Clinical translation in the virtual liver network.
Ontology highlight
ABSTRACT:
SUBMITTER: Kuepfer L
PROVIDER: S-EPMC4120019 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Fluorescence labeling and imaging provide an opportunity to observe the structure of biological tissues, playing a crucial role in the field of histopathology. However, when labeling and imaging biological tissues, there are still some challenges, e.g., time-consuming tissue preparation steps, expensive reagents, and signal bias due to photobleaching. To overcome these limitations, we present a deep-learning-based method for fluorescence translation of tissue sections, which is achieved by conditional generative adversarial network (cGAN). Experimental results from mouse kidney tissues demonstrate that the proposed method can predict the other types of fluorescence images from one raw fluorescence image, and implement the virtual multi-label fluorescent staining by merging the generated different fluorescence images as well. Moreover, this proposed method can also effectively reduce the time-consuming and laborious preparation in imaging processes, and further saves the cost and time.Supplementary informationThe online version contains supplementary material available at 10.1007/s43657-023-00094-1.
| S-EPMC10425324 | biostudies-literature
Project description:Although advances in neuroimaging have yielded insights into the intrinsic organization of human brain networks and their relevance to psychiatric and neurological disorders, there has been no translation of these insights into clinical practice. One necessary step toward clinical translation is identifying a summary metric of network function that is reproducible, reliable, and has known normative data, analogous to normed neuropsychological tests. Our aim was therefore to establish the proof of principle for such a metric, focusing on the default mode network (DMN). We compared three candidate summary metrics: global clustering coefficient, characteristic path length, and average connectivity. Across three samples totaling 322 healthy, mostly Caucasian adults, average connectivity performed best, with good internal consistency (Cronbach's α=0.69-0.70) and adequate eight-week test-retest reliability (intra-class coefficient=0.62 in a subsample N=65). We therefore present normative data for average connectivity of the DMN and its sub-networks. These proof of principle results are an important first step for the translation of neuroimaging to clinical practice. Ultimately, a normed summary metric will allow a single patient's DMN function to be quantified and interpreted relative to normative peers.
| S-EPMC5682602 | biostudies-literature
Project description:Liver failure is a life-threatening complication of infections restricting the host's response to infection. The pivotal role of the liver in metabolic, synthetic, and immunological pathways enforces limits the host's ability to control the immune response appropriately, making it vulnerable to ineffective pathogen resistance and tissue damage. Deregulated networks of liver diseases are gradually uncovered by high-throughput, single-cell resolved OMICS technologies visualizing an astonishing diversity of cell types and regulatory interaction driving tolerogenic signaling in health and inflammation in disease. Therefore, this review elucidates the effects of the dysregulated host response on the liver, consequences for the immune response, and possible avenues for personalized therapeutics.
| S-EPMC9338540 | biostudies-literature
Project description:Maintenance of internal homeostasis is a sophisticated process, during which almost all organs get involved. Liver plays a central role in metabolism and involves in endocrine, immunity, detoxification and storage, and therefore it communicates with distant organs through such mechanisms to regulate pathophysiological processes. Dysfunctional liver is often accompanied by pathological phenotypes of distant organs, including the eyes. Many reviews have focused on crosstalk between the liver and gut, the liver and brain, the liver and heart, the liver and kidney, but with no attention paid to the liver and eyes. In this review, we summarized intimate connections between the liver and the eyes from three aspects. Epidemiologically, we suggest liver-related, potential, protective and risk factors for typical eye disease as well as eye indicators connected with liver status. For molecular mechanism aspect, we elaborate their inter-organ crosstalk from metabolism (glucose, lipid, proteins, vitamin, and mineral), detoxification (ammonia and bilirubin), and immunity (complement and inflammation regulation) aspect. In clinical application part, we emphasize the latest advances in utilizing the liver-eye axis in disease diagnosis and therapy, involving artificial intelligence-deep learning-based novel diagnostic tools for detecting liver disease and adeno-associated viral vector-based gene therapy method for curing blinding eye disease. We aim to focus on and provide novel insights into liver and eyes communications and help resolve existed clinically significant issues.
