic role of lamin A/C and vimentin in cell transition and migration under strong confinement. The dynamic variations in lamin A/C and vimentin expression establish a positive feedback loop in response to confinement, effectively promoting amoeboid migration by modulating nuclear deformability while ensuring cell viability. This work shed light on modulating cell response to microenvironments by altering the expression of lamin A/C and/or vimentin, which may be a more efficient way of inhibiting cancer metastasis.

A new peptide, VD11, promotes structural and functional recovery after spinal cord injury.

The regenerative capacity of the central nervous system is very limited and few effective treatments are currently available for spinal cord injury. It is therefore a priority to develop new drugs that can promote structural and functional recovery after spinal cord injury. Previous studies have shown that peptides can promote substantial repair and regeneration of injured tissue. While amphibians have a pronounced ability to regenerate the spinal cord, few studies have investigated the effect of amphibian spinal cord-derived peptides on spinal cord injury. Here we report for the first time the successful identification and isolation of a new polypeptide, VD11 (amino acid sequence: VDELWPPWLPC), from the spinal cord of an endemic Chinese amphibian (Odorrana schmackeri). In vitro experiments showed that VD11 promoted the secretion of nerve growth factor and brain-derived neurotrophic factor in BV2 cells stimulated with lipopolysaccharide, as well as the proliferation and synaptic elongation of PC12 cells subjected to hypoxia. In vivo experiments showed that intravertebral injection of VD11 markedly promoted recovery of motor function in rats with spinal cord injury, alleviated pathological damage, and promoted axonal regeneration. Furthermore, RNA sequencing and western blotting showed that VD11 may affect spinal cord injury through activation of the AMPK and AKT signaling pathways. In summary, we discovered a novel amphibian-derived peptide that promotes structural and functional recovery after spinal cord injury.

Deep learning driven colorectal lesion detection in gastrointestinal endoscopic and pathological imaging.

Colorectal cancer has the second highest incidence of malignant tumors and is the fourth leading cause of cancer deaths in China. Early diagnosis and treatment of colorectal cancer will lead to an improvement in the 5-year survival rate, which will reduce medical costs. The current diagnostic methods for early colorectal cancer include excreta, blood, endoscopy, and computer-aided endoscopy. In this paper, research on image analysis and prediction of colorectal cancer lesions based on deep learning is reviewed with the goal of providing a reference for the early diagnosis of colorectal cancer lesions by combining computer technology, 3D modeling, 5G remote technology, endoscopic robot technology, and surgical navigation technology. The findings will supplement the research and provide insights to improve the cure rate and reduce the mortality of colorectal cancer.

ESM1/HIF­1α pathway modulates chronic intermittent hypoxia­induced non­small­cell lung cancer proliferation, stemness and epithelial­mesenchymal transition.

Obstructive sleep apnea (OSA) is a sleep­related disorder characterized by chronic intermittent hypoxia (CIH). Previous studies have found that intermittent hypoxia promotes drug resistance, cell proliferation, migration and invasion in non­small cell lung cancer (NSCLC). Endothelial cell­specific molecule­1 (ESM1) is a molecule shown to be overexpressed in several types of tumors. The purpose of this study was to investigate the correlation between CIH and ESM1 and their potential roles in the progression of NSCLC. Tumorspheres, cell viability and colony formation assays were used to evaluate cell proliferation. The expression levels of cancer stem cell (CSC) markers CD44, CD133, OCT4 and SOX2 were measured with western blotting and/or RT­qPCR. Transwell assays were applied to assess cell migration and invasion. Changes in the expression levels of epithelial­mesenchymal transition (EMT)­associated proteins were also detected by western blotting. The results indicated that CIH enhanced lung cancer stem cell (LCSC) NSCLC progression by promoting stemness, drug resistance, cell proliferation, migration and invasion via the ESM1/HIF­1α pathway. Unexpectedly, inhibition of ESM1 reversed the CIH­involved negative effects on LCSCs and in a mouse model. ESM1 therefore appears to be crucial mediator of CIH­mediated lung cancer progression.

OsATX1 Interacts with Heavy Metal P1B-Type ATPases and Affects Copper Transport and Distribution.

