Human autoinflammatory disease reveals ELF4 as a transcriptional regulator of inflammation.

Transcription factors specialized to limit the destructive potential of inflammatory immune cells remain ill-defined. We discovered loss-of-function variants in the X-linked ETS transcription factor gene ELF4 in multiple unrelated male patients with early onset mucosal autoinflammation and inflammatory bowel disease (IBD) characteristics, including fevers and ulcers that responded to interleukin-1 (IL-1), tumor necrosis factor or IL-12p40 blockade. Using cells from patients and newly generated mouse models, we uncovered ELF4-mutant macrophages having hyperinflammatory responses to a range of innate stimuli. In mouse macrophages, Elf4 both sustained the expression of anti-inflammatory genes, such as Il1rn, and limited the upregulation of inflammation amplifiers, including S100A8, Lcn2, Trem1 and neutrophil chemoattractants. Blockade of Trem1 reversed inflammation and intestine pathology after in vivo lipopolysaccharide challenge in mice carrying patient-derived variants in Elf4. Thus, ELF4 restrains inflammation and protects against mucosal disease, a discovery with broad translational relevance for human inflammatory disorders such as IBD.

A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts.

Predicting interactions between microbes and hosts plays critical roles in microbiome population genetics and microbial ecology and evolution. How to systematically characterize the sophisticated mechanisms and signal interplay between microbes and hosts is a significant challenge for global health risks. Identifying microbe-host interactions (MHIs) can not only provide helpful insights into their fundamental regulatory mechanisms, but also facilitate the development of targeted therapies for microbial infections. In recent years, computational methods have become an appealing alternative due to the high risk and cost of wet-lab experiments. Therefore, in this study, we utilized rich microbial metagenomic information to construct a novel heterogeneous microbial network (HMN)-based model named KGVHI to predict candidate microbes for target hosts. Specifically, KGVHI first built a HMN by integrating human proteins, viruses and pathogenic bacteria with their biological attributes. Then KGVHI adopted a knowledge graph embedding strategy to capture the global topological structure information of the whole network. A natural language processing algorithm is used to extract the local biological attribute information from the nodes in HMN. Finally, we combined the local and global information and fed it into a blended deep neural network (DNN) for training and prediction. Compared to state-of-the-art methods, the comprehensive experimental results show that our model can obtain excellent results on the corresponding three MHI datasets. Furthermore, we also conducted two pathogenic bacteria case studies to further indicate that KGVHI has excellent predictive capabilities for potential MHI pairs.

PTBGRP: predicting phage-bacteria interactions with graph representation learning on microbial heterogeneous information network.

Identifying the potential bacteriophages (phage) candidate to treat bacterial infections plays an essential role in the research of human pathogens. Computational approaches are recognized as a valid way to predict bacteria and target phages. However, most of the current methods only utilize lower-order biological information without considering the higher-order connectivity patterns, which helps to improve the predictive accuracy. Therefore, we developed a novel microbial heterogeneous interaction network (MHIN)-based model called PTBGRP to predict new phages for bacterial hosts. Specifically, PTBGRP first constructs an MHIN by integrating phage-bacteria interaction (PBI) and six bacteria-bacteria interaction networks with their biological attributes. Then, different representation learning methods are deployed to extract higher-level biological features and lower-level topological features from MHIN. Finally, PTBGRP employs a deep neural network as the classifier to predict unknown PBI pairs based on the fused biological information. Experiment results demonstrated that PTBGRP achieves the best performance on the corresponding ESKAPE pathogens and PBI dataset when compared with state-of-art methods. In addition, case studies of Klebsiella pneumoniae and Staphylococcus aureus further indicate that the consideration of rich heterogeneous information enables PTBGRP to accurately predict PBI from a more comprehensive perspective. The webserver of the PTBGRP predictor is freely available at http://120.77.11.78/PTBGRP/.

Histone deacetylase 6 deficiency protects the liver against ischemia/reperfusion injury by activating PI3K/AKT/mTOR signaling.