| S-EPMC10566185 | biostudies-literature
Project description:Surveying people via the Internet presents both opportunities and challenges. The opportunities include quick access to respondents all over the world enabling fast realization of surveys at low costs. The challenges include a lack of control over both the sampling process and research implementation, as well as low response rates. This article describes a method of obtaining an appropriate sample of people for survey research utilising the power of the Internet, while simultaneously allowing the researcher to minimise risk thanks to enhanced control over the sampling process and the implementation of the survey. The proposed method could be used mainly in economic and social surveys; it allows researchers to reach selected groups of respondents and to conduct surveys on a global scale.•The proposed sampling method uses LinkedIn's network structure to quickly reach a dispersed population•Creating a list of units belonging to the study population resembles the snowball method, though the units are selected for the sample by the researcher and not indicated by the respondents.
| S-EPMC8374516 | biostudies-literature
Project description: Not available
| S-EPMC4607605 | biostudies-literature
Project description:Non-invasive diagnosis of chemotherapy-associated liver injuries (CALI) is still an unmet need. The present study aims to elucidate the contribution of radiomics to the diagnosis of sinusoidal dilatation (SinDil), nodular regenerative hyperplasia (NRH), and non-alcoholic steatohepatitis (NASH). Patients undergoing hepatectomy for colorectal metastases after chemotherapy (January 2018-February 2020) were retrospectively analyzed. Radiomic features were extracted from a standardized volume of non-tumoral liver parenchyma outlined in the portal phase of preoperative post-chemotherapy computed tomography. Seventy-eight patients were analyzed: 25 had grade 2-3 SinDil, 27 NRH, and 14 NASH. Three radiomic fingerprints independently predicted SinDil: GLRLM_f3 (OR = 12.25), NGLDM_f1 (OR = 7.77), and GLZLM_f2 (OR = 0.53). Combining clinical, laboratory, and radiomic data, the predictive model had accuracy = 82%, sensitivity = 64%, and specificity = 91% (AUC = 0.87 vs. AUC = 0.77 of the model without radiomics). Three radiomic parameters predicted NRH: conventional_HUQ2 (OR = 0.76), GLZLM_f2 (OR = 0.05), and GLZLM_f3 (OR = 7.97). The combined clinical/laboratory/radiomic model had accuracy = 85%, sensitivity = 81%, and specificity = 86% (AUC = 0.91 vs. AUC = 0.85 without radiomics). NASH was predicted by conventional_HUQ2 (OR = 0.79) with accuracy = 91%, sensitivity = 86%, and specificity = 92% (AUC = 0.93 vs. AUC = 0.83 without radiomics). In the validation set, accuracy was 72%, 71%, and 91% for SinDil, NRH, and NASH. Radiomic analysis of liver parenchyma may provide a signature that, in combination with clinical and laboratory data, improves the diagnosis of CALI.
| S-EPMC8234168 | biostudies-literature
Project description:Gold nanoparticles display unique physicochemical features, which can be useful for therapeutic purposes. After two decades of preclinical progress, gold nanoconstructs are slowly but steadily transitioning into clinical trials. Although initially thought to be "magic golden bullets" that could be used to treat a wide range of diseases, current consensus has moved toward a more realistic approach, where gold nanoformulations are being investigated to treat specific disorders. These therapeutic applications are dictated by the pharmacokinetics and biodistribution profiles of gold nanoparticles. Here, we analyze the current clinical landscape of therapeutic gold nanoconstructs, discuss the shared characteristics that allowed for their transition from bench to bedside, and examine existing hurdles that need to be overcome before they can be approved for clinical use.
| S-EPMC9432795 | biostudies-literature
Project description:Immunomodulatory therapeutics represent a unique class of drug products that have tremendous potential to rebalance malfunctioning immune systems and are quickly becoming one of the fastest-growing areas in the pharmaceutical industry. For these drugs to become mainstream medicines, they must provide greater therapeutic benefit than the currently used treatments without causing severe toxicities. Immunomodulators, cell-based therapies, antibodies, and viral therapies have all achieved varying amounts of success in the treatment of cancers and/or autoimmune diseases. However, many challenges related to precision dosing, off-target effects, and manufacturing hurdles will need to be addressed before we see widespread adoption of these therapies in the clinic. This review provides a perspective on the progress of immunostimulatory and immunosuppressive therapies to date and discusses the opportunities and challenges for clinical translation of the next generation of immunomodulatory therapeutics.
| S-EPMC8567306 | biostudies-literature
Project description:Silica nanoparticles have entered clinical trials for a variety of biomedical applications, including oral drug delivery, diagnostics, plasmonic resonance and photothermal ablation therapy. Preliminary results indicate the safety, efficacy and viability of silica nanoparticles under these clinical scenarios.
| S-EPMC8496429 | biostudies-literature