Copper (Cu) is an essential micronutrient for plant growth. However, the molecular mechanisms underlying Cu trafficking and distribution to different organs in rice (Oryza sativa) are poorly understood. Here, we report the function and role of Antioxidant Protein1 (OsATX1), a Cu chaperone in rice. Knocking out OsATX1 resulted in increased Cu concentrations in roots, whereas OsATX1 overexpression reduced root Cu concentrations but increased Cu accumulation in the shoots. At the reproductive stage, the concentrations of Cu in developing tissues, including panicles, upper nodes and internodes, younger leaf blades, and leaf sheaths of the main tiller, were increased significantly in OsATX1-overexpressing plants and decreased in osatx1 mutants compared with the wild type. The osatx1 mutants also showed a higher Cu concentration in older leaves. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that OsATX1 interacts with the rice heavy metal P1B-ATPases HMA4, HMA5, HMA6, and HMA9. These results suggest that OsATX1 may function to deliver Cu to heavy metal P1B-ATPases for Cu trafficking and distribution in order to maintain Cu homeostasis in different rice tissues. In addition, heterologous expression of OsATX1 in the yeast (Saccharomyces cerevisiae) cadmium-sensitive mutant Δycf1 increased the tolerance to Cu and cadmium by decreasing their respective concentrations in the transformed yeast cells. Taken together, our results indicate that OsATX1 plays an important role in facilitating root-to-shoot Cu translocation and the redistribution of Cu from old leaves to developing tissues and seeds in rice.

Ube2D3 and Ube2N are essential for RIG-I-mediated MAVS aggregation in antiviral innate immunity.

Innate immunity plays a pivotal role in virus infection. RIG-I senses viral RNA and initiates an effective innate immune response for type I interferon production. To transduce RIG-I-mediated antiviral signalling, a mitochondrial protein MAVS forms prion-like aggregates to activate downstream kinases and transcription factors. However, the activation mechanism of RIG-I is incompletely understood. Here we identify two ubiquitin enzymes Ube2D3 and Ube2N through chromatographic purification as activators for RIG-I on virus infection. We show that together with ubiquitin ligase Riplet, Ube2D3 promotes covalent conjugation of polyubiquitin chains to RIG-I, while Ube2N preferentially facilitates production of unanchored polyubiquitin chains. In the presence of these polyubiquitin chains, RIG-I induces MAVS aggregation directly on the mitochondria. Our data thus reveal two essential polyubiquitin-mediated mechanisms underlying the activation of RIG-I and MAVS for triggering innate immune signalling in response to viral infection in cells.

An autoinhibitory mechanism modulates MAVS activity in antiviral innate immune response.

In response to virus infection, RIG-I senses viral RNA and activates the adaptor protein MAVS, which then forms prion-like filaments and stimulates a specific signalling pathway leading to type I interferon production to restrict virus proliferation. However, the mechanisms by which MAVS activity is regulated remain elusive. Here we identify distinct regions of MAVS responsible for activation of transcription factors interferon regulatory factor 3 (IRF3) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). These IRF3- and NF-κB-stimulating regions recruit preferential TNF receptor-associated factors (TRAFs) for downstream signalling. Strikingly, these regions' activities are inhibited by their respective adjacent regions in quiescent MAVS. Our data thus show that an autoinhibitory mechanism modulates MAVS activity in unstimulated cells and, on viral infection, individual regions of MAVS are released following MAVS filament formation to activate antiviral signalling cascades.

Inhaled corticosteroid influence toll like receptor 2 expression in induced sputum from patients with COPD.

BACKGROUND: The link between long-term ICS therapy and respiratory infection in COPD patients is controversial. We investigated the effect of long-term use of inhaled corticosteroid on Toll like receptor 2 (TLR2) expression in induced sputum from COPD patients. METHODS: 51 patients were divided into two groups according to their treatment history: long-term ICS treatment group (patients who have used ICS (equivalent to Fluticasone Propionate (FP) ≥ 500 ug/day for more than 1 year) (n = 21) and ICS naive group (who have never routinely used ICS before, n = 29). In their induced sputum, we tested TLR2 extracellular and intracellular expression on macrophages using flowcytometry. TLR2 and tumor necrosis factor αmRNA expression were also evaluated by real-time PCR. RESULTS: TLR2 extracellular expression on the macrophages from induced sputum in long-term ICS treatment group was lower than the ICS naïve group (13.69% ± 1.17% vs 20.12% ± 4.37%, p = 0.019). TLR2 intracellular expression in the macrophages, the TLR2 and TNFαmRNA in the induced sputum also showed a trend towards decreased endpoint in ICS long-term treatment group compare to ICS naïve group but did not reach significance. TLR2 extracellular and TLR2 intracellular expression were strongly related (r = 0.645, p = P = 0.017) as well as TNFαmRNA and TLR2 mRNA expression (r = 0.894, p = 0.0001). CONCLUSION: Long-term use of ICS may have negative influence on TLR2 expression in the airway of severe COPD patient.