Liver transplantation (LT) is the only effective method to treat end-stage liver disease. Hepatic ischemia-reperfusion injury (IRI) continues to limit the prognosis of patients receiving LT. Histone deacetylase 6 (HDAC6) is a unique HDAC member involved in inflammation and apoptosis. However, its role and mechanism in hepatic IRI have not yet been reported. We examined HDAC6 levels in liver tissue from LT patients, mice challenged with liver IRI, and hepatocytes subjected to hypoxia/reoxygenation (H/R). In addition, HDAC6 global-knockout (HDAC6-KO) mice, adeno-associated virus-mediated liver-specific HDAC6 overexpressing (HDAC6-LTG) mice, and their corresponding controls were used to construct hepatic IRI models. Hepatic histology, inflammatory responses, and apoptosis were detected to assess liver injury. The molecular mechanisms of HDAC6 in hepatic IRI were explored in vivo and in vitro. Moreover, the HDAC6-selective inhibitor tubastatin A was used to detect the therapeutic effect of HDAC6 on liver IRI. Together, our results showed that HDAC6 expression was significantly upregulated in liver tissue from LT patients, mice subjected to hepatic I/R surgery, and hepatocytes challenged by hypoxia/reoxygenation (H/R) treatment. Compared with control mice, HDAC6 deficiency mitigated liver IRI by inhibiting inflammatory responses and apoptosis, whereas HDAC6-LTG mice displayed the opposite phenotype. Further molecular experiments show that HDAC6 bound to and deacetylated AKT and HDAC6 deficiency improved liver IRI by activating PI3K/AKT/mTOR signaling. In conclusion, HDAC6 is a key mediator of hepatic IRI that functions to promote inflammation and apoptosis via PI3K/AKT/mTOR signaling. Targeting hepatic HDAC6 inhibition may be a promising approach to attenuate liver IRI.

Genomic characterization and immunotherapy for microsatellite instability-high in cholangiocarcinoma.

BACKGROUND: Microsatellite instability-high (MSI-H) is a unique genomic status in many cancers. However, its role in the genomic features and immunotherapy in cholangiocarcinoma (CCA) is unclear. This study aimed to systematically investigate the genomic characterization and immunotherapy efficacy of MSI-H patients with CCA. METHODS: We enrolled 887 patients with CCA in this study. Tumor samples were collected for next-generation sequencing. Differences in genomic alterations between the MSI-H and microsatellite stability (MSS) groups were analyzed. We also investigated the survival of PD-1 inhibitor-based immunotherapy between two groups of 139 patients with advanced CCA. RESULTS: Differential genetic alterations between the MSI-H and MSS groups included mutations in ARID1A, ACVR2A, TGFBR2, KMT2D, RNF43, and PBRM1 which were enriched in MSI-H groups. Patients with an MSI-H status have a significantly higher tumor mutation burden (TMB) (median 41.7 vs. 3.1 muts/Mb, P < 0.001) and more positive programmed death ligand 1 (PD-L1) expression (37.5% vs. 11.9%, P < 0.001) than those with an MSS status. Among patients receiving PD-1 inhibitor-based therapy, those with MSI-H had a longer median overall survival (OS, hazard ratio (HR) = 0.17, P = 0.001) and progression-free survival (PFS, HR = 0.14, P < 0.001) than patients with MSS. Integrating MSI-H and PD-L1 expression status (combined positive score ≥ 5) could distinguish the efficacy of immunotherapy. CONCLUSIONS: MSI-H status was associated with a higher TMB value and more positive PD-L1 expression in CCA tumors. Moreover, in patients with advanced CCA who received PD-1 inhibitor-based immunotherapy, MSI-H and positive PD-L1 expression were associated with improved both OS and PFS. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov on 07/01/2017 (NCT03892577).

A biomedical knowledge graph-based method for drug-drug interactions prediction through combining local and global features with deep neural networks.

