Efficacy of taurine-enhanced enteral nutrition in improving the outcomes of critically ill patients: A systematic review and meta-analysis.

BACKGROUND: Taurine is considered an immunomodulatory agent. From current reports on clinical studies, we conducted a systematic review and meta-analysis to investigate the effects of taurine-enhanced enteral nutrition (EN) on the outcomes of critically ill patients to resolve conflicting evidence in literature. METHODS: Literature from PubMed, EMBASE, Web of Science, Cochrane Library, CNKI, SINOMED, and WanFang databases were retrieved, and randomized controlled trials (RCTs) were identified. The time range spanned from January 1, 2000, to January 31, 2024. The Cochrane Collaboration Tool was used to evaluate the risk of bias. We used the GRADE approach to rate the quality of evidence and the I2 test to assess the statistical heterogeneity of the results. Risk ratio (RR), mean difference (MD), and 95% confidence interval (95% CI) were used to analyze measurement data. RESULTS: Four trials involving 236 patients were finally included. The meta-analysis results indicated that taurine-enhanced EN did not reduce mortality (RR = 0.70, p = 0.45, 95% CI [0.28, 1.80], two trials, 176 participants, low quality). There was also no significant difference in length of stay in the intensive care unit (ICU) between the taurine-enhanced EN and control groups. Taurine-enhanced EN may reduce pro-inflammatory factor interleukin-6 (IL-6) levels in critically ill patients（the result about IL-6 cannot be pooled）. However, taurine-enhanced EN had no significant impact on high-sensitivity-C-reactive protein levels (MD = -0.41, p = 0.40, 95% CI [-1.35, 0.54], two trials, 60 participants, low quality). DISCUSSION: Taurine-enhanced EN may reduce IL-6 levels and is not associated with improved clinical outcomes in critically ill patients, which may have potential immunoregulatory effects in critically ill patients. Given that published studies have small samples, the above conclusions need to be verified by more rigorously designed large-sample clinical trials.

Characterising the challenges of managing difficult red blood cell alloantibodies in liver transplant recipients.

AIMS: Formation of red blood cell alloantibodies (RBCAs) complicates transfusion support in liver transplantation (LT). Difficult RBCAs (DAs, >3 antibodies or antibodies for which <25% donors are antigen negative) further challenge care. This study characterises DA outcomes relative to non-difficult RBCAs (NDAs). METHODS: Single-centre, retrospective analysis of LT patients (2002-2021). RBCAs were defined as clinically significant antibodies. DAs were compared with NDAs. RESULTS: 89 patients had clinically significant RBCAs (DA=50, NDA=39). More DAs were anti-Jka, anti-M; fewer were anti-E, anti-K (all p<0.05). DA patients often had multiple antibodies (44% vs 12.8% NDA, p=0.0022). Probability of finding antigen-negative blood was lower for DAs (17.4% vs 68.1% NDA, p<0.0001) as was RBCs received (9.4 vs 14.7 units in NDA, p=0.0036). Although survival was similar, patients with DAs had more adverse reactions (8% vs 0%, p=0.128). Some antibodies appeared to occur with specific liver diseases (such as primary sclerosing cholangitis, alcoholic steatohepatitis and recurrent disease); however, due to low sample size, definitive conclusions cannot be made. CONCLUSIONS: DA LT recipients contain >1 RBCA, have a lower probability of finding antigen negative blood and may experience more adverse transfusion event (ATE). Despite this, the incidence of ATEs was still quite low.

A New Framework Combining Diffusion Models and the Convolution Classifier for Generating Images from EEG Signals.

The generation of images from electroencephalography (EEG) signals has become a popular research topic in recent research because it can bridge the gap between brain signals and visual stimuli and has wide application prospects in neuroscience and computer vision. However, due to the high complexity of EEG signals, the reconstruction of visual stimuli through EEG signals continues to pose a challenge. In this work, we propose an EEG-ConDiffusion framework that involves three stages: feature extraction, fine-tuning of the pretrained model, and image generation. In the EEG-ConDiffusion framework, classification features of EEG signals are first obtained through the feature extraction block. Then, the classification features are taken as conditions to fine-tune the stable diffusion model in the image generation block to generate images with corresponding semantics. This framework combines EEG classification and image generation means to enhance the quality of generated images. Our proposed framework was tested on an EEG-based visual classification dataset. The performance of our framework is measured by classification accuracy, 50-way top-k accuracy, and inception score. The results indicate that the proposed EEG-Condiffusion framework can extract effective classification features and generate high-quality images from EEG signals to realize EEG-to-image conversion.

