Dynamic changes of cellular immune function and individualized adjustments of immunosup-pressant for the management of severe infection after liver transplantation

Objective To explore the dynamic changes of the cellular immune function in severe infection after liver transplantation,and to guide the individualized immunology adjustment. Methods 378 cases of liver transplantation were analyzed retrospectively. Seventy - four cases ( infection group) suffered serious infection,including 54 cases cured ( cure group) ,20 cases died (

Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy

BACKGROUND Liver disease indicates any pathology that can harm or destroy the liver or prevent it from normal functioning.The global community has recently witnessed an increase in the mortality rate due to liver disease.This could be attributed to many factors,among which are human habits,awareness issues,poor healthcare,and late detection.To curb the growing threats from liver disease,early detection is critical to help reduce the risks and improve treatment outcome.Emerging technologies such as machine learning,as shown in this study,could be deployed to assist in enhancing its prediction and treatment.AIM To present a more efficient system for timely prediction of liver disease using a hybrid eXtreme Gradient Boosting model with hyperparameter tuning with a view to assist in early detection,diagnosis,and reduction of risks and mortality associated with the disease.METHODS The dataset used in this study consisted of 416 people with liver problems and 167 with no such history.The data were collected from the state of Andhra Pradesh,India,through https://www.kaggle.com/datasets/uciml/indian-liver-patientrecords.The population was divided into two sets depending on the disease state of the patient.This binary information was recorded in the attribute"is_patient".RESULTS The results indicated that the chi-square automated interaction detection and classification and regression trees models achieved an accuracy level of 71.36%and 73.24%,respectively,which was much better than the conventional method.The proposed solution would assist patients and physicians in tackling the problem of liver disease and ensuring that cases are detected early to prevent it from developing into cirrhosis(scarring)and to enhance the survival of patients.The study showed the potential of machine learning in health care,especially as it concerns disease prediction and monitoring.CONCLUSION This study contributed to the knowledge of machine learning application to health and to the efforts toward combating the problem of liver disease.However,relevant authorities have to invest more into machine learning research and other health technologies to maximize their potential.

Examining ecosystem(dis-)services on liver fluke infection in rural Northeast Thailand

Background The direct reliance of humans on and their interactions with freshwater ecosystems in the Lower Mekong Basin have given rise to parasitic infections,which is particularly prevalent in Northeast Thailand where raw fish consumption is practiced.This study examined the interactions between environments,ecosystem(dis-)services,human raw fish consumption habits,and raw fish dish sharing on liver fluke infection risk.Method Water fecal contents and the first intermediate snail host were sampled between June and September of 2019.One hundred twenty questionnaires were surveyed in two villages of different environmental surroundings,one next to a river and the other located inland,in Northeast Thailand.Multivariate regression analyses using linear mixed effect models assessed the influence of social,behavioral and perceptual factors on raw fish consumption frequency,willingness to avoid consumption and liver fluke infection status.Social network analysis compared the degree of raw fish dish sharing between the villages and assessed the probable influence of connections to fish procurement locations and sharing activities on liver fluke infection risk.Results High abundance of the first intermediate snail host and presence of fecal contamination in water could endanger both villages to ecosystem disservices of parasitic transmission.The river-side village relied more on provisioning ecosystem services than the inland village(29.7%vs.16.1%of villages)to consume raw fish as their main source of protein.Males in both villages(64.5 and 40.4 days/year for the respective villages)are also likely to consume koi pla and pla som,higher risk fish dishes,more frequently than females(4.1 and 4.3 days/year for the respective villages).The consumption habits of both villages were driven mostly by deriving cultural ecosystem services.Participation in raw fish dish sharing activities significantly reduced the odds of an individual being willing to avoid the consumption(Odds ratio=0.19).Network analysis suggested that river-side villagers had a more direct raw fish dish sharing interaction and they procured fish from multiple locations;these characteristics might potentially account for more liver fluke infected households in the village.Conclusion Villagers’raw fish consumption is driven by deriving cultural ecosystem services,and the geographic settings of the villages potentially affect villagers’fish procurement locations and infection risk.The findings underscore the linkages between villagers and their surrounding ecosystem environments as pertinent determinants for foodborne parasitic disease risk.

γδ T cells in liver diseases

γδ T cells display unique developmental, distributional, and functional patterns and can rapidly respond to various insults and contribute to diverse diseases. Different subtypes of γδ T cells are produced in the thymus prior to their migration to peripheral tissues, γδ T cells are enriched in the liver and exhibit liver-specific features. Accumulating evidence reveals that γδ T cells play important roles in liver infection, non-alcoholic fatty liver disease, autoimmune hepatitis, liver fibrosis and cirrhosis, and fiver cancer and regeneration. In this study, we review the properties of hepatic γδ T cells and summarize the roles of γδ T cells in liver diseases. We believe that determining the properties and functions of γδ T cells in liver diseases enhances our understanding of the pathogenesis of liver diseases and is useful for the design of novel γδ T cell-based therapeutic regimens for liver diseases.

Ultrasmall Ga-ICG nanoparticles based gallium ion/photodynamic synergistic therapy to eradicate biofilms and against drug-resistant bacterial liver abscess

Pyogenic liver abscess and keratitis are aggressive bacterial infections and the treatment has failed to eradicate bacteria in infectious sites completely owing to the currently severe drug resistance to existing antibiotics.Here,we report a simple and efficient one-step development of ultrasmall non-antibiotic nanoparticles(ICG-Ga NPs)containing clinically approved gallium(Ⅲ)(Ga^(3+))and liver targeting indocyanine green(ICG)molecules to eradicate multi-drug resistant(MDR)bacteria thought the synergetic effect of photodynamic therapy and iron metabolism blocking.The ICG-Ga NPs induced photodynamic effect could destroy the bacterial membrane,further boost the endocytosis of Ga^(3+),then replace iron in bacteria cells to disrupt bacterial iron metabolism,and demonstrate the synergetic bacterial killing and biofilm disrupting effects.The ICG-Ga NPs show an excellent therapeutic effect against extended spectrumβ-lactamases Escherichia coli(ESBL E.coli)and significantly improve treatment outcomes in infected liver abscess and keratitis.Meanwhile,the ultrasmall size of ICG-Ga NPs could be cleared rapid via renal clearance route,guaranteeing the biocompatibility.The protective effect and good biocompatibility of ICG-Ga NPs will facilitate clinical treatment of bacteria infected diseases and enable the development of next-generation non-antibiotic antibacterial agents.