Drug-drug interactions (DDIs) prediction is a challenging task in drug development and clinical application. Due to the extremely large complete set of all possible DDIs, computer-aided DDIs prediction methods are getting lots of attention in the pharmaceutical industry and academia. However, most existing computational methods only use single perspective information and few of them conduct the task based on the biomedical knowledge graph (BKG), which can provide more detailed and comprehensive drug lateral side information flow. To this end, a deep learning framework, namely DeepLGF, is proposed to fully exploit BKG fusing local-global information to improve the performance of DDIs prediction. More specifically, DeepLGF first obtains chemical local information on drug sequence semantics through a natural language processing algorithm. Then a model of BFGNN based on graph neural network is proposed to extract biological local information on drug through learning embedding vector from different biological functional spaces. The global feature information is extracted from the BKG by our knowledge graph embedding method. In DeepLGF, for fusing local-global features well, we designed four aggregating methods to explore the most suitable ones. Finally, the advanced fusing feature vectors are fed into deep neural network to train and predict. To evaluate the prediction performance of DeepLGF, we tested our method in three prediction tasks and compared it with state-of-the-art models. In addition, case studies of three cancer-related and COVID-19-related drugs further demonstrated DeepLGF's superior ability for potential DDIs prediction. The webserver of the DeepLGF predictor is freely available at http://120.77.11.78/DeepLGF/.

A novel circRNA-miRNA association prediction model based on structural deep neural network embedding.

A large amount of clinical evidence began to mount, showing that circular ribonucleic acids (RNAs; circRNAs) perform a very important function in complex diseases by participating in transcription and translation regulation of microRNA (miRNA) target genes. However, with strict high-throughput techniques based on traditional biological experiments and the conditions and environment, the association between circRNA and miRNA can be discovered to be labor-intensive, expensive, time-consuming, and inefficient. In this paper, we proposed a novel computational model based on Word2vec, Structural Deep Network Embedding (SDNE), Convolutional Neural Network and Deep Neural Network, which predicts the potential circRNA-miRNA associations, called Word2vec, SDNE, Convolutional Neural Network and Deep Neural Network (WSCD). Specifically, the WSCD model extracts attribute feature and behaviour feature by word embedding and graph embedding algorithm, respectively, and ultimately feed them into a feature fusion model constructed by combining Convolutional Neural Network and Deep Neural Network to deduce potential circRNA-miRNA interactions. The proposed method is proved on dataset and obtained a prediction accuracy and an area under the receiver operating characteristic curve of 81.61% and 0.8898, respectively, which is shown to have much higher accuracy than the state-of-the-art models and classifier models in prediction. In addition, 23 miRNA-related circular RNAs (circRNAs) from the top 30 were confirmed in relevant experiences. In these works, all results represent that WSCD would be a helpful supplementary reliable method for predicting potential miRNA-circRNA associations compared to wet laboratory experiments.

SERS detection of volatile gas in spoiled pork with the Ag/MoS2 nano-flower cavity/PVDF micron-bowl cavity (FIB) substrate.

Putrescine and cadaverine are significant volatile indicators used to assess the degree of food spoilage. Herein, we propose a micro-nano multi cavity structure for surface-enhanced Raman spectroscopy (SERS) to analyze the volatile gas putrescine and cadaverine in decomposing food. The MoS2 nano-flowers are inserted into a PVDF micro-cavity through in-situ growth, followed by vacuum evaporation technology of Ag nanoparticles to form an Ag/MoS2 nano-flower cavity/PVDF micron-bowl cavity (FIB) substrate. The micro-nano multi cavity structure can improve the capture capacity of both light and gas, thereby exhibiting high sensitivity (EF = 7.71 × 107) and excellent capability for gas detection of 2-naphthalenethiol. The SERS detections of the putrescine and cadaverine are achieved in the spoiled pork samples with the FIB substrate. Therefore, this substrate can provide an efficient, accurate, and feasible method for the specific and quantitative detection in the food safety field.