Clinical and Molecular Correlates of the Index of Severity for Eosinophilic Esophagitis.

BACKGROUND: The Index of Severity for Eosinophilic Esophagitis (I-SEE) is a new expert-defined clinical tool that classifies disease severity of eosinophilic esophagitis (EoE). OBJECTIVE: We aimed to determine whether I-SEE is associated with patient characteristics and/or molecular features of EoE. METHODS: We analyzed a prospective cohort of patients with EoE from the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR). Associations between I-SEE and clinical and molecular features (EoE Diagnostic Panel [EDP]) were assessed. RESULTS: In 318 patients with chronic EoE (adults 209, children 109), the median total I-SEE score was 7.0, with a higher symptoms and complications score in children than adults (4.0 vs. 1.0; P < .001) and higher inflammatory and fibrostenotic features scores in adults than children (3.0 vs. 1.0 and 3.0 vs. 0.0, respectively; both P < .001). Total I-SEE score had a bimodal distribution with the inactive to moderate categories and severe category. EDP score correlated with total I-SEE score (r = -0.352, P < .001) and both inflammatory and fibrostenotic features scores (r = -0.665, P< .001; r = -0.446, P < .001, respectively), but not with symptoms and complications scores (r = 0.047, P = .408). Molecular severity increased from inactive to mild and moderate, but not severe categories. Longitudinal changes of modified I-SEE scores and inflammatory and fibrostenotic features scores reflected the histologic and molecular activity. CONCLUSIONS: I-SEE associated with select clinical features across severity categories and with EoE molecular features for non-severe categories, warranting further validation.

Non-epithelial Gene Expression Correlates with Symptom Severity in Adults with Eosinophilic Esophagitis.

BACKGROUND: The mechanistic basis of the variable symptomatology seen in eosinophilic esophagitis (EoE) remains poorly understood. OBJECTIVE: We examined the correlation of a validated, patient-reported outcome (PRO) metric with a broad spectrum of esophageal transcripts to uncover potential symptom pathogenesis. METHODS: Data were extracted from 146 adults with EoE through the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR). Patients were subgrouped by esophageal dilation history. We compared a validated PRO metric, the EoE Activity Index (EEsAI), with a set of transcripts expressed in the esophagus of patients with EoE, the EoE Diagnostic Panel (EDP). We utilized single-cell RNA sequencing data to identify the cellular source of EEsAI-related EDP genes and further analyzed patients with mild and severe symptoms. RESULTS: The EEsAI correlated with the EDP total score, especially in patients without recent esophageal dilation (r = -0.31, P = .003). We identified 14 EDP genes that correlated with EEsAI scores (r ≥ 0.3, P < .05). Of these, 11 were expressed in non-epithelial cells and 3 in epithelial cells; during histologic remission, only 4/11 (36%) non-epithelial versus 3/3 (100%) epithelial genes had decreased expression to <50% of that in active EoE. Fibroblasts expressed 5/11 (45%) non-epithelial EEsAI-associated EDP genes. A subset of non-epithelial (8/11, 73%), but not EoE-representative (0/4, 0%; CCL26, CAPN14, DSG1, SPINK7), genes was upregulated in patients with EoE with the highest versus lowest symptom burden. CONCLUSION: The correlation of symptoms and non-epithelial esophageal gene expression substantiates that non-epithelial cells (e.g., fibroblasts) likely contribute to symptom severity.

Histopathology of Eosinophilic Esophagitis.

Microscopic examination of esophageal biopsies is essential to diagnose eosinophilic esophagitis (EoE). Eosinophil inflammation is the basis for the diagnosis, but additional abnormalities may contribute to persistent symptoms and epithelial barrier dysfunction. Both peak eosinophil count and assessments of additional features should be included in pre-therapy and post-therapy pathology reports. Pathologic abnormalities identified in esophageal biopsies of EoE are reversible in contrast to esophageal strictures.

Histopathology of Eosinophilic Gastrointestinal Diseases Beyond Eosinophilic Esophagitis.