Study on the effects of rapamycin and the mTORC1/2 dual inhibitor OSI-027 on the metabolism of colon cancer cells based on UPLC-MS/MS metabolomics.

mTORC1/2 dual inhibitors may be more effective than mTORC1 inhibitor rapamycin. However, their metabolic impacts on colon cancer cells remain unexplored. We conducted a comparative analysis of the anti-proliferative effects of rapamycin and the novel OSI-027 in colon cancer cells HCT-116, evaluating their metabolic influences through ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS/MS). Our results demonstrate that OSI-027 more effectively inhibits colon cancer cell proliferation than rapamycin. Additionally, we identified nearly 600 metabolites from the spectra, revealing significant differences in metabolic patterns between cells treated with OSI-027 and rapamycin. Through VIP value screening, we pinpointed crucial metabolites contributing to these distinctions. For inhibiting glycolysis and reducing glucose consumption, OSI-027 was likely to be more potent than rapamycin. For amino acids metabolism, although OSI-027 has a broad effect as rapamycin, their effects in degrees were not exactly the same. These findings address the knowledge gap regarding mTORC1/2 dual inhibitors and lay a foundation for their further development and research.

Disparate Radiation-Induced Microstructural Injuries in Whole-Brain White Matter of Patients With Nasopharyngeal Carcinoma: A Longitudinal Study Using Multishell Diffusion MRI.

BACKGROUND: Evidence for prevention strategies of radiotherapy (RT)-related injury in patients with nasopharyngeal carcinoma (NPC) was lacking. Understanding the dynamic alterations in the cerebral white matter (WM) microstructure after RT may be helpful. PURPOSE: To investigate the dynamic alterations in the whole brain WM microstructure in patients with NPC in the 12 months after RT using multishell diffusion MRI (MS-dMRI). STUDY TYPE: Single-center longitudinal study. POPULATION: A total of 28 treatment-naïve patients with pathologically confirmed NPC (age: 39.68 ± 8.93 years, 11 female) and 20 healthy controls (age: 40.65 ± 9.76 years, 7 female). FIELD STRENGTH/SEQUENCES: A 3 T, MS-dMRI using a single-shot echo planar imaging sequence. ASSESSMENT: MS-dMRI was acquired at baseline for the NPC patients and healthy controls, at 0-3 (acute, AC), 6 (early delayed, ED) and 12 months (late delayed, LD) after RT for the NPC patients. The mean and maximum radiation doses to the temporal lobe were acquired. The quality of images was reviewed. MS-dMRI was analyzed using tract-based spatial statistics (TBSS). The presentations of injury were defined by the findings of TBSS. STATISTICAL TESTS: Chi-square, t tests, repeated ANOVA, and Spearman-rank correlation analysis were used. P < 0.05 was considered to be statistically significant. RESULTS: TBSS showed two WM injuries (injuries 1 and 2). Injury 1 emerged in the ED phase in the bilateral temporal poles and persisted throughout the ED and LD phases. Injury 2 developed from the AC to ED phase in the bilateral hemisphere and partially recovered in the LD phase. In the ED and LD phases, the multiple diffusion metrics were well correlated (r > 0.5 or <-0.5) with the RT dose, especially in the WM tracts in the temporal lobes. DATA CONCLUSION: Disparate WM injuries were observed in NPC patients after RT. The injuries may be primarily or secondarily induced by radiation. Injury 1 may be irreversible, while injury 2 seems to partially recover. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 4.

Degradation Behavior of Medical MgZZC-1 in Various Simulated Body Fluids.

Magnesium-based biodegradable metal bone implants exhibit superior mechanical properties compared to biodegradable polymers for orthopedic and cardiovascular stents. In this study, MgZZC-x (x = 1, 1.2) alloys were screened by in vitro biocompatibility tests in three simulated body fluids under nontoxic conditions. The MgZZC-1 alloys with better biocompatibility were selected to predict the days required for complete degradation. The evolution of degradation products was analyzed, and the mechanism of formation of the product film was inferred. A degradation kinetic model was established to investigate the effect of MEM components on the degradation of the alloys. The results demonstrate that the proteins in MEM can greatly retard the degradation progress by attaching to the surface of MgZZC-1 alloys, which are predicted to degrade completely within 341 days. The carbonate and phosphate buffers were adjusted to pH in MEM solution, delaying the degradation of magnesium alloys. This process in MEM more accurately reflects the actual degradation in the body and is superior to that in Hanks and SBF solutions. This study will promote the application of biodegradable materials in clinical medicine.

Preparation of Superhydrophobic Coating on X80 Steel and Its Corrosion Resistance in Oilfield Produced Water.