Eosinophilic gastrointestinal diseases (EGID), such as eosinophilic gastritis (EoG), eosinophilic enteritis, and eosinophilic colitis (EoC), are chronic inflammatory conditions characterized by persistent gastrointestinal symptoms and elevated levels of activated eosinophils in the gastrointestinal tract. EoG and eosinophilic duodenitis (EoD) are strongly associated with food allergen triggers and TH2 inflammation, whereas EoC shows minimal transcriptomic overlap with other EGIDs. The level of expression of certain genes associated with TH2 immune response is associated with certain histopathologic findings of EoG, EoD, and EoC. Current immune therapy for EoG depletes tissue eosinophilia with persistence of other histopathologic features of disease.

A Large-Scale Three-Dimensional Apparatus to Study Failure Mechanisms of Rockfalls in Underground Engineering Contexts.

Rockfalls are an important factor affecting underground engineering safety. However, there has been limited progress in understanding and predicting these disasters in the past few years. Therefore, a large-scale three-dimensional experimental simulation apparatus to study failure mechanisms of rockfalls occurring during underground engineering was developed. This apparatus, measuring 4 m × 4 m × 3.3 m in size, can achieve vertical and horizontal symmetric loading. It not only simulates the structure and stress environment of a rock mass but also simulates the stepwise excavation processes involved in underground engineering. A complete simulation experiment of rockfalls in an underground engineering context was performed using this apparatus. Dynamic evolution characteristics of block displacement, temperature, natural vibration frequency, and acoustic emissions occurring during rockfalls were studied during the simulation. These data indicate there are several indicators that could be used to predict rockfalls in underground engineering contexts, leading to better prevention and control.

Can three-dimensional nitrate structure be reconstructed from surface information with artificial intelligence? - A proof-of-concept study.

Nitrate is one of the essential variables in the ocean that is a primary control of the upper ocean pelagic ecosystem. Its three-dimensional (3D) structure is vital for understanding the dynamic and ecosystem. Although several gridded nitrate products exist, the possibility of reconstructing the 3D structure of nitrate from surface data has never been exploited. In this study, we employed two advanced artificial intelligence (AI) networks, U-net and Earthformer, to reconstruct nitrate concentration in the Indian Ocean from surface data. Simulation from an ecosystem model was utilized as the labeling data to train and test the AI networks, with wind vectors, wind stress, sea surface temperature, sea surface chlorophyll-a, solar radiation, and precipitation as the input. We compared the performance of two networks and different pre-processing methods. With the input features decomposed into climatology and anomaly components, the Earthformer achieved optimal reconstruction results with a lower normalized mean square error (NRMSE = 0.1591), spatially and temporally, outperforming U-net (NRMSE = 0.2007) and the climatology prediction (NRMSE = 0.2089). Furthermore, Earthformer was more capable of identifying interannual nitrate anomalies. With a network interpretation technique, we quantified the spatio-temporal importance of every input feature in the best case (Earthformer with decomposed inputs). The influence of different input features on nitrate concentration in the adjacent Java Sea exhibited seasonal variation, stronger than the interannual one. The feature importance highlighted the role of dynamic factors, particularly the wind, matching our understanding of the dynamic controls of the ecosystem. Our reconstruction and network interpretation technique can be extended to other ecosystem variables, providing new possibilities in studies of marine environment and ecology from an AI perspective.

Tissue-specific reprogramming leads to angiogenic neutrophil specialization and tumor vascularization in colorectal cancer.

Neutrophil (PMN) tissue accumulation is an established feature of ulcerative colitis (UC) lesions and colorectal cancer (CRC). To assess the PMN phenotypic and functional diversification during the transition from inflammatory ulceration to CRC we analyzed the transcriptomic landscape of blood and tissue PMNs. Transcriptional programs effectively separated PMNs based on their proximity to peripheral blood, inflamed colon, and tumors. In silico pathway overrepresentation analysis, protein-network mapping, gene signature identification, and gene-ontology scoring revealed unique enrichment of angiogenic and vasculature development pathways in tumor-associated neutrophils (TANs). Functional studies utilizing ex vivo cultures, colitis-induced murine CRC, and patient-derived xenograft models demonstrated a critical role for TANs in promoting tumor vascularization. Spp1 (OPN) and Mmp14 (MT1-MMP) were identified by unbiased -omics and mechanistic studies to be highly induced in TANs, acting to critically regulate endothelial cell chemotaxis and branching. TCGA data set and clinical specimens confirmed enrichment of SPP1 and MMP14 in high-grade CRC but not in patients with UC. Pharmacological inhibition of TAN trafficking or MMP14 activity effectively reduced tumor vascular density, leading to CRC regression. Our findings demonstrate a niche-directed PMN functional specialization and identify TAN contributions to tumor vascularization, delineating what we believe to be a new therapeutic framework for CRC treatment focused on TAN angiogenic properties.

Tetrahydropiperine, a natural alkaloid with neuroprotective effects in ischemic stroke.

BACKGROUND: Ischemic stroke (IS) is a life-threatening neurological disease with various pathological mechanisms. Tetrahydropiperine (THP) is a natural alkaloid with protective effects against multiple diseases, such as seizure, and pain. This study was to examine the impact of THP on IS and investigate its potential mechanism. MATERIAL AND METHODS: We employed network pharmacology and molecular docking techniques to identify the target proteins of THP for intervention in IS. Adult male Sprague-Dawley rats were used to create a permanent middle cerebral artery occlusion model. PC-12 cells were chosen to establish an oxygen-glucose deprivation (OGD) cell model. Disease modeling followed by nimodipine (NIMO); 3-methyladenine (3-MA) and rapamycin (RAP) interventions. Open field test, Longa score, balance beam test, and forelimb grip test were used to measure motor and neurological functions. The degree of neurological damage recovery was assessed through behavioral analysis, and cerebral infarction volume was determined using TTC staining. Morphological changes were examined through HE and Nissl staining, and ultrastructural changes in neurons were observed using transmission electron microscopy. The protein expression of autophagy and related pathways was analyzed through Western blot (WB). The appropriate hypoxia time and drug concentration were determined using CCK-8 assay, which also measured cell survival rate. RESULTS: The network pharmacology findings indicated that the impact of THP on IS was enhanced in the PI3K/Akt signaling pathway. THP demonstrated robust docking capability with proteins associated with the autophagy and PI3K/Akt/mTOR, as indicated by the molecular docking outcomes. THP significantly improved behavioral damage, reduced the area of cerebral infarction, ameliorated histopathological damage from ischemia, increase neuronal survival, and alleviated ultrastructural damage in neurons (P < 0.05). THP enhanced the survival of PC-12 cells induced by OGD and ameliorated the morphological harm to the cells (P < 0.05). THP was found to elevate the quantities of P62, LC3-Ⅰ, PI3K, P-AKt/Akt, and P-mTOR/mTOR proteins while reducing the levels of Atg7 and Beclin1 proteins. The results of transmission electron microscopy showed no autophagosomes in the THP, 3-MA, and 3-MA + THP groups. CONCLUSION: The activation of the PI3K/Akt/mTOR signaling pathway by THP inhibits autophagy and provides relief from neurological damage in IS.

Hydraulic conductivity and microscopic properties of polyanionic cellulose and microscale zero-valent iron amended sand/bentonite backfills exposed to dichloromethane solution.

Leachate comprising organic contaminants such as dichloromethane is frequently discharged into groundwater at contaminated sites and unlined landfills. Soil-bentonite backfills in vertical cutoff walls are extensively employed to contain the flow of contaminated groundwater, thereby safeguarding the downstream groundwater environmental quality and ecosystem. This study presented a comprehensive evaluation of effects of dichloromethane-impacted groundwater on hydraulic conductivity and microscopic characteristics of soil-bentonite backfills amended with polymer namely polyanionic cellulose and microscale zero-valent iron. The results showed the amended backfills exhibited lower hydraulic conductivity than the unamended backfill regardless of the permeant type, i.e., tap water and dichloromethane solution. Scanning electron microscopy coupled with energy-dispersive spectrometry analyses demonstrated that polyanionic cellulose hydrogel could effectively coat sand, bentonite, and microscale zero-valent iron particles, providing protection of bentonite particles against attacks imposed by the dichloromethane and multivalent iron ions, and diminish aggregation of microscale zero-valent iron particles in the amended backfills. X-ray diffraction results indicated there was no intercalation of polyanionic cellulose and microscale zero-valent iron into the montmorillonite platelets of bentonite particles. Based on the Fourier Transform Infrared Spectroscopy Spectra analysis, a new functional group (-CH2) was identified on the polyanionic cellulose amended bentonite particles. The results demonstrated that amendment with polyanionic cellulose and microscale zero-valent iron is a promising approach to improve the performance of soil-bentonite backfills in containing flow of dichloromethane-impacted groundwater.

A modular chemoenzymatic cascade strategy for the structure-customized assembly of ganglioside analogs.