Corrosion is an unavoidable issue that steel encounters during service; however, the generic methods employed for corrosion prevention often need high cost or preparation conditions. In this study, a facile chemical replacement deposition method was proposed to realize an anticorrosion superhydrophobic coating on a X80 steel surface. The growth mechanism of the rough structure and its impact on the wettability of the superhydrophobic coating were analyzed. The superhydrophobic coating, deposited for 50 s and modified for 30 min, achieved optimal electrochemical properties and a maximum water contact angle. The immersion test, in the saturated CO2 oilfield produced water, demonstrated the better corrosion resistance of superhydrophobic coating than X80 steel. Correspondingly, a kinetic corrosion model was established to analyze the anticorrosion mechanism. In summary, this method significantly improves the corrosion resistance of X80 steel and is attractive for other industrial fields.

Sulforaphane Attenuates AOM/DSS-Induced Colorectal Tumorigenesis in Mice via Inhibition of Intestinal Inflammation.

Sulforaphane (SFN) is a compound derived from cruciferous plants. It has received considerable attention in recent years due to its effectiveness in cancer prevention and anti-inflammatory properties. The purpose of this study was to evaluate the antitumor potential of sulforaphane on colitis-associated carcinogenesis (CAC) through the establishment of a mouse model with AOM/DSS. First, AOM/DSS and DSS-induced model were established and administered SFN for 10 wk, and then the severity of colitis-associated colon cancer was examined macroscopically and histologically. Subsequently, immune cells and cytokines in the tumor microenvironment (TME) were quantified. Finally, the influence of sulforaphane was also investigated using different colon cell lines. We found that sulforaphane treatment decreased tumor volume, myeloid-derived suppressor cells (MDSC) expansion, the expression of the proinflammatory cytokine IL-1ß, and the level of IL-10 in serum. Also, it enhanced the antitumor activities of CD8+ T cells and significantly reduced tumorigenesis as induced by AOM/DSS. SFN also attenuated intestinal inflammation in DSS-induced chronic colitis by reshaping the inflammatory microenvironment. This work demonstrates that sulforaphane suppresses carcinogenesis-associated intestinal inflammation and prevents AOM/DSS-induced intestinal tumorigenesis and progression.

The stress granule protein G3BP1 promotes pre-condensation of cGAS to allow rapid responses to DNA.

Cyclic GMP-AMP synthase (cGAS) functions as a key sensor for microbial invasion and cellular damage by detecting emerging cytosolic DNA. Here, we report that GTPase-activating protein-(SH3 domain)-binding protein 1 (G3BP1) primes cGAS for its prompt activation by engaging cGAS in a primary liquid-phase condensation state. Using high-resolution microscopy, we show that in resting cells, cGAS exhibits particle-like morphological characteristics, which are markedly weakened when G3BP1 is deleted. Upon DNA challenge, the pre-condensed cGAS undergoes liquid-liquid phase separation (LLPS) more efficiently. Importantly, G3BP1 deficiency or its inhibition dramatically diminishes DNA-induced LLPS and the subsequent activation of cGAS. Interestingly, RNA, previously reported to form condensates with cGAS, does not activate cGAS. Accordingly, we find that DNA - but not RNA - treatment leads to the dissociation of G3BP1 from cGAS. Taken together, our study shows that the primary condensation state of cGAS is critical for its rapid response to DNA.

Ho(III)-coordination Complex: Fluorescence Performances and Combined with Captopril-Hydrogels against Glioma.

In this study, a novel dinuclear lanthanide complex, denoted as [Ho2(L)2(acac)2(CH3OH)2]·CH3OH (1) (where H2L is 2-[((4-methyl)-2-(carboxyl)-imino)]methyl]-8-hydroxyquinoline, and Hacac is acetylacetonate), was successfully synthesized and characterized using single-crystal and elemental analysis, with the auxiliary ligand ß-diketonate and the 8-hydroxyquinoline Schiff base derivative serving as the foundation. Through ligand-to-metal charge transfer, Compound 1 demonstrated remarkable green fluorescence properties, showcasing potential applications in green fluorescence materials and fluorescence sensing. Additionally, Hyaluronic Acid (HA)/Carboxymethyl Chitosan (CMCS) hydrogels were synthesized through a chemical method. Utilizing captopril as a drug model, a novel metal gel granule of captopril was developed and assessed for its inhibitory activity against glioma cells. Molecular docking simulations revealed that only the methanol group in the Ho complex could contribute a polar atom for the formation of binding interactions.