Gangliosides play vital biological regulatory roles and are associated with neurological system diseases, malignancies, and immune deficiencies. They have received extensive attention in developing targeted drugs and diagnostic markers. However, it is difficult to obtain enough structurally defined gangliosides and analogs especially at an industrial-relevant scale, which prevent exploring structure-activity relationships and identifying drug ingredients. Here, we report a highly modular chemoenzymatic cascade assembly (MOCECA) strategy for customized and large-scale synthesis of ganglioside analogs with various glycan and ceramide epitopes. We typically accessed five gangliosides with therapeutic promising and systematically prepared ten GM1 analogs with diverse ceramides. Through further process amplification, we achieved industrial production of ganglioside GM1 in the form of modular assembly at hectogram scale. Using MOCECA-synthesized GM1 analogs, we found unique ceramide modifications on GM1 could enhance the ability to promote neurite outgrowth. By comparing the structures with synthetic analogs, we further resolved the problem of contradicting descriptions for GM1 components in different pharmaceutical documents by reinterpreting the exact two-component structures of commercialized GM1 drugs. Because of its applicability and stability, the MOCECA strategy can be extended to prepare other glycosphingolipid structures, which may pave the way for developing new glycolipid drugs.

MntJULiP and Jutils: Differential splicing analysis of RNA-seq data with covariates.

Differences in alternative splicing patterns can reveal important markers of phenotypic differentiation, including biomarkers of disease. Emerging large and complex RNA-seq datasets from disease and population studies include multiple confounders such as sex, age, ethnicity and clinical attributes, which demand highly specialized data analysis tools. However, few methods are equipped to handle the new challenges. We describe an implementation of our programs MntJULiP and Jutils for differential splicing detection and visualization from RNA-seq data that takes into account covariates. MntJULiP detects intron-level differences in alternative splicing from RNA-seq data using a Bayesian mixture model. Jutils visualizes alternative splicing variation with heatmaps, PCA and sashimi plots, and Venn diagrams. Our tools are scalable and can process thousands of samples within hours. We applied our methods to the collection of GTEx brain RNA-seq samples to deconvolute the effects of sex and age at death on the splicing patterns. In particular, clustering of covariate adjusted data identifies a subgroup of individuals undergoing a distinct splicing program during aging. MntJULiP and Jutils are implemented in Python and are available from https://github.com/splicebox/.

Gastrointestinal bleeding following Heartmate 3 left ventricular assist device implantation: The Michigan Bleeding Risk Model.

BACKGROUND: Gastrointestinal bleeding (GIB) results in frequent hospitalizations and impairs quality of life in durable left ventricular assist device (LVAD) recipients. Anticipation of these events before implantation could have important implications for patient selection and management. METHODS: The study population included all adult HeartMate 3 (HM3) primary LVAD recipients enrolled in the STS Intermacs registry from January 2017 to December 2020. Using multivariable modeling methodologies, we investigated the relationships between preimplantation characteristics and postimplant bleeding, bleeding and death, and additional bleeding episodes on subsequent bleeding episodes and created a risk score to predict the likelihood of post-LVAD GIB based solely on preimplantation factors. RESULTS: Of 6,425 patients who received an HM3 LVAD, 1,010 (15.7%) patients experienced GIB. Thirteen preimplantation factors were independent predictors of post-LVAD GIB. A risk score was created from these factors and calculated for each patient. By 3 years postimplant, GIB occurred in 11%, 26%, and 43% of low-, medium- and high-risk patients, respectively. Experiencing 1 post-LVAD GIB event was associated with an increased risk for further GIB events, with 33.9% of patients experiencing at least 1 recurrence. While post-LVAD GIB was associated with mortality, there was no relationship between number of GIB events and death. CONCLUSIONS: The Michigan Bleeding Risk Model is a simple tool, which facilitates the prediction of post-LVAD GIB in HM3 recipients using 13 preimplant variables. The implementation of this tool may help in the risk stratification process and may have therapeutic and clinical implications in HM3 LVAD recipients.

METTL3-mediated m6A RNA methylation was involved in aluminum-induced neurotoxicity.

Aluminum (Al) exposure has been linked to the development of a variety of neurodegenerative diseases. However, whether m6A RNA methylation participated in Al-induced neurotoxicity remain to be defined. In this study, mice were administrated with aluminum-lactate at dose of 220 mg/kg. bw by gavage for 3 months. Meanwhile, the primary hippocampal neurons were isolated and treated with 0, 50, 100, 150 µM aluminum-lactate, respectively for 7 days. Al exposure caused neuronal shrinkage, decreased Nissl bodies, and increased apoptosis. In accordance, in vitro studies also showed that Al exposure led to neuronal apoptosis in a dose-dependent manner, together with the decline in m6A RNA methylation levels. Moreover, the mRNA expression of Mettl3, Mettl14, Fto, and Ythdf2 were decreased upon Al exposure. Notably, the protein expression of METTL3 was dramatically down-regulated by 42% and 35% in Al-treated mice and neurons, suggesting METTL3 might exert a crucial role in Al-induced neurotoxicity. We next established a mouse model with hippocampus-specific overexpressing of Mettl3 gene to confirm the regulatory role of RNA methylation and found that METTL3 overexpression relieved the neurological injury induced by Al. The integrated MeRIP-seq and RNA-seq analysis elucidated that 631 genes were differentially expressed at both m6A RNA methylation and mRNA expression. Notably, EGFR tyrosine kinase inhibitor resistance, Rap1 signaling pathway, protein digestion and absorption might be involved in Al-induced neurotoxicity. Moreover, VEGFA, Thbs1, and PDGFB might be the central molecules. Collectively, our findings provide the novel sight into the role of m6A RNA methylation in neurodegenerative disease induced by Al.

Evaluation and clinical practice of pathogens and antimicrobial resistance genes of BioFire FilmArray Pneumonia panel in lower respiratory tract infections.

BACKGROUND: Existing panels for lower respiratory tract infections (LRTIs) are slow and lack quantification of important pathogens and antimicrobial resistance, which are not solely responsible for their complex etiology and antibiotic resistance. BioFire FilmArray Pneumonia (PN) panels may provide rapid information on their etiology. METHODS: The bronchoalveolar lavage fluid of 187 patients with LRTIs was simultaneously analyzed using a PN panel and cultivation, and the impact of the PN panel on clinical practice was assessed. The primary endpoint was to compare the consistency between the PN panel and conventional microbiology in terms of etiology and drug resistance, as well as to explore the clinical significance of the PN panel. The secondary endpoint was pathogen detection using the PN panel in patients with community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP). RESULTS: Fifty-seven patients with HAP and 130 with CAP were included. The most common pathogens of HAP were Acinetobacter baumannii and Klebsiella pneumoniae, with the most prevalent antimicrobial resistance (AMR) genes being CTX-M and KPC. For CAP, the most common pathogens were Haemophilus influenzae and Staphylococcus aureus, with the most frequent AMR genes being CTX-M and VIM. Compared with routine bacterial culture, the PN panel demonstrated an 85% combined positive percent agreement (PPA) and 92% negative percent agreement (NPA) for the qualitative identification of 13 bacterial targets. PN detection of bacteria with higher levels of semi-quantitative bacteria was associated with more positive bacterial cultures. Positive concordance between phenotypic resistance and the presence of corresponding AMR determinants was 85%, with 90% positive agreement between CTX-M-type extended-spectrum beta-lactamase gene type and phenotype and 100% agreement for mecA/C and MREJ. The clinical benefit of the PN panel increased by 25.97% compared with traditional cultural tests. CONCLUSION: The bacterial pathogens and AMR identified by the PN panel were in good agreement with conventional cultivation, and the clinical benefit of the PN panel increased by 25.97% compared with traditional detection. Therefore, the PN panel is recommended for patients with CAP or HAP who require prompt pathogen diagnosis and resistance identification.

A Review on the Application of Hospice Care in Patients with Advanced Cancer.

Hospice care is to improve the quality of life and help patients die comfortably, peacefully and dignified by controlling pain and discomfort symptoms and providing physical, psychological and spiritual care and humanistic care in the final stage of the patient's life. Hospice care clients were primarily cancer patients at first and then slowly extended to other critically patients. Hospice care can alleviate the physical, psychosocial and mental problems of patients with advanced cancer, meet the diversified and multi-level health service needs of patients, improve the quality of life of patients and their families, and also save medical expenditure and improve the efficiency of medical resources. At present, there were few studies on hospice care for Chinese patients with advanced cancer. In this study, the needs of hospice care for patients with advanced cancer were reviewed from physical comfort and pain reduction, dignity maintenance, social support, and help calm death, and specific screening and evaluation tools for hospice care for patients with advanced cancer. And this study was summarized to review the influencing factors of hospice care in order to provide a reference for clinical hospice care practice for patients with advanced cancer in China.