Assessing health-related quality of life of Chinese population using CQ-11D.

PURPOSE: This study aimed to assess the health-related quality of life (HRQoL) of the Chinese population by using the Chinese medicine quality of life-11 dimensions (CQ-11D) questionnaire and to identify factors associated with HRQoL. METHODS: The data was derived from a survey conducted by the Institute of Pharmacoeconomics Evaluation at Beijing University of Chinese Medicine on the quality of life of the Chinese population. The sex and age of respondents were considered through quota sampling. Demographic, socioeconomic, and health indicators were collected using the structured questionnaire. We performed bivariate analyses first to examine the associations between the above factors and the HRQoL of respondents measured by the CQ-11D. Multivariate linear regression and ordinal logistic regression models were established to analyze the factors (demographic, socioeconomic, and health indicators) differences in HRQoL, as well as the risk of each group reporting problems across the 11 dimensions of CQ-11D. RESULTS: From February 2021 to November 2022, a total of 7,604 respondents were involved and 7,498 respondents were included. The sample approximated the general adult Chinese population in terms of age, sex, and district of residence, and each geographic distribution ranged from 9.71 to 25.54%. Of the respondents, 45.84% were male, and 89.82% were Han ethnicity. The mean utility score ranged from 0.796 to 0.921 as age increased. According to the respondents, most health problems were identified in the PL (fatigue) (70.16%) and SM (quality of sleep) (63.63%) dimensions. The CQ-11D index scores varied with the demographic and socioeconomic characteristics of respondents, except for ethnicity (p > 0.05) and income (p > 0.05). The multivariate analysis revealed significant negative associations between health utility scores and various factors. These factors include sex (female), age over 65, belonging to ethnic minorities, rural household registration, being widowed or divorced, having a primary school education or below, being a student or unemployed, having a low income of 0-1,300, engaging in smoking or drinking, limited participation in physical activities, experiencing changes in self-perceived health status compared to the previous year, and having chronic diseases. The odds of respondents reporting problems in 11 dimensions varied among different socio-demographic groups. CONCLUSIONS: This study reports the first Chinese population norms for the CQ-11D derived using a representative sample of the Chinese general population. Self-reported health status measured by the CQ-11D varies among different socio-economic groups. In addition to participation a physical activity and the presence of chronic disease, smoking and drinking also significantly influence HRQoL.

Design and application of a novel "turn-on" fluorescent probe for imaging sulfite in living cells and inflammation models.

Sulfite is one of the main existing forms of sulfur dioxide (SO2) in living system, which has been recognized as an endogenous mediator in inflammation. Evidence has accumulated to show that abnormal level of sulfite is associated with many inflammatory diseases, including neurological diseases and cancers. Herein, a novel fluorescent probe named QX-OA was designed and synthesized to detect sulfite. QX-OA was constructed by choosing quinolinium-xanthene as the fluorophore and levulinate as the specific and relatively steady recognition reaction. The probe showed remarkable green turn-on signal at 550 nm, together with high sensitivity (90-fold) and excellent selectivity to sulfite over other possible interfering species. In the meantime, QX-OA was successfully applied to visualize endogenous and exogenous sulfite in Hela cells. In the LPS-induced inflammation model, QX-OA could visualize the dose-dependent increase of sulfite level (0-2 mg/mL). Consequently, QX-OA was determined to be a potential method for detecting sulfite in pre-clinical diagnosis.

Novel BODIPY-based nano-biomaterials with enhanced D-A-D structure for NIR-triggered photodynamic and photothermal therapy.

Near-infrared (NIR) responsive nanoparticles are an important platform for multimodal phototherapy. Importantly, the simultaneous NIR-triggered photodynamic (PDT) and photothermal (PTT) therapy is a powerful approach to increase the antitumor efficiency of phototherapic nanoparticles due to the synergistic effect. Herein, a boron dipyrromethene (BODIPY)-based amphiphilic dye with enhanced electron donor-acceptor-donor (D-A-D) structure (BDP-AP) was designed and synthesized, which could self-assemble into stable nanoparticles (BDP-AP NPs) for the synergistic NIR-triggered PDT/PTT therapy. BDP-AP NPs synchronously generated singlet oxygen (1O2) and achieved preeminent photothermal conversion efficiency (61.42%). The in vitro and in vivo experiments showed that BDP-AP NPs possessed negligible dark cytotoxicity and infusive anticancer performance. BDP-AP NPs provide valuable guidance for the construction of PDT/PTT-synergistic NIR nanoagents to improve the efficiency of photoinduced cancer therapy in the future.

A comparative study of Chinese medicine quality of life assessment scale (CQ-11D) and EQ-5D-5L and SF-6D scales based on Chinese population.

PURPOSE: To measure health-related quality of life in the Chinese population using three universal health utility scales (CQ-11D, EQ-5D-5L, and SF-6D) and to compare the differences in the results obtained by the different scales to provide a reference for future utility on health-related quality of life in the Chinese population. METHODS: According to the Chinese population's distribution area, gender, and age, quota sampling was conducted. Three scales, CQ-11D, EQ-5D-5L, and SF-6D, whose results were self-reported, were collected in succession after collecting respondents' demographic information. The health utility value and floor/ceiling effect were explained. Bland-Altman was used to evaluate the consistency, the intraclass correlation coefficient was used to evaluate the correlation, and the receiver operating characteristic curve was used to evaluate the discriminative validity of the scale. RESULTS: The mean utility values of the CQ-11D, EQ-5D-5L, and SF-6D scales, respectively, were 0.891, 0.927, and 0.841. The floor effect did not appear in any of the three scales, but the ceiling effect did, and the EQ-5D-5L ceiling effect was the most severe. The limits of the agreement interval for CQ-11D versus EQ-5D-5L in the total sample population were (-0.245,0.172); for CQ-11D versus SF-6D, they were (- 0.256,0.354); and for EQ-5D-5L versus SF-6D, they were (-0.199,0.371). The consistency of the three scales is satisfactory overall. In the total population, the intraclass correlation coefficient between CQ-11D and EQ-5D-5L was 0.709, while EQ-5D-5L and SF-6D were 0.0.565 and that between EQ-5D-5L and SF-6D was 0.472. According to the subject operation curve results, the area under the curve for the total sample population of CQ-11D was 0.746, EQ-5D-5L was 0.669, and SF-6D was 0.734. CONCLUSION: The CQ-11D is inferior to the EQ-5D-5L, but superior to the SF-6D. There is a strong correlation between the health utility values of the total population as measured by the three scales and those of the healthy population. The CQ-11D scale is the most sensitive to differences between populations and diseases.

ACE2 mediates tryptophan alleviation on diarrhea by repairing intestine barrier involved mTOR pathway.

The membrane-delimited receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), angiotensin-converting enzyme 2 (ACE2), which is expressed in the intestine, collaborates with broad neutral amino acid transporter 1 (B0AT1). Tryptophan (Trp) is transported into intestinal epithelial cells by ACE2 and B0AT1. However, whether ACE2 and its binding protein B0AT1 are involved in Trp-mediated alleviation of intestinal injury is largely unknown. Here, we used weaned piglets and IPEC-J2 cells as models and found that ACE2/B0AT1 alleviated lipopolysaccharide (LPS)-induced diarrhea and promoted intestinal barrier recovery via transport of Trp. The levels of the aryl hydrocarbon receptor (AhR) and mechanistic target of rapamycin (mTOR) pathways were altered by ACE2. Dietary Trp supplementation in LPS-treated weaned piglets revealed that Trp alleviated diarrhea by promoting ACE2/B0AT1 expression, and examination of intestinal morphology revealed that the damage to the intestinal barrier was repaired. Our study demonstrated that ACE2 accompanied by B0AT1 mediated the alleviation of diarrhea by Trp through intestinal barrier repair via the mTOR